sports research articles

Latest Articles

Low Energy Availability (LEA) in Male Athletes: A Review of the Literature

George Minoso 2024-10-21T09:45:40-05:00 October 23rd, 2024 | Book Reveiws , Research , Sports Nutrition |

Authors: Brandon L. Lee 1

1 The Department of Exercise, Health, and Sport Sciences, Pennsylvania Western University

Corresponding Author:

Brandon L. Lee, MS, RD, CCRP 10263 4th Armored Division Dr. Fort Drum, NY 13603 [email protected] 315-772-0689

Brandon L. Lee, MS, RD, CCRP is a Holistic Health and Fitness (H2F) Dietitian for the U.S. Army Forces Command and a Doctor of Health Science (DHSc) student at Pennsylvania Western University. Brandon’s research interests include energy systems and metabolism, energy availability, andragogical methods for adult learning, and reflective practice to enhance learning in formal education..

Purpose: Low energy availability (LEA) is a physiological state when there is inadequate energy to meet the demands placed on the body, often through physical activity, exercise, or sports. LEA can impact any athlete engaged in a sport with low energy intake or excessive energy expenditure. LEA is a precursor to the onset of The Male Athlete Triad (MAT) and Relative Energy Deficiency in Sport (RED-S). There is no defined low energy availability threshold specific to male athletes engaged in high-energy expenditure sports leading to MAT and RED-S. This literature review evaluates the literature on the relationship between LEA and signs or symptoms of MAT and RED-S to establish a low energy availability threshold specific to male athletes engaged in high-energy expenditure sports.

Methods: The Pennsylvania Western University library electronic database was used for the literature search. Search terms included “male athletes”, “low energy availability”, “male athlete triad”, “relative energy deficiency in sport”, and “energy deficiency”. Research studies included cross-sectional, experimental, systematic reviews, meta-analyses, case studies, and some narrative and literature reviews. Studies must have been peer-reviewed and published within five years of the literature search (12/2018- 12/2023).

Results: A review of the literature shows that it is difficult to determine a LEA threshold due to present research gaps and inconsistent findings related to health and performance consequences. Based on the results of experimental studies, practitioners can expect an LEA threshold of 20-25kcal per kilogram (kg) of fat-free mass (FFM) per day in male athletes engaged in high energy-expenditure sports.

Conclusions: Athletes engaged in sports that lead to inadequate energy intake or high energy expenditure are at risk for LEA, MAT, and RED-S. Experimental research on the LEA threshold in athletes engaged in physiologically demanding sports is the greatest research gap. Based on present findings, male athletes may have an LEA threshold of <30kcal/kg of FFM/day.

Applications in Sport: Healthy nutritional practices are essential to sports performance. Interdisciplinary sports performance teams must collaborate with nutrition professionals to develop effective LEA prevention, screening, and intervention protocols.

Keywords: energy intake, energy deficiency, energy expenditure of exercise, male athlete triad, relative energy deficiency in sport, sports nutrition

Energy availability (EA) is the energy dedicated to body system functions. In sports nutrition, energy availability is defined as the amount of energy remaining to support an athlete’s bodily functions after energy expenditure of exercise (EEE) is deducted from energy intake (EI) (2). Health and athletic performance issues arise when athletes have inadequate energy intake or excessive energy expenditure, depleting their EA. The designated term for this is low energy availability (LEA). LEA is defined as a physiological state when there is inadequate energy to meet the demands placed on the body, often through physical activity, exercise, or sports (23). Causes of LEA include obsessive causes (disordered eating or eating disorders), intentional causes (attempts to modify body mass or composition), and inadvertent causes (byproduct of high EEE) (1). LEA can impact any athlete engaged in a sport with low energy intake or excessive energy expenditure. LEA is most common in sports of high intensity, duration, volume, or frequency and in sports that emphasize low body weight/fat, aesthetics, or thinness, including distance cycling and running, triathlons, tactical (i.e., military), swimming, gymnastics, wrestling, bodybuilding, martial arts, boxing, soccer, tennis, rowing, horse racing, and volleyball. LEA is a precursor to the onset of both The Male Athlete Triad (MAT) and Relative Energy Deficiency in Sport (RED-S), two conditions that result in weakened physiological functions, with the former focused on reproductive and bone health decline (22). The problem is the prevalence of LEA among male athletes participating in high-energy expenditure sports, leading to potential health and performance issues. Additionally, there is no defined low energy availability threshold specific to male athletes engaged in high-energy expenditure sports leading to MAT and RED-S (3, 4, 5, 9, 11, 14, 17, 22, 26). This literature review aims to evaluate the literature on the relationship between LEA and signs or symptoms of MAT and RED-S to establish a defined low energy availability threshold specific to male athletes engaged in high-energy expenditure sports. This literature review will report on LEA’s impact on health, body composition, athletic performance; establish LEA thresholds, and address research gaps.

RELATIVE ENERGY DEFICIENCY IN SPORT (RED-S) LEA is a common precursor to many health and athletic performance issues. In 2014, the International Olympic Committee (IOC) developed a consensus statement titled “Beyond the Female Athlete Triad: Relative Energy Deficiency in Sport (RED-S)” and established RED-S as a new condition that refers to diminished physiological processes due to relative energy deficiency. The most current IOC RED-S models show that RED-S can impact the following systems: immunological, menstrual/reproductive function and bone health (related to athlete triad), endocrine, metabolic, hematological, growth and development, psychological, cardiovascular, and gastrointestinal. Moreover, another IOC RED-S model shows the potential performance effects of RED-S, including decreased endurance performance, increased injury risk, decreased training response, impaired judgment, decreased coordination, decreased concentration, irritability, depression, decreased glycogen stores, and decreased muscle strength (19). Much of the research on the impact of LEA and the cascade of events that lead to RED-S has primarily been conducted on female athletes, and the findings are extrapolated to their male counterparts; however, this is changing.

MALE ATHLETE TRIAD The Male Athlete Triad (MAT) was first introduced in the 64th Annual Meeting of the American College of Sports Medicine (ACSM) in 2017 (6). MAT has comprised three essential components: LEA (sometimes referred to as energy deficiency), impaired bone health, and suppression of the hypothalamic-pituitary-gonadal (HPG) axis (22). Prevention and treatment methods of MAT hinge on the EA or energetic status of the athlete at risk. Nattiv et al. (2021) explain that energy deficiency or LEA is confirmed when one of the following metabolic adaptations is presented: reduced RMR compared to body size or fat-free mass (FFM), unintentional weight loss resulting in a new low set point, underweight body mass index (BMI), and reduced metabolic hormones such as triiodothyronine (T3), leptin, and several more. Hypogonadotropic hypogonadism can manifest as oligospermia (deficiency of sperm in the semen) or decreased libido (reduced sexual drive). Lastly, poor bone health can manifest as osteopenia, osteoporosis, or bone stress injury (22). The energetic status of the athlete can vary greatly depending on frequency, intensity, duration, type of sport, volume, and progression. Nattiv et al. (2021) have surmised that male athletes engaged in leanness sports typically have low energy intake compared to recommended amounts from the Institute of Medicine Daily Recommended Intakes or Food and Agriculture Organization of the United Nations/World Health Organization. Unfortunately, male leanness sports or weight-class athletes potentially consume up to 1000kcal/day less than required to support their exercise demands (22). Athletes consistently at risk for MAT include runners and cyclists, primarily if they compete in long-distance competitions.

Cardiovascular Health Cardiovascular health (CVH) is essential to every athlete engaged in any sport. A healthy cardiovascular system effectively moves blood from one location to another to transport oxygen-containing blood cells for muscular activity. Langan-Evans et al. (2021) studied the impact of incorporating daily fluctuations in LEA on cardiorespiratory capacity via treadmill test in one combat athlete preparing to make weight for competition. The athlete experienced microcycle EA fluctuations ranging from 7 to 31 kcal per kilogram (kg) of FFM/day (mean EA of 20kcal/kg of FFM/day) for seven days and did not experience any significant changes in resting heart rate, cardio output, or overall CVH (14). Theoretically, LEA would have significant structural, conduction, repolarization, and peripheral vascular effects on CVH (17). However, a scant amount of research establishes any correlation between CVH and LEA, and primary research studies conducted within the past five years have yet to establish causation between the two. On the other hand, Fagerberg (2018) has found that EA <25kcal/kg FFM over six months in bodybuilders preparing for a competition can impact CVH by reducing heart rate. According to Fagerberg (2018), low body fat percentages in bodybuilders worsen CVH risk (4). This heart rate reduction, paired with low body fat, is likely a physiological adaptation to conserve energy and sustain life. There needs to be more consistency in the literature regarding the impact of LEA on CVH.

Physiological Health LEA and RED-S are both physiological and psychological health risks. Sports that emphasize leanness (e.g., cycling) or have weight divisions (e.g., combat sports) often place additional mental stress on athletes to perform well and possess a specific physique. For example, Schofield et al. (2021) found that male cyclists are at risk for LEA and RED-S due to rigid weight management practices, desire for leanness, disordered eating and eating disorders, and body dissatisfaction (26). Elevating psychological health is commonly conducted via a questionnaire or interview. Langbein et al. (2021) explored the subjective experience of RED-S in endurance athletes through semi-structured, open-ended interviews. The first male participant commented on hitting “rock bottom” and the body’s sensitivity to energy intake changes. In addition, the other male athlete appeared to have a transactional relationship with food and exercise, void of any joy or performance goals. Both male athletes reported negative psychological consequences regarding RED-S; these consequences included increased rates of irritability because they were obsessed with food and exercise and feelings of helplessness and despair (15). Perelman et al. (2022) also examined the male athlete’s psychological state by evaluating and intervening on body dissatisfaction, drive for muscularity, body-ideal internalization, and muscle dysmorphia. Male athlete participants (n=79) were from various sports, including baseball, golf, soccer, swimming, track and field, volleyball, and wrestling. The results showed that group sessions focused on reframing ideal body perception, the consequences of RED-S, encouraging positive self-talk, and reviewing strategies to modify energy balance healthfully can significantly reduce body dissatisfaction, body-ideal internalization, and drive for muscularity (p < .05) (24). The results demonstrate the value of understanding, supporting, and guiding an athlete’s psychological state toward personal health and satisfaction.

Reproductive Health Functional hypogonadotropic hypogonadism is one of the three primary pillars of the MAT. LEA can induce disruptions to the hypothalamic-pituitary-gonadal (HPG) axis, resulting in functional hypogonadotropic hypogonadism. Signs of hypogonadotropic hypogonadism include (1) reductions of testosterone (T) and luteinizing hormone (LH), (2) decreased T and responsiveness of gonadotropins to gonadotropin-releasing hormone (GnRH) stimulation after training, (3) alterations in spermatogenesis, and (4) self-reported data on decreased libido and sexual desire (22). Most current research studies examine free and total T as an indicator of HPG axis suppression. Lundy et al. (2022) categorize low total T (<16nmol/L) and low free T (<333 pmol/L) as primary indicators for LEA (16). A significant contribution to this area comes from the work by Jurov et al. (2021) who conducted a non-randomized experimental study with a crossover design to investigate the reproductive health impacts of progressively reducing EA by 50% for 14 days in well-trained and elite endurance male athletes. The results demonstrated a positive correlation between T levels and measured EA; as EA declined, so did T (9). The empirical evidence on the causal relationship between LEA and T has been growing over recent years, with studies such as one conducted by Dr. Iva Jurov and colleagues. In three progressive steps, their quasi-experimental study reduced EA (via increasing EEE and controlling EI) in well-trained and elite male endurance athletes. Participants had statistically significant T changes starting at the 50% EA reduction phase with a mean EA of 17.3 ± 5.0kcal/kg of FFM/day for 14 days (p < 0.037). Furthermore, T levels continued to significantly decline at 75% EA reduction phase with a mean EA of 8.83 ± 3.33 for ten days (p < 0.095) (10). Conversely, in another quasi-experimental study by Jurov et al. (2022b), endurance male athletes had their EA reduced by 25% by increasing EEE and controlling EI for 14 days. The mean EA was 22.4 ± 6.3kcal/kg of FFM/day. The results show no significant changes to T levels, potentially indicating that a greater EA reduction was required to induce change (11). Stenqvist et al. (2020) conducted four weeks of intensified endurance training designed to increase aerobic performance and determine the impact of T and T: cortisol ratio on well-trained male athletes. After the four weeks of intensified endurance training, the results showed that total T significantly increased by 8.1% (p=0.011) while free T (+4.1%, p=0.326), total T: cortisol ratio (+1.6%, p=0.789), and free T: cortisol ratio (-3.2%, p=0.556) did not have significant changes when compared to baseline (27). It is complex to determine the EA threshold defined by HPG axis suppression. Research on LEA and suppression of the HPG axis (i.e., T reduction) have demonstrated varied results based on athlete EA study design features (e.g., high EEE intensity or low EI duration); however, endurance athletes remain at the highest risk (18, 22, 26).

Bone Health The last pillar of the MAT is osteoporosis with or without bone stress injury (BSI). Impaired bone health is most common in athletes in sports that have low-impact loading patterns, such as cycling, swimming, or distance running. Bone mineral density (BMD) is the primary measurement method to evaluate overall bone health and risk for osteoporosis. Dual-energy x-ray absorptiometry (DXA) is the gold standard for assessing bone density, but quantitative computed tomography (QCT) is also emerging as an equally acceptable alternative. In outpatient or rehabilitation settings, frequency of DXA scans is recommended no sooner than every ten months to allow for detectable changes in bone mineral density (17). Risk factors for low BMD include LEA, low body weight (<85% of ideal body weight), hypogonadism, running mileage >30/week, and a history of stress fractures (22). In addition to BMD, other indicators of bone health include bone mineral content (BMC), markers of bone formation including β-carboxyl-terminal cross-linked telopeptide of type I collagen (β-CTX), bone alkaline phosphatase, and osteocalcin, and markers of bone resorption including amino-terminal propeptide of type-1 procollagen (P1NP), tartrate-resistant acid phosphatase, and carboxy-terminal collagen cross-links (4, 17). Studies will occasionally implement biomarkers such as Vitamin D and calcium to evaluate dietary intake and risk of BSI or osteoporosis. What is the prevalence of low BMD in athletes? Tam et al. (2018) evaluated the bone health and body composition of elite male Kenyan runners (n=15) compared to healthy individuals. The results showed that 40% of Kenyan runners have Z-scores indicating low bone mineral density in their lumbar spine for their respective age (z-score <−2.0). This study did not measure energy availability with bone mineral density (29). However, based on previous research, low bone mineral density may have LEA origins. Heikura et al. (2018) studied the BMD of middle- and long-distance runners and race walkers and found that athletes had an LEA (21kcal/kg of FFM/day) (7). Athletes with a moderate EA generally had better z-scores than the LEA athletes; however, the differences were not statistically significant. Similarly, Õnnik et al. (2022) found that high-level Kenyan male distance runners had an average EI of 1581kcal, and male controls had an average EI of 1454kcal per day. The male athletes did not show a statistically significant difference in BMD (p = 0.293) compared to the male control group, with only one runner (out of 20) at risk for osteoporosis (lumbar spine z-score <1.0) (23). Cyclists are at the highest risk for poor bone health due to chronic LEA, reduced osteogenic simulation, and low levels of impact or resistance (26). Keay et al. (2018) assessed the efficacy of a sport-specific EA questionnaire and clinical interview (SEAQ-I) in British professional cyclists at risk of developing RED-S. Based on the results of the SEAQ-I, 28% (n=14) were identified with LEA, and 44% of the cyclists had low lumbar spine BMD (z-score <-1.0) (p< 0.001). Also, cyclists with a history of lack of load-bearing sports or activities had the lowest BMD (p= 0.013) (13). This study demonstrates a clear association between LEA and reduced lumbar spine BMD in professional cyclists. In a randomized controlled trial, Keay et al. (2019) investigated the efficacy of an educational intervention with British competitive cyclists to improve energy availability and bone health. The researchers induced LEA by 25% (mean EA of 22.4 ± 6.3kcal/kg of FFM/day) for 14 days. Athletes who implemented nutritional strategies (provided by nutrition professionals) to improve EA and strength training strategies to improve skeletal loading saw lumbar spine BMD improvements. Mean vitamin D levels significantly improved from pre-season (90.6 ± 23.8 nmol/L) to post-season (103.6nmol/L; p=0.0001). Calcium, correct calcium, and alkaline phosphatase had no statistically significant changes between pre-season and post-season (12). Keay et al. have established the prevalence of LEA and poor bone health in cyclists and demonstrated nutrition education efficacy for BMD improvements. Noteworthy findings such as these help to raise awareness in the cycling community and can inform preventative or rehabilitative strategies.

BODY COMPOSITION Body composition is the distinction between fat mass and fat-free mass. Fat-free mass includes water, tissue, organs, bones, and muscle (e.g., skeletal muscle). Body composition control and maintenance are essential for an athlete’s health, performance, and mindset. Research measurements of body composition include weight, body mass index, body fat percentage, lean mass, and water content. According to Lundy et al. (2022), a body mass index <18.5 kg/m2 is a primary indicator of LEA; this suggests body composition changes in response to LEA (16). What is the impact of LEA on body composition? Stenqvist et al. (2020) implemented a four-week intensified endurance training designed to increase aerobic performance and elevate body composition’s impact on well-trained cyclists. The results did not show statistically significant changes in energy intake, body weight, fat mass, or fat-free mass. Body weight loss was potentially averted due to reduced resting metabolic rate as a protective mechanism (27). Whereas Stenqvist et al. (2020) focused on increasing EEE, Jurov et al. (2021) attempted to induce LEA via EI manipulation. Jurov et al. (2021) progressively reduced EA by 50% for 14 days in well-trained and elite endurance male athletes; the results showed no significant changes in body mass and fat-free mass (9). Regarding resistance training and LEA, Murphy and Koehler (2022) conducted a meta-analysis to quantify the discrepancy in lean mass accretion between interventions providing resistance training in an energy deficit and those without an energy deficit. The literature findings demonstrated lean mass gains impairment in athletes resistance training in an energy deficit compared to those training without an energy deficit (significantly, p = 0.02). The results also surmised that an energy deficit of as much as 500kcal/day could impede lean mass gains (21). Roth et al. (2023) evaluated the impact of a relatively high- versus moderate volume resistance training program on alterations in lean mass during caloric restriction in male weightlifters. The results showed that whole-body lean mass significantly declined in both groups (high and moderate volume groups) following six weeks of energy restriction. The high-volume group had an EA of 31.7 ± 2.8kcal/kg of FFM/day, and the moderate-volume group had an EA of 29.3 ± 4.2kcal/kg of FFM/day (25). Both studies demonstrate that muscle hypertrophy is unattainable in the presence of LEA. Furthermore, Murphy and Koehler (2020) found that three days of caloric restriction at an EA of 15kcal/kg of FFM/day in recreational weightlifters resulted in significant reductions in weight (p<0.01), fat mass (p<0.01), and lean mass (p<0.001). Also, the total mass loss was significant (p<0.01) when compared to a control group (EA of 40kcal/kg of FFM/day) (20). The results of studies focused on resistance training and caloric restriction hold applicability for athletes in sports that rely on lean mass gains while manipulating EI, such as bodybuilding (4).

CARDIORESPIRATORY ENDURANCE Cardiorespiratory endurance (CRE) is the ability of the lungs, heart, and blood vessels to deliver sufficient oxygen to cells to meet the physiological demands of exercise and physical activity (8). Evaluating maximal oxygen uptake or VO2max is a standard CRE measure. A VO2 max of 67.9 ± 7.4 mL/kg/min is categorized as a high fitness level (28). What is the impact of induced LEA on CRE performance outcomes? Jurov et al. (2021) investigated the endurance performance impact of progressively reducing energy availability by 50% for 14 days in well-trained and elite endurance male athletes. The researchers increased EEE to achieve a mean energy availability of 17.3 ± 5 kcal/kg of FFM/day. The results showed lowered EA reduced endurance performance, as indicated by respiratory compensation point (RC) and VO2max. Jurov et al. (2022b) reduced EA by 25% (by increasing EEE and controlling EI) in trained endurance male athletes and monitored for aerobic performance changes. The results showed that inducing LEA by 25% (mean EA of 22.4 ± 6.3kcal/kg of FFM/day) for 14 days reduced hemoglobin levels, indirectly impacting VO2max and aerobic performance (11). Beyond research conducted by Dr. Iva Jurov and colleagues, there is insufficient experimental research on LEA and CRE.

MUSCULAR STRENGTH AND ENDURANCE In recent years, few experimental studies have evaluated the impact of LEA on muscular strength, endurance, and athletic performance. Research on athletic performance and LEA has shown that endurance athletes with an EA of 17.3 ± 5 kcal/kg of FFM/day show no reductions in agility t-tests, power output, or countermovement jump results, indicating no association with EA (9). Also, Jurov et al. (2022b) found that a mean EA of 22.4 +/- 6.3kcal/kg of FFM/day in endurance male athletes for 14 days results in significant changes to explosive power (countermovement jump) but not agility t-tests (11). Furthermore, Jurov et al. (2022a) also reduced EA (via increasing exercise energy expenditure and controlling energy intake) in male endurance athletes to evaluate performance and muscular power impact. The results showed significant reductions in explosive power (measured via vertical jump height test) at a mean EA of 22.4, 17.3, and 8.82 kcal/kg of FFM/day. Based on these findings, athletes reach the LEA threshold after a long time in an energy-deficient state, such as ten to 14 days (10). However, Stenqvist et al. (2020) aimed to measure peak power in male cyclists after four weeks of intensified endurance training. The results showed that the cyclists significantly improved their peak power output (4.8%, p < 0.001) and functional threshold power (6.5%, p < 0.001) measured via stationary bike. Possibly, the EEE of the intervention was insufficient to induce LEA but instead induced the Specific Adaptation to Imposed Demands (SAID) principle in the athletes (27). Regarding weightlifters, Murphy and Koehler (2022) studied whether energy deficiency impairs strength gains in response to resistance training. This research study was a meta-analysis of randomized controlled trials. The study findings showed that strength gains were comparable between resistance training groups in either an energy deficit or a balance state. These results demonstrated that low energy availability for prolonged periods (i.e., RED-S) did not impede strength output (21). There are a few studies that report bodybuilders with strength declines with estimations of EA <20 kcal/kg of FFM/day (4). The theory remains that inadequate energy intake will inevitably reduce muscular strength and output.

LOW ENERGY AVAILABILITY THRESHOLD To date, optimal EA levels and the threshold for LEA in male athletes are under investigation. However, many research studies are cross-sectional, only demonstrating a correlation between athletes and energy availability (e.g., LEA commonly found in endurance athletes). The scant number of current experimental studies often fail to induce LEA and thereby fail to establish clear LEA thresholds. To prevent LEA and subsequent conditions such as RED-S and MAT, athletes need to maintain their energy availability. Primarily, athletes need to ensure adequate EI and carefully manage their EEE. Current EA “zones” for female athletes are also applied to male athletes until experimental research can demonstrate a need for separate guidelines. EA >45kcal/kg of FFM/day supports body mass gain and maintains healthy physiological functions; 45kcal/kg of FFM/day is optimal for weight maintenance and healthy physiological functions; 30-45kcal/kg of FFM/day is considered suboptimal and at-risk for reduced physiological functions; and ≤30kcal/kg of FFM/day is considered low energy availability (1, 3, 4, 9, 10, 14, 17, 26). Research by Jurov and colleagues has demonstrated mixed results regarding performance outcomes, body composition, and bone health (9, 10, 11). Mean energy availability in those studies ranged between 17-22 kcal/kg of FFM/day (9, 11). Based on their research findings, Jurov and colleagues have proposed a range of 9-25kcal/kg of FFM/day (mean value of 17kcal/kg of FFM/day) for an LEA threshold (10). Regarding performance and body composition outcomes, Murphy and Koehler (2020) conducted a randomized, single-blind, repeated-measures crossover trial that showed three days of caloric restriction at an EA of 15kcal/kg of FFM/day induced considerable anabolic resistance to a heavy resistance training bout (20). In a case study by Langan-Evans et al. (2021), an EA of 20kcal/kg per FFM/day led to weight loss and fat loss without signs of MAT and RED-S. However, an EA of <10kcal/kg of FFM/day did result in signs and symptoms of MAT and RED-S, including disruptions to the hypothalamic-pituitary-gonadal axis, resting metabolic rate (measured), and resting metabolic rate (ratio) (14). Additionally, some LEA thresholds may need to be sport-specific. For instance, Fagerberg et al. (2018) suggest an LEA threshold of 20-25kcal/kg of FFM/day for male bodybuilders with a lower body fat percentage (4). Research to establish EA zones and an LEA threshold for male athletes continues, and guidelines primarily still consider ≤30kcal/kg of FFM/day appropriate for male athletes. However, some researchers have also contested that male athletes can go lower before exhibiting signs and symptoms of MAT and RED-S.

RESEARCH GAPS There are sizable research gaps regarding LEA and RED-S. First, this literature was unable to address the impact of LEA on endocrine, metabolic, hematological, and gastrointestinal health due to insufficient research published in the past five years. Mountjoy et al. (2018) identified the following research gaps: (1) lack of practical tools to measure and detect LEA and RED-S, (2) lack of validated prevention interventions for RED-S, (3) RED-s in male athlete research, (4) health and performance consequences of RED-S research, and (5) lack of evidence-based guidelines for treatment and return-to-play for athletes with RED-S. Research gaps focused on male athletes with MAT are even more prominent (19).

Moreover, Fredericson et al. (2021) listed several research gaps that need scientific attention, including screening protocols to detect MAT in adolescent and young males, identification of MAT energetic and metabolic impact factors, prevalence of DEED in male athletes with MAT, evaluating the efficacy and effectiveness of clearance and return-to-play protocols, risk assessment for BSI and poor bone health, prevalence of MAT in military recruits, health interventions on the prevention and treatment of MAT, and lastly, cutoff values (or threshold) for LEA (5). Addressing these research gaps would enable sports and health practitioners to effectively prevent and treat LEA, RED-S, and MAT, ensuring athlete health and sports performance.

SUMMARY LEA is defined as a physiological state when there is inadequate energy to meet the demands placed on the body, often through physical activity, exercise, or sports (23). LEA can impact any athlete engaged in a sport with low energy intake or excessive energy expenditure. LEA is a precursor to the onset of both The Male Athlete Triad (MAT) and Relative Energy Deficiency in Sport (RED-S), two conditions that result in weakened physiological functions, with the former focused on reproductive and bone health decline (22).

Recent literature has shown mixed results on LEA’s impact on immunological health, metabolic markers, bone health, body composition, cardiorespiratory endurance, and muscular strength and endurance. There has been little evidence to connect LEA and endocrine, metabolic, hematological, and gastrointestinal health. However, a notable causal relationship exists between LEA and psychological health and reproductive health. Currently, there is still no defined low energy availability threshold specific to male athletes, however, EA zones from 15-25kcal/kg of FFM/day may be appropriate based on current literature (4, 20, 10, 18, 22, 26).

APPLICATION TO SPORT Healthy nutritional practices are essential to sports performance. Interdisciplinary sports performance teams must collaborate with nutrition professionals such as Registered Dietitians accredited by the Commission on Dietetic Registration to develop effective LEA prevention, screening, and intervention protocols. Preventative measures must prioritize energy availability, modify sporting culture to encourage energy intake, and mitigate barriers to calorie- and nutrient-dense foods in male athletes. Screening protocols must include EA evaluations based on dietary intake, exercise energy expenditure, and fat-free mass measured via DXA or bioelectrical impedance analysis. Male athletes with an EA ≤20-25kcal/kg of FFM/day must receive nutritional guidance to reduce health and performance impairments. Intervention protocols must be enacted when LEA is confirmed and should primarily focus on increasing energy intake, decreasing energy expenditure, and addressing other associated aspects such as psychological health. Athletes, coaches, and practitioners must raise LEA awareness, dispel energy consumption stigmas, and foster an environment where food and nutrition fuel peak performance.

ACKNOWLEDGEMENTS This work was supported by the Pennsylvania Western University Department of Exercise, Health, and Sport Sciences. The author would like to thank Dr. Marc Federico and Dr. Brian Oddi for their guidance and feedback on the manuscript

• Burke, L., Deakin, V., Minehan, M. (2021). Clinical sports nutrition. (6th ed.). Sydney, Australia: McGraw Hill Education.
• Burke, L. M., Lundy, B., Fahrenholtz, I. L., & Melin, A. K. (2018). Pitfalls of conducting and interpreting estimates of energy availability in free-living athletes. International Journal of Sport Nutrition & Exercise Metabolism, 28(4), 350–363. https://doi.org/10.1123/ijsnem.2018-0142
• Egger, T., & Flueck, J. L. (2020). Energy availability in male and female elite wheelchair athletes over seven consecutive training days. Nutrients, 12(11). https://doi.org/10.3390/nu12113262
• Fagerberg, P. (2018). Negative consequences of LEA in natural male bodybuilding: A review. International Journal of Sport Nutrition & Exercise Metabolism, 28(4), 385–402. https://doi.org/10.1123/ijsnem.2016-0332
• Fredericson, M., Kussman, A., Misra, M., Barrack, M. T., De Souza, M. J., Kraus, E., Koltun, K. J., Williams, N. I., Joy, E., & Nattiv, A. (2021). The male athlete triad- A consensus statement from the female and male athlete triad coalition part II: Diagnosis, treatment, and return-to-play. Clinical Journal of Sport Medicine, 31(4), 349–366. https://doi.org/10.1097/JSM.0000000000000948
• Hattori, S., Aikawa, Y., & Omi, N. (2022). Female athlete triad and male athlete triad syndrome induced by low energy availability: An animal model. Calcified Tissue International, 111(2), 116–123. https://doi.org/10.1007/s00223-022-00983-z
• Heikura, I. A., Uusitalo, A. L. T., Stellingwerff, T., Bergland, D., Mero, A. A., & Burke, L. M. (2018). Low energy availability is difficult to assess, but outcomes have a large impact on bone injury rates in elite distance athletes. International Journal of Sport Nutrition & Exercise Metabolism, 28(4), 403–411. https://doi.org/10.1123/ijsnem.2017-0313
• Hoeger, W. W., Hoeger, S. A., Hoeger, C. I., & Fawson, A. L. (2019). Lifetime physical fitness & wellness: A personalized program (15th ed.). Boston, MA: Cengage Learning.
• Jurov, I., Keay, N., & Rauter, S. (2021). Severe reduction of energy availability in controlled conditions causes poor endurance performance, impairs explosive power, and affects hormonal status in trained male endurance athletes. Applied Sciences (2076-3417), 11(18), 8618. https://doi.org/10.3390/app11188618
• Jurov, I., Keay, N., & Rauter, S. (2022a). Reducing energy availability in male endurance athletes: A randomized trial with a three-step energy reduction. Journal of the International Society of Sports Nutrition, 19(1), 179–195. https://doi.org/10.1080/15502783.2022.2065111
• Jurov, I., Keay, N., Spudić, D., & Rauter, S. (2022b). Inducing LEA in trained endurance male athletes results in poorer explosive power. European Journal of Applied Physiology, 122(2), 503–513. https://doi.org/10.3389/fendo.2020.512365
• Keay, N., Francis, G., Entwistle, I., & Hind, K. (2019). Clinical evaluation of education relating to nutrition and skeletal loading in competitive male road cyclists at risk of RED-Ss (RED-S): 6-month randomised controlled trial. BMJ Open Sport & Exercise Medicine, 5, 1–8. https://doi.org/10.1136/bmjsem-2019-000523
• Keay, N., Francis, G., & Hind, K. (2018). Low energy availability assessed by a sport-specific questionnaire and clinical interview indicative of bone health, endocrine profile and cycling performance in competitive male cyclists. BMJ Open Sport & Exercise Medicine, 4(1), e000424. https://doi.org/10.1136/bmjsem-2018-000424
• Langan-Evans, C., Germaine, M., Artukovic, M., Oxborough, D. L., Areta, J. L., Close, G. L., & Morton, J. P. (2021). The psychological and physiological consequences of LEA in a male combat sport athlete. Medicine & Science in Sports & Exercise, 53(4), 673–683. https://doi.org/10.1249/MSS.0000000000002519
• Langbein, R. K., Martin, D., Allen-Collinson, J., Crust, L., & Jackman, P. C. (2021). “I’d got self-destruction down to a fine art”: A qualitative exploration of relative energy deficiency in sport (RED-S) in endurance athletes. Journal of Sports Sciences, 39(14), 1555–1564. https://doi.org/10.1080/02640414.2021.1883312
• Lundy, B., Torstveit, M. K., Stenqvist, T. B., Burke, L. M., Garthe, I., Slater, G. J., Ritz, C., & Melin, A. K. (2022). Screening for low energy availability in male athletes: Attempted validation of LEAM-Q. Nutrients, 14(9), 1873. https://doi.org/10.3390/nu14091873
• McGuire, A., Warrington, G., & Doyle, L. (2020). LEA in male athletes: A systematic review of incidence, associations, and effects. Translational Sports Medicine, 3(3), 173–187. https://doi.org/10.1002/tsm2.140
• Moris, J. M., Olendorff, S. A., Zajac, C. M., Fernandez-del-Valle, M., Webb, B. L., Zuercher, J. L., Smith, B. K., Tucker, K. R., & Guilford, B. L. (2022). Collegiate male athletes exhibit conditions of the male athlete triad. Applied Physiology, Nutrition & Metabolism, 47(3), 328–336. https://doi.org/10.1139/apnm-2021-0512
• Mountjoy, M., Sundgot-Borgen, J., Burke, L., Ackerman, K. E., Blauwet, C., Constantini, N., Lebrun, C., Lundy, B., Melin, A., Meyer, N., Sherman, R., Tenforde, A. S., Torstveit, M. K., & Budgett, R. (2018). International olympic committee (IOC) consensus statement on relative energy deficiency in sport (RED-S): 2018 update. International Journal of Sport Nutrition & Exercise Metabolism, 28(4), 316–331. https://doi.org/10.1123/ijsnem.2018-0136
• Murphy, C., & Koehler, K. (2020). Caloric restriction induces anabolic resistance to resistance exercise. European Journal of Applied Physiology, 120(5), 1155–1164. https://doi.org/10.1007/s00421-020-04354-0
• Murphy, C., & Koehler, K. (2022). Energy deficiency impairs resistance training gains in lean mass but not strength: A meta‐analysis and meta‐regression. Scandinavian Journal of Medicine & Science in Sports, 32(1), 125–137. https://doi.org/10.1111/sms.14075
• Nattiv, A., De Souza, M. J., Koltun, K. J., Misra, M., Kussman, A., Williams, N. I., Barrack, M. T., Kraus, E., Joy, E., & Fredericson, M. (2021). The male athlete triad- A consensus statement from the female and male athlete triad coalition part 1: Definition and scientific basis. Clinical Journal of Sport Medicine, 31(4), 335–348. https://doi.org/10.1097/JSM.0000000000000946
• Õnnik, L., Mooses, M., Suvi, S., Haile, D. W., Ojiambo, R., Lane, A. R., & Hackney, A. C. (2022). Prevalence of triad-red-s symptoms in high-level Kenyan male and female distance runners and corresponding control groups. European Journal of Applied Physiology, 122(1), 199–208. https://doi.org/10.1007/s00421-021-04827-w
• Perelman, H., Schwartz, N., Yeoward, D. J., Quiñones, I. C., Murray, M. F., Dougherty, E. N., Townsel, R., Arthur, C. J., & Haedt, M. A. A. (2022). Reducing eating disorder risk among male athletes: A randomized controlled trial investigating the male athlete body project. International Journal of Eating Disorders, 55(2), 193–206. https://doi.org/10.1002/eat.23665
• Roth, C., Schwiete, C., Happ, K., Rettenmaier, L., Schoenfeld, B. J., & Behringer, M. (2023). Resistance training volume does not influence lean mass preservation during energy restriction in trained males. Scandinavian Journal of Medicine & Science in Sports, 33(1), 20–35. https://doi.org/10.1111/sms.14237
• Schofield, K. L., Thorpe, H., & Sims, S. T. (2021). Where are all the men? LEA in male cyclists: A review. European Journal of Sport Science, 21(11), 1567–1578. https://doi.org/10.1080/17461391.2020.1842510
• Stenqvist, T. B., Torstveit, M. K., Faber, J., & Melin, A. K. (2020). Impact of a 4-week intensified endurance training intervention on markers of RED-S (RED-S) and performance among well-trained male cyclists. Frontiers in Endocrinology, 11. https://doi.org/10.3389/fendo.2020.512365
• Sui, X., LaMonte, M. J., & Blair, S. N. (2007). Cardiorespiratory fitness as a predictor of nonfatal cardiovascular events in asymptomatic women and men. American Journal of Epidemiology, 165(12), 1413–1423.
• Tam, N., Santos-Concejero, J., Tucker, R., Lamberts, R. P., & Micklesfield, L. K. (2018). Bone health in elite Kenyan runners. Journal of Sports Sciences, 36(4), 456–461. https://doi.org/10.1080/02640414.2017.1313998

Order of passive and interactive sports consumption and its influences on consumer emotions and sports gambling

Qshequilla Parham Mitchell 2024-10-11T13:41:23-05:00 October 11th, 2024 | Research , Sports Studies |

Authors: Anthony Palomba 1 , Angela Zhang 2 , and David Hedlund 3

1 Department of Communication, Darden School of Business, University of Virginia, Charlottesville, VA, USA 2 Department of Public Relations, Gaylord College of Journalism and Mass Communication, The University of Oklahoma, Norman, OK, USA 3 Department of Sport Management, Collings College of Professional Studies, St. John’s University, Queens, NY, USA

Anthony Palomba

100 Darden Blvd.

Charlottesville, VA, 22903

Anthony Palomba is an assistant professor of business administration at the Darden School of Business at the University of Virginia. He is fascinated by media, entertainment, and advertising firms. First, his research explores how and why audiences consume entertainment, and strives to understand how audience measurement can be enhanced to predict consumption patterns. Second, he studies how technological innovations influence competition among entertainment and media firms. Third, he is interested in incorporating machine learning and artificial intelligence tools to better understand consumer and firm behaviors.

Angela Zhang is an assistant professor in public relations. Her research interests span both corporate crisis communication and disaster risk communication in natural and manmade disasters. Her research primarily aims to understand how people process crisis and risk information and how we can communicate better during crises. For example, her work examines how linguistic cues in crisis messages affect people process crisis information, how and why risk information is propagated on social media, and how users communicate and cope on social media after crises. For corporate crisis communication, her research examines effectiveness of crisis prevention strategies such as CSR and DEI communication, as well as crisis response strategies.

Dr. Hedlund is an Associate Professor and the Chairperson of the Division of Sport Management, and he has more than twenty years of domestic and international experience in sport, esports, coaching, business and education. As an author, Dr. Hedlund is the lead editor of the first textbook ever published on esports titled Esports Business Management, and he has more than 30 additional journal, book chapter and related types of publications, in addition to approximately 50 research presentations. In recent years, Dr. Hedlund has acted as a journal, conference and book reviewer for sport, esports and business organizations from around the world, and he is an award-winning reviewer and editorial board member for the International Journal of Sports Marketing and Sponsorship.

This study explores how alternating between video game and television experiences influences consumer emotions and subsequent decision-making. Findings indicate that playing a video game after watching a video clip enhances positive emotions (H1 supported) and affects post-experiment betting scores based on pre-experiment gambling bets (H2 supported). Winning teams in video games and elevated positive emotions also positively influence post-experiment betting scores (H3 and H4 partially supported). The interaction effect shows that the sequence of media consumption (TV to video game) increases betting scores (H5 supported). The study contributes to understanding how appraisal tendency theory and mood management theory explain the impact of media consumption order on sports gambling decisions. Video games, as interactive stimuli, elevate consumer moods and influence betting behavior more than passive viewing. Practically, integrating video game and video clip data aids comprehensive audience measurement and targeted advertising strategies, advancing algorithmic forecasting in enhancing consumer engagement and decision-making.

Key Words: Mood management, Appraisal tendency theory, sports, gambling, video games

   introduction.

            The NFL is one of the most powerful media and entertainment brands in the marketplace, routinely curating legions of television and online video viewers for every annual season. In 2019, it averaged about 16.5 million viewers per game, roughly 33% above the 12.43 million viewing average for the top six non-sports programs (Porter, 2021). Additionally, over the last thirty years, the Madden NFL video game franchise has introduced generations to simulated immersive engagement. The legalization of sports gambling (Cason et al., 2020) has expanded how consumers can further engage with the NFL. NFL executives have discussed using mobile cell phones to aid sports fans in stadiums to make live bets throughout the course of a game (Martins, 2020). Audiences can watch the NFL and NFL game day content on the Xbox One, including up to date news and highlights from select NFL teams (Tuttle, 2016). Given these diverse modes of engagement, consumers often switch across a multitude of different activities. This frequent medium switching can significantly impact their moods and, subsequently, how they execute various tasks, including sports gambling. The phenomenon of media multitasking, where consumers engage with multiple forms of media simultaneously, complicates how they regulate their moods and make subsequent decisions (Deloitte, 2018). Younger consumers, in particular, are more inclined to switch between media than older consumers (Beuckels et al., 2021).

            The increasingly diverse modes of engagement with the NFL, spanning from live game viewing and video game simulations to real-time betting, have led to a phenomenon of frequent media switching among consumers. This constant toggling between different platforms and activities can significantly impact their emotional states, subsequently influencing their decision-making processes, including those related to sports gambling. While previous research has examined task switching in general contexts (Yeykelis, Cummings, & Reeves, 2014) and the impact of media multitasking on advertising (Garaus, Wagner, & Back, 2017), the specific application of appraisal tendency theory to understand how these rapid emotional shifts induced by media switching affect sports gambling behaviors remains largely unexplored. Moreover, social media use while viewing television, a phenomenon that has grown in the last decade, has reconfigured the commodification of audiences, and has also created different markets to understand how consumers multi-task, and how to measure audience engagement (Kosterich & Napoli, 2016). Uniquely, social media may be used to track propensity to make season ticket purchases (Popp et al., 2023) among other sports consumption activities (Du et al., 2023). Recent studies have implicated the legalization of sports gambling as potentially increasing fandom and engagement among fans, and can further elevate communication across stakeholders involved in a sports event (Stadder & Naraine, 2020).

There is a gap in understanding, however, how consumer judgments and decisions are informed by emotions (Han, Lerner, & Keltner, 2007). Understanding this dynamic is critical for comprehending the evolution of fandom and identifying how sports teams can further engage fans. As consumers navigate between watching games, participating in video game simulations, and placing live bets, their engagement strategies and emotional states may significantly influence their decisions and loyalty. By examining these interactions, sports organizations can develop more effective methods to maintain and enhance fan engagement in an increasingly digital and interconnected world.

            The implications of this study are broad and vast for academics along with sports and entertainment managers. The complex nature of media switching in sports consumption furthers our understanding of how affective disposition theory may be applied toward the multi-platform and multi-activity nature of modern sports engagement. It could lead to the development of a more nuanced understanding of how affective dispositions are formed and how they influence decision-making in this context. Microsoft (parent brand of Xbox console series) and the NFL have an agreement in which the NFL can provide fantasy football scores and updates on Xbox One consoles and allow fans to stream certain NFL games from their Xbox One consoles (Chansanchai, 2016). Additionally, Microsoft is able to trace not only what consumers play on Xbox One consoles, but also what TV or SVOD viewing apps fans engage to view content. Together, disparate information on video game play and video viewing can be combined to further identify trends in cross-platform sports consumption behavior and inferred consumer emotional states, which can help illuminate how consumer judgement surrounding sports gambling may be impacted.

NFL INDUSTRY

            The National Football league has been a celebrated sports league in the United States and abroad over the last one hundred years. It draws the highest attendance per professional sports game in the United States, at about sixty-six thousand, and during its 2019 season, it hosted nearly sixteen million total viewers per game (Gough, 2021). The total revenue of all NFL teams was slightly over $15 billion in 2019, and average franchise value was just over $3 billion in 2020. Sports betting on Super bowls alone in Nevada accrued nearly $160 million in 2020 (Gough, 2021). While there are no clear figures regarding sports merchandise sales, NFL revenue by team in 2019 was led by the Dallas Cowboys ($980 million), New England Patriots ($630 million), NY Giants ($547 million) and Houston Texans ($530 million) through last place Las Vegas Raiders ($383 million) (Gough, 2020).

            Aside from tickets, television revenue, and merchandise, the NFL has produced different avenues to engage fan bases. The league has recently embraced sports partnerships with Caesars Entertainment, Draft Kings and FanDuel. This allows these three external partners to engage in retail and online sports betting and engage with fans as well, using sports content from NFL media, as well as data, to market these experiences to fans (NFL, 2021). In fact, the NFL is expected to earn just over $2 billion annually from the sports gambling marketplace (Chiari, 2018). The NFL’s current TV media deals across CBS, ABC/ESPN, NBC, and Fox earn it just over $10 billion per season (Birnbaum, 2021). Arguably, one of the NFL’s highest profile merchandise revenue streams comes from its partnership with Electronic Arts (EA) to release an annual, updated version of Madden NFL , generating roughly $600 million annually for EA (Reyes, 2021). By embracing diverse engagement avenues, the NFL not only diversifies its revenue streams but also caters to the evolving preferences of modern sports consumers. This multi-faceted approach reflects the league’s recognition of the complex interplay between media consumption, mood, and fan behavior, ultimately enhancing the overall fan experience in an increasingly digital and interconnected world.

NFL FOOTBALL AS A VIDEO GAME EXPERIENCE: MADDEN NFL

            There are few video games that possess the dominance and market monopolization as does the Madden NFL franchise. It exists as the only simulated NFL football video game available to consumers (Sarkar, 2020), and it is markedly popular among consumers. In fact, for the last twenty years, every Madden NFL video game installation has debuted as the top selling U.S. game in August each year (Wilson, 2022). The video game franchise itself has blossomed into its own celebrated video game season, as video game play expectedly rises during August in anticipation for the upcoming NFL season (Skiver, 2022). Madden NFL fans have been found to be more devoted and knowledgeable about the NFL. Additionally, they are less likely to miss viewing football games on Sundays, as 42% have stated they never miss a football game due to external activities. They are likely to attend at least one NFL game each annual season (IGN Staff, 2012).

            Video gamers’ moods and subsequent judgment may be impacted by their own experiences. Video game play is an immersive experience, as the required technology helps to transport users into a digital world. The level of presence that is achieved can amplify mediated environment perceived quality, user effects, as well as overall experience (Tamborini & Bowman, 2010). Consumer familiarity with video game play may also influence how they experience presence (Lachlan & Krcmar, 2011). Consumers who view NFL games and play NFL video games may experience wins and loss outcomes in both passive and interactive manners. Sports video game play is motivated by possessing deep passion for the sport, gaming interest, entertainment value, competition, and identifying with the team or sport itself (Kim & Ross, 2006). Consumer emotions can be volatile during sports engagement, as winning and losing can impact overall game satisfaction (Yim & Byon, 2018). Emotions are tied to sports engagement in a primal manner, as consumers vicariously live through sports athletes and align themselves with sports teams, invoking a type of tribalism (Meir & Scott, 2007).

MOOD MANAGEMENT THEORY

               Mood management theory concerns how consumers may manage their own moods through consumption of different mediums. Zillmann (1988) states that there are several traits that may impact whether a medium may repair or enhance a particular mood. First, there is the excitatory potential, or how exciting a message may be for consumers. Second, there is absorption potential, which examines how well a media message will be absorbed by an individual. Third, there is the semantic affinity, which relates to the connection from the current participant mood to a media message, which can moderate the impact of absorption potential. Finally, there is hedonic valence, in which pleasant messages can interrupt consumers’ bad moods (Zillmann, 1988). This study is focused on exploring how consumers’ gambling decisions are influenced by their experiences, both positive and negative, related to predicting scores between teams, and placing a bet on them. Specifically, it aims to investigate the impact of semantic affinity and the excitatory potential of stimuli involved in the process on consumer decision-making in gambling contexts.

               Sports viewing or sports video game play can lead to evaluated states of physiological and psychological arousal, stirring hostile or expressive responses to game outcomes. Arousal has been found to be precipitated by aggressive or hostile states (Zillman, 1983), based on events during the game (Berkowitz, 1989). Hostility can be traced to the dissatisfaction with an outcome, or inability to attain a desired goal. Viewing violent sports competition can also heighten hostility and create greater inclinations toward aggressive behavior. Participants who had high identification with America and viewed an American boxer against a Russian boxer were found to have elevated blood pressure compared to those who had low identification with American (Branscombe & Wann, 1992). Additionally, spectators that have high team identification have higher levels of happiness compared to those with low team identification. The way a message is delivered can impact the effect of a message on consumers, as there are distinct characteristics related to each medium (Dijkstra, Buijtels & van Raaij, 2005).

               Mood management is clearly influential as to how participants respond to video and video game play. Participants who may feel frustration may feel further frustration from viewing violent content (Zillmann & Johnson, 1973). One study by Bryant and Zillmann illustrated that participants who view violent sports did not experience mood repair (Donohew, Sypher, & Higgens,1988). Fulfillment of intrinsic needs can influence selection of video games with varying levels of participant demand (Reinecke et al., 2012). Television has been found to reduce boredom and stress among consumers (Bryant & Zillmann, 1984). In managing moods, this can also impact subsequent decision-making, sometimes surreptitiously and without awareness from participants.

APPRAISAL TENDENCY THEORY

            Appraisal tendency theory considers how different types of emotions within similar valences (e.g., anger and fear) may impact judgement. There are two types of influences that may impact how consumers make judgments. Integral emotion is based on individual experiences that might preempt but be relevant to a subsequent decision. Differently, incidental emotion is due to conceivably irrelevant though impactful elements that can inform decision-making, which may include being influenced by traffic, watching television, or engaging in other non-relevant actions. These influences can carry over to the decision-making process (Schwarz & Clore, 1983; Bodenhausen, Kramer, & Susser, 1994). Moreover, consumers who are angry tend to perceive less risk from engaging in new situations (Han, Lerner, & Keltner, 2007).

            Integral emotion is under examination in this study, as an outcome from a related medium stimulus can impact a subsequent decision that is likely informed by that stimulus. After finding that they have won in a video game, it may be that consumers are less inclined to bet against the team that they just lost against. This subjective pain(joy) based on the first stimulus may be stronger from playing a video game than from viewing a sports clip. Moreover, consumers may seek variety in consumption decisions when they are induced to a negative emotion (Chuang, Kung, & Sun, 2008). Therefore, subsequent decision-making may be informed by the order of passive and interactive media consumed by each individual.

MEDIUM MODALITY

               Mediums that engage multiple senses are likely to lead to impactful communication with consumers (Jacoby, Hoyer & Zimmer, 1983). Television offers engagement through visual and auditory senses, while gaming stimulates both but creates an immersive experience, in which consumers are transported into a virtual world (Kuo, Hiler, & Lutz, 2017). Differently, consumers do not have control over passive mediums such as television, as the content is predetermined and is under the yolk of the sender, creating different delivery systems (Van Raaij, 1998). Video game play offers opportunities for players to speed up game play, based on gaming flexibility as well as how quickly a consumer can finish tasks. Video game play is positioned to evoke cognitive responses, through the speed of information dissemination, since the consumer possesses more control over the experience. Conflated with the demanded attention from video game play, consumers will likely have greater affective responses from video game play than from video viewing (Dijkstra, Buijtels, & van Raaij, 2005).

               In consideration of this study, it follows that the simulated aspect of video game play can further influence decision-making. Consumers are inclined to experience improved decision-making and risk assessment through video game play (Reynaldo et al., 2020), as well as cognitive tasks (Chisholm & Kingstone, 2015). Video game play may also induce lowered physiological stress (Russoniello, O’Brien, & Parks, 2009), and emotional regulation (Villani et al., 2018). While there is scant research surrounding video game play simulations and making subsequent real-life decisions, it is ostensibly clear that video game play can heighten and sharpen decision-making skills as well as emotion regulation. Consumers who are attentive toward a simulated video game play experience may be influenced by its outcome in making a subsequent decision. This can include perceiving the winning team in the simulated game as likely to beat the same opposing team in a real-life match up.

H1: Consumers who play a video game (view a video clip) first will be more inclined to have lower (higher) positive emotions.

SPORTS GAMBLING

               Recently, sports gambling has become legalized or recent legislation has been passed to make it legal in 50% of states in the United States (Rodenberg, 2021). While fans have placed bets on horse-racing and even major league sports, its legalization provides a lawful and safe forum for myriad fans to place bets on teams. However, since many gamblers may not invest time in understanding spreads and other esoteric metrics that gambling managers may use to measure likelihoods of outcomes, playing a Madden NFL game can serve consumers to anticipate potential outcomes in real life match ups. Madden NFL’s algorithms have been harvested in the past to predict Super Bowl outcomes. In fact, EA typically runs one hundred simulations to predict which team will win each year in the Super Bowl (Wiedey, 2020). Additionally, fans are also able to make wagers on major league baseball simulated video games (Cohen, 2020). Younger sports fans may be more inclined to play Madden NFL games as a way to simulate outcomes, and become more familiar with teams to anticipate actual game outcomes. Additionally, sports gamblers are betting on simulated sports, in which Madden NFL video games are simulated through the popular video game streaming site Twitch, and consumers are able to bet on the outcome (Campbell, 2021).   

               Previous studies have highlighted why consumers engage in sports gambling. One study found that consumers engage in sports gambling to seek out social interaction and relaxation through engagement with betting apps, though their effect on problematic gambling and non-problematic gambling varied across these dimensions (Whelan et al., 2021). Consumers may seek out consumer purchases as a way to blunt negative emotions, or may further satiate their positive mood by pursuing purchases that bring them joy. Video game play can engender excitatory potential, stimulating arousal levels and inspiring consumers in negative moods to make consumer purchases or execute notably different gambling bets. The heightened arousal levels experienced by consumers during video game play can create greater vacillation in subsequent decision-making, including sports gambling bets. Tangentially related to this, if a consumer is in a positive mood, this optimism may impact their inclination to bet more on a sports match up. Additionally, the order of engaging a passive medium versus an interactive medium is critical to analyze. Video game play can heighten immersion in content, and provide further confidence in a team. Consumers may be able to participate in high-scoring video game match ups. Additionally, consumers may be spurred to bet on characters with whom they have virtual relationships (Palomba, 2020). Finally, video game play can lead to experiencing dopamine release, leading to greater felt pleasure (Koepp et al., 1998). Together, these may lead consumers to have greater optimism for post-betting scores.

H2: Consumer pre-experiment bet scores will have an anchoring effect and still inform post-experiment bet scores.

H3: The team that wins in the video game will have a greater positive relationship with post experiment bet scores than the team with the highest score in the video clip.

H4: Consumers who experience strong positive (negative) emotions after viewing a video clip will positively (negatively) influence post-experiment bet scores.

H5: Consumption order and time will have an interaction effect that when consumption order is VG to TV, betting scores will decrease from pre-betting to post-betting (pre-betting will be higher than post-betting); when consumption order is TV to VG, betting scores will increase from pre-betting to post-betting (pre-betting will be lower than post-betting).

               A 4×2 experiment was conducted here, in which participants were exposed to one of four different video clips, and one of two outcomes in a video game play match up. The New York Giants and Dallas Cowboys were the two teams that were selected for this experiment. Since this experiment took place in the mid-Atlantic region, it was believed that participants were less inclined to like either team. Moreover, these two teams have a storied and high-profile rivalry between them. For the video stimulus, participants were exposed to a randomized video clip highlighting a matchup between the NY Giants and Dallas Cowboys, in which one of four scenarios appeared: a) The NY Giants win by a wide margin (20 points), b) The NY Giants win by a slim margin (3 points), c) The Dallas Cowboys win by a slim margin (3 points), and d) The Dallas Cowboys win by a wide margin (20 points). Each video clip was about five minutes long. The video game stimulus involved playing a Madden NFL video game match up on an Xbox One video game console between the NY Giants and Dallas Cowboys. Participants were able to select which team they desired to play as and in which stadium to play in. The quarters in the Madden NFL game were kept at the default setting of six minutes each, ensuring participants experienced immersion but also maintained the experience to be similar to viewing the video clip.

               Participants in the A condition (VG to TV) first played the video game followed by viewing the video clip, and participants in the B condition (TV to VG) first viewed the video clip followed by the video game play. as well as playing a Madden NFL session implicating both teams. After each condition, participants were asked to evaluate their current emotions. After the video clip, participants were asked to state the final score and which team won in the clip to ensure that they were paying attention to the clip itself. Moreover, after the video game condition, participants were asked to state which team they played as, the final score, as well as what sports stadium they played in.

               To measure fandom, a scale from (Wann, 2002) was used here. It consisted of statements regarding self-assessment of fandom, including statements such as “I consider myself to be a football fan,” “My friends see me as a football fan,” and “I believe that following football is the most enjoyable form of entertainment.” It was measured on a 1 (strongly disagree) to 5 (strongly agree) Likert scale.

               To measure current emotions, a scale from Diener and Emmons (1984) was used here. The scale consisted of emotions statements including “joy,” “pleased,” “enjoyment,” “angry,” and other emotion statements. It was measured on a 1 (not at all) to 7 (extremely much) Likert scale.

               It was believed that the current emotions scale, though exhaustive, did not capture extreme aggression that may be felt by sports fans. An ancillary aggression scale (Sinclair 2005; Spielberger, 1999) was used here. The scale consisted of aggression statements including “I feel like yelling at somebody,” “I am mad,” and “I feel like banging on the table.” It was measured on a 1 (not at all) to 5 (extremely) Likert scale.

               To measure for team identification, a scale by Naylor, Hedlund, and Dickson (2017) was used here. The scale consisted of statements including “I know a lot of information about my favorite National Football League team,” “I am very knowledgeable about my favorite National Football League team,” and “I am very familiar with my favorite National Football League team.” It was measured on a 1 (not at all) to 5 (extremely) Likert scale.

               To measure for commitment to team, a scale by Hedlund, Biscaia, and Leal (2020) was used here. The scale consisted of statements including “I am a true fan of the team,” “I am very committed to the team,” and “I will attend my team’s games in the future.” It was measured on a 1 (not at all) to 5 (definitely) Likert scale.

               To measure for brand loyalty toward Madden NFL, a scale by Yoo and Donthu (2001) was used here. The scale consisted of statements including “I consider myself to be loyal to Madden football,” “Madden football would be my first football video game choice,” and “The likely quality of Madden NFL is extremely high.” It was measured on a 1 (strongly disagree) to 5 (strongly agree) Likert scale.

               Descriptive analytics were run to break down video clip and video game play exposure to participants. After data-cleaning was executed, one hundred and thirteen participants (n=113) remained for analysis. 63.7% of participants were male. Additionally, across ethnicity, participants were Caucasian (58.4%), Asian-American (16.8%), African-American (8.8%), Hispanic (2.7%) and also identified as other races (13.3%). Among participants’ favorite NFL teams, they included the Washington Commodores (16.8%), New England Patriots (8.0%), and Philadelphia Eagles (8.0%). Less participants were fans of the New York Giants (4.4%) and Dallas Cowboys (1.8%). To gain a sense of faith participants had among each team, participants were asked to imagine making a bet between a pre bet on an imagined match up between the NY Giants and Dallas Cowboys. Participants on average placed the Dallas Cowboys (M=25.77, SD=9.102) past the NY Giants (M=20.67, SD=8.715) and bet roughly $14.37 on average.

               Across all video clips, participants viewed the Giants winning by a lot (23.4%), Giants winning by a little (28.7%), Cowboys winning by a lot (25.5%), and Cowboys winning by a little (22.3%). Participants viewed the Giants winning 49.5% of the time and the Cowboys winning 50.5% of the time. In relation to video game difficulty level exposure, 51.3% of participants were exposed to pro-level difficulty (2/4 level of difficulty), and 48.7% were exposed to all-pro level difficulty (3/4 level of difficulty). This was done to ensure that Madden football players felt challenged and greater immersion during video game play (Csikszentmihalyi, 1975; Falstein, 2005; Nacke, 2012; Missura, 2015). 50.9% of participants played as the Dallas Cowboys, and 49.1% played as the NY Giants. In the video game itself, the Dallas Cowboys won 64% of the time, and the NY Giants won 36% of the time. Finally, participants won 74.8% of the time. Moreover, 58% of participants elected to play in NY Giants home stadium, MetLife Stadium, and 42% elected to play in AT&T Stadium, the Dallas Cowboys’ home stadium. Before analyses could be conducted, it was necessary to run factor analyses to reduce the amount of emotion statements necessary for analyses. For all factor analyses across pre-experimental mood, post video mood, and post video game mood, varimax rotations were run.

               For post video emotions, the factor analysis had a KMO of .895 and the Bartlett’s Test of Sphericity was statistically significant. The first factor loading had 12.717 eigenvalue and explained 48.913% of variance in the data. The first loading, violent, included I feel like kicking somebody (.919), I feel like hitting someone (.908), I feel like breaking things (.880), I feel like pounding somebody (.880), and I feel like yelling at somebody (.874) and had a Cronbach’s alpha score of .972. The second factor loading had an eigenvalue of 5.022 and explained 19.317% of variance in the data. This scale, entitled irritated, included frustrated (.865), annoyed (.835), angry (.820), depressed (.800), and sad (.768), and had a Cronbach’s alpha score of .928. The third factor loading had an eigenvalue of 2.311 and explained 8.890% of variance in the data. This scale, entitled positive, included pleased (.919), joy (.914), glad (.904), delighted (.900), and fun (.898) and had a Cronbach’s alpha score of .953.

               For post video game emotions, a factor analysis was run. The KMO =.879 and the Bartlett’s test of sphericity was statistically significant. The first factor loading had an eigenvalue of 13.119, and it explained 50.458% of variance in the data set. The first factor loading, violent, included I feel like hitting someone (.866), I feel like breaking things (.858), I feel like banging on the table (.853), I feel like pounding somebody (.840) and I feel like kicking somebody (.840) with a Cronbach’s alpha score of .965. The second factor loading had an eigenvalue of 4.640 and explained 17.846% of variance in the data set. This scale, positive, included joy (.915), glad (.910), delighted (.897), pleased (.884), and fun (.860), and possessed a Cronbach’s alpha score of .952.  The third factor loading had an eigenvalue of 1.783 and explained 6.858% of variance in the data set. This scale, irritated, included gloomy (.832), depressed (.798), sad (.747), anxious (.628), and angry (.531) and had a Cronbach’s alpha score of .905.

               There was emotional variance across mediums (Table 1). Paired T-tests were run across an assortment of feelings here. For most of the emotions that were measured for in this experiment, participants generally felt better after playing the video game against viewing the clip itself across both conditions. For instance, in total, joy (M=4.38, SD=1.928), glad (M=4.45,

SD=1.785), and delighted (M=4.32, SD=1.904) all increased across all conditions after the video game play condition. Hypothesis 1 is supported here.

Emotion variance across mediums.

To test hypotheses 2-4, multiple linear regressions were running for predicting consumer post experiment score bets in table 2 and table 3. In table 2, Across both conditions, pre bet Giants score (β=.413, p<.001), pre bet Cowboys score (β=-.269, p<.012), and video Giants score (β=.225, p<.021) explained 34.6% of variance toward estimating Giants post experiment bet score. In the TV to VG condition, pre bet Giants score (β=.505, p<.003), pre bet Cowboys score (β=-.442, p<.008) explained 35.5% of variance toward estimating Giants post experiment bet score. In the VG to TV condition, pre bet Giants score (β=.430, p<.018) and Giants winning in VG (β=-.583, p<.024) explained 28.9% of variance toward estimating Giants post experiment bet score.

Consumer post bets – Giants.

               In table 3, across both conditions, pre bet Cowboys score (β=.467, p<.001), Cowboys winning in video game (β= .342, p<.038), and video Cowboy score (β=.226, p<.024) explained 27.4% of variance toward estimating Giants post experiment bet score. In the TV to VG condition, pre bet Cowboys score (β=.394, p<.014), Cowboys winning in video game (β= .613, p<.029), Cowboys video score (β=.352, p<.020), Giants video game score (β=.470, p<.034), and feeling positive after viewing the video clip (β=.476, p<.020), explained 38.8% of variance toward estimating Giants post experiment bet score. In the VG to TV condition, Cowboys winning in the video game (β=.469, p<.035), Cowboys video score (β= .276, p<.047), Giants video game score (β=-.517, p<.021), Cowboys video game score (β=-.450, p<.022), and feeling violent after the video clip (β=-.583, p<.011) explained 46.2% of variance toward estimating Cowboys post experiment bet score. Together, these results supported hypothesis 2 and provided partial support for hypotheses 3 and 4.

Consumer post bets – Cowboys.

               To answer the fifth hypothesis, a mixed between-within subjects analysis of variance was conducted to understand the effects of consumption order (TV to VG vs. VG to TV) and game results (NY giant wins a lot vs. Cowboy wins a lot) on participants’ sports betting scores on the two teams (NY Giants and Dallas Cowboys, respectively), across two time periods (pre- and post-experiment).

               For betting scores on NY Giants, a significant interaction effect was found between time and order (Wilks’ Lambda = .89, F (1, 35) = 4.54, p =.04). Both pre and post-betting scores for those under the order condition TV to VG ( = 15.83, SD=5.79 and = 18.72, SD=8.10) scored lower than those under the VG TO TV conditions ( = 23.57, SD=9.67 and = 20.19, SD=8.54). Betting scores for NY Giant has increased for order TV to VG ( = 15.83, SD=5.79 to = 18.72, SD=8.10) but betting scores for order VG to TV has decreased ( = 23.57, SD=9.67 to = 20.19, SD=8.54). However, the main effects for time were not significant, nor were the interaction effects between time and game results, and between time, game results, and order (Figure 1). For betting scores on Dallas Cowboys, no significant main effects or interaction effects were found on any of the variables.

Pre-betting and post-betting scores.

               This study worked to demonstrate how toggling between video game and television experiences could influence consumer emotions and inform subsequent decision-making. Consumers who played a video game after viewing a video clip were more inclined to feel positive (H1 supported). Pre-experiment gambling bets informed post experiment bet scores (H2 supported). There was some evidence that suggested winning teams in video games held a positive influence over post experiment bet scores (H3 partially supported) and that high levels of positive emotions also held a positive influence over post experiment bet scores (H4 partially supported). Finally, there was an interaction effect in which consumption order and time, in which betting scores will increase in the TV to VG condition (H5 supported). Together, the evidence illustrates how powerful the order of medium engagement is for consumers, and that these particular sequences can not only impact post-moods, but also decision-making among consumers.

               This study contributes to the understanding of how appraisal tendency theory and mood management theory further elucidate the influence of media consumption sequencing on subsequent sports gambling decision-making. Specifically, the sequential order of media engagement was found to affect consumers’ semantic affinities between their recent media exposures (such as watching sports clips or engaging in video game sports simulations) and their subsequent decisions regarding sports wagering, albeit to a limited extent. Additionally, consumers’ moods were elevated by video game play, compared to viewing sports clips, supporting the excitatory potential of interactive stimuli here (Zillmann, 1988; Reinecke et al., 2012). In particular, the winning team in a video game simulation was able to impact post-consumer scores for the Cowboys, and moderately impact post-consumer scores for the Giants. This illustrates that video game simulations can be used to inform subsequent decision-making including estimating a team’s score during a post bet, an advancement of appraisal tendency theory. Previously, this had not been applied to mixed media modality studies, and this illustrates that previous media consumption activities can impact subsequent decision-making. Overall, post-betting scores were elevated in part based on the video game to television media consumption order, illustrating the anchoring effect established from consumers’ first playing video game match ups. Additionally, while pre bets can inform how consumers may produce bets after engaging in media, playing simulated video games can be impactful, whether it is the final score or which team won. It should be stated that the bulk of consumers played as the Cowboys, which may illustrate why the Giants winning in the video game held a negative relationship toward the Giants post bet score. It may be that for some consumers, there is interest in proving a simulation wrong, whereas others are positively informed by this experience.

               In regards to mood management theory, in particular semantic affinity and excitation potential, consumer moods were elevated during video game play. From a passive to an interactive activity, this illustrates that this can further intensify emotional valences across positive (e.g. joy, pleased, fun) and negative (gloomy, annoyed) states. This furthers our understanding of how order of media consumption can impact particular moods for consumers. Having agency over an experience, and allowing consumers to co-create their own experiences while playing a simulated matchup further elevates positive feelings. Differently viewing video clips can evoke a range of emotions in consumers, including contentment as well as feelings of anxiety, depression, sadness, or gloominess. A passive entertainment experience that does not include consumers in the co-creation process (especially if their favorite team is not featured in the clip itself), can create dower moods among consumers. Only 6% of participants possessed affinity for either the Cowboys or the Giants, which did not improve mood during video viewing. However, video game play was able to overcome this obstacle and uplift moods.

PRACTICAL IMPLICATIONS

               Integrating video game data with video clip data collection facilitates the development of a comprehensive media audience measurement approach. This approach enables practitioners to gauge engagement across both passive and interactive consumption modes. Additionally, it contributes to establishing a new market information framework (Meyer & Rowan, 1977), potentially minimizing analytical redundancies as consumers’ behaviors are tracked seamlessly across various media platforms. The technological disruption of multi-tasking, task-switching, and sequential tasking have created multiple opportunities to measure audiences differently, particularly as 5G becomes widely available in NFL stadiums. Verizon has recently stated that its 5G ultra Wideband service can ensure connectivity for fans during live games (Ashraf, 2023). The ability to engage smart phone devices in a sports stadium allows audiences to gain a sense of how audiences are responding to a game, which may include measuring the amount of bets. For homebound patrons, consolidating data sets in a cohesive and aggregated fashion enables the development of advanced algorithms for forecasting. This helps in deciphering the audience’s mindset based on their past media consumption patterns leading up to watching an NFL game or engaging in Madden NFL gameplay. Currently, Amazon offers X-Ray for Thursday Night Football fans, which is a sophisticated graphical overlay that allows fans to follow statistics in real time along with generated two-minute highlight reels (Forristal, 2023). Therefore, calcified sport consumer profiles and proclivities for communication with each other can be further facilitated through these strategies (Kirkwood, Yap, & Xu, 2018).

               This creates a vehicle for programmatic strategy advertising and public relations, by which automated advertisements and public relations addresses can be targeted toward participants after an activity in order to enhance or repair a sports fan experience. More attention from consumers may be given to positive television advertisements that follow engaging programming rather than calm programming (Lee, Potter & Han, 2023). Consumers gain greater joy on spending money on experiential products including sports events (Nicolao, Irwin, & Goodman, 2009) and so consumers may seek out experiences more so than merchandise. Moreover, the ability to track consumer behavior in virtual spaces has implications for how advertisements may be placed and how consumers may engage with them (Ahn, Kim & Kim, 2022).  The order of consumption can aid practitioners in elevating video game play. Not only can it impact post betting video game scores, but it can also enhance positive moods for consumers. In particular, consumers who experience their own team or a favored team winning in a video game or simulated match up may feel delighted or joy, which may subsequently encourage them to increase the post experience bet score for one or both teams. This can therefore encourage more risk taking among consumers, and perhaps even more spending for that matter. Furthermore, when fans experience negative emotions after their favorite team loses a live match, the NFL team can strategically encourage them to replay the matchup in Madden NFL. This allows fans to reimagine the live game, thus re-writing the experience itself, and mitigating any temporary damage to brand loyalty or equity.

LIMITATIONS AND FUTURE STUDIES

               There were several limitations in this study. First, most participants were inclined to push for in favor of the Cowboys in the pre-bet. Recall that the NY Giants pre bet score was less (M=20.67, SD=8.715) compared to the Dallas Cowboys (M=25.77, SD=9.102). This indicates markedly more confidence in the Dallas Cowboys’ abilities among the participants. However, while the Cowboys won 64% of the time in the video game, participants only played as them for roughly 51% of the time. Moreover, 58% of participants elected to play in the NY Giants arena. Consequently, many participants were surprised by losses to the NY Giants when playing in the Giants’ stadium. Future studies should consider allowing participants to play as their favorite teams or testing various types of advertisements on them. It may also be valuable to examine how participants respond to playing in stadiums that are geographically close to or far from their hometowns. Additionally, investigating how the order of media consumption affects consumer behavior related to memorabilia, tickets, and other sports-related purchases offers a promising area for academic research.

• Ahn, S., Kim, J., Kim, J. (2022). The bifold triadic relationships framework: A theoretical primer for advertising research in the Metaverse. Journal of Advertising, 51 (5), 592-607.
• Ashraf, C. (2023, October 19). Verizon’s 5G Ultra Wideband keeps football fans connected in all 30 NFL stadiums. Verizon News Center . Retrieved May 28, 2024, from https://www.verizon.com/about/news/verizon-5g-ultra-wideband-football-fans-connected-30-nfl-stadiums
• Berkowitz, L. (1989). Frustration-aggression hypothesis: Examination and reformulation.  Psychological Bulletin ,  106 (1), 59-73.
• Beuckels, E., De Jans, S., Cauberghe, V., Hudders, L. (2021). Keepin gup with media multitasking: An eye-tracking study among children and adults to investigate the impact of media multitasking behavior on switching frequency, advertising attention, and advertising effectiveness.  Journal of Advertising ,  50 (2), 197-206.
• Birnbaum, J. (2021, March 19). NFL’s new TV deals will hand teams $300 million a year, and still won’t drive franchise values higher. Forbes. Retrieved February 20, 2023, from https://www.forbes.com/sites/justinbirnbaum/2021/03/19/nfls-new-tv-deals-hand-teams-300-million-per-year-and-still-wont-drive-franchise-values-higher/?sh=4f0127794f04
• Bodenhausen, G., Kramer, G., & Susser, K. (1994). Happiness and stereotypic thinking in social judgment. Journal of Personality and Social Psychology , 66 , 621-632.
• Branscombe, N., & Wann, D. (1992). Physiological arousal and reactions to outgroup members during competitions that implicate an important social identity.  Aggressive Behavior ,  18 , 85-93.
• Bryant, J., & Zillmann, D. (1984). Using television to alleviate boredom and stress: Selective exposure as a function of induced excitational states. Journal of Broadcasting, 28(1), 1-20.
• Campbell, S. (2021, January 21). How to bet on simulation sports: Sim sports betting guide. In  OddsShark . Retrieved April 29, 2021, from https://www.oddsshark.com/esports/sim-sports/how-to-bet
• Cason, D., Lee, M., Lee, J., Yeo, I., Arner, E. (2020). The impact of legalization of sports gambling: How motivation, fandom, and gender influence sport-related consumption.  International Journal of Sport Communication ,  13 (4), 643-654.
• Chansanchai, A. (2016, October 10). Partnership between Microsoft and NFL continues to score high for players, coaches, and fans. In  Microsoft Features . Retrieved April 27, 2021, from https://news.microsoft.com/features/partnership-between-microsoft-and-nfl-continues-to-score-high-for-players-coaches-and-fans/
• Chiari, M. (2018, September 5). Nielsen Report: NFL could make $2.3 billion a year from gambling market.  Bleacher Report . Retrieved February 20, 2023, from  https://bleacherreport.com/articles/2794282-nielsen-report-nfl-could-make-23-billion-a-year-from-gambling-market
• Chisholm, J., & Kingstone, A. (2015). Action video games and improved attentional control: Disentangling selection – and response-based processes.  Psychonomic Bulletin & Review ,  22 , 1430-1436.
• Chuang, S., Kung, C., & Sun, Y. (2008). The effects of emotions on variety-seeking behavior. Social Behavior and Personality , 36 (3), 425-432.
• Cohen, A. (2020, February 5). MLB fans can now bet on virtual games powered by Sportradar. In  SportTechie . Retrieved April 27, 2021, from https://www.sporttechie.com/mlb-baseball-fans-sports-betting-virtual-games-sportradar-data
• Csikszentmihalyi, M. (1975).  Beyond boredom and anxiety . San Francisco, CA: Jossey-Bass Publishers.
• Deloitte. (2018). Deloitte Digital Media Trends 2018: Executive Summary.  Deloitte . Retrieved May 15, 2024, from  file:///Users/palombaa/Downloads/tmt-global-deloitte-digital-media-trends-survey-2018.pdf
• Diener, E., & Emmons, R. (1984). The independence of positive and negative affect.  Journal of Personality and Social Psychology ,  47 (5), 1105-1117.
• Dijkstra, M., Buijtels, H., & Van Raaij, W. (2005). Separate and joint effects of medium type on consumer responses: A comparison of television, print, and the Internet.  Journal of Business Research ,  58 , 377-386.
• Donohew, L., Sypher, H., Higgins, E. (1988). Communication, social cognition, and affect. Lawrence Erlbaum Associates.
• Du, J., Mamo, Y., Floyd, C., Karthikeyan, N., James, J. (2023). Machine learning in sport social media research: Practical uses and opportunities.  International Journal of Sport Communication ,  17 (1), 97-106.
• Falstein, N. (2005). Understanding fun – the theory of natural funativity. In S. Rabin (Ed.), Introduction to game development. Hingham, MA: Charles River Media.
• Forristal, L. (2023, August 24). Amazon brings new AI-driven features to Thursday Night Football. Tech Crunch . Retrieved May 28, 2024, from https://techcrunch.com/2023/08/24/amazon-prime-video-ai-features-thursday-night-football/
• Garaus, M., Wagner, U., Back, A. (2017). The effect of media multitasking on advertising message effectiveness.  Psychology & Marketing ,  34 (2), 138-156.
• Gough, C. (2020, October 2). Revenue of National Football League (NFL) teams 2019 Published by Christina Gough, Oct 2, 2020 The statistic ranks all franchises of the National Football League according to revenue in 2019. In  Statista . Retrieved April 29, 2021, from https://www.statista.com/statistics/193553/revenue-of-national-football-league-teams-in-2010/
• Gough, C. (2021, March 29). National Football League (NFL) – Statistics & Facts. In  Statista . Retrieved April 29, 2021, from https://www.statista.com/topics/963/national-football-league/#:~:text=The%20NFL%20is%20also%20the,total%20throughout%20the%202019%20season
• Han, S., Lerner, J., & Keltner, D. (2007). Feelings and consumer decision making: The appraisal-tendency framework. Journal of Consumer Psychology , 17 (3), 158-168.
• Hedlund, D. P., Biscaia, R., & Leal, M. D. (2020). Classifying Sport Consumers: From Casual to Tribal Fans. In C. Wang (Ed.), Handbook of Research on the Impact of Fandom in Society and Consumerism (pp. 323-356).
• IGN Staff. (2012, June 14). Study finds playing Madden NFL creates more passionate & knowledgeable football fans. In  IGN . Retrieved April 30, 2021, from https://www.ign.com/articles/2009/08/20/study-finds-playing-madden-nfl-creates-more-passionate-knowledgeable-football-fans
• Jacoby, J., Hoyer, W., Zimmer, M. (1983). To read, view, or listen? A cross-media comparison of comprehension. Current Issues and Research in Advertising , 6 (1), 201-217.
• Kim, Y., & Ross, S. (2006). An exploration of motives in sport video gaming.  Journal of Sports Marketing & Sponsorship ,  8 , 34-46.
• Kirkwood, M., Yap, S., Xu, Y. (2018). An exploration of sport fandom in online communities.  International Journal of Sport Communication ,  12 (1), 55-78.
• Koepp, M. J., Gunn, R. N., Lawrence, A. D., Cunningham, V. J., Dagher, A., Jones, T., Brooks, D. J., Bench, C. J., Grasby, P. M. (1998). Evidence for striatal dopamine release during a video game. Nature , 393, 266-268.
• Kosterich, A., & Napoli, P. (2016). Reconfiguring the audience commodity: The institutionalization of social TV analytics as market information regime.  Television & New Media ,  17 (3), 254-271.
• Kuo, A., Hiler, J., & Lutz, R. (2017). From Super Mario to Skyrim: A framework for the evolution of video game consumption.  Journal of Consumer Behavior ,  16 , 101-120.
• Lachlan, K., & Krcmar, M. (2011). Experiencing presence in video games: The role of presence tendencies, game experience, and time spent in play.  Communication Research Reports ,  28 (1), 27-31.
• Lee, M., Potter, R., Han, J. (2023). Motivational system approach to understand ad processing following various game outcomes. Sport Management Review , 26 (4), 517-539.
• Martins, D. (2020, December 11). Betting lounges vs. mobile betting in stadiums and arenas. In  BettersInsider . Retrieved April 27, 2021, from https://www.bettorsinsider.com/news/2020/12/10/betting-lounges-vs-mobile-betting-in-stadiums-and-arenas-are-a-new-frontier-for-sports-gambling
• Meir, R., & Scott, D. (2007). Tribalism: Definition, identification, and relevance to the marketing of professional sports franchises.  International Journal of Sports Marketing & Sponsorship ,  8 (4), 330-346.
• Meyer, J., & Rowan, B. (1977). Institutionalized organizations: Formal structure as myth and ceremony.  American Journal of Sociology ,  83 (2), 340-363.
• Missura, O. (2015). Dynamic difficulty adjustment. Doctoral dissertation, Bonn: University Rheinischen Friedrich-Wilhelms, Bonn
• Nacke, L. (2012). Flow in Games: Proposing a Flow Experience Model.
• Naylor, M., Hedlund, D., & Dickson, G. (2017). Team identification full circle: The important of cognition, evaluation, and affect. International Journal of Sport Management , 18 , 573-592.
• NFL. (2021, April 15). NFL announces tri-exclusive official sports betting partners. In  NFL . Retrieved April 29, 2021, from https://www.nfl.com/news/nfl-announces-tri-exclusive-sports-betting-partners
• Nicolao, L., Irwin, J., & Goodman, J. (2009). Happiness for sale: Do experiential purchases make consumers happier than material purchases?  Journal of Consumer Research ,  36 (2), 188-198.
• Palomba, A. (2020). How high brand loyalty consumers achieve relationships with virtual worlds and its elements through presence. Journal of Media Business Studies , 17 (3/4), 243-260.
• Popp, N., Du, J., Shapiro, S., Simmons, J. (2023). Using artificial intelligence to detect the relationship between social media sentiment and season ticket purchases.  International Journal of Sport Communication ,  17 (1), 17-31.
• Porter, R. (2021, January 30). TV long view: Even in a down year, the NFL’s ratings are untouchable. In  The Hollywood Reporter . Retrieved April 27, 2021, from https://www.hollywoodreporter.com/live-feed/tv-long-view-nfl-ratings-dominance-2020#:~:text=In%202019%2C%20the%20league%20averaged,biggest%20entertainment%20shows%20only%20widened .
• Reinecke, L., Tamborini, R., Grizzard, M., Lewis, R., Eden, A., Bowman, N. (2012). Characterizing mood management as need satisfaction: The effects of intrinsic needs on selective exposure and mood repair.  Journal of Communication ,  62 , 437-453.
• Reyes, L. (2021, December 29). The story on how John Madden came to be involved with wildly popular EA sports NFL video game.  USA Today . Retrieved February 20, 2023, from  https://www.usatoday.com/story/sports/nfl/2021/12/29/madden-nfl-video-game-ea-sports/9044657002/
• Reynaldo, C., Christian, R., Hosea, H., Gunawan, A. (2021). Using video games to improve capabilities in decision making and cognitive skill: A literature review.  Procedia Computer Science ,  179 , 211-221.
• Rodenberg, R. (2021, April 7). United States of sports betting: An updated map of where every state stands. In  ESPN . Retrieved April 27, 2021, from https://www.espn.com/chalk/story/_/id/19740480/the-united-states-sports-betting-where-all-50-states-stand-legalization
• Russoniello, C., O’Brien, K., Parks, J. (2009). The effectiveness of casual video games in improving mood and decreasing stress.  Journal of Cyber Therapy & Rehabilitation ,  2 (1), 53-66.
• Sarkar, S. (2020, March 10). 2k returns to making NFL video games, but not a Madden competitor. Polygon. Retrieved May 28, 2024, from https://www.polygon.com/2020/3/10/21172310/nfl-2k-sports-football-video-games-deal-ea-madden
• Schwarz, N., & Clore, G. (1983). Mood, misattribution, and judgments of well-being: Informative and directive functions of affective states. Journal of Personality and Social Psychology , 45 (3), 513-523.
• Sinclair, J. (2005).  Exploration of state and trait anger, anger expression, and perfectionism in collegiate springboard divers . [Master’s thesis, Georgia Southern University]. Electronic Theses and Dissertations.
• Skiver, K. (2022, August 18). Madden 23 early access: Here are two ways to play before the 2022 release. In  Sporting News . Retrieved November 2, 2022, from https://www.sportingnews.com/us/nfl/news/madden-23-early-access-play-2022-release-date/ndegqutcgw0tez5dvhk1jqnt#:~:text=Mid%2DAugust%20is%2C%20traditionally%2C,game%20early%20via%20early%20access
• Spielberger, C. (1999).  Manual for the state-trait anger expression inventory-2 . Odessa, FL: Psychological Assessment Resources.
• Stadder, E., & Naraine, M. (2020). Place your bets: An exploratory study of sports-gambling operators’ use of Twitter for relationship marketing.  International Journal of Sport Communication ,  13 (2), 157-180.
• Tamborini, R., Bowman, N., Eden, A., Grizzard, M., Organ, A. (2010). Defining media enjoyment as the satisfaction of intrinsic needs. Journal of Communication , 60 (4), 758-777.
• Tuttle, W. (2016, September 9). Watch football your way on Xbox. In  Xbox Wire . Retrieved April 28, 2021, from https://news.xbox.com/en-us/2016/09/09/watch-football-your-way-on-xbox/
• Van Raaij, W. (1998). Interactive communication: Consumer power and initiative. Journal of Marketing Communications , 4 (1), 1-8.
• Villani, D., Carissoli, C., Triberti, S., Marchetti, A., Gilli, G., Riva, G. (2018). Videogames for emotion regulation: A systematic review.  Games for Health Journal ,  7 (2), 85-99.
• Wann, D. (2002). Preliminary validation of a measure for assessing identification as a sport fan: The Sport Fandom Questionnaire.  International Journal of Sport Management ,  3 , 103-115.
• Whelan, E., Laato, S., Islam, A., & Billieux, J. (2021). A casino in my pocket: Gratifications associated with obsessive and harmonious passion for mobile gaming.  PLoS One ,  16 (2), 1-16.
• Wiedey, B. (2020, January 31). Madden Super Bowl prediction 2020: Can video game correct recent history with Super Bowl 54. In  Sporting News . Retrieved April 27, 2021, from https://www.sportingnews.com/us/nfl/news/madden-super-bowl-prediction-2020-history/11dyx2slhr41m1sqixa06v00y7
• Wilson, J. (2022, August 20). Madden debuts as top-selling game in U.S. for 23rd consecutive year. In  The Esports Observer . Retrieved November 2, 2022, from https://www.sportsbusinessjournal.com/Esports/Sections/Media/2022/09/NPD-Group-August-2022-video-game-sales-Madden-NFL-2023.aspx
• Yeykelis, L., Cummings, J., Reeves, B. (2014). Multitasking on a single device: Arousal and the frequency, anticipation, and prediction of switching between media content on a computer. Journal of Communication , 64 (1), 167-192.
• Yim, B., & Byon, K. (2018). The influence of emotions on game and service satisfaction and behavioral intention in winning and losing situations: Moderating effect of identification with the team. Sport Marketing Quarterly , 27 , 93-106.
• Yoo, B., & Donthu, N. (2001). Developing and validating a multidimensional consumer-based brand equity scale. Journal of Business Research , 52 , 1-14.
• Zillmann, D. (1983). Transfer of excitation in emotional behavior. In J. T. Cacioppo & R. E. Petty (eds.), Social psychophysiology: A sourcebook. New York: Guilford, pp. 215–240.
• Zillmann, D. (1988). Mood management through communication choices . American Behavioral Scientist , 31 (3), 327-340.
• Zillmann, D., & Johnson, R. (1973). Motivated aggressiveness perpetuated by exposure to aggressive films and reduced by exposure to nonaggressive films.  Journal of Research in Personality ,  7 (3), 261-276.

The authors thank the Institute for Business in Society at the Darden School of Business for research support.

Selection and Performance Rationale of Wood vs. Aluminum Baseball Bats

George Minoso 2024-09-26T07:03:33-05:00 September 28th, 2024 | Sport Training , Sports Studies |

Authors: Vilas G. Pol 1

AUTHORS INSTITUATIONAL AFFILIATION:

1 Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana, 47907, United States 

Vilas G. Pol

Purdue University

Davidson School of Chemical Engineering

West Lafayette, Indiana 47906

[email protected]

Acknowledgments

We would like to express our sincere gratitude to Sunkalp Vilas Pol for his valuable contribution to this research. His assistance in this article is greatly appreciated and played an important role in the development of this paper. We commend his dedication and enthusiasm for learning.

Selection and Performance Rationale of Wood vs. Aluminum Baseball Bats 

USA Youth Baseball approves metal/alloy, composite, and wood (or a combination) bats for use in baseball games. However, players, parents, and coaches often face a dilemma when selecting a superior baseball bat, as bat quality depends on material, durability, performance, sensation, player preference, and balance. The purpose of this experimental investigation is to understand the maximum exit velocity of a baseball and overall performance of maple wood vs. aluminum bats. This is accomplished by hitting a stationary ball on a tee as well as with two different pitch speeds (30 and 40 MPH from a roller pitching machine), measured by a speed radar (accuracy ±1 MPH) in a controlled environment. It is hypothesized that when the material of the baseball bat changes, the exit velocity of the ball would change due to the trampoline effect (compression of the solid metal barrel) when hitting with the metal/aluminum bat compared to the solid wood bat. Apart from similar barrel size, length, and weight of the bats, it is observed that the metallic aluminum bat is slightly superior (2-3%) because of the trampoline effect when the balls were hit off the tee and with the machine at 30 MPH speed. Interestingly, for the 40 MPH automatic pitching machine test, the wood bat was 3-4% superior to the aluminum bat, possibly due to high impact speeds with less than 1 ms impact duration and minimum energy losses in the bat, or even due to the strength of the batter. The data were collected by a 12U youth baseball player in three different sessions for better accuracy and reproducibility. In fact, high-quality (hence expensive) wood or aluminum bats could lead to analogous outcomes (±1-2% variations) when used in a controlled environment, not significantly contributing to winning the baseball game.

Keywords : Exit velocity, Trampoline effect, Barrel size and length, Controlled environment, Efficiency  

INTRODUCTION

Baseball is a popular American game played between two teams of nine members with a bat, a ball, and gloves on a diamond-shaped field with alternating batters (offense) and fielders (defense). The batter’s goal is to hit the ball hard enough, putting it out of reach of the fielding team to make a complete circuit around the bases to obtain a ‘run,’ with the team scoring the highest number of runs winning the game. This is typically made of either of wood or a lightweight metal such as aluminum. Now the mystery question is which bat (wood or aluminum) should be selected for such an important task.

During the last century, there has been significant research and development in the baseball field including selection of bats, barrel diameter, shape, length, and composition. Naturally, wood and aluminum bats are considered based on their performance, affordability, and safety. Typically, the more expensive bats use higher quality materials, hence better properties such as lightweight materials leading to longer distances and more power while producing minimal vibrations.

Due to lots of discussion in the open literature arguing which material bats are superior, this study particularly focuses on the experimental investigation of the exit velocity of most common aluminum and wood bats. It was hypothesized that using a maple wood bat versus an aluminum baseball bat of the same length, barrel size, weight, and producers used to strike the ball might create a different exit velocity because of varied physical properties of bat materials, including the commonly known trampoline effect (barrel compresses and expands) while using the hollow aluminum bat compared to the solid wood bat.

In 2022, Sherwood et al. studied five aluminum and wood baseball bats and observed that the field performance of these bats strongly correlated with the ball–bat coefficient of restitution COR . They predicted the relationship between wood baseball bat profile and durability based on finite element modelling of 15 profiles used from 15 MLB players (1). Russell described the effect of cylindrical barrel and flexural bending vibrations (2) on softball and baseball bats with respect to their performance including understanding the sweet spot and the origin of the ping (3) sound. Shenoy et al. predicted a model for the performance of solid wood and hollow metal bats with an experimental agreement for the impact speed, ball types, bat models, and impact locations (4).  It is observed that the energy dissipation between the bat and the ball happens through ball deformation, elastic bat vibration and contact friction (4). In 2002, Sherwood et al. investigated the durability of the wooden bat based on the slope of grain impact and impact location, with statistical analysis and finite element modeling. In other study they predicted the relationship between wood baseball bat profile and durability (5). In 2003, Drane and Sherwood described the effect of moisture content on the wooden bat, increasing the velocity by a maximum of 1% (6). In 2002, Penna et al. described that the exit velocity can depend on the skill level of the player or a higher performing bat (7). The systematic literature review created a knowledge gap to investigate the dilemma in selecting the most effective bat that would contribute in winning the baseball game.

This article methodically answers that question with experimental evidence through carefully measuring and comparing the average exit velocities of an aluminum and a wood bat with reproducibility. Though both bats had similar speeds, exit velocity measurements show that the aluminum bat is 2-3% superior because of the hypothesized trampoline effect when the balls were hit off of the tee and against 30 MPH pitches from the ball roller pitching machine. Surprisingly, for the 40 MPH automatic pitching machine test wood bat was 3-4% superior to the aluminum bat possibly due to less than 1 ms impact duration with the minimum energy losses in the bat or even the strength of the batter. This article provides experimental evidence for 12U youth baseball players that high quality wood or aluminum bats could lead to the analogous outcomes with 1-2% variations when used in a controlled environment.

A standard pitching machine manufactured by Junior Hack Attack was utilized to set up the velocity of the ball being pitched. The speed radar was purchased from Bushnell with an accuracy of ±1 MPH. The velocity gun was calibrated utilizing the set speed of the pitching machine and reading of the radar to a 1 MPH accuracy. The aluminum bat with a length of 31 inches, 23 ounces, and a barrel size of 2 ¾ inches was purchased from Marucci. The maple wood bat with a length of 31 inches, and a barrel size of 2 ¾ inches was purchased from Victus Nox (The brand Marucci owns Victus Nox) . A bucket of standard baseballs was purchased from Wilson . A standard batting tee manufactured by Tanners Tees was utilized for the tee tests. An indoor baseball and softball facility (Lifelong Sports, Lafayette, Indiana, USA) was used for these experiments. Figure 1 depicts all used baseball accessories.

Two different velocities of =30 and 40 MPH were set by adjusting left, bottom, and right knobs of a standard pitching machine (Figure 1). The balls were loaded into the pitching machine by a person with approximately 15 second intervals between the pitched balls. The batter wore the requisite safety equipment (helmet, arm guard, leg guard, and batting gloves) while hitting the balls as they were pitched. The speed radar was set up approximately 4 feet behind the batter and the exit velocity was measured after the bat had contacted the ball. Ten balls were set on the batting tee (one at a time) and hit within 15 second intervals. The handheld speed gun was used behind the batter and pointed at approximately where the ball would be headed. Three trial runs were carried out before the final experiment to find errors in the experiment and to correct them. After hitting ten balls with the aluminum bat, the wood bat was used to hit the next ten balls to minimize the error, assuming that the batter’s strength is similar between tests conducted sequentially. Within each set of experimental conditions, the exit velocity of the balls was categorized and reported as the highest (Hi), lowest (Low) and average (Avg) speeds. In some cases, the aluminum bat’s sound frequencies affected the speed gun measurements. These experiments and speed measurements were repeated. Newly purchased baseball balls were used for the measurements to minimize the error. Please note some of the concerns in wood versus aluminum bats are i) the wood bat breaking could happen due to the ball hitting around the handle area or the end, ii) the wood bat could hurt players’ hands due to high impact speeds and vibrations, and iii) the aluminum bat cracking could occur as the metal shrinks in the cold with unsafe storage.  

Typically, commercial baseball pitching machines are arm type (stores balls on sides in an arm shape, which automatically dispenses balls) or roller type (person must manually put balls into the machine). Both machines can dispense different pitches (8) such as fastball, curveball, screwball, slider, etc. To carry out the experiments in a controlled air, moisture, and temperature environment for better accuracy, we used roller type dispenser at LifeLong Sports, Lafayette, Indiana, USA.

Fig. 2 depicts the exit velocity data from 10 balls that were hit off of the tee with maple wood and aluminum bats. The highest exit velocity for the balls that were hit by the wood bat ranges from 57 to 62 MPH, while more consistent 61 MPH for the aluminum bat. The lower velocity and average exit velocity data demonstrate that the effect of using either wood or aluminum bat is negligible when the balls were hit off the tee.

In Fig. 3 , 10 balls were pitched at 30 MPH and the exit velocity data was collected for maple wood and aluminum bats. The highest exit velocity for the balls that were hit by aluminum bat ranges from 61 to 63 MPH, while being 55 to 61 MPH for the wood bat. The lowest exit velocity for the balls that were hit by wood bat ranges from 40 to 43 MPH, while 50 to 51 MPH for the aluminum bat. Overall, 2-3% superior performance of the metal bat was observed due to hollow vibrating wall of the bat (similar to a drum upon impact), producing a loud ping sound (9). The exit velocity of the balls was almost double the velocity of balls impacting to the bat.   In fact, the wall bends slightly in an inner direction retaining some of the vibrational energy and then coils back after impacting on the bat. The low frequency ping sound (1,000 Hz) indicates softer, thinner wall thickness of metal bat while high frequency (2,000 Hz) ping sound indicates bat wall is thicker, hence stiffer (9). The trampoline effect on the metal bat helps gain a little more speed compared to the wooden bat (9).

At high pitch speeds of the incoming balls (40 MPH), the obtained data show a slightly different trend, as seen in Fig. 4 . The highest exit velocity for the balls that were hit by the aluminum bat ranges from 51 to 53 MPH, while being 57 to 58 MPH for the wood bat. The low exit velocity for the balls that were hit by the aluminum bat ranges from 40-41 MPH, while being 41-45 MPH for the wood bat. Namely, the wood bat showed a slightly superior exit velocity compared to the metal bat. This could be due to high impact speeds with less than 1 ms impact duration with the minimum energy percolation in the bat (9). As baseballs from the same batch were used for both the 30 MPH and 40 MPH pitch tests, these differences can be attributed to differences in the bat material rather than the baseballs themselves. In these conditions, a solid wood bat could perform better than the thin-walled metal bat because of minimized trampoline effect. The wood bat does not ping as loud as metal meaning that it imparts most of the stored elastic energy to the ball with less energy left in the wall of the bat to vibrate (9). Other possible reasons the wood bat was better with enhanced exit velocity are hitting with the harder grain or the shape of the balls (possibly deformed on the harder wood bat), and differences in manufacturing of the bats. These reasons also support why the wood bat performed superior in the 40 MPH test. When 10 balls were hit on both bats with 30 MPH and 40 MPH pitches, the measured exit velocity ranged from 40-63 MPH at low, medium and highest velocities confirming that most of the stored energy is returned to the ball without significant dissipation.  

The trampoline effect describes noticeable elasticity in objects impacting at high speeds with applicability to sports such as baseball (the ball and bat), golf (the ball and club), and tennis (the ball and racquet) such that they act like a spring analogous to when we jump on the trampoline  and get bounced back. In baseball, the elasticity of a bat upon the impact of baseball is different for wood and aluminum bats. Typically, when the baseball hits a wood bat, the ball compresses losing more than half of its energy, but when using a hollow aluminum bat, the bat compresses rather than the ball.

The fundamental physics understanding of the trampoline effect in baseball and softball bats was documented by Nathan et al. two decades ago (10) who identified that upon the high-speed impact between a bat and baseball, the original center-of-mass kinetic energy is transformed into compressional energy. Certain energy is stowed in vibrational modes (hoop modes), providing this stored energy to the baseball with minimum dissipation of energy with larger ball exit velocity due to the trampoline effect (10). In other words, the elasticity of a bat upon the impact of baseball determines the magnitude of the resultant trampoline effect (Fig. 5) . Typically, when the ball impacts on the aluminum bat, because of its hollow nature the bat barrel compresses to lose energy and returns it to the ball soon after. On the wood bat, the ball compresses and loses up to 75% of energy in frictional forces (10). Typically, during the bat-ball collision, the exit velocity of the ball would be dependent on the effective mass/weight of the bat. However, this is a negligible effect in the experiments reported in this work as both bats possess similar masses. The exit velocity is at its peak at the place on the bat where maximum power was applied on the surface of ball, storing more elastic energy, and subsequently imparting it back to the ball (9).  

Conclusions

Controlling for the barrel size, length, and weight of the bat, it is experimentally measured and observed that aluminum bat is 2-3% superior when balls were hit off of the tee and against 30 MPH machine-pitched balls because of the trampoline effect. Remarkably, for the 40 MPH automatic pitching machine test, the wood bat was 3-4 % superior to the aluminum bat possibly due to high impact speeds with less than 1 ms impact duration with the minimum energy losses in the wood bat or even the strength of the young batter. Even though both bats had similar speeds, exit velocity measurements were measurably different. Therefore, it can be concluded that high quality wood and aluminum bats could lead to analogous outcomes when used in a controlled environment.  

Application in Sport

The outstanding performance of a baseball player can be highly dependent on the selection of a metal or wood baseball bat, its balance, durability and feel in addition to the player’s capabilities. In general, metal bats are known to provide enhanced power, durability, and a broader sweet spot while wood bats provide a traditional feel, tailoring options, and a smaller sweet spot. This article offers insight into the rationale behind selecting a bat with peace of mind for the player, parent, and coach corroborating that high quality (hence expensive) wood or aluminum bats could lead to analogous outcomes with 1-2% variations when used in a controlled environment. Eventually, use of a metal or wood baseball bat is a personal choice, guided by player strength and abilities. 

• Patrick Drane, Joshua Fortin-Smith, James Sherwood, and David Kretschmann, Predict the relationship between wood baseball bat profile and durability, Procedia Engineering,  2016, 147, 425–430. 
• Alan M. Nathan, J. J. Crisco, R. M. Greenwald, D. A. Russell, Lloyd V. Smith, A Comparative study of baseball bat performance, Sports Engineering, 2011, 13, 153-162. 
• Daniel A. Russell, Acoustics and vibration of baseball and softball bats, Acoustics Today, 2017, 13(4), 35.  
• Mahesh M Shenoy, Lloyd V Smith, John T Axtell, Performance assessment of wood, metal and composite baseball bats, Structures,  2001, 397-404. 
• Blake Campshure, Patrick Drane and James A. Sherwood, An investigation of wood baseball bat durability as a function of bat profile and slope of grain using finite element modeling and statistical analysis, Appl. Sci. 2022, 12, 3494.  
• P. J. Drane & J.A. Sherwood, The effects of moisture content and work hardening on baseball bat performance, Materials Science, 2003, 1-7 (Corpus ID: 44456022). 
• J. J. Crisco, R. M. Greenwald, J. D. Blume, and L. H. Penna, Batting performance of wood and metal baseball bats. Med. Sci. Sports Exerc ., 2002, 34, 10, 1675–1684. 
• Nippon Kikai Gakkai Ronbunshu, C Hen, Study on throw accuracy for baseball pitching machine with roller (Study of Seam of Ball and Roller), Transactions of the Japan Society of Mechanical Engineers , Part C , November 2007, 73(735):2962-2967. 
• R. Cross, Physics of Baseball & Softball, Springer Science Business Media, LLC 2011, Chapter 13, 221- 234. 
• Nathan, D. A. Russell, L. V. Smith, The physics of the trampoline effect in baseball and softball bats, Physics, 2004, Corpus ID: 6993139. 

Prevalence of Normal Weight Obesity Amongst Young Adults in the Southeastern United States

Qshequilla Parham Mitchell 2024-09-23T09:54:55-05:00 September 23rd, 2024 | Sports Health & Fitness |

Authors: Helena Pavlovic, Tristen Dolesh, Christian Barnes, Angila Berni, Nicholas Castro, Michel Heijnen, Alexander McDaniel, Sarah Noland, Lindsey Schroeder, Tamlyn Shields, Jessica Van Meter, and Wayland Tseh*

AUTHORS INSTITUATIONAL AFFILIATION: School of Health and Applied Human Sciences, University of North Carolina Wilmington, Wilmington, North Carolina, United States of America

Wayland Tseh, Ph.D.

University of North Carolina Wilmington

School of Health and Applied Human Sciences

601 South College Road

Wilmington, North Carolina, 28403-5956

Phone Number: 910.962.2484

E-Mail:   [email protected]

‘Normal weight obesity (NWO) is characterized by a normal or low body mass index (BMI) alongside a high percentage of body fat, which increases the risk for hypokinetic diseases.  This study aims to investigate the prevalence of NWO among a sample of young, non-sedentary adults.  Two hundred and fifty-four apparently healthy volunteers (Age = 22.2 ± 7.2 yrs; Height = 171.5 ± 9.6 cm; Body Mass = 69.9 ± 13.4 kg) provided informed consent prior to participation. Body mass index was calculated by dividing body mass (kg) by height squared (m 2 ).  Body fat percentage was measured using the BODPOD ® G/S, which utilizes air displacement plethysmography to accurately estimate body composition.  Class I Obesity and Low/Normal BMI categorizations were defined by the American College of Sports Medicine. Data revealed that 12.2% of the overall sample exhibited NWO, with a higher prevalence among males (17.2%) compared to females (9.8%).  The study also seeks to evaluate whether individuals with NWO face greater health risks than those with similar BMI but lower body fat percentages.  From a practical perspective, identifying individuals with NWO is an opportunity for clinicians to proactively educate their clients regarding the health risks associated with hypokinetic disease(s).

Keywords : Body Mass Index, BODPOD, Percent Body Fat, Normal Weight Obesity

Within the United States, the prevalence of obesity has dramatically increased over the past 50 years given the ubiquitous obesogenic environment (31). In 2019, Ward and colleagues yielded compelling predictive insights indicating a trajectory wherein, by the year 2030, nearly 50% of adults will be afflicted by obesity (48.9%) with heightened prevalence exceeding 50% in 29 states, demonstrating a pervasive nationwide trend (50). Moreover, no state is anticipated to exhibit a prevalence below 35% (50). Projections also indicate that a substantial proportion of the adult population is anticipated to experience severe obesity, with an estimated 24.2% affected by 2030 (50). Against this backdrop, the predictive analyses conducted by Ward and associates (50) underscored the widespread and escalating severity of the obesity epidemic across the United States. These findings are indicative of an impending public health challenge, necessitating strategic interventions and policy considerations to mitigate the escalating burden of obesity and its associated health implications. When delineating the magnitude of obesity, clinicians and practitioners must employ precise instrumentation capable of quantifying a client’s body composition in terms of percentage body fat. Numerous methodologies exist for this purpose, encompassing hydrostatic weighing, bioelectrical impedance analysis, air displacement plethysmography, skinfold assessment, and dual-energy x-ray absorptiometry scan.

Drawing from antecedent research studies, dual-energy X-ray absorptiometry (DXA) is acknowledged as the clinical gold standard for appraising body composition (9, 10, 12, 21, 25, 26, 42, 47). However, a notable drawback of DXA lies in its emission of low-level radiation (6, 9, 32, 45, 47), thereby subjecting clients to unnecessary radiation exposure (1, 33). An alternative method is utilizing the BOD POD ® Gold Standard (GS), which employs air displacement plethysmography to estimate body composition. Previous literature has heralded the BOD POD ® GS as the applied, pragmatic gold standard for assessing body composition due to its validity (2, 7, 38), as well as its within- and between-day reliability (48). Additionally, owing to the BOD POD ® GS’s facile and non-invasive procedures, most individuals can attain accurate measures of body composition values, specifically pertaining to percent body fat, enabling the discernment of pounds of fat-free mass and fat mass.

According to the American College of Sports Medicine (ACSM), males with a percent body fat ≥ 25% and females ≥ 32% (4) are predisposed to an elevated risk of developing a myriad of hypokinetic diseases, notably cardiovascular disease(s), metabolic syndrome, and cardiometabolic dysfunction (14, 27, 35, 37, 39, 40, 43, 44, 46, 51, 56). Another evaluative approach involves the calculation of Body Mass Index (BMI), derived from dividing body weight in kilograms by square of height in meters (4). Given the ease and efficiency of calculating BMI, the obesity-related classification in which it provides at the individual level is potentially flawed (3, 8, 22, 24, 41, 53, 56).

Presently, within the United States, a dearth of research exists on the prevalence of normal weight obesity (NWO) amongst apparently healthy young adults (11,52). Normal weight obesity is characterized by individuals exhibiting a low BMI (<18.5 kg∙m -2 ) or normal BMI (18.5 – 24.9 kg∙m -2 ) yet manifesting obesity-related percentage body fat values (male = ≥20%; female = ≥30%) (5, 14, 20, 36, 37, 40, 43, 44, 57). Individuals with low/normal BMI and high percentage body fat values face an augmented risk of hypokinetic diseases, as their seemingly normal exterior masks a deleteriously high amount of body fat beneath the surface layer. Previous research endeavors have revealed the prevalence of NWO amongst a population of South Americans (14, 34, 40, 44), Central Europeans (15), and Asians (28-30, 37, 54, 55, 57, 58). Given that most aforesaid research studies on NWO have been conducted internationally, it is of paramount interest to ascertain the prevalence of NWO domestically. Consequently, the primary objective of this research study is to investigate the prevalence of normal-weight obesity among a sample of ostensibly healthy males and females.

Participants

All participants were required to report to the Body Composition Laboratory to complete a singular session. Before the participants arrived, volunteers were instructed to abstain from consuming caffeinated sustenance or beverages that may acutely influence body mass. Moreover, researchers advised participants to refrain from vigorous physical activity/exercise the night before and prior to their appointed session. Upon arrival, volunteers read and signed an informed consent form approved by the University’s Institutional Review Board for human subject use (IRB#: H23-0499). As displayed in Table 1, a cohort comprising 254 male and female volunteers were recruited to participate in this study.

Below highlights the details of the singular Session required for each participant.

Body Mass Index (BMI)

Before each assessment, participants were asked to remove any unattached item(s) from their body, such as shoes, socks, rings, bracelets, and/or glasses.  Height was measured to the nearest 0.5 cm as participants stood barefoot, with both legs together, with their back to a Seca 217 Mobile Stadiometer (Model Number 2171821009, USA).  Body mass was measured on a Tanita Multi-Frequency Total Body Composition Analyzer with Column (Model DC-430U, Tanita Corporation, Japan) to the nearest 0.1 kg.  Body mass index was calculated using body mass expressed in kilograms (kg) divided by height expressed in meters squared (m 2 ).  Body mass index categorizations, set forth via ACSM (4), for low BMI was (<18.5 kg∙m -2 ) and normal BMI was (18.5 – 24.9 kg∙m -2 ).

BOD POD ® Gold Standard (GS)

BOD POD ® Gold Standard (GS) (COSMED USA Inc., USA) was calibrated daily according to the manufacturer’s instructions with a 50.238 Liter cylindrical volume provided by COSMED USA Inc.  Specific details illustrating the technicalities of the calibration mechanism are published elsewhere (16, 18).  Because different clothing schemes have been shown to underestimate percentage body fat (%BF) results from the BOD POD ® (19, 49), female participants were instructed to wear one- or two-piece bathing suit or sports bra and compression shorts, while male participants were instructed to wear form-fitted compression shorts.  All participants wore a swim-like cap provided by COSMED USA Inc.  After race, height, and age were inputted by a technician into the BOD POD ® GS kiosk, participants were asked to step on an electronic scale to determine body mass to the nearest .045 kg.  Once the BOD POD ® GS system recorded body mass, participants were instructed to sit comfortably and breathe normally within the BOD POD ® GS for two trials lasting 40 seconds per trial.  A third trial was conducted if Trials 1 and 2 had high variability.  Once both (or three) trials were conducted, body composition values, specifically, body mass, percent body fat, fat-free mass, and fat mass, were immediately displayed on the kiosk viewer and recorded by a technician.  Once height, body mass, and body composition assessments were completed, participants dressed back into their original clothing and exited the Body Composition Lab.

Statistical Analyses

Descriptive statistics (mean ± SD) were derived to describe the sample population.  A Chi-Square Goodness of Fit Test was used to determine the prevalence of low/normal BMI values with obesity-related percent body fat.  For all analyses, statistical significance was established at p < 0.05.

At the conclusion of the study, 254 volunteers were recruited, and zero dropped out, therefore, all 254 participants’ results were included in the statistical analyses. Table 2 displays the descriptive measures of the study participants.

The chi-squared statistic was 1.886 (df = 1, p = 0.17) indicating no statistical difference in NWO between males (17.2%) and females (9.8%).

As stated previously, there is a dearth of data determining the prevalence of NWO domestically, more specifically, within the southeast region of the United States.  Therefore, the primary objective of this research study was to investigate the frequency of NWO amongst a sample of apparently healthy individuals.  Participants completed a singular data collection session whereby height, body mass, and percentage body fat were quantified via BOD POD ® GS.  Within this current study, low and normal BMI classifications were <18.5 kg∙m -2 and 18.5 – 24.9 kg∙m -2 , respectively.  Class I obesity for females and males were ≥ 32% and ≥ 25%, respectively.  Given said thresholds, data revealed that 12.2% of the overall sample exhibited NWO, with a higher prevalence amongst males (17.2%) compared to females (9.8%).  These findings are relatively comparable within other research investigating the prevalence of NWO amongst a sample of young adults (5, 35, 44, 57).

In 2017, Ramsaran and Maharaj investigated the prevalence of NWO within a cohort of 236 young adults (mean age = 21.3 ± 2.5 years).  The quantification of %BF was accomplished using the Tanita Ironman body composition analyzer.  Subsequent data analyses unveiled a heightened prevalence of NWO among the male participants (14.4%), surpassing their female counterparts (5.5%).  The outcomes of the current study align with the findings reported by Ramsaran and Maharaj (44), wherein NWO manifested in 17.2% of males and 9.8% of females. A nuanced distinction between the two investigations lies in the designated thresholds for %BF. Ramsaran and Maharaj (44) set the elevated %BF thresholds at ≥ 23.1% for males and ≥ 33.3% for females. In contrast, the current study employed thresholds of ≥ 25.0% for males and ≥ 32.0% for females.  Notwithstanding the marginal elevation (+1.9%) in the %BF threshold within the current study, males exhibited a greater prevalence (+2.8%) compared to Ramsaran and Maharaj’s (44) dataset.  Conversely, the current study adopted a lower %BF threshold (–1.3%) for females and uncovered a higher prevalence of NWO (+4.4%).  These subtle yet discernible variations in %BF thresholds may elucidate the divergent prevalence rates of NWO observed between the two scholarly investigations.

Akin to Ramsaran and Maharaj (44) and the present investigation, Anderson and colleagues (5) examined the incidence of NWO within a more modest cohort of 94 young adults (mean age = 19.6 ± 1.5 years).  The quantification of %BF was assessed via DXA. The %BF thresholds were predicated on National Health and Nutrition Examination Survey standards, establishing obesity values of ≥ 30.0% for males and ≥ 35.0% for females.  Findings elucidated an NWO prevalence in males (26.7%) and females (7.8%). Noteworthy is the marked elevation in male NWO rates (+9.5%) and marginal reduction (–2.0%) in female NWO rates compared to the current study.  While discrepancies may be attributed to variances in sample size (254 in the present study vs. 94 in Anderson et al.), divergent methodologies for %BF assessment (utilizing BOD POD® GS presently as opposed to DXA in Anderson et al.), and distinct %BF thresholds (ACSM criteria in the current study versus NHANES in Anderson et al.), the overarching findings remain concordant. Specifically, data from all three research investigations underscore the consistent pattern wherein males manifest elevated NWO prevalence rates relative to their female counterparts.

In contradistinction to the two previous research investigations and the current study, Zhang et al. (57) explored the NWO prevalence amongst 383 young adults (mean age = 20.4 ± 1.6 years). Assessment of %BF was executed through bioelectrical impedance analyses (BIA) employing the InBody 720 device. Obesity classification was contingent upon threshold values of ≥20.0% for males and ≥30.0% for females, as established by Zhang and associates (57).  Analyses unveiled an NWO prevalence of 13.2% in males and 27.5% in females, a prominent deviation from the present study’s findings. The contrasting NWO prevalence patterns observed between the two studies are notably discernible. Specifically, Zhang and colleagues (57) reported a higher prevalence in females than males, whereas the current investigation revealed the converse. This discordance is seemingly attributable to variances in the %BF thresholds implemented for obesity classification. Zhang et al. (57) utilized a considerably lower threshold for males at 20.0%, as opposed to the 25.0% threshold applied in the current study. Similarly, for females, Zhang et al. (57) employed a lower %BF threshold at 30.0%, whereas the present study utilized a more conservative threshold of 32.0%. Moreover, a salient methodological distinction lies in the apparatus employed for %BF quantification. The current study utilized the BOD POD ® GS, acknowledged as the applied gold standard for assessing body composition, while Zhang et al. (57) employed the InBody 720 BIA. These methodological nuances likely contribute to the divergent findings between the present research and Zhang et al. (57), underscoring the importance of rigorously evaluating both threshold criteria and assessment modalities when interpreting and comparing NWO prevalence data.

In a recent investigation, Maitiniyazi et al. (35) endeavored to ascertain the prevalence of NWO within a cohort of 279 young adults (mean age = 21.7 ± 2.1 years). Percentage body fat was assessed utilizing the InBody 770 BIA method.  Obesity classification thresholds were established at 20.0% for males and 30.0% for females.  Parallel to the observed NWO patterns delineated by Zhang and colleagues (57), Maitiniyazi et al. also discerned a higher prevalence of NWO in females (40.1%) as opposed to males (25.5%).  Notably, while these NWO trends align with the patterns identified by Zhang et al. (57), they markedly deviate from the outcomes of the current investigation.  Such discordant findings may find elucidation in the nuanced disparities in the thresholds employed to categorize obesity and the instrumentation deployed for %BF quantification.  Specifically, the divergence in %BF thresholds used for obesity classification emerges as a significant factor. Maitiniyazi et al. (35) employed thresholds different from those of Zhang et al. (57) and the current study, thereby contributing to the observed inconsistencies. Additionally, the equipment utilized to quantify %BF introduces another layer of methodological variation. While Zhang et al. (57) implemented InBody 720 BIA and the current study utilized BOD POD ® GS, Maitiniyazi et al. deployed the InBody 770 BIA method.  These divergent methodological approaches underscore the imperative of meticulous consideration when interpreting and comparing NWO prevalence data, highlighting the multifaceted nature of the interplay between obesity thresholds and assessment methodologies in elucidating NWO prevalence.

CONCLUSIONS

This comprehensive investigation contributes significantly to our understanding of NWO prevalence within a young adult population, particularly within the Southeast region of the United States.  The study employed the BOD POD ® GS for precise measurement of height, body mass, and percentage body fat, revealing a higher, but not statistically different, prevalence in NWO between males and females.  These results align with similar studies collectively emphasizing the consistent pattern of elevated NWO prevalence in males relative to females.  The study’s alignment with said research investigations further underscores the robustness of the findings, notwithstanding variations in sample size, methodology, and threshold criteria.  Conversely, discrepancies with other research investigations highlight the sensitivity of NWO prevalence to %BF thresholds and assessment modalities.  Despite the divergence in outcomes, these studies collectively reinforce the need for careful consideration of methodological nuances in interpreting and comparing NWO prevalence data.

APPLICATION IN SPORTS

From a practical perspective, the findings emphasize the importance of incorporating regional and demographic variations when assessing NWO prevalence.  Furthermore, the study underscores the relevance of employing standardized methodologies in ensuring consistency and comparability across investigations.  Future endeavors in this domain should continue to explore regional variations, refine %BF threshold criteria, and employ advanced methodologies for accurate NWO characterization.  This knowledge is pivotal for tailoring preventive measures and interventions; more precisely, accurately identifying NWO individuals is an opportunity for clinicians to proactively educate their clients regarding the health risks associated with hypokinetic disease(s), particularly cardiovascular disease(s), metabolic syndrome, and cardiometabolic dysfunction.

• Alawi, M., Begum, A., Harraz, M., Alawi, H., Bamagos, S., Yaghmour, A., & Hafiz, L. (2021). Dual-Energy X-Ray Absorptiometry (DEXA) Scan Versus Computed Tomography for Bone Density Assessment. Cureus , 13 (2), e13261. https://doi.org/10.7759/cureus.13261
• Alemán-Mateo, H., Huerta, R. H., Esparza-Romero, J., Méndez, R. O., Urquidez, R., & Valencia, M. E. (2007). Body composition by the four-compartment model: validity of the BOD POD for assessing body fat in Mexican elderly. European journal of clinical nutrition , 61 (7), 830–836. https://doi.org/10.1038/sj.ejcn.1602597
• Alqarni, A. M., Aljabr, A. S., Abdelwahab, M. M., Alhallafi, A. H., Alessa, M. T., Alreedy, A. H., Elmaki, S. A., Alamer, N. A., & Darwish, M. A. (2023). Accuracy of body mass index compared to whole-body dual energy X-ray absorptiometry in diagnosing obesity in adults in the Eastern Province of Saudi Arabia: A cross-sectional study. Journal of family & community medicine , 30 (4), 259–266. https://doi.org/10.4103/jfcm.jfcm_85_23
• American College of Sports Medicine. (2020). ACSM’s guidelines for exercise testing and prescription (11 th ed.). Wolters Kluwer.
• Anderson, K. C., Hirsch, K. R., Peterjohn, A. M., Blue, M. N. M., Pihoker, A. A., Ward, D. S., Ondrak, K. S., & Smith-Ryan, A. E. (2020). Characterization and prevalence of obesity among normal weight college students. International journal of adolescent medicine and health , 35 (1), 81–88. https://doi.org/10.1515/ijamh-2020-0240
• Bachrach L. K. (2000). Dual energy X-ray absorptiometry (DEXA) measurements of bone density and body composition: promise and pitfalls. Journal of pediatric endocrinology & metabolism: JPEM , 13 Suppl 2 , 983–988.
• Ballard, T. P., Fafara, L., & Vukovich, M. D. (2004). Comparison of Bod Pod and DXA in female collegiate athletes. Medicine and science in sports and exercise , 36 (4), 731–735. https://doi.org/10.1249/01.mss.0000121943.02489.2b
• Batsis, J. A., Sahakyan, K. R., Rodriguez-Escudero, J. P., Bartels, S. J., Somers, V. K., & Lopez-Jimenez, F. (2013). Normal weight obesity and mortality in United States subjects ≥60 years of age (from the Third National Health and Nutrition Examination Survey). The American journal of cardiology , 112 (10), 1592–1598. https://doi.org/10.1016/j.amjcard.2013.07.014
• Bazzocchi, A., Ponti, F., Albisinni, U., Battista, G., & Guglielmi, G. (2016). DXA: Technical aspects and application. European journal of radiology , 85 (8), 1481–1492. https://doi.org/10.1016/j.ejrad.2016.04.004
• Bilsborough, J. C., Greenway, K., Opar, D., Livingstone, S., Cordy, J., & Coutts, A. J. (2014). The accuracy and precision of DXA for assessing body composition in team sport athletes. Journal of sports sciences , 32 (19), 1821–1828. https://doi.org/10.1080/02640414.2014.926380
• Brown, A. F., Alfiero, C. J., Brooks, S. J., Kviatkovsky, S. A., Smith-Ryan, A. E., & Ormsbee, M. J. (2021). Prevalence of Normal Weight Obesity and Health Risk Factors for the Female Collegiate Dancer. Journal of strength and conditioning research , 35 (8), 2321–2326. https://doi.org/10.1519/JSC.0000000000004064
• Clayton, P., Trak-Fellermeier, M. A., Macchi, A., Galván, R., Bursac, Z., Huffman-Ercanli, F., Liuzzi, J., & Palacios, C. (2023). The association between hydration status and body composition in healthy children and adolescents. Journal of pediatric endocrinology & metabolism : JPEM , 36 (5), 470–477. https://doi.org/10.1515/jpem-2022-0462
• Centers for Disease Control and Prevention. (Year). National Health and Nutrition Examination Survey (NHANES). Retrieved from [URL]
• Cota, B. C., Priore, S. E., Ribeiro, S. A. V., Juvanhol, L. L., de Faria, E. R., de Faria, F. R., & Pereira, P. F. (2022). Cardiometabolic risk in adolescents with normal weight obesity. European journal of clinical nutrition , 76 (6), 863–870. https://doi.org/10.1038/s41430-021-01037-7
• Čuta, M., Bařicová, K., Černý, D., & Sochor, O. (2019). Normal-weight obesity frequency in the Central European urban adult female population of Brno, Czech Republic. Central European journal of public health , 27 (2), 131–134. https://doi.org/10.21101/cejph.a5133
• Collins, M. A., Millard-Stafford, M. L., Sparling, P. B., Snow, T. K., Rosskopf, L. B., Webb, S. A., & Omer, J. (1999). Evaluation of the BOD POD for assessing body fat in collegiate football players. Medicine and science in sports and exercise , 31 (9), 1350–1356. https://doi.org/10.1097/00005768-199909000-00019
• Dencker, M., Thorsson, O., Lindén, C., Wollmer, P., Andersen, L. B., & Karlsson, M. K. (2007). BMI and objectively measured body fat and body fat distribution in prepubertal children. Clinical physiology and functional imaging , 27 (1), 12–16. https://doi.org/10.1111/j.1475-097X.2007.00709
• Dempster, P., & Aitkens, S. (1995). A new air displacement method for the determination of human body composition. Medicine and science in sports and exercise , 27 (12), 1692–1697.
• Fields, D. A., Hunter, G. R., & Goran, M. I. (2000). Validation of the BOD POD with hydrostatic weighing: influence of body clothing. International journal of obesity and related metabolic disorders: journal of the International Association for the Study of Obesity , 24 (2), 200–205. https://doi.org/10.1038/sj.ijo.0801113
• Franco, L. P., Morais, C. C., & Cominetti, C. (2016). Normal-weight obesity syndrome: diagnosis, prevalence, and clinical implications. Nutrition reviews , 74 (9), 558–570. https://doi.org/10.1093/nutrit/nuw019
• Frija-Masson, J., Mullaert, J., Vidal-Petiot, E., Pons-Kerjean, N., Flamant, M., & d’Ortho, M. P. (2021). Accuracy of Smart Scales on Weight and Body Composition: Observational Study. JMIR mHealth and uHealth , 9 (4), e22487. https://doi.org/10.2196/22487
• Gómez-Ambrosi, J., Silva, C., Galofré, J. C., Escalada, J., Santos, S., Gil, M. J., Valentí, V., Rotellar, F., Ramírez, B., Salvador, J., & Frühbeck, G. (2011). Body adiposity and type 2 diabetes: increased risk with a high body fat percentage even having a normal BMI. Obesity (Silver Spring, Md.) , 19 (7), 1439–1444. https://doi.org/10.1038/oby.2011.36
• Gómez-Ambrosi, J., Silva, C., Galofré, J. C., Escalada, J., Santos, S., Millán, D., Vila, N., Ibañez, P., Gil, M. J., Valentí, V., Rotellar, F., Ramírez, B., Salvador, J., & Frühbeck, G. (2012). Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity. International journal of obesity (2005) , 36 (2), 286–294. https://doi.org/10.1038/ijo.2011.100
• Hung, C. H. (2011). The Association between Body Mass Index and Body Fat in College Students: Asian Journal of Physical Education &Amp; Recreation , 17 (1), 18–24. https://doi.org/10.24112/ajper.171883
• Murray-Hurtado, M., Martín Rivada, Á., Quintero Alemán, C., Ruiz Alcántara, M. P., & Ramallo Fariña, Y. (2023). Body composition and nutritional status changes in adolescents with anorexia nervosa. Anales de pediatria , 99 (3), 162–169. https://doi.org/10.1016/j.anpede.2023.06.015
• Hussain, Z., Jafar, T., Zaman, M. U., Parveen, R., & Saeed, F. (2014). Correlations of skin fold thickness and validation of prediction equations using DEXA as the gold standard for estimation of body fat composition in Pakistani children. BMJ open , 4 (4), e004194. https://doi.org/10.1136/bmjopen-2013-004194
• Jean, N., Somers, V. K., Sochor, O., Medina-Inojosa, J., Llano, E. M., & Lopez-Jimenez, F. (2014). Normal-weight obesity: implications for cardiovascular health. Current atherosclerosis reports , 16 (12), 464. https://doi.org/10.1007/s11883-014-0464-7
• Jia, A., Xu, S., Xing, Y., Zhang, W., Yu, X., Zhao, Y., Ming, J., & Ji, Q. (2018). Prevalence and cardiometabolic risks of normal weight obesity in Chinese population: A nationwide study. Nutrition, metabolism, and cardiovascular diseases: NMCD ,  28 (10), 1045–1053. https://doi.org/10.1016/j.numecd.2018.06.015
• Kapoor, N., Furler, J., Paul, T. V., Thomas, N., & Oldenburg, B. (2019). Normal Weight Obesity: An Underrecognized Problem in Individuals of South Asian Descent. Clinical therapeutics , 41 (8), 1638–1642. https://doi.org/10.1016/j.clinthera.2019.05.016
• Kobayashi, M., Pattarathitwat, P., Pongprajakand, A., & Kongkaew, S. (2023). Association of normal weight obesity with lifestyle and dietary habits in young Thai women: A cross-sectional study. Obesity Pillars (Online) , 5 , 100055. https://doi.org/10.1016/j.obpill.2023.100055
• Kranjac, A. W., & Kranjac, D. (2023). Explaining adult obesity, severe obesity, and BMI: Five decades of change. Heliyon , 9 (5), e16210. https://doi.org/10.1016/j.heliyon.2023.e16210
• Krugh, M., & Langaker, M. D. (2023). Dual-Energy X-Ray Absorptiometry. In StatPearls . StatPearls Publishing.
• Kurmaev, D. P., Bulgakova, S. V., & Treneva, E. V. (2022). Advances in gerontology , 35 (2), 294–301.
• Madeira, F. B., Silva, A. A., Veloso, H. F., Goldani, M. Z., Kac, G., Cardoso, V. C., Bettiol, H., & Barbieri, M. A. (2013). Normal weight obesity is associated with metabolic syndrome and insulin resistance in young adults from a middle-income country. PloS one , 8 (3), e60673. https://doi.org/10.1371/journal.pone.0060673
• Maitiniyazi, G., Chen, Y., Qiu, Y. Y., Xie, Z. X., He, J. Y., & Xia, S. F. (2021). Characteristics of Body Composition and Lifestyle in Chinese University Students with Normal-Weight Obesity: A Cross-Sectional Study. Diabetes, metabolic syndrome and obesity: targets and therapy , 14 , 3427–3436. https://doi.org/10.2147/DMSO.S325115
• Manapurath, R. M., Hadaye, R., & Gadapani, B. (2022). Normal Weight Obesity: Role of apoB and Insulin Sensitivity in Predicting Future Cardiovascular Risk. International journal of preventive medicine , 13 , 31. https://doi.org/10.4103/ijpvm.IJPVM_139_20
• Mohammadian Khonsari, N., Khashayar, P., Shahrestanaki, E., Kelishadi, R., Mohammadpoor Nami, S., Heidari-Beni, M., Esmaeili Abdar, Z., Tabatabaei-Malazy, O., & Qorbani, M. (2022). Normal Weight Obesity and Cardiometabolic Risk Factors: A Systematic Review and Meta-Analysis. Frontiers in endocrinology , 13 , 857930. https://doi.org/10.3389/fendo.2022.857930
• Noreen, E. E., & Lemon, P. W. (2006). Reliability of air displacement plethysmography in a large, heterogeneous sample. Medicine and science in sports and exercise , 38 (8), 1505–1509. https://doi.org/10.1249/01.mss.0000228950.60097.01
• Oliveros, E., Somers, V. K., Sochor, O., Goel, K., & Lopez-Jimenez, F. (2014). The concept of normal weight obesity. Progress in cardiovascular diseases , 56 (4), 426–433. https://doi.org/10.1016/j.pcad.2013.10.003
• Passos, A. F. F., Santos, A. C., Coelho, A. S. G., & Cominetti, C. (2023). Associations between Normal-Weight Obesity and Disturbances in the Lipid Profile of Young Adults. Associações entre Obesidade Eutrófica e Alterações no Perfil Lipídico de Adultos Jovens. Arquivos brasileiros de cardiologia , 120 (9), e20220914. https://doi.org/10.36660/abc.20220914
• Phillips, C. M., Tierney, A. C., Perez-Martinez, P., Defoort, C., Blaak, E. E., Gjelstad, I. M., Lopez-Miranda, J., Kiec-Klimczak, M., Malczewska-Malec, M., Drevon, C. A., Hall, W., Lovegrove, J. A., Karlstrom, B., Risérus, U., & Roche, H. M. (2013). Obesity and body fat classification in the metabolic syndrome: impact on cardiometabolic risk metabotype. Obesity (Silver Spring, Md.) , 21 (1), E154–E161. https://doi.org/10.1002/oby.20263
• Pinheiro, A. C. D. B., Filho, N. S., França, A. K. T. D. C., Fontenele, A. M. M., & Santos, A. M. D. (2019). Sensitivity and specificity of the body mass index in the diagnosis of obesity in patients with non-dialysis chronic kidney disease: a comparison between gold standard methods and the cut-off value purpose. Nutricion hospitalaria , 36 (1), 73–79. https://doi.org/10.20960/nh.1880
• Rakhmat, I. I., Putra, I. C. S., Wibowo, A., Henrina, J., Nugraha, G. I., Ghozali, M., Syamsunarno, M. R. A. A., Pranata, R., Akbar, M. R., & Achmad, T. H. (2022). Cardiometabolic risk factors in adults with normal weight obesity: A systematic review and meta-analysis. Clinical obesity , 12 (4), e12523. https://doi.org/10.1111/cob.12523
• Ramsaran, C., & Maharaj, R. G. (2017). Normal weight obesity among young adults in Trinidad and Tobago: prevalence and associated factors. International journal of adolescent medicine and health , 29 (2), /j/ijamh.2017.29.issue-2/ijamh-2015-0042/ijamh-2015-0042.xml. https://doi.org/10.1515/ijamh-2015-0042
• Sabatier, J. P., & Guaydier-Souquieres, G. (1989). Noninvasive methods of bone-mass measurement. Clinical rheumatology , 8 Suppl 2 , 41–45. https://doi.org/10.1007/BF02207232
• Shea, J. L., King, M. T., Yi, Y., Gulliver, W., & Sun, G. (2012). Body fat percentage is associated with cardiometabolic dysregulation in BMI-defined normal weight subjects. Nutrition, metabolism, and cardiovascular diseases: NMCD , 22 (9), 741–747. https://doi.org/10.1016/j.numecd.2010.11.009
• Toombs, R. J., Ducher, G., Shepherd, J. A., & De Souza, M. J. (2012). The impact of recent technological advances on the trueness and precision of DXA to assess body composition. Obesity (Silver Spring, Md.) , 20 (1), 30–39. https://doi.org/10.1038/oby.2011.211
• Tseh, W., Caputo, J. L., & Keefer, D. J. (2010). Validity and reliability of the BOD POD ® S/T tracking system. International journal of sports medicine , 31 (10), 704–708. https://doi.org/10.1055/s-0030-1255111
• Vescovi, J. D., Zimmerman, S. L., Miller, W. C., & Fernhall, B. (2002). Effects of clothing on accuracy and reliability of air displacement plethysmography. Medicine and science in sports and exercise , 34 (2), 282–285. https://doi.org/10.1097/00005768-200202000-00016
• Ward, Z. J., Bleich, S. N., Cradock, A. L., Barrett, J. L., Giles, C. M., Flax, C., Long, M. W., & Gortmaker, S. L. (2019). Projected U.S. State-Level Prevalence of Adult Obesity and Severe Obesity. The New England journal of medicine , 381 (25), 2440–2450. https://doi.org/10.1056/NEJMsa1909301
• Wijayatunga, N. N., & Dhurandhar, E. J. (2021). Normal weight obesity and unaddressed cardiometabolic health risk-a narrative review. International journal of obesity (2005) , 45 (10), 2141–2155. https://doi.org/10.1038/s41366-021-00858-7
• Wijayatunga, N. N., Kim, H., Hays, H. M., & Kang, M. (2022). Objectively Measured Physical Activity Is Lower in Individuals with Normal Weight Obesity in the United States. International journal of environmental research and public health , 19 (18), 11747. https://doi.org/10.3390/ijerph191811747
• Wilson, O. W. A., Zou, Z. H., Bopp, M., & Bopp, C. M. (2019). Comparison of obesity classification methods among college students. Obesity research & clinical practice , 13 (5), 430–434. https://doi.org/10.1016/j.orcp.2019.09.003
• Yamashiro, K., Yamaguchi, N., Sagawa, K., Tanei, S., Ogata, F., Nakamura, T., & Kawasaki, N. (2023). Relationship of masked obesity to self-reported lifestyle habits, ideal body image, and anthropometric measures in Japanese university students: A cross-sectional study. PloS one , 18 (2), e0281599. https://doi.org/10.1371/journal.pone.0281599
• Yasuda T. (2019). Anthropometric, body composition, and somatotype characteristics of Japanese young women: Implications for normal-weight obesity syndrome and sarcopenia diagnosis criteria. Interventional medicine & applied science , 11 (2), 117–121. https://doi.org/10.1556/1646.11.2019.14
• Zapata, J. K., Azcona-Sanjulian, M. C., Catalán, V., Ramírez, B., Silva, C., Rodríguez, A., Escalada, J., Frühbeck, G., & Gómez-Ambrosi, J. (2023). BMI-based obesity classification misses children and adolescents with raised cardiometabolic risk due to increased adiposity. Cardiovascular diabetology , 22 (1), 240. https://doi.org/10.1186/s12933-023-01972-8
• Zhang, M., Schumann, M., Huang, T., Törmäkangas, T., & Cheng, S. (2018). Normal weight obesity and physical fitness in Chinese university students: an overlooked association. BMC public health , 18 (1), 1334. https://doi.org/10.1186/s12889-018-6238-3
• Zhu, Y., Maruyama, H., Onoda, K., Zhou, Y., Huang, Q., Hu, C., Ye, Z., Li, B., & Wang, Z. (2023). Body mass index combined with (waist + hip)/height accurately screened for normal-weight obesity in Chinese young adults. Nutrition , 108 , 111939. https://doi.org/10.1016/j.nut.2022.111939
• Zhu, Y., Wang, Z., Maruyama, H., Onoda, K., & Huang, Q. (2022). Body Fat Percentage and Normal-Weight Obesity in the Chinese Population: Development of a Simple Evaluation Indicator Using Anthropometric Measurements. International journal of environmental research and public health , 19 (7), 4238. https://doi.org/10.3390/ijerph19074238

Adult exercisers’ attitudes toward female and male personal fitness trainers: Influence of gender, age, and exercise experience

Qshequilla Parham Mitchell 2024-09-16T09:32:10-05:00 September 13th, 2024 | General , Sport Training |

Authors: Edward P. Hebert 1 , and Jada McGuin 2

1 Department of Kinesiology and Health Studies, Southeastern Louisiana University, Hammond, LA, USA 2 Fitt House, Baton Rouge, LA, USA

Edward Hebert

SLU Box 10845

Hammond, LA 70810

[email protected]

985-549-2132

Edward Hebert, PhD is a Professor in the Department of Kinesiology and Health Studies at Southeastern Louisiana University. His research interests include exercise motivation and adherence; and morale, efficacy, and burnout among health and wellness professionals.

Jada McGuin, MS, MHA is a health and wellness professional and the Owner/Operator of The Fitt House in Baton Rouge. Her professional interests focus on the implementation of preventative measures such as health screening, exercise, and lifestyle interventions to reduce the prevalence of chronic illness and diseases.

This study describes attitudes of adult exercisers toward female and male personal fitness trainers, and compares responses of male and female, younger vs older exercisers, and those with varying levels of exercise experience. Recruited from 4 fitness gyms, 201 adults aged 18 to 77 completed an anonymous survey where they provided relative attitude ratings toward female vs. male fitness trainers specific to the trainer’s knowledge, helping meet personal fitness goals, following their directions, comfort discussing struggles with exercise, working with the trainer for an extended time, and referring others to them. Participants rated male trainers higher for fitness knowledge, and were more willing to follow their directions, work with them for an extended time, and refer clients to them, but perceived a female trainer more favorably for discussing their struggles with exercise. Significant gender, age, and experience differences were found. Gender-biased perceptions were highest among male, older, and inexperienced exercisers, who had more positive attitudes toward male fitness trainers. Attitudes of women, younger, and experienced exercisers tended to be more neutral, and favor female trainers for meeting personal goals and discussing struggles. The results of this exploratory study suggest gender-biased exercise attitudes are influenced by participant gender, as well as age and experience, and provide impetus for additional research on exercise attitudes.

Keywords : personal training, beliefs, perceptions, biases

Recent decades have seen a great expansion of the fitness industry signaled by an increase in the number of adults exercising in fitness centers around the world. This rise has been attributed to a number of factors including global recognition of the benefits of physical activity, endorsement of exercise by the medical community, and growth of the fitness industry (1, 29). Yet, exercise adherence remains problematic (9, 25, 37, 38, 41) and fitness clubs tend to have low retention rates (7, 17, 18, 29, 36, 42). The practice of exercising with a personal fitness trainer (PFT) has increased in popularity and personal training has become a standard feature in many settings (5, 27, 29, 43, 44). PFTs design and supervise exercise programs, and help clients set and reach personal goals. In addition, they engage in practices to promote an active lifestyle, motivate clients, and facilitate their exercise competence and self-efficacy, which can play an important role in exercise adherence (29, 35, 44). Studies of consumers consistently identify a fitness club’s staff, and fitness leaders’ instruction, feedback, and support as among the most important factors in customer satisfaction (19, 33). In addition, satisfaction with individualized training is positively associated with exercise motivation and self-efficacy (44). Consistent evidence points to the benefits of exercising with a PFT. Studies show that individuals who train with a PFT are more likely to attend exercise sessions and adhere to programs (2, 14, 22, 32). Those who train with a PFT have been found to exercise at higher intensities (31, 40) and make greater strength and fitness gains (30, 31) than those who exercise independently. These results are similar to findings comparing individuals who train alone vs. under the supervision of a fitness professional (11, 16).

Studies of fitness settings have often concluded that gender plays a role in gym-related attitudes and behaviors. In their review, Håman et al. (20) suggested fitness gym spaces are strongly associated with male bodies and norms, and gender norms influence social practices and behaviors there. Exercise motivation has been tied to weight loss for women and enhancing muscularity among men (24). Certain types of exercise are considered masculine or feminine, and exercisers have been shown to use gendered language to refer to areas of the gym (8). Interview-based studies of PFTs indicate that a clients’ gender influences their advice (20) and they recognize that gender plays a role in clients’ selection of a trainer (35).

The results of previous interview-based studies (27, 34) indicated that women prefer a female PFT. This preference is based on perceptions of being less self-conscious about their bodies with a female trainer, and the beliefs that a female trainer would better understand and empathize with their struggles with exercise and comfort levels in the gym. Survey-based research comparing perceptions of male and female fitness trainers have studied the attitudes of college students, and produced mixed results. In their study of 402 undergraduates, Fisher et al. (15) found no clear preference for a male or female PFT, yet hypothetical female PFTs received higher ratings for general perceptions of competence, and participants’ willingness to discuss progress and take instructions/corrections from them, compared to male trainers. Boerner et al. (5) similarly found that college undergraduates perceived female PFTs as more competent and knowledgeable than males. However, male students preferred to work with a male fitness trainer, while female students had no gender preference. Similarly, Magnusen and Rhea (28) found female college Division I athletes had no preference for a male or female strength coach, whereas males preferred a male coach.

Thus, research to date on attitudes toward male vs. female PFTs has provided mixed results, and survey-based studies to date have exclusively examined perceptions of college students, which may be different from non-college aged adults. In addition, research has yet to examine how attitudes toward male/female fitness trainers may vary with other potentially-influential factors such as age and exercise experience. Thus, the purpose of this exploratory study was to examine attitudes toward male and female PFTs in a sample of adult members of fitness gyms, and compare responses with respect to participant gender, age, and exercise experience.

Participants were 201 (144 female; 57 male) adult members of four fitness centers from one city in the southeast United States who responded to an online survey. They ranged in age from 18 to 77 years (mean = 35.87, SD = 14.87 years). Self-reported experience levels were Beginner (n=59), Intermediate (n=91) and Advanced (n=51). Over half of the sample indicated exercising four or more times per week (54.9%), with 25.3% indicating three times per week, and 20.1% once a week. Table 1 provides the number and percent of male and female participants in age and exercise experience groups.

Prior to data collection, the study was approved by the Institutional Review Board of the authors’ university. Participants were recruited from fitness centers via email with the cooperation of the managers. Two facilities were small gyms that offered only individual and small group training, and two were larger traditional fitness centers that housed a variety of equipment and amenities, and provided personal training services and group exercise classes as well as independent exercise. A recruiting email with a link to an anonymous online survey was sent to all members of the two small gyms, and members of the larger gyms who had expressed interest in personal training. Participants were assured of anonymity and informed their participation was voluntary and they were providing consent to participate by completing the survey.

Data were collected February-March 2021 using a survey created for the study. Survey items were based on and relatively similar to those used in previous research on attitudes toward female/male fitness trainers (15). Item content was guided by previous research examining criteria for selecting a PFT (20, 29, 35) and on reasons people may prefer a male/female PFT (27, 34). After initial development, the survey was reviewed by researchers with expertise in fitness who provided feedback and recommendations.

The first section sought demographic information including gender, age, level of fitness experience (beginner, intermediate, or advanced), and frequency of exercise during the last month. The next section focused on participant’s attitudes about working with a PFT, specifically how their attitudes would be influenced by the trainer’s gender. It included 6 face-valid items: (1) “My belief about the trainer’s knowledge about fitness,” (2) “My belief in the trainer’s desire for me to meet my personal fitness goals,” (3) “My willingness to follow the trainer’s directions about exercise,” (4) “My level of comfort discussing my struggles with exercise with the trainer,” (5) “My willingness to continue working with the trainer for an extended length of time,” and (6) “My willingness to refer clients to the trainer.” Participants responded to teach item on a 5-option scale: Higher for a female trainer, slightly higher for a female trainer, the same for a female or male trainer, slightly higher for a male trainer, or higher for a male trainer.

Data Analysis

For data analysis, ratings were translated to a numerical scale from -2 to 2 with the neutral response in the center: (-2) Higher for a female trainer), (-1) Slightly higher for a female trainer), (0) The same for a female or male trainer, (1) Slightly higher for a male trainer, and (2) Higher for a male trainer. Responses were also coded categorically as neutral, or favoring a male or female trainer. Descriptive statistics (mean, standard deviation, and percent of responses indicating a neutral response or favoring a female/male PFT) for responses to each item are reported for the entire sample.

Responses were also analyzed with respect to three independent variables (gender, age group, and fitness experience). Three levels of fitness experience were self -reported Beginner, Intermediate, and Advanced. For the purpose of the study, participants were divided into two age groups operationally defined as younger (18-39 years) and older (40 years and older) exercisers. Numerical responses were analyzed using three separate MANOVAs with the 6 survey items as dependent measures. Significant main effects were further analyzed using independent t-tests or one-way ANOVA. Partial Omega Squared ( η p 2 ) and Cohen’s d were reported as indicators of effect size. In addition to these analyses, the percent of participants whose responses were neutral or favored a male or female PFT were reported for groups.

As shown in Figure 1, as a whole, participants tended to have higher ratings of male PFTs relative to fitness knowledge, willingness to follow their directions, working with the trainer for an extended time, and referring clients to them. However, they tended to perceive a female PFT more favorably for discussing their struggles with exercise. The percent of responses that were neutral or favored a male/female trainer yielded similar patterns. Overall, more people indicated positive attitudes toward a male than a female PFT for expectations of fitness knowledge (31.3% vs. 5.5%), as well as willingness to follow the trainer’s directions (29.9% vs. 10.9%), working with the trainer for an extended time (20.9% vs. 11.9%), and referring other clients to the trainer (17.4% vs. 5.5%). For comfort discussing struggles with exercise, 41.8% indicated a preference for a female trainer with only 24.4% preferring a male trainer. For most items, 50-60% of participants indicated a neutral response (the same for a male or female trainer), with the exception of comfort discussing concerns for which only 33.3% indicated no preference.

Attitudes of Male and Female Respondents

As shown in Figure 2, responses of male and female exercisers showed clear gender differences. Mean values indicated men rated a male PFT higher than a female PFT for all items. By comparison, female exercisers’ responses tended to vary more across items, and average responses were near neutral for several items. The MANOVA indicated significant differences between male and female respondents were present [Wilks’ Lambda=.845, p <.001, η p 2 = .16]. Follow up comparisons indicated significant differences for four items: expectations for the trainer to help meet personal fitness goals [ t (199)=4.20, p <.001, Cohen’s d =1.14], willingness to follow the trainer’s directions [ t (199)=2.71, p <.01, Cohen’s d =1.00], comfort discussing exercise struggles [ t (199)=5.24, p <.001, Cohen’s d =1.24], and willingness to work with the trainer for an extended time [ t (199)=2.01, p <.05, Cohen’s d =.93].

Gender-biased patterns were also evident in the percent of ratings which were neutral vs. favored a male or female PFT (see Table 2). A higher percent of male exercisers indicated they would be more comfortable discussing their struggles with a male (43.9%) than a female trainer (17.5%), whereas female exercisers indicated a preference for a female (51.4%) over a male PFT (16.9%). A similar same-gender preference was indicated for perceptions of the trainer’s desire to help meet personal fitness goals, and working with them for an extended time.

Attitudes of Younger vs. Older Exercisers

Older exercisers (aged 40 and over) tended to favor a male PFT for all items, whereas younger exercises (18-39 years) had more varied responses and were near neutral for several items (see Figure 3). Responses were found to vary significantly by age group [Wilks’ Lambda= .884, p <.05, η p 2 = .06]. Follow-up comparisons indicated significant differences for two items: meeting personal goals [ t (197)=2.88, p <.01, Cohen’s d =0.45], and discussing struggles [ t (197)=3.18, p <.01, Cohen’s d =0.49]. As indicated in Table 3, for these items, older exercisers tended to have either neutral attitudes or favor a male trainer, whereas younger exercisers more often favored a female trainer.

Variation as a Function of Exercise Experience

Mean scores for individuals varying in exercise experience are shown in Figure 4. The MANOVA comparing responses was significant [Wilks’ Lambda=.839, p <.001, η p 2 = .08]. One way ANOVA follow-up comparisons indicated a significant difference for only one item: expectations for the PFT’s knowledge [ F (2,198=7.14, p <.001, η p 2 =.086]. Post-hoc Student-Newman-Keuls comparisons indicated beginning exercisers had significantly greater expectations of fitness knowledge for male trainers ( p <.05), whereas knowledge expectations of male vs. female trainers were similar for exercisers with intermediate or advanced experience. Examination of response percentages (Table 4) shows a clear pattern of reduced gender-bias as exercise experience increased. For example, only 35.6% of beginner-level exercisers indicated expectations for a trainer to help them meet personal exercise goals would be the same for a male or female trainer, but this neutral rating increasing to 53.8% of intermediate exercisers, and 64.7% of advanced exercisers. This same pattern of increasing neutral response with higher exercise experience was observed for all items.

Research supports the benefits of exercising with a PFT (2, 14, 22, 30, 32, 40), and evidence suggests that gender plays a role in exercise attitudes and behaviors, including selection of a trainer (20, 26, 35, 39). Previous survey-based research on attitudes toward male and female PFTs have studied undergraduate students; attitudes of adult fitness center members have not been investigated. An additional limitation of existing research is the failure to examine variables that may play a role in these attitudes. This study examined attitudes toward male and female PFTs among 201 adult fitness center members. Perceptions were reported for the entire sample, and analyzed relative to participant gender, age group, and exercise experience.

As a whole, more participants favored a male over a female trainer for expectations of fitness-related knowledge, willingness for follow the trainer’s directions, working with the trainer for an extended time, and referring other clients to them. However, adults tended to be more comfortable discussing struggles and concerns with exercise with a female trainer. Fisher et al. (15) similarly reported college students had a more positive attitude about discussing progress with female than male trainers.

Age Differences

Our results showed age-related attitudinal differences. Specifically, older exercisers favored a male PFT, whereas younger respondents favored a female PFT primarily with respect to two items: assistance achieving personal goals and discussing exercise-related struggles. These findings are different from those reported in studies of college students, who overall, viewed female PFTs as more competent and knowledgeable than males (5, 15). Thus, these age-related attitudinal differences may be one of the more notable findings of this study, and may reflect changes in broader gender role-related attitudes among generations (10, 13).

Differences among Male and Female Exercisers

Comparisons between the responses of male and female exercisers revealed two important findings. First, men rated a male PFT higher than a female PFT for all items, while female exercisers’ ratings were more neutral. This is consistent with previous research on college students (5) and Division I university athletes (28) that indicated males preferred to work with a male PFT or strength coach, while females had no clear preference. Second, large and significant differences were observed between responses of men and women for several attitudes including those associated with knowledge, help meet personal goals, following directions, discussing concerns, and working with the trainer for an extended time. While men rated a male PFT higher for all items, women had more favorable perceptions of female PFTs for two specific items: discussing their struggles with exercise, and expectations regarding the trainer’s desire to help them meet personal fitness goals.

These findings align favorably with the results of previous interview-based studies indicating that women who choose a female PFT attribute this decision to beliefs that a female would have a greater empathy for them, and a better understanding of their bodies, struggles, and comfort levels (27, 34). These findings are also consistent with gender-preference research in healthcare. Drummond et al. (12), for example, found that college athletes felt more comfortable when provided care by an athletic trainer of the same gender, and a same-gender healthcare provider preference has been found for physicians and nurses when interactions are of an intimate nature (6, 23). When providing reasons for a healthcare provider of the same gender, women indicate it is due to comfort levels discussing problems and the perception that a female provider will take more personal interest in them (23).

Experience as a Mediator of Gender-Bias

We also examined attitudes toward male/female PFTs as a function of exercise experience, and used self-ratings as the basis for group formation. Comparisons indicated that, as exercise experience increased, gender-biased ratings decreased. Among beginning exercisers, 37% indicated their expectations for a PFT’s knowledge was neutral (the same for a male or female), whereas 65% of intermediate and 90% of advanced exercisers indicated so. This pattern of increasing gender-neutrality with exercise experience was observed for all items. These results suggest that gender-biased attitudes toward male/female PFTs may reduce with experience. This interpretation is consistent with the ideas that, while fitness-based attitudes and practices are influenced by gender norms and expectations, they are not fixed, but are fluid and can be changed with experience (3, 4, 20).

CONCLUSIONS, LIMITATIONS, AND DIRECTIONS FOR FUTURE RESEARCH

The results of this study indicate that many adult exercisers have gender-biased perceptions of PFTs with higher expectations for a male trainer’s fitness-based knowledge, and willingness to follow a male trainer’s directions and refer clients to him, yet are more comfortable discussing their struggles with a female trainer. Consistent with prior research on college students, these attitudes vary with participant gender. Men had stronger preferences for a same-gender PFT than women did, yet many women tended to favor a female PFT for interest in their personal goals and discussing their struggles and concerns. In addition, potentially important findings from this study are that gender-biased attitudes varied by age and exercise experience. Further research examining how these and other factors and experiences influence gender-referenced perceptions of fitness and fitness professionals is warranted, as is extending research on fitness-related attitudes beyond that of college students.

Previous research on this topic (5, 15) has primarily surveyed convenience samples of undergraduate students whose participation and experience in exercise was unknown, whereas participants in this study were adult fitness center members primarily between 20 and 39 years of age, most who identified as having intermediate or advanced exercise experience, and who exercised 3 or more times a week. Thus, the findings of this study may be more generalizable to typical adults who exercise on a regular basis. However, it should be acknowledged that, while data were derived from a sample of adults from multiple fitness centers, all gyms were from the same region of the U.S., and respondents were primarily female. Age-related differences were examined among two groups with an arbitrary dividing point. Thus, future research on this topic using more varied samples, more adult males, among varying age groups, and additional potentially influential variables is recommended.

APPLICATIONS IN SPORT

Fitness professionals should recognize that gender plays a role in exercise attitudes and behaviors, including the selection of PFTs and exercise leaders to work with. Data from this study highlight specific beliefs that may play a role in PFT preferences, and how these preferences vary with exerciser’s gender, age, and level of exercise experience. As a result, fitness professionals can strive to behave and communicate in ways that both support clients’ preference, but also seek to overcome biases that may exist.

• Andreasson, J., & Johansson, T. (2014). The fitness revolution: Historical transformations in the global gym and fitness culture. Sport Science Review, 23(3-4), 91-112. doi: 10.2478/ssr-2014-0006
• Arikawa, A. Y., O’Dougherty, M., & Schmitz, K. H. (2011). Adherence to a strength training intervention in adult women. Journal of Physical Activity and Health, 8(1), 111-118. https://doi.org/10.1123/jpah.8.1.111
• Azzarito, L., & Katzew, A. (2010). Performing identities in physical education: (En)gendering fluid selves. Research Quarterly for Exercise and Sport, 81(1), 25-37. https://doi.org/10.1080/02701367.2010.10599625
• Barker-Ruchti, N., Grahn, K., & Lindgren, E. C. (2016). Shifting, crossing and transforming gender boundaries in physical cultures. Sport in Society, 19(5), 615-625. https://doi.org/10.1080/17430437.2015.1073942
• Boerner, P. R., Polasek, K. M., True, L., Lind, E., & Hendrick, J. L. (2021). Is what you see what you get? Perceptions of personal trainers’ competence, knowledge, and preferred sex of personal trainer relative to physique. Journal of Strength & Conditioning Research, 35(7), 1949-1955. doi: 10.1519/JSC.0000000000003027
• Chur‐Hansen, A. (2002). Preferences for female and male nurses: The role of age, gender and previous experience – Year 2000 compared with 1984. Journal of Advanced Nursing, 37(2), 192-198. https://doi.org/10.1046/j.1365-2648.2002.02079.x
• Clavel San Emeterio, I., García-Unanue, J., Iglesias-Soler, E., Luis Felipe, J., & Gallardo, L. (2019). Prediction of abandonment in Spanish fitness centres. European Journal of Sport Science, 19(2), 217-224. https://doi.org/10.1080/17461391.2018.1510036
• Coen, S. E., Rosenberg, M. W., & Davidson, J. (2018). “It’s gym, like g-y-m not J-i-m”: Exploring the role of place in the gendering of physical activity. Social Science & Medicine, 196, 29-36. https://doi.org/10.1016/j.socscimed.2017.10.036
• Collado-Mateo, D., Lavín-Pérez, A. M., Peñacoba, C., Del Coso, J., Leyton-Román, M., Luque-Casado, A., Gasque, P., Fernandez-del-Olmo, M. A., & Amado-Alonso, D. (2021). Key factors associated with adherence to physical exercise in patients with chronic diseases and older adults: An umbrella review. International Journal of Environmental Research and Public Health, 18(4), 2023. https://doi.org/10.3390/ijerph18042023
• Cotter, D., Hermsen, J. M., & Vanneman, R. (2011). The end of the gender revolution? Gender role attitudes from 1977 to 2008. American Journal of Sociology, 117(1), 259-289.
• Coutts, A. J., Murphy, A. J., & Dascombe, B. J. (2004). Effect of direct supervision of a strength coach on measures of muscular strength and power in young rugby league players. Journal of Strength and Conditioning Research, 18(2), 316-323. http://hdl.handle.net/10453/9724
• Drummond, J. L., Hostetter, K., Laguna, P. L., Gillentine, A., & Del Rossi, G. (2007). Self-reported comfort of collegiate athletes with injury and condition care by same-sex and opposite-sex athletic trainers. Journal of Athletic Training, 42(1), 106-112. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1896076/
• Eagly, A. H., Nater, C., Miller, D. I., Kaufmann, M., & Sczesny. S. (2020). Gender stereotypes have changed: A cross-temporal meta-analysis of U.S. public opinion polls from 1946 to 2018. American Psychologist, 75(3), 301-315. http://dx.doi.org/10.1037/amp0000494
• Fischer, D. V., & Bryant, J. (2008). Effect of certified personal trainer services on stage of exercise behavior and exercise mediators in female college students. Journal of American College Health, 56(4), 369-376. https://doi.org/10.3200/JACH.56.44.369-376
• Fisher, J. P., Platts, C., & Stopforth, M. (2013). Attitudes toward and preferences for male and female personal trainers. International Journal of Exercise Science, 6(4), 256-268.
• Gentil, P., & Bottaro, M. (2010). Influence of supervision ratio on muscle adaptations to resistance training in nontrained subjects. Journal of Strength & Conditioning Research, 24(3), 639-643. doi: 10.1519/JSC.0b013e3181ad3373
• Gjestvang, C., Abrahamsen, F., Stensrud, T., & Haakstad, L. A. (2020). Motives and barriers to initiation and sustained exercise adherence in a fitness club setting: A one‐year follow‐up study. Scandinavian Journal of Medicine & Science in Sports, 30(9), 1796-1805. https://doi.org/10.1111/sms.13736
• Gjestvang, C., Abrahamsen, F., Stensrud, T., & Haakstad, L. A. (2021). What makes individuals stick to their exercise regime? A one-year follow-up study among novice exercisers in a fitness club setting. Frontiers in Psychology, 12, 638928. https://doi.org/10.3389/fpsyg.2021.638928
• Gocłowska, S., Piątkowska, M., & Lenartowicz, M. (2019). Customer satisfaction and its measurement in fitness clubs of Warsaw. Economics & Sociology, 12(2), 205-218. doi:10.14254/2071-789X.2019/12-2/12
• Håman, L., Yring, H., Prell, H., & Lindgren, E. C. (2020). Personal trainers’ health advice in the fitness gym space from a gender perspective. International Journal of Qualitative Studies on Health and Well-being, 15, 1794364. https://doi.org/10.1080/17482631.2020.1794364
• International Health, Racquet and Sportsclub Association IHRSA. The 2020 IHRSA global report: The state of the health club industry. IHRSA.
• Jeffery, R. W., Wing, R. R., Thorson, C., & Burton, L. R. (1998). Use of personal trainers and financial incentives to increase exercise in a behavioral weight-loss program. Journal of Consulting and Clinical Psychology, 66(5), 777-783. https://doi.org/10.1037/0022-006X.66.5.777
• Kerssens, J. J., Bensing, J. M., & Andela, M. G. (1997). Patient preference for genders of health professionals. Social Science & Medicine, 44(10), 1531-1540. https://doi.org/10.1016/S0277-9536(96)00272-9
• Kilpatrick, M., Hebert, E., & Bartholomew, J. (2005). College students’ motivation for physical activity: Differentiating men’s and women’s motives for sport participation and exercise. Journal of American College Health, 54(2), 87-94. http://dx.doi.org/10.3200/JACH.54.2.87-94
• Lakicevic, N., Gentile, A., Mehrabi, S., Cassar, S., Parker, K., Roklicer, R., Bianco, A., & Drid, P. (2020). Make fitness fun: Could novelty be the key determinant for physical activity adherence? Frontiers in Psychology, 11, 577522. https://doi.org/10.3389/fpsyg.2020.577522
• León-Quismondo, J., García-Unanue, J., & Burillo, P. (2020). Service perceptions in fitness centers: IPA approach by gender and age. International Journal of Environmental Research and Public Health, 17(8), 2844. https://doi.org/10.3390/ijerph17082844
• Madeson, M. N., Hultquist, C. N., Church, A., & Fisher, L. A. (2010). A phenomenological investigation of women’s experiences with personal training. International Journal of Exercise Science, 3(3), 157-169. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4738891/
• Magnusen, M. J., & Rhea, D. J. (2009). Division I athletes’ attitudes toward and preferences for male and female strength and conditioning coaches. Journal of Strength & Conditioning Research, 23(4), 1084-1090. doi: 10.1519/JSC.0b013e318199d8c4
• Maguire, J. S. (2001). Fit and flexible: The fitness industry, personal trainers and emotional service labor. Sociology of Sport Journal, 18(4), 379-402. ttps://doi.org/10.1123/ssj.18.4.379
• Maloof, R. M., Zabik, R. M., & Dawson, M. L. (2001). The effect of use of a personal trainer on improvement of health related fitness for adults. Medicine & Science in Sports & Exercise, 33(5), S74.
• Mazzetti, S. A., Kraemer, W. J., Volek, J. S., Duncan, N. D., Ratamess, N. A., Gomez, A. L., Newton, R. U., Hakkinen, K., & Fleck, S. J. (2000). The influence of direct supervision of resistance training on strength performance. Medicine and Science in Sports and Exercise, 32(6), 1175-1184.
• McClaran, S. R. (2003). The effectiveness of personal training on changing attitudes towards physical activity. Journal of Sports Science & Medicine, 2(1), 10-14. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3937569/
• McGuire, A. M., Anderson, D. F., & Trail, G. (2009). Examination of consumer differences on the importance and satisfaction with fitness service attributes. International Journal of Sport Management, 10(1), 102-119.
• Melton, D., Dail, T. K., Katula, J. A., & Mustian, K. M. (2011). Women’s perspectives of personal trainers: A qualitative study. The Sport Journal, 14(1), 0104. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4439248/
• Melton, D. I., Katula, J. A., & Mustian, K. M. (2008). The current state of personal training: An industry perspective of personal trainers in a small southeast community. Journal of Strength and Conditioning Research, 22(3), 883-889. doi: 10.1519/JSC.0b013e3181660dab
• Middelkamp, J., Van Rooijen, M., & Steenbergen, B. (2016). Attendance behavior of ex-members in fitness clubs: A retrospective study applying the stages of change. Perceptual and Motor Skills, 122(1), 350-359. https://doi.org/10.1177/0031512516631075
• Peters, A. E., Kraus, W. E., & Mentz, R. J. (2023). New paradigms to address long-term exercise adherence, an achilles heel of lifestyle interventions. Circulation, 147(21), 1565-1567. https://doi.org/10.1161/CIRCULATIONAHA.123.064161
• Picorelli, A. M. A., Pereira, L. S. M., Pereira, D. S., Felício, D., & Sherrington, C. (2014). Adherence to exercise programs for older people is influenced by program characteristics and personal factors: A systematic review. Journal of Physiotherapy, 60(3), 151-156. https://doi.org/10.1016/j.jphys.2014.06.012
• Pridgeon, L., & Grogan, S. (2012). Understanding exercise adherence and dropout: An interpretative phenomenological analysis of men and women’s accounts of gym attendance and non-attendance. Qualitative Research in Sport, Exercise and Health, 4(3), 382-399. https://doi.org/10.1080/2159676X.2012.712984
• Ratamess, N. A., Faigenbaum, A. D., Hoffman, J. R., & Kang, J. (2008). Self-selected resistance training intensity in healthy women: The influence of a personal trainer. Journal of Strength & Conditioning Research, 22(1), 103-111. doi: 10.1519/JSC.0b013e31815f29cc
• Rodrigues, F., Bento, T., Cid, L., Pereira Neiva, H., Teixeira, D., Moutão, J., Marinho, D. A., & Monteiro, D. (2018). Can interpersonal behavior influence the persistence and adherence to physical exercise practice in adults? A systematic review. Frontiers in Psychology, 9, 2141. https://doi.org/10.3389/fpsyg.2018.02141
• Sperandei, S., Vieira, M. C., & Reis, A. C. (2016). Adherence to physical activity in an unsupervised setting: Explanatory variables for high attrition rates among fitness center members. Journal of Science and Medicine in Sport, 19(11), 916-920. https://doi.org/10.1016/j.jsams.2015.12.522
• Thompson, W. R. (2022). Worldwide survey of fitness trends for 2022. ACSM’s Health & Fitness Journal, 26(1), 11-20.
• Wayment, H. A., & McDonald, R. L. (2017). Sharing a personal trainer: Personal and social benefits of individualized, small-group training. Journal of Strength & Conditioning Research, 31(11), 3137-3145. doi: 10.1519/JSC.0000000000001764

• Systematic review update
• Open access
• Published: 21 June 2023

The impact of sports participation on mental health and social outcomes in adults: a systematic review and the ‘Mental Health through Sport’ conceptual model

• Narelle Eather   ORCID: orcid.org/0000-0002-6320-4540 1 , 2 ,
• Levi Wade   ORCID: orcid.org/0000-0002-4007-5336 1 , 3 ,
• Aurélie Pankowiak   ORCID: orcid.org/0000-0003-0178-513X 4 &
• Rochelle Eime   ORCID: orcid.org/0000-0002-8614-2813 4 , 5  

Systematic Reviews volume  12 , Article number:  102 ( 2023 ) Cite this article

93k Accesses

38 Citations

332 Altmetric

Metrics details

Sport is a subset of physical activity that can be particularly beneficial for short-and-long-term physical and mental health, and social outcomes in adults. This study presents the results of an updated systematic review of the mental health and social outcomes of community and elite-level sport participation for adults. The findings have informed the development of the ‘Mental Health through Sport’ conceptual model for adults.

Nine electronic databases were searched, with studies published between 2012 and March 2020 screened for inclusion. Eligible qualitative and quantitative studies reported on the relationship between sport participation and mental health and/or social outcomes in adult populations. Risk of bias (ROB) was determined using the Quality Assessment Tool (quantitative studies) or Critical Appraisal Skills Programme (qualitative studies).

The search strategy located 8528 articles, of which, 29 involving adults 18–84 years were included for analysis. Data was extracted for demographics, methodology, and study outcomes, and results presented according to study design. The evidence indicates that participation in sport (community and elite) is related to better mental health, including improved psychological well-being (for example, higher self-esteem and life satisfaction) and lower psychological ill-being (for example, reduced levels of depression, anxiety, and stress), and improved social outcomes (for example, improved self-control, pro-social behavior, interpersonal communication, and fostering a sense of belonging). Overall, adults participating in team sport had more favorable health outcomes than those participating in individual sport, and those participating in sports more often generally report the greatest benefits; however, some evidence suggests that adults in elite sport may experience higher levels of psychological distress. Low ROB was observed for qualitative studies, but quantitative studies demonstrated inconsistencies in methodological quality.

Conclusions

The findings of this review confirm that participation in sport of any form (team or individual) is beneficial for improving mental health and social outcomes amongst adults. Team sports, however, may provide more potent and additional benefits for mental and social outcomes across adulthood. This review also provides preliminary evidence for the Mental Health through Sport model, though further experimental and longitudinal evidence is needed to establish the mechanisms responsible for sports effect on mental health and moderators of intervention effects. Additional qualitative work is also required to gain a better understanding of the relationship between specific elements of the sporting environment and mental health and social outcomes in adult participants.

Peer Review reports

Introduction

The organizational structure of sport and the performance demands characteristic of sport training and competition provide a unique opportunity for participants to engage in health-enhancing physical activity of varied intensity, duration, and mode; and the opportunity to do so with other people as part of a team and/or club. Participation in individual and team sports have shown to be beneficial to physical, social, psychological, and cognitive health outcomes [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. Often, the social and mental health benefits facilitated through participation in sport exceed those achieved through participation in other leisure-time or recreational activities [ 8 , 9 , 10 ]. Notably, these benefits are observed across different sports and sub-populations (including youth, adults, older adults, males, and females) [ 11 ]. However, the evidence regarding sports participation at the elite level is limited, with available research indicating that elite athletes may be more susceptible to mental health problems, potentially due to the intense mental and physical demands placed on elite athletes [ 12 ].

Participation in sport varies across the lifespan, with children representing the largest cohort to engage in organized community sport [ 13 ]. Across adolescence and into young adulthood, dropout from organized sport is common, and especially for females [ 14 , 15 , 16 ], and adults are shifting from organized sports towards leisure and fitness activities, where individual activities (including swimming, walking, and cycling) are the most popular [ 13 , 17 , 18 , 19 ]. Despite the general decline in sport participation with age [ 13 ], the most recent (pre-COVID) global data highlights that a range of organized team sports (such as, basketball, netball volleyball, and tennis) continue to rank highly amongst adult sport participants, with soccer remaining a popular choice across all regions of the world [ 13 ]. It is encouraging many adults continue to participate in sport and physical activities throughout their lives; however, high rates of dropout in youth sport and non-participation amongst adults means that many individuals may be missing the opportunity to reap the potential health benefits associated with participation in sport.

According to the World Health Organization, mental health refers to a state of well-being and effective functioning in which an individual realizes his or her own abilities, is resilient to the stresses of life, and is able to make a positive contribution to his or her community [ 20 ]. Mental health covers three main components, including psychological, emotional and social health [ 21 ]. Further, psychological health has two distinct indicators, psychological well-being (e.g., self-esteem and quality of life) and psychological ill-being (e.g., pre-clinical psychological states such as psychological difficulties and high levels of stress) [ 22 ]. Emotional well-being describes how an individual feels about themselves (including life satisfaction, interest in life, loneliness, and happiness); and social well–being includes an individual’s contribution to, and integration in society [ 23 ].

Mental illnesses are common among adults and incidence rates have remained consistently high over the past 25 years (~ 10% of people affected globally) [ 24 ]. Recent statistics released by the World Health Organization indicate that depression and anxiety are the most common mental disorders, affecting an estimated 264 million people, ranking as one of the main causes of disability worldwide [ 25 , 26 ]. Specific elements of social health, including high levels of isolation and loneliness among adults, are now also considered a serious public health concern due to the strong connections with ill-health [ 27 ]. Participation in sport has shown to positively impact mental and social health status, with a previous systematic review by Eime et al. (2013) indicated that sports participation was associated with lower levels of perceived stress, and improved vitality, social functioning, mental health, and life satisfaction [ 1 ]. Based on their findings, the authors developed a conceptual model (health through sport) depicting the relationship between determinants of adult sports participation and physical, psychological, and social health benefits of participation. In support of Eime’s review findings, Malm and colleagues (2019) recently described how sport aids in preventing or alleviating mental illness, including depressive symptoms and anxiety or stress-related disease [ 7 ]. Andersen (2019) also highlighted that team sports participation is associated with decreased rates of depression and anxiety [ 11 ]. In general, these reviews report stronger effects for sports participation compared to other types of physical activity, and a dose–response relationship between sports participation and mental health outcomes (i.e., higher volume and/or intensity of participation being associated with greater health benefits) when adults participate in sports they enjoy and choose [ 1 , 7 ]. Sport is typically more social than other forms of physical activity, including enhanced social connectedness, social support, peer bonding, and club support, which may provide some explanation as to why sport appears to be especially beneficial to mental and social health [ 28 ].

Thoits (2011) proposed several potential mechanisms through which social relationships and social support improve physical and psychological well-being [ 29 ]; however, these mechanisms have yet to be explored in the context of sports participation at any level in adults. The identification of the mechanisms responsible for such effects may direct future research in this area and help inform future policy and practice in the delivery of sport to enhance mental health and social outcomes amongst adult participants. Therefore, the primary objective of this review was to examine and synthesize all research findings regarding the relationship between sports participation, mental health and social outcomes at the community and elite level in adults. Based on the review findings, the secondary objective was to develop the ‘Mental Health through Sport’ conceptual model.

This review has been registered in the PROSPERO systematic review database and assigned the identifier: CRD42020185412. The conduct and reporting of this systematic review also follows the Preferred Reporting for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 30 ] (PRISMA flow diagram and PRISMA Checklist available in supplementary files ). This review is an update of a previous review of the same topic [ 31 ], published in 2012.

Identification of studies

Nine electronic databases (CINAHL, Cochrane Library, Google Scholar, Informit, Medline, PsychINFO, Psychology and Behavioural Sciences Collection, Scopus, and SPORTDiscus) were systematically searched for relevant records published from 2012 to March 10, 2020. The following key terms were developed by all members of the research team (and guided by previous reviews) and entered into these databases by author LW: sport* AND health AND value OR benefit* OR effect* OR outcome* OR impact* AND psych* OR depress* OR stress OR anxiety OR happiness OR mood OR ‘quality of life’ OR ‘social health’ OR ‘social relation*’ OR well* OR ‘social connect*’ OR ‘social functioning’ OR ‘life satisfac*’ OR ‘mental health’ OR social OR sociolog* OR affect* OR enjoy* OR fun. Where possible, Medical Subject Headings (MeSH) were also used.

Criteria for inclusion/exclusion

The titles of studies identified using this method were screened by LW. Abstract and full text of the articles were reviewed independently by LW and NE. To be included in the current review, each study needed to meet each of the following criteria: (1) published in English from 2012 to 2020; (2) full-text available online; (3) original research or report published in a peer-reviewed journal; (4) provides data on the psychological or social effects of participation in sport (with sport defined as a subset of exercise that can be undertaken individually or as a part of a team, where participants adhere to a common set of rules or expectations, and a defined goal exists); (5) the population of interest were adults (18 years and older) and were apparently healthy. All papers retrieved in the initial search were assessed for eligibility by title and abstract. In cases where a study could not be included or excluded via their title and abstract, the full text of the article was reviewed independently by two of the authors.

Data extraction

For the included studies, the following data was extracted independently by LW and checked by NE using a customized Google Docs spreadsheet: author name, year of publication, country, study design, aim, type of sport (e.g., tennis, hockey, team, individual), study conditions/comparisons, sample size, where participants were recruited from, mean age of participants, measure of sports participation, measure of physical activity, psychological and/or social outcome/s, measure of psychological and/or social outcome/s, statistical method of analysis, changes in physical activity or sports participation, and the psychological and/or social results.

Risk of bias (ROB) assessment

A risk of bias was performed by LW and AP independently using the ‘Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies’ OR the ‘Quality Assessment of Controlled Intervention Studies’ for the included quantitative studies, and the ‘Critical Appraisal Skills Programme (CASP) Checklist for the included qualitative studies [ 32 , 33 ]. Any discrepancies in the ROB assessments were discussed between the two reviewers, and a consensus reached.

The search yielded 8528 studies, with a total of 29 studies included in the systematic review (Fig.  1 ). Tables  1 and 2 provide a summary of the included studies. The research included adults from 18 to 84 years old, with most of the evidence coming from studies targeting young adults (18–25 years). Study samples ranged from 14 to 131, 962, with the most reported psychological outcomes being self-rated mental health ( n  = 5) and depression ( n  = 5). Most studies did not investigate or report the link between a particular sport and a specific mental health or social outcome; instead, the authors’ focused on comparing the impact of sport to physical activity, and/or individual sports compared to team sports. The results of this review are summarized in the following section, with findings presented by study design (cross-sectional, experimental, and longitudinal).

Flow of studies through the review process

Effects of sports participation on psychological well-being, ill-being, and social outcomes

Cross-sectional evidence.

This review included 14 studies reporting on the cross-sectional relationship between sports participation and psychological and/or social outcomes. Sample sizes range from n  = 414 to n  = 131,962 with a total of n  = 239,394 adults included across the cross-sectional studies.

The cross-sectional evidence generally supports that participation in sport, and especially team sports, is associated with greater mental health and psychological wellbeing in adults compared to non-participants [ 36 , 59 ]; and that higher frequency of sports participation and/or sport played at a higher level of competition, are also linked to lower levels of mental distress in adults . This was not the case for one specific study involving ice hockey players aged 35 and over, with Kitchen and Chowhan (2016) Kitchen and Chowhan (2016) reporting no relationship between participation in ice hockey and either mental health, or perceived life stress [ 54 ]. There is also some evidence to support that previous participation in sports (e.g., during childhood or young adulthood) is linked to better mental health outcomes later in life, including improved mental well-being and lower mental distress [ 59 ], even after controlling for age and current physical activity.

Compared to published community data for adults, elite or high-performance adult athletes demonstrated higher levels of body satisfaction, self-esteem, and overall life satisfaction [ 39 ]; and reported reduced tendency to respond to distress with anger and depression. However, rates of psychological distress were higher in the elite sport cohort (compared to community norms), with nearly 1 in 5 athletes reporting ‘high to very high’ distress, and 1 in 3 reporting poor mental health symptoms at a level warranting treatment by a health professional in one study ( n  = 749) [ 39 ].

Four studies focused on the associations between physical activity and sports participation and mental health outcomes in older adults. Physical activity was associated with greater quality of life [ 56 ], with the relationship strongest for those participating in sport in middle age, and for those who cycled in later life (> 65) [ 56 ]. Group physical activities (e.g., walking groups) and sports (e.g., golf) were also significantly related to excellent self-rated health, low depressive symptoms, high health-related quality of life (HRQoL) and a high frequency of laughter in males and females [ 60 , 61 ]. No participation or irregular participation in sport was associated with symptoms of mild to severe depression in older adults [ 62 ].

Several cross-sectional studies examined whether the effects of physical activity varied by type (e.g., total physical activity vs. sports participation). In an analysis of 1446 young adults (mean age = 18), total physical activity, moderate-to-vigorous physical activity, and team sport were independently associated with mental health [ 46 ]. Relative to individual physical activity, after adjusting for covariates and moderate-to-vigorous physical activity (MVPA), only team sport was significantly associated with improved mental health. Similarly, in a cross-sectional analysis of Australian women, Eime, Harvey, Payne (2014) reported that women who engaged in club and team-based sports (tennis or netball) reported better mental health and life satisfaction than those who engaged in individual types of physical activity [ 47 ]. Interestingly, there was no relationship between the amount of physical activity and either of these outcomes, suggesting that other qualities of sports participation contribute to its relationship to mental health and life satisfaction. There was also some evidence to support a relationship between exercise type (ball sports, aerobic activity, weightlifting, and dancing), and mental health amongst young adults (mean age 22 years) [ 48 ], with ball sports and dancing related to fewer symptoms of depression in students with high stress; and weightlifting related to fewer depressive symptoms in weightlifters exhibiting low stress.

Longitudinal evidence

Eight studies examined the longitudinal relationship between sports participation and either mental health and/or social outcomes. Sample sizes range from n  = 113 to n  = 1679 with a total of n  = 7022 adults included across the longitudinal studies.

Five of the included longitudinal studies focused on the relationship between sports participation in childhood or adolescence and mental health in young adulthood. There is evidence that participation in sport in high-school is protective of future symptoms of anxiety (including panic disorder, generalised anxiety disorder, social phobia, and agoraphobia) [ 42 ]. Specifically, after controlling for covariates (including current physical activity), the number of years of sports participation in high school was shown to be protective of symptoms of panic and agoraphobia in young adulthood, but not protective of symptoms of social phobia or generalized anxiety disorder [ 42 ]. A comparison of individual or team sports participation also revealed that participation in either context was protective of panic disorder symptoms, while only team sport was protective of agoraphobia symptoms, and only individual sport was protective of social phobia symptoms. Furthermore, current and past sports team participation was shown to negatively relate to adult depressive symptoms [ 43 ]; drop out of sport was linked to higher depressive symptoms in adulthood compared to those with maintained participation [ 9 , 22 , 63 ]; and consistent participation in team sports (but not individual sport) in adolescence was linked to higher self-rated mental health, lower perceived stress and depressive symptoms, and lower depression scores in early adulthood [ 53 , 58 ].

Two longitudinal studies [ 35 , 55 ], also investigated the association between team and individual playing context and mental health. Dore and colleagues [ 35 ] reported that compared to individual activities, being active in informal groups (e.g., yoga, running groups) or team sports was associated with better mental health, fewer depressive symptoms and higher social connectedness – and that involvement in team sports was related to better mental health regardless of physical activity volume. Kim and James [ 55 ] discovered that sports participation led to both short and long-term improvements in positive affect and life satisfaction.

A study on social outcomes related to mixed martial-arts (MMA) and Brazilian jiu-jitsu (BJJ) showed that both sports improved practitioners’ self-control and pro-social behavior, with greater improvements seen in the BJJ group [ 62 ]. Notably, while BJJ reduced participants’ reported aggression, there was a slight increase in MMA practitioners, though it is worth mentioning that individuals who sought out MMA had higher levels of baseline aggression.

Experimental evidence

Six of the included studies were experimental or quasi-experimental. Sample sizes ranged from n  = 28 to n  = 55 with a total of n  = 239 adults included across six longitudinal studies. Three studies involved a form of martial arts (such as judo and karate) [ 45 , 51 , 52 ], one involved a variety of team sports (such as netball, soccer, and cricket) [ 34 ], and the remaining two focused on badminton [ 57 ] and handball [ 49 ].

Brinkley and colleagues [ 34 ] reported significant effects on interpersonal communication (but not vitality, social cohesion, quality of life, stress, or interpersonal relationships) for participants ( n  = 40) engaging in a 12-week workplace team sports intervention. Also using a 12-week intervention, Hornstrup et al. [ 49 ] reported a significant improvement in mental energy (but not well-being or anxiety) in young women (mean age = 24; n  = 28) playing in a handball program. Patterns et al. [ 57 ] showed that in comparison to no exercise, participation in an 8-week badminton or running program had no significant improvement on self-esteem, despite improvements in perceived and actual fitness levels.

Three studies examined the effect of martial arts on the mental health of older adults (mean ages 79 [ 52 ], 64 [ 51 ], and 70 [ 45 ] years). Participation in Karate-Do had positive effects on overall mental health, emotional wellbeing, depression and anxiety when compared to other activities (physical, cognitive, mindfulness) and a control group [ 51 , 52 ]. Ciaccioni et al. [ 45 ] found that a Judo program did not affect either the participants’ mental health or their body satisfaction, citing a small sample size, and the limited length of the intervention as possible contributors to the findings.

Qualitative evidence

Three studies interviewed current or former sports players regarding their experiences with sport. Chinkov and Holt [ 41 ] reported that jiu-jitsu practitioners (mean age 35 years) were more self-confident in their lives outside of the gym, including improved self-confidence in their interactions with others because of their training. McGraw and colleagues [ 37 ] interviewed former and current National Football League (NFL) players and their families about its impact on the emotional and mental health of the players. Most of the players reported that their NFL career provided them with social and emotional benefits, as well as improvements to their self-esteem even after retiring. Though, despite these benefits, almost all the players experienced at least one mental health challenge during their career, including depression, anxiety, or difficulty controlling their temper. Some of the players and their families reported that they felt socially isolated from people outside of the national football league.

Through a series of semi-structured interviews and focus groups, Thorpe, Anders [ 40 ] investigated the impact of an Aboriginal male community sporting team on the health of its players. The players reported they felt a sense of belonging when playing in the team, further noting that the social and community aspects were as important as the physical health benefits. Participating in the club strengthened the cultural identity of the players, enhancing their well-being. The players further noted that participation provided them with enjoyment, stress relief, a sense of purpose, peer support, and improved self-esteem. Though they also noted challenges, including the presence of racism, community conflict, and peer-pressure.

Quality of studies

Full details of our risk of bias (ROB) results are provided in Supplementary Material A . Of the three qualitative studies assessed using the Critical Appraisal Skills Program (CASP), all three were deemed to have utilised and reported appropriate methodological standards on at least 8 of the 10 criteria. Twenty studies were assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies, with all studies clearly reporting the research question/s or objective/s and study population. However, only four studies provided a justification for sample size, and less than half of the studies met quality criteria for items 6, 7, 9, or 10 (and items 12 and 13 were largely not applicable). Of concern, only four of the observational or cohort studies were deemed to have used clearly defined, valid, and reliable exposure measures (independent variables) and implemented them consistently across all study participants. Six studies were assessed using the Quality Assessment of Controlled Intervention Studies, with three studies described as a randomized trial (but none of the three reported a suitable method of randomization, concealment of treatment allocation, or blinding to treatment group assignment). Three studies showed evidence that study groups were similar at baseline for important characteristics and an overall drop-out rate from the study < 20%. Four studies reported high adherence to intervention protocols (with two not reporting) and five demonstrated that.study outcomes were assessed using valid and reliable measures and implemented consistently across all study participants. Importantly, researchers did not report or have access to validated instruments for assessing sport participation or physical activity amongst adults, though most studies provided psychometrics for their mental health outcome measure/s. Only one study reported that the sample size was sufficiently powered to detect a difference in the main outcome between groups (with ≥ 80% power) and that all participants were included in the analysis of results (intention-to-treat analysis). In general, the methodological quality of the six randomised studies was deemed low.

Initially, our discussion will focus on the review findings regarding sports participation and well-being, ill-being, and psychological health. However, the heterogeneity and methodological quality of the included research (especially controlled trials) should be considered during the interpretation of our results. Considering our findings, the Mental Health through Sport conceptual model for adults will then be presented and discussed and study limitations outlined.

Sports participation and psychological well-being

In summary, the evidence presented here indicates that for adults, sports participation is associated with better overall mental health [ 36 , 46 , 47 , 59 ], mood [ 56 ], higher life satisfaction [ 39 , 47 ], self-esteem [ 39 ], body satisfaction [ 39 ], HRQoL [ 60 ], self-rated health [ 61 ], and frequency of laughter [ 61 ]. Sports participation has also shown to be predictive of better psychological wellbeing over time [ 35 , 53 ], higher positive affect [ 55 ], and greater life satisfaction [ 55 ]. Furthermore, higher frequency of sports participation and/or sport played at a higher level of competition, have been linked to lower levels of mental distress, higher levels of body satisfaction, self-esteem, and overall life satisfaction in adults [ 39 ].

Despite considerable heterogeneity of sports type, cross-sectional and experimental research indicate that team-based sports participation, compared to individual sports and informal group physical activity, has a more positive effect on mental energy [ 49 ], physical self-perception [ 57 ], and overall psychological health and well-being in adults, regardless of physical activity volume [ 35 , 46 , 47 ]. And, karate-do benefits the subjective well-being of elderly practitioners [ 51 , 52 ]. Qualitative research in this area has queried participants’ experiences of jiu-jitsu, Australian football, and former and current American footballers. Participants in these sports reported that their participation was beneficial for psychological well-being [ 37 , 40 , 41 ], improved self-esteem [ 37 , 40 , 41 ], and enjoyment [ 37 ].

Sports participation and psychological ill-being

Of the included studies, n  = 19 examined the relationship between participating in sport and psychological ill-being. In summary, there is consistent evidence that sports participation is related to lower depression scores [ 43 , 48 , 61 , 62 ]. There were mixed findings regarding psychological stress, where participation in childhood (retrospectively assessed) was related to lower stress in young adulthood [ 41 ], but no relationship was identified between recreational hockey in adulthood and stress [ 54 ]. Concerning the potential impact of competing at an elite level, there is evidence of higher stress in elite athletes compared to community norms [ 39 ]. Further, there is qualitative evidence that many current or former national football league players experienced at least one mental health challenge, including depression, anxiety, difficulty controlling their temper, during their career [ 37 ].

Evidence from longitudinal research provided consistent evidence that participating in sport in adolescence is protective of symptoms of depression in young adulthood [ 43 , 53 , 58 , 63 ], and further evidence that participating in young adulthood is related to lower depressive symptoms over time (6 months) [ 35 ]. Participation in adolescence was also protective of manifestations of anxiety (panic disorder and agoraphobia) and stress in young adulthood [ 42 ], though participation in young adulthood was not related to a more general measure of anxiety [ 35 ] nor to changes in negative affect [ 55 ]). The findings from experimental research were mixed. Two studies examined the effect of karate-do on markers of psychological ill-being, demonstrating its capacity to reduce anxiety [ 52 ], with some evidence of its effectiveness on depression [ 51 ]. The other studies examined small-sided team-based games but showed no effect on stress or anxiety [ 34 , 49 ]. Most studies did not differentiate between team and individual sports, though one study found that adolescents who participated in team sports (not individual sports) in secondary school has lower depression scores in young adulthood [ 58 ].

Sports participation and social outcomes

Seven of the included studies examined the relationship between sports participation and social outcomes. However, very few studies examined social outcomes or tested a social outcome as a potential mediator of the relationship between sport and mental health. It should also be noted that this body of evidence comes from a wide range of sport types, including martial arts, professional football, and workplace team-sport, as well as different methodologies. Taken as a whole, the evidence shows that participating in sport is beneficial for several social outcomes, including self-control [ 50 ], pro-social behavior [ 50 ], interpersonal communication [ 34 ], and fostering a sense of belonging [ 40 ]. Further, there is evidence that group activity, for example team sport or informal group activity, is related to higher social connectedness over time, though analyses showed that social connectedness was not a mediator for mental health [ 35 ].

There were conflicting findings regarding social effects at the elite level, with current and former NFL players reporting that they felt socially isolated during their career [ 37 ], whilst another study reported no relationship between participation at the elite level and social dysfunction [ 39 ]. Conversely, interviews with a group of indigenous men revealed that they felt as though participating in an all-indigenous Australian football team provided them with a sense of purpose, and they felt as though the social aspect of the game was as important as the physical benefits it provides [ 40 ].

Mental health through sport conceptual model for adults

The ‘Health through Sport’ model provides a depiction of the determinants and benefits of sports participation [ 31 ]. The model recognises that the physical, mental, and social benefits of sports participation vary by the context of sport (e.g., individual vs. team, organized vs. informal). To identify the elements of sport which contribute to its effect on mental health outcomes, we describe the ‘Mental Health through Sport’ model (Fig.  2 ). The model proposes that the social and physical elements of sport each provide independent, and likely synergistic contributions to its overall influence on mental health.

The Mental Health through Sport conceptual model

The model describes two key pathways through which sport may influence mental health: physical activity, and social relationships and support. Several likely moderators of this effect are also provided, including sport type, intensity, frequency, context (team vs. individual), environment (e.g., indoor vs. outdoor), as well as the level of competition (e.g., elite vs. amateur).

The means by which the physical activity component of sport may influence mental health stems from the work of Lubans et al., who propose three key groups of mechanisms: neurobiological, psychosocial, and behavioral [ 64 ]. Processes whereby physical activity may enhance psychological outcomes via changes in the structural and functional composition of the brain are referred to as neurobiological mechanisms [ 65 , 66 ]. Processes whereby physical activity provides opportunities for the development of self-efficacy, opportunity for mastery, changes in self-perceptions, the development of independence, and for interaction with the environment are considered psychosocial mechanisms. Lastly, processes by which physical activity may influence behaviors which ultimately affect psychological health, including changes in sleep duration, self-regulation, and coping skills, are described as behavioral mechanisms.

Playing sport offers the opportunity to form relationships and to develop a social support network, both of which are likely to influence mental health. Thoits [ 29 ] describes 7 key mechanisms by which social relationships and support may influence mental health: social influence/social comparison; social control; role-based purpose and meaning (mattering); self-esteem; sense of control; belonging and companionship; and perceived support availability [ 29 ]. These mechanisms and their presence within a sporting context are elaborated below.

Subjective to the attitudes and behaviors of individuals in a group, social influence and comparison may facilitate protective or harmful effects on mental health. Participants in individual or team sport will be influenced and perhaps steered by the behaviors, expectations, and norms of other players and teams. When individual’s compare their capabilities, attitudes, and values to those of other participants, their own behaviors and subsequent health outcomes may be affected. When others attempt to encourage or discourage an individual to adopt or reject certain health practices, social control is displayed [ 29 ]. This may evolve as strategies between players (or between players and coach) are discussion and implemented. Likewise, teammates may try to motivate each another during a match to work harder, or to engage in specific events or routines off-field (fitness programs, after game celebrations, attending club events) which may impact current and future physical and mental health.

Sport may also provide behavioral guidance, purpose, and meaning to its participants. Role identities (positions within a social structure that come with reciprocal obligations), often formed as a consequence of social ties formed through sport. Particularly in team sports, participants come to understand they form an integral part of the larger whole, and consequently, they hold certain responsibility in ensuring the team’s success. They have a commitment to the team to, train and play, communicate with the team and a potential responsibility to maintain a high level of health, perform to their capacity, and support other players. As a source of behavioral guidance and of purpose and meaning in life, these identities are likely to influence mental health outcomes amongst sport participants.

An individual’s level of self-esteem may be affected by the social relationships and social support provided through sport; with improved perceptions of capability (or value within a team) in the sporting domain likely to have positive impact on global self-esteem and sense of worth [ 64 ]. The unique opportunities provided through participation in sport, also allow individuals to develop new skills, overcome challenges, and develop their sense of self-control or mastery . Working towards and finding creative solutions to challenges in sport facilitates a sense of mastery in participants. This sense of mastery may translate to other areas of life, with individual’s developing the confidence to cope with varied life challenges. For example, developing a sense of mastery regarding capacity to formulate new / creative solutions when taking on an opponent in sport may result in greater confidence to be creative at work. Social relationships and social support provided through sport may also provide participants with a source of belonging and companionship. The development of connections (on and off the field) to others who share common interests, can build a sense of belonging that may mediate improvements in mental health outcomes. Social support is often provided emotionally during expressions of trust and care; instrumentally via tangible assistance; through information such as advice and suggestions; or as appraisal such feedback. All forms of social support provided on and off the field contribute to a more generalised sense of perceived support that may mediate the effect of social interaction on mental health outcomes.

Participation in sport may influence mental health via some combination of the social mechanisms identified by Thoits, and the neurobiological, psychosocial, and behavioral mechanisms stemming from physical activity identified by Lubans [ 29 , 64 ]. The exact mechanisms through which sport may confer psychological benefit is likely to vary between sports, as each sport varies in its physical and social requirements. One must also consider the social effects of sports participation both on and off the field. For instance, membership of a sporting team and/or club may provide a sense of identity and belonging—an effect that persists beyond the immediacy of playing the sport and may have a persistent effect on their psychological health. Furthermore, the potential for team-based activity to provide additional benefit to psychological outcomes may not just be attributable to the differences in social interactions, there are also physiological differences in the requirements for sport both within (team vs. team) and between (team vs. individual) categories that may elicit additional improvements in psychological outcomes. For example, evidence supports that exercise intensity moderates the relationship between physical activity and several psychological outcomes—supporting that sports performed at higher intensity will be more beneficial for psychological health.

Limitations and recommendations

There are several limitations of this review worthy of consideration. Firstly, amongst the included studies there was considerable heterogeneity in study outcomes and study methodology, and self-selection bias (especially in non-experimental studies) is likely to influence study findings and reduce the likelihood that study participants and results are representative of the overall population. Secondly, the predominately observational evidence included in this and Eime’s prior review enabled us to identify the positive relationship between sports participation and social and psychological health (and examine directionality)—but more experimental and longitudinal research is required to determine causality and explore potential mechanisms responsible for the effect of sports participation on participant outcomes. Additional qualitative work would also help researchers gain a better understanding of the relationship between specific elements of the sporting environment and mental health and social outcomes in adult participants. Thirdly, there were no studies identified in the literature where sports participation involved animals (such as equestrian sports) or guns (such as shooting sports). Such studies may present novel and important variables in the assessment of mental health benefits for participants when compared to non-participants or participants in sports not involving animals/guns—further research is needed in this area. Our proposed conceptual model also identifies several pathways through which sport may lead to improvements in mental health—but excludes some potentially negative influences (such as poor coaching behaviors and injury). And our model is not designed to capture all possible mechanisms, creating the likelihood that other mechanisms exist but are not included in this review. Additionally, an interrelationship exits between physical activity, mental health, and social relationships, whereby changes in one area may facilitate changes in the other/s; but for the purpose of this study, we have focused on how the physical and social elements of sport may mediate improvements in psychological outcomes. Consequently, our conceptual model is not all-encompassing, but designed to inform and guide future research investigating the impact of sport participation on mental health.

The findings of this review endorse that participation in sport is beneficial for psychological well-being, indicators of psychological ill-being, and social outcomes in adults. Furthermore, participation in team sports is associated with better psychological and social outcomes compared to individual sports or other physical activities. Our findings support and add to previous review findings [ 1 ]; and have informed the development of our ‘Mental Health through Sport’ conceptual model for adults which presents the potential mechanisms by which participation in sport may affect mental health.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Eime RM, Young JA, Harvey JT, Charity MJ, Payne WR. A systematic review of the psychological and social benefits of participation in sport for adults: informing development of a conceptual model of health through sport. Int J Behav Nutr Phys Act. 2013;10:135.

Article   PubMed   PubMed Central   Google Scholar  

Ishihara T, Nakajima T, Yamatsu K, Okita K, Sagawa M, Morita N. Relationship of participation in specific sports to academic performance in adolescents: a 2-year longitudinal study. Scand J Med Sci Sports. 2020.

Cope E, Bailey R, Pearce G. Why do children take part in, and remain involved in sport?: implications for children’s sport coaches. Int J Coach Sci. 2013;7:55–74.

Google Scholar  

Harrison PA, Narayan G. Differences in behavior, psychological factors, and environmental factors associated with participation in school sports and other activities in adolescence. J Sch Health. 2003;73(3):113–20.

Article   PubMed   Google Scholar  

Allender S, Cowburn G, Foster C. Understanding particpation in sport and physical activity among children and adults: a review of qualitative studies. Health Educ Res. 2006;21(6):826–35.

Adachi P, Willoughby T. It’s not how much you play, but how much you enjoy the game: The longitudinal associations between adolescents’ self-esteem and the frequency versus enjoyment of involvement in sports. J Youth Adolesc. 2014;43(1):137–45.

Malm C, Jakobsson J, Isaksson A. Physical activity and sports-real health benefits: a review with insight into the public health of Sweden. Sports (Basel, Switzerland). 2019;7(5):127.

PubMed   Google Scholar  

Mills K, Dudley D, Collins NJ. Do the benefits of participation in sport and exercise outweigh the negatives? An academic review. Best Pract Res Clin Rheumatol. 2019;33(1):172–87.

Howie EK, Guagliano JM, Milton K, Vella SA, Gomersall SR,Kolbe-Alexander TL, et al. Ten research priorities related to youth sport, physical activity, and health. 2020;17(9):920.

Vella SA, Swann C, Allen MS, Schweickle MJ, Magee CA. Bidirectional associations between sport involvement and mental health in adolescence. Med Sci Sports Exerc. 2017;49(4):687–94.

Andersen MH, Ottesen L, Thing LF. The social and psychological health outcomes of team sport participation in adults: An integrative review of research. Scand J Public Health. 2019;47(8):832–50.

Rice SM, Purcell R, De Silva S, Mawren D, McGorry PD, Parker AG. The mental health of elite athletes: a narrative systematic review. Sports medicine (Auckland, NZ). 2016;46(9):1333–53.

Article   Google Scholar  

Hulteen RM, Smith JJ, Morgan PJ, Barnett LM, Hallal PC, Colyvas K, et al. Global participation in sport and leisure-time physical activities: a systematic review and meta-analysis. Prev Med. 2017;95:14–25.

Eime RM, Harvey J, Charity M, Westerbeek H. Longitudinal Trends in Sport Participation and Retention of Women and Girls. Front Sports Act Living. 2020;2:39.

Brooke HL, Corder K, Griffin SJ, van Sluijs EMF. Physical activity maintenance in the transition to adolescence: a longitudinal study of the roles of sport and lifestyle activities in british youth. PLoS ONE. 2014;9(2): e89028.

Coll CVN, Knuth AG, Bastos JP, Hallal PC, Bertoldi AD. Time trends of physical activity among Brazilian adolescents over a 7-year period. J Adolesc Health. 2014;54:209–13.

Klostermann C, Nagel S. Changes in German sport participation: Historical trends in individual sports. Int Rev Sociol Sport. 2012;49:609–34.

Eime RM, Harvey J, Charity M. Sport participation settings: where and “how” do Australians play sport? BMC Public Health. 2020;20(1):1344.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Lim SY, Warner S, Dixon M, Berg B, Kim C, Newhouse-Bailey M. Sport Participation Across National Contexts: A Multilevel Investigation of Individual and Systemic Influences on Adult Sport Participation. Eur Sport Manag Q. 2011;11(3):197–224.

World Health Organisation. Mental Health Action Plan 2013–2020. Geneva: World Health Orgnaisation; 2013.

Keyes C. Bridging Occupational, Organizational and Public Health. Netherlands: Springer Dordrecht; 2014.

Ryff C, Love G, Urry H, Muller D, Rosenkranz M, Friedman E, et al. Psychological well-being and ill-being: Do they have distinct or mirrored biological correlates? Psychother Psychosom. 2006;75:85–95.

Australian Government. Social and emotional wellbeing: Development of a children’s headline indicator information paper. Canberra: Australian Institute of Health and Welfare; 2013.

Global Burden of Disease Injury IP. Collaborators, Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392(10159):1789–858.

World Health Organisation. Mental disorders: Fact sheet 2019 [Available from: https://www.who.int/news-room/fact-sheets/detail/mental-disorders .

Mental Health [Internet]. 2018 [cited 12 March 2021]. Available from: https://ourworldindata.org/mental-health ' [Online Resource].

Newman MG, Zainal NH. The value of maintaining social connections for mental health in older people. The Lancet Public Health. 2020;5(1):e12–3.

Eime RM, Harvey JT, Brown WJ, Payne WR. Does sports club participation contribute to health-related quality of life? Med Sci Sports Exerc. 2010;42(5):1022–8.

Thoits PA. Mechanisms linking social ties and support to physical and mental health. J Health Soc Behav. 2011;52(2):145–61.

Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. PLoS Med. 2021;18(3): e1003583.

Eime RM, Young JA, Harvey JT, Charity MJ, Payne WR. A systematic review of the psychological and social benefits of participation in sport for adults: informing development of a conceptual model of health through sport. Int J Behav Nutr Phys Act. 2013;10(1):135.

Critical Appraisal Skills Programme. CASP Qualitative Studies Checklist2019 1/12/2021]. Available from: https://casp-uk.b-cdn.net/wp-content/uploads/2018/01/CASP-Qualitative-Checklist-2018.pdf .

National Institutes from Health. Quality assessment tool for observational cohort and cross-sectional studies 2014 [Available from: https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools .

Brinkley A, McDermott H, Grenfell-Essam R. It’s time to start changing the game: a 12-week workplace team sport intervention study. Sports Med Open. 2017;3(1):30–41.

Doré I, O’Loughlin JL, Schnitzer ME, Datta GD, Fournier L. The longitudinal association between the context of physical activity and mental health in early adulthood. Ment Health Phys Act. 2018;14:121–30.

Marlier M, Van Dyck D, Cardon G, De Bourdeaudhuij I, Babiak K, Willem A. Interrelation of sport participation, physical activity, social capital and mental health in disadvantaged communities: A sem-analysis. PLoS ONE [Internet]. 2015; 10(10):[e0140196 p.]. Available from: http://ezproxy.newcastle.edu.au/login?url=http://ezproxy.newcastle.edu.au/login?url=http://ovidsp.ovid.com/ovidweb.cgi?T=JS&CSC=Y&NEWS=N&PAGE=fulltext&D=med12&AN=26451731 .

McGraw SA, Deubert CR, Lynch HF, Nozzolillo A, Taylor L, Cohen I. Life on an emotional roller coaster: NFL players and their family members’ perspectives on player mental health. J Clin Sport Psychol. 2018;12(3):404–31.

Mickelsson T. Modern unexplored martial arts – what can mixed martial arts and Brazilian Jiu-Jitsu do for youth development?. Eur J Sport Sci. 2020;20(3):386–93. https://doi.org/10.1080/17461391.2019.1629180 .

Purcell R, Rice S, Butterworth M, Clements M. Rates and Correlates of Mental Health Symptoms in Currently Competing Elite Athletes from the Australian National High-Performance Sports System. Sports Med. 2020.

Thorpe A, Anders W, Rowley K. The community network: an Aboriginal community football club bringing people together. Aust J Prim Health. 2014;20(4):356–64.

Appelqvist-Schmidlechner K, Vaara J, Hakkinen A, Vasankari T, Makinen J, Mantysaari M, et al. Relationships between youth sports participation and mental health in young adulthood among Finnish males. Am J Health Promot. 2018;32(7):1502–9.

Ashdown-Franks G, Sabiston CM, Solomon-Krakus S, O’Loughlin JL. Sport participation in high school and anxiety symptoms in young adulthood. Ment Health Phys Act. 2017;12:19–24.

Brunet J, Sabiston CM, Chaiton M, Barnett TA, O’Loughlin E, Low NC, et al. The association between past and current physical activity and depressive symptoms in young adults: a 10-year prospective study. Ann Epidemiol. 2013;23(1):25–30.

Chinkov AE, Holt NL. Implicit transfer of life skills through participation in Brazilian Jiu-jitsu. J Appl Sport Psychol. 2016;28(2):139–53. https://doi.org/10.1080/10413200.2015.1086447 .

Ciaccioni S, Capranica L, Forte R, Chaabene H, Pesce C, Condello G. Effects of a judo training on functional fitness, anthropometric, and psychological variables in old novice practitioners. J Aging Phys Act. 2019;27(6):831–42.

Doré I, O’Loughlin JL, Beauchamp G, Martineau M, Fournier L. Volume and social context of physical activity in association with mental health, anxiety and depression among youth. Prev Med. 2016;91:344–50.

Eime R, Harvey J, Payne W. Dose-response of women’s health-related quality of life (HRQoL) and life satisfaction to physical activity. J Phys Act Health. 2014;11(2):330–8.

Gerber M, Brand S, Elliot C, Holsboer-Trachsler E, Pühse U. Aerobic exercise, ball sports, dancing, and weight Lifting as moderators of the relationship between Stress and depressive symptoms: an exploratory cross-sectional study with Swiss university students. Percept Mot Skills. 2014;119(3):679–97.

Hornstrup T, Wikman JM, Fristrup B, Póvoas S, Helge EW, Nielsen SH, et al. Fitness and health benefits of team handball training for young untrained women—a cross-disciplinary RCT on physiological adaptations and motivational aspects. J Sport Health Sci. 2018;7(2):139–48.

Mickelsson T. Modern unexplored martial arts–what can mixed martial arts and Brazilian Jiu-Jiutsu do for youth development? Eur J Sport Sci. 2019.

Jansen P, Dahmen-Zimmer K. Effects of cognitive, motor, and karate training on cognitive functioning and emotional well-being of elderly people. Front Psychol. 2012;3:40.

Jansen P, Dahmen-Zimmer K, Kudielka BM, Schulz A. Effects of karate training versus mindfulness training on emotional well-being and cognitive performance in later life. Res Aging. 2017;39(10):1118–44.

Jewett R, Sabiston CM, Brunet J, O’Loughlin EK, Scarapicchia T, O’Loughlin J. School sport participation during adolescence and mental health in early adulthood. J Adolesc Health. 2014;55(5):640–4.

Kitchen P, Chowhan J. Forecheck, backcheck, health check: the benefits of playing recreational ice hockey for adults in Canada. J Sports Sci. 2016;34(21):2121–9.

Kim J, James JD. Sport and happiness: Understanding the relations among sport consumption activities, long-and short-term subjective well-being, and psychological need fulfillment. J Sport Manage. 2019.

Koolhaas CH, Dhana K, Van Rooij FJA, Schoufour JD, Hofman A, Franco OH. Physical activity types and health-related quality of life among middle-aged and elderly adults: the Rotterdam study. J Nutr Health Aging. 2018;22(2):246–53.

Article   CAS   PubMed   Google Scholar  

Patterson S, Pattison J, Legg H, Gibson AM, Brown N. The impact of badminton on health markers in untrained females. J Sports Sci. 2017;35(11):1098–106.

Sabiston CM, Jewett R, Ashdown-Franks G, Belanger M, Brunet J, O’Loughlin E, et al. Number of years of team and individual sport participation during adolescence and depressive symptoms in early adulthood. J Sport Exerc Psychol. 2016;38(1):105–10.

Sorenson SC, Romano R, Scholefield RM, Martin BE, Gordon JE, Azen SP, et al. Holistic life-span health outcomes among elite intercollegiate student-athletes. J Athl Train. 2014;49(5):684–95.

Stenner B, Mosewich AD, Buckley JD, Buckley ES. Associations between markers of health and playing golf in an Australian population. BMJ Open Sport Exerc Med. 2019;5(1).

Tsuji T, Kanamori S, Saito M, Watanabe R, Miyaguni Y, Kondo K. Specific types of sports and exercise group participation and socio-psychological health in older people. J Sports Sci. 2020;38(4):422–9.

Yamakita M, Kanamori S, Kondo N, Kondo K. Correlates of regular participation in sports groups among Japanese older adults: JAGES cross–sectional study. PLoS ONE. 2015;10(10):e0141638.

Howie EK, McVeigh JA, Smith AJ, Straker LM. Organized sport trajectories from childhood to adolescence and health associations. Med Sci Sports Exerc. 2016;48(7):1331–9.

Chinkov AE, Holt NL. Implicit transfer of life skills through participation in Brazilian Jiu-Jitsu. J Appl Sport Psychol. 2016;28(2):139–53.

Lubans D, Richards J, Hillman C, Faulkner G, Beauchamp M, Nilsson M, et al. Physical activity for cognitive and mental health in youth: a systematic review of mechanisms. Pediatrics. 2016;138(3):e20161642.

Lin TW, Kuo YM. Exercise benefits brain function: the monoamine connection. Brain Sci. 2013;3(1):39–53.

Dishman RK, O’Connor PJ. Lessons in exercise neurobiology: the case of endorphins. Ment Health Phys Act. 2009;2(1):4–9.

Download references

Acknowledgements

We would like to acknowledge the work of the original systematic review conducted by Eime, R. M., Young, J. A., Harvey, J. T., Charity, M. J., and Payne, W. R. (2013).

No funding associated with this study.

Author information

Authors and affiliations.

Centre for Active Living and Learning, University of Newcastle, University Drive, Callaghan, NSW, 2308, Australia

Narelle Eather & Levi Wade

College of Human and Social Futures, School of Education, University of Newcastle, University Drive, Callaghan, NSW, 2308, Australia

Narelle Eather

College of Health, Medicine, and Wellbeing, School of Medicine and Public Health, University of Newcastle, University Drive, Callaghan, NSW, 2308, Australia

Institute for Health and Sport, Victoria University, Ballarat Road, Footscray, VIC, 3011, Australia

Aurélie Pankowiak & Rochelle Eime

School of Science, Psychology and Sport, Federation University Australia, University Drive, Mount Helen, VIC, 3350, Australia

Rochelle Eime

You can also search for this author in PubMed   Google Scholar

Contributions

All authors contributed to the conducting of this study and reporting the findings. The titles of studies identified were screened by LW, and abstracts and full text articles reviewed independently by LW and NE. For the included studies, data was extracted independently by LW and checked by NE, and the risk of bias assessment was performed by LW and AP independently. All authors have read and approved the final version of the manuscript and agree with the order of presentation of the authors.

Corresponding author

Correspondence to Narelle Eather .

Ethics declarations

Ethics approval and consent to participate.

Not applicable

Consent for publication

Competing interests.

The authors declare they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: supplementary table a..

Risk of bias.

Additional file 2: Supplementary Table B.

PRISMA Checklist.  

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Eather, N., Wade, L., Pankowiak, A. et al. The impact of sports participation on mental health and social outcomes in adults: a systematic review and the ‘Mental Health through Sport’ conceptual model. Syst Rev 12 , 102 (2023). https://doi.org/10.1186/s13643-023-02264-8

Download citation

Received : 30 August 2021

Accepted : 31 May 2023

Published : 21 June 2023

DOI : https://doi.org/10.1186/s13643-023-02264-8

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Experimental
• Observational
• Psychological health
• Mental health
• Social health

Systematic Reviews

ISSN: 2046-4053

• Submission enquiries: Access here and click Contact Us
• General enquiries: [email protected]

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• 31 March 2021

Sports science

• Richard Hodson

You can also search for this author in PubMed   Google Scholar

The competition to be crowned the fastest, strongest or most technically proficient sportsperson on the planet will once again reach its peak this summer when athletes descend on Tokyo for the Olympic Games. The global pandemic might rule out the throng of enthusiastic spectators that are typical of such an event, but millions will eagerly watch on television as the very best go toe-to-toe.

Access options

Access Nature and 54 other Nature Portfolio journals

Get Nature+, our best-value online-access subscription

24,99 € / 30 days

cancel any time

Subscribe to this journal

Receive 51 print issues and online access

185,98 € per year

only 3,65 € per issue

Rent or buy this article

Prices vary by article type

Prices may be subject to local taxes which are calculated during checkout

Nature 592 , S1 (2021)

doi: https://doi.org/10.1038/d41586-021-00814-5

This article is part of Nature Outlook: Sports science , an editorially independent supplement produced with the financial support of third parties. About this content .

Related Articles

• Cell biology
• Machine learning

This plankton balloons in size to soar upwards through the water

Research Highlight 23 OCT 24

Chromatin remodelling drives immune cell–fibroblast communication in heart failure

Article 23 OCT 24

Targeting immune–fibroblast cell communication in heart failure

Nuclear release of eIF1 restricts start-codon selection during mitosis

AlphaFold reveals how sperm and egg hook up in intimate detail

News 17 OCT 24

Selective utilization of glucose metabolism guides mammalian gastrulation

Article 16 OCT 24

AI watermarking must be watertight to be effective

Editorial 23 OCT 24

AI-designed DNA sequences regulate cell-type-specific gene expression

News & Views 23 OCT 24

Google unveils invisible ‘watermark’ for AI-generated text

News 23 OCT 24

Associate or Senior Editor, Nature Communications (Structural Biology, Biochemistry, or Biophysics)

Job Title: Associate or Senior Editor, Nature Communications (Structural Biology, Biochemistry, or Biophysics) Locations: New York, Philadelphia, S...

New York City, New York (US)

Springer Nature Ltd

Faculty (Open Rank) - Bioengineering and Immunoengineering

The Pritzker School of Molecular Engineering (PME) at the University of Chicago invites applications for multiple faculty positions (open rank) in ...

Chicago, Illinois

University of Chicago, Pritzker School of Molecular Engineering

Postdoctoral Position in Hematology-Oncology – Morizono Lab 2024-2025

The Morizono lab at UCLA is recruiting talented postdoctoral fellows with an interest in the development of gene therapy against HIV-1 infection.

Los Angeles, California

UCLA Department of Medicine - Division of Hematology-Oncology

Associate or Senior Editor (Environmental Social Sciences)

Title:  Associate or Senior Editor (Environmental Social Sciences) Organization: Nature Communications Location:  New York, Philadelphia, Jersey Ci...

Facility Administrator

APPLICATION CLOSING DATE: December 2nd, 2024 Human Technopole (HT) is an interdisciplinary life science research institute, created and supported b...

Human Technopole

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

• Frontiers in Psychology
• Movement Science
• Research Topics

Advances in Sport Science: Latest Findings and New Scientific Proposals

Total Downloads

Total Views and Downloads

About this Research Topic

In sports, measuring is essential. The science surrounding physical activity and sport has been experiencing unstoppable growth for more than 30 years. Increasing the performance of athletes via strategies and recommendations backed by scientific evidence has become a necessity. Many sports and ...

Keywords : Performance analysis, individual sport, collective sports, adapted sports, parasports, match analysis, high performance, tactics, technique, female sport, women's sport

Important Note : All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Topic Editors

Topic coordinators, recent articles, submission deadlines.

Submission closed.

Participating Journals

Total views.

• Demographics

No records found

total views article views downloads topic views

Top countries

Top referring sites, about frontiers research topics.

With their unique mixes of varied contributions from Original Research to Review Articles, Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author.

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

Sport psychology and performance meta-analyses: A systematic review of the literature

Roles Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Kinesiology and Sport Management, Texas Tech University, Lubbock, Texas, United States of America, Education Academy, Vytautas Magnus University, Kaunas, Lithuania

Roles Data curation, Methodology, Writing – original draft

Affiliation Department of Psychological Sciences, Texas Tech University, Lubbock, Texas, United States of America

Roles Data curation, Methodology

Roles Writing – original draft, Writing – review & editing

Affiliation Department of Kinesiology and Sport Management, Honors College, Texas Tech University, Lubbock, Texas, United States of America

Roles Data curation, Methodology, Writing – original draft, Writing – review & editing

Affiliation Faculty of Education, Health and Well-Being, University of Wolverhampton, Walsall, West Midlands, United Kingdom

Roles Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Affiliation Division of Research & Innovation, University of Southern Queensland, Toowoomba, Queensland, Australia

• Marc Lochbaum, 
• Elisabeth Stoner, 
• Tristen Hefner, 
• Sydney Cooper, 
• Andrew M. Lane, 
• Peter C. Terry

• Published: February 16, 2022
• https://doi.org/10.1371/journal.pone.0263408
• Peer Review
• Reader Comments

Sport psychology as an academic pursuit is nearly two centuries old. An enduring goal since inception has been to understand how psychological techniques can improve athletic performance. Although much evidence exists in the form of meta-analytic reviews related to sport psychology and performance, a systematic review of these meta-analyses is absent from the literature. We aimed to synthesize the extant literature to gain insights into the overall impact of sport psychology on athletic performance. Guided by the PRISMA statement for systematic reviews, we reviewed relevant articles identified via the EBSCOhost interface. Thirty meta-analyses published between 1983 and 2021 met the inclusion criteria, covering 16 distinct sport psychology constructs. Overall, sport psychology interventions/variables hypothesized to enhance performance (e.g., cohesion, confidence, mindfulness) were shown to have a moderate beneficial effect ( d = 0.51), whereas variables hypothesized to be detrimental to performance (e.g., cognitive anxiety, depression, ego climate) had a small negative effect ( d = -0.21). The quality rating of meta-analyses did not significantly moderate the magnitude of observed effects, nor did the research design (i.e., intervention vs. correlation) of the primary studies included in the meta-analyses. Our review strengthens the evidence base for sport psychology techniques and may be of great practical value to practitioners. We provide recommendations for future research in the area.

Citation: Lochbaum M, Stoner E, Hefner T, Cooper S, Lane AM, Terry PC (2022) Sport psychology and performance meta-analyses: A systematic review of the literature. PLoS ONE 17(2): e0263408. https://doi.org/10.1371/journal.pone.0263408

Editor: Claudio Imperatori, European University of Rome, ITALY

Received: September 28, 2021; Accepted: January 18, 2022; Published: February 16, 2022

Copyright: © 2022 Lochbaum et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Sport performance matters. Verifying its global importance requires no more than opening a newspaper to the sports section, browsing the internet, looking at social media outlets, or scanning abundant sources of sport information. Sport psychology is an important avenue through which to better understand and improve sport performance. To date, a systematic review of published sport psychology and performance meta-analyses is absent from the literature. Given the undeniable importance of sport, the history of sport psychology in academics since 1830, and the global rise of sport psychology journals and organizations, a comprehensive systematic review of the meta-analytic literature seems overdue. Thus, we aimed to consolidate the existing literature and provide recommendations for future research.

The development of sport psychology

The history of sport psychology dates back nearly 200 years. Terry [ 1 ] cites Carl Friedrich Koch’s (1830) publication titled [in translation] Calisthenics from the Viewpoint of Dietetics and Psychology [ 2 ] as perhaps the earliest publication in the field, and multiple commentators have noted that sport psychology experiments occurred in the world’s first psychology laboratory, established by Wilhelm Wundt at the University of Leipzig in 1879 [ 1 , 3 ]. Konrad Rieger’s research on hypnosis and muscular endurance, published in 1884 [ 4 ] and Angelo Mosso’s investigations of the effects of mental fatigue on physical performance, published in 1891 [ 5 ] were other early landmarks in the development of applied sport psychology research. Following the efforts of Koch, Wundt, Rieger, and Mosso, sport psychology works appeared with increasing regularity, including Philippe Tissié’s publications in 1894 [ 6 , 7 ] on psychology and physical training, and Pierre de Coubertin’s first use of the term sport psychology in his La Psychologie du Sport paper in 1900 [ 8 ]. In short, the history of sport psychology and performance research began as early as 1830 and picked up pace in the latter part of the 19 th century. Early pioneers, who helped shape sport psychology include Wundt, recognized as the “father of experimental psychology”, Tissié, the founder of French physical education and Legion of Honor awardee in 1932, and de Coubertin who became the father of the modern Olympic movement and founder of the International Olympic Committee.

Sport psychology flourished in the early 20 th century [see 1, 3 for extensive historic details]. For instance, independent laboratories emerged in Berlin, Germany, established by Carl Diem in 1920; in St. Petersburg and Moscow, Russia, established respectively by Avksenty Puni and Piotr Roudik in 1925; and in Champaign, Illinois USA, established by Coleman Griffith, also in 1925. The period from 1950–1980 saw rapid strides in sport psychology, with Franklin Henry establishing this field of study as independent of physical education in the landscape of American and eventually global sport science and kinesiology graduate programs [ 1 ]. In addition, of great importance in the 1960s, three international sport psychology organizations were established: namely, the International Society for Sport Psychology (1965), the North American Society for the Psychology of Sport and Physical Activity (1966), and the European Federation of Sport Psychology (1969). Since that time, the Association of Applied Sport Psychology (1986), the South American Society for Sport Psychology (1986), and the Asian-South Pacific Association of Sport Psychology (1989) have also been established.

The global growth in academic sport psychology has seen a large number of specialist publications launched, including the following journals: International Journal of Sport Psychology (1970), Journal of Sport & Exercise Psychology (1979), The Sport Psychologist (1987), Journal of Applied Sport Psychology (1989), Psychology of Sport and Exercise (2000), International Journal of Sport and Exercise Psychology (2003), Journal of Clinical Sport Psychology (2007), International Review of Sport and Exercise Psychology (2008), Journal of Sport Psychology in Action (2010), Sport , Exercise , and Performance Psychology (2014), and the Asian Journal of Sport & Exercise Psychology (2021).

In turn, the growth in journal outlets has seen sport psychology publications burgeon. Indicative of the scale of the contemporary literature on sport psychology, searches completed in May 2021 within the Web of Science Core Collection, identified 1,415 publications on goal setting and sport since 1985; 5,303 publications on confidence and sport since 1961; and 3,421 publications on anxiety and sport since 1980. In addition to academic journals, several comprehensive edited textbooks have been produced detailing sport psychology developments across the world, such as Hanrahan and Andersen’s (2010) Handbook of Applied Sport Psychology [ 9 ], Schinke, McGannon, and Smith’s (2016) International Handbook of Sport Psychology [ 10 ], and Bertollo, Filho, and Terry’s (2021) Advancements in Mental Skills Training [ 11 ] to name just a few. In short, sport psychology is global in both academic study and professional practice.

Meta-analysis in sport psychology

Several meta-analysis guides, computer programs, and sport psychology domain-specific primers have been popularized in the social sciences [ 12 , 13 ]. Sport psychology academics have conducted quantitative reviews on much studied constructs since the 1980s, with the first two appearing in 1983 in the form of Feltz and Landers’ meta-analysis on mental practice [ 14 ], which included 98 articles dating from 1934, and Bond and Titus’ cross-disciplinary meta-analysis on social facilitation [ 15 ], which summarized 241 studies including Triplett’s (1898) often-cited study of social facilitation in cycling [ 16 ]. Although much meta-analytic evidence exists for various constructs in sport and exercise psychology [ 12 ] including several related to performance [ 17 ], the evidence is inconsistent. For example, two meta-analyses, both ostensibly summarizing evidence of the benefits to performance of task cohesion [ 18 , 19 ], produced very different mean effects ( d = .24 vs d = 1.00) indicating that the true benefit lies somewhere in a wide range from small to large. Thus, the lack of a reliable evidence base for the use of sport psychology techniques represents a significant gap in the knowledge base for practitioners and researchers alike. A comprehensive systematic review of all published meta-analyses in the field of sport psychology has yet to be published.

Purpose and aim

We consider this review to be both necessary and long overdue for the following reasons: (a) the extensive history of sport psychology and performance research; (b) the prior publication of many meta-analyses summarizing various aspects of sport psychology research in a piecemeal fashion [ 12 , 17 ] but not its totality; and (c) the importance of better understanding and hopefully improving sport performance via the use of interventions based on solid evidence of their efficacy. Hence, we aimed to collate and evaluate this literature in a systematic way to gain improved understanding of the impact of sport psychology variables on sport performance by construct, research design, and meta-analysis quality, to enhance practical knowledge of sport psychology techniques and identify future lines of research inquiry. By systematically reviewing all identifiable meta-analytic reviews linking sport psychology techniques with sport performance, we aimed to evaluate the strength of the evidence base underpinning sport psychology interventions.

Materials and methods

This systematic review of meta-analyses followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 20 ]. We did not register our systematic review protocol in a database. However, we specified our search strategy, inclusion criteria, data extraction, and data analyses in advance of writing our manuscript. All details of our work are available from the lead author. Concerning ethics, this systematic review received a waiver from Texas Tech University Human Subject Review Board as it concerned archival data (i.e., published meta-analyses).

Eligibility criteria

Published meta-analyses were retained for extensive examination if they met the following inclusion criteria: (a) included meta-analytic data such as mean group, between or within-group differences or correlates; (b) published prior to January 31, 2021; (c) published in a peer-reviewed journal; (d) investigated a recognized sport psychology construct; and (e) meta-analyzed data concerned with sport performance. There was no language of publication restriction. To align with our systematic review objectives, we gave much consideration to study participants and performance outcomes. Across multiple checks, all authors confirmed study eligibility. Three authors (ML, AL, and PT) completed the final inclusion assessments.

Information sources

Authors searched electronic databases, personal meta-analysis history, and checked with personal research contacts. Electronic database searches occurred in EBSCOhost with the following individual databases selected: APA PsycINFO, ERIC, Psychology and Behavioral Sciences Collection, and SPORTDiscus. An initial search concluded October 1, 2020. ML, AL, and PT rechecked the identified studies during the February–March, 2021 period, which resulted in the identification of two additional meta-analyses [ 21 , 22 ].

Search protocol

ML and ES initially conducted independent database searches. For the first search, ML used the following search terms: sport psychology with meta-analysis or quantitative review and sport and performance or sport* performance. For the second search, ES utilized a sport psychology textbook and used the chapter title terms (e.g., goal setting). In EBSCOhost, both searches used the advanced search option that provided three separate boxes for search terms such as box 1 (sport psychology), box 2 (meta-analysis), and box 3 (performance). Specific details of our search strategy were:

Search by ML:

• sport psychology, meta-analysis, sport and performance
• sport psychology, meta-analysis or quantitative review, sport* performance
• sport psychology, quantitative review, sport and performance
• sport psychology, quantitative review, sport* performance

Search by ES:

• mental practice or mental imagery or mental rehearsal and sports performance and meta-analysis
• goal setting and sports performance and meta-analysis
• anxiety and stress and sports performance and meta-analysis
• competition and sports performance and meta-analysis
• diversity and sports performance and meta-analysis
• cohesion and sports performance and meta-analysis
• imagery and sports performance and meta-analysis
• self-confidence and sports performance and meta-analysis
• concentration and sports performance and meta-analysis
• athletic injuries and sports performance and meta-analysis
• overtraining and sports performance and meta-analysis
• children and sports performance and meta-analysis

The following specific search of the EBSCOhost with SPORTDiscus, APA PsycINFO, Psychology and Behavioral Sciences Collection, and ERIC databases, returned six results from 2002–2020, of which three were included [ 18 , 19 , 23 ] and three were excluded because they were not meta-analyses.

• Box 1 cohesion
• Box 2 sports performance
• Box 3 meta-analysis

Study selection

As detailed in the PRISMA flow chart ( Fig 1 ) and the specified inclusion criteria, a thorough study selection process was used. As mentioned in the search protocol, two authors (ML and ES) engaged independently with two separate searches and then worked together to verify the selected studies. Next, AL and PT examined the selected study list for accuracy. ML, AL, and PT, whilst rating the quality of included meta-analyses, also re-examined all selected studies to verify that each met the predetermined study inclusion criteria. Throughout the study selection process, disagreements were resolved through discussion until consensus was reached.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0263408.g001

Data extraction process

Initially, ML, TH, and ES extracted data items 1, 2, 3 and 8 (see Data items). Subsequently, ML, AL, and PT extracted the remaining data (items 4–7, 9, 10). Checks occurred during the extraction process for potential discrepancies (e.g., checking the number of primary studies in a meta-analysis). It was unnecessary to contact any meta-analysis authors for missing information or clarification during the data extraction process because all studies reported the required information. Across the search for meta-analyses, all identified studies were reported in English. Thus, no translation software or searching out a native speaker occurred. All data extraction forms (e.g., data items and individual meta-analysis quality) are available from the first author.

To help address our main aim, we extracted the following information from each meta-analysis: (1) author(s); (2) publication year; (3) construct(s); (4) intervention based meta-analysis (yes, no, mix); (5) performance outcome(s) description; (6) number of studies for the performance outcomes; (7) participant description; (8) main findings; (9) bias correction method/results; and (10) author(s) stated conclusions. For all information sought, we coded missing information as not reported.

Individual meta-analysis quality

ML, AL, and PT independently rated the quality of individual meta-analysis on the following 25 points found in the PRISMA checklist [ 20 ]: title; abstract structured summary; introduction rationale, objectives, and protocol and registration; methods eligibility criteria, information sources, search, study selection, data collection process, data items, risk of bias of individual studies, summary measures, synthesis of results, and risk of bias across studies; results study selection, study characteristics, risk of bias within studies, results of individual studies, synthesis of results, and risk of bias across studies; discussion summary of evidence, limitations, and conclusions; and funding. All meta-analyses were rated for quality by two coders to facilitate inter-coder reliability checks, and the mean quality ratings were used in subsequent analyses. One author (PT), having completed his own ratings, received the incoming ratings from ML and AL and ran the inter-coder analysis. Two rounds of ratings occurred due to discrepancies for seven meta-analyses, mainly between ML and AL. As no objective quality categorizations (i.e., a point system for grouping meta-analyses as poor, medium, good) currently exist, each meta-analysis was allocated a quality score of up to a maximum of 25 points. All coding records are available upon request.

Planned methods of analysis

Several preplanned methods of analysis occurred. We first assessed the mean quality rating of each meta-analysis based on our 25-point PRISMA-based rating system. Next, we used a median split of quality ratings to determine whether standardized mean effects (SMDs) differed by the two formed categories, higher and lower quality meta-analyses. Meta-analysis authors reported either of two different effect size metrics (i.e., r and SMD); hence we converted all correlational effects to SMD (i.e., Cohen’s d ) values using an online effect size calculator ( www.polyu.edu.hk/mm/effectsizefaqs/calculator/calculator.html ). We interpreted the meaningfulness of effects based on Cohen’s interpretation [ 24 ] with 0.20 as small, 0.50 as medium, 0.80 as large, and 1.30 as very large. As some psychological variables associate negatively with performance (e.g., confusion [ 25 ], cognitive anxiety [ 26 ]) whereas others associate positively (e.g., cohesion [ 23 ], mental practice [ 14 ]), we grouped meta-analyses according to whether the hypothesized effect with performance was positive or negative, and summarized the overall effects separately. By doing so, we avoided a scenario whereby the demonstrated positive and negative effects canceled one another out when combined. The effect of somatic anxiety on performance, which is hypothesized to follow an inverted-U relationship, was categorized as neutral [ 35 ]. Last, we grouped the included meta-analyses according to whether the primary studies were correlational in nature or involved an intervention and summarized these two groups of meta-analyses separately.

Study characteristics

Table 1 contains extracted data from 30 meta-analyses meeting the inclusion criteria, dating from 1983 [ 14 ] to 2021 [ 21 ]. The number of primary studies within the meta-analyses ranged from three [ 27 ] to 109 [ 28 ]. In terms of the description of participants included in the meta-analyses, 13 included participants described simply as athletes, whereas other meta-analyses identified a mix of elite athletes (e.g., professional, Olympic), recreational athletes, college-aged volunteers (many from sport science departments), younger children to adolescents, and adult exercisers. Of the 30 included meta-analyses, the majority ( n = 18) were published since 2010. The decadal breakdown of meta-analyses was 1980–1989 ( n = 1 [ 14 ]), 1990–1999 ( n = 6 [ 29 – 34 ]), 2000–2009 ( n = 5 [ 23 , 25 , 26 , 35 , 36 ]), 2010–2019 ( n = 12 [ 18 , 19 , 22 , 27 , 37 – 43 , 48 ]), and 2020–2021 ( n = 6 [ 21 , 28 , 44 – 47 ]).

https://doi.org/10.1371/journal.pone.0263408.t001

As for the constructs covered, we categorized the 30 meta-analyses into the following areas: mental practice/imagery [ 14 , 29 , 30 , 42 , 46 , 47 ], anxiety [ 26 , 31 , 32 , 35 ], confidence [ 26 , 35 , 36 ], cohesion [ 18 , 19 , 23 ], goal orientation [ 22 , 44 , 48 ], mood [ 21 , 25 , 34 ], emotional intelligence [ 40 ], goal setting [ 33 ], interventions [ 37 ], mindfulness [ 27 ], music [ 28 ], neurofeedback training [ 43 ], perfectionism [ 39 ], pressure training [ 45 ], quiet eye training [ 41 ], and self-talk [ 38 ]. Multiple effects were generated from meta-analyses that included more than one construct (e.g., tension, depression, etc. [ 21 ]; anxiety and confidence [ 26 ]). In relation to whether the meta-analyses included in our review assessed the effects of a sport psychology intervention on performance or relationships between psychological constructs and performance, 13 were intervention-based, 14 were correlational, two included a mix of study types, and one included a large majority of cross-sectional studies ( Table 1 ).

A wide variety of performance outcomes across many sports was evident, such as golf putting, dart throwing, maximal strength, and juggling; or categorical outcomes such as win/loss and Olympic team selection. Given the extensive list of performance outcomes and the incomplete descriptions provided in some meta-analyses, a clear categorization or count of performance types was not possible. Sufficient to conclude, researchers utilized many performance outcomes across a wide range of team and individual sports, motor skills, and strength and aerobic tasks.

Effect size data and bias correction

To best summarize the effects, we transformed all correlations to SMD values (i.e., Cohen’s d ). Across all included meta-analyses shown in Table 2 and depicted in Fig 2 , we identified 61 effects. Having corrected for bias, effect size values were assessed for meaningfulness [ 24 ], which resulted in 15 categorized as negligible (< ±0.20), 29 as small (±0.20 to < 0.50), 13 as moderate (±0.50 to < 0.80), 2 as large (±0.80 to < 1.30), and 1 as very large (≥ 1.30).

https://doi.org/10.1371/journal.pone.0263408.g002

https://doi.org/10.1371/journal.pone.0263408.t002

Study quality rating results and summary analyses

Following our PRISMA quality ratings, intercoder reliability coefficients were initially .83 (ML, AL), .95 (ML, PT), and .90 (AL, PT), with a mean intercoder reliability coefficient of .89. To achieve improved reliability (i.e., r mean > .90), ML and AL re-examined their ratings. As a result, intercoder reliability increased to .98 (ML, AL), .96 (ML, PT), and .92 (AL, PT); a mean intercoder reliability coefficient of .95. Final quality ratings (i.e., the mean of two coders) ranged from 13 to 25 ( M = 19.03 ± 4.15). Our median split into higher ( M = 22.83 ± 1.08, range 21.5–25, n = 15) and lower ( M = 15.47 ± 2.42, range 13–20.5, n = 15) quality groups produced significant between-group differences in quality ( F 1,28 = 115.62, p < .001); hence, the median split met our intended purpose. The higher quality group of meta-analyses were published from 2015–2021 (median 2018) and the lower quality group from 1983–2014 (median 2000). It appears that meta-analysis standards have risen over the years since the PRISMA criteria were first introduced in 2009. All data for our analyses are shown in Table 2 .

Table 3 contains summary statistics with bias-corrected values used in the analyses. The overall mean effect for sport psychology constructs hypothesized to have a positive impact on performance was of moderate magnitude ( d = 0.51, 95% CI = 0.42, 0.58, n = 36). The overall mean effect for sport psychology constructs hypothesized to have a negative impact on performance was small in magnitude ( d = -0.21, 95% CI -0.31, -0.11, n = 24). In both instances, effects were larger, although not significantly so, among meta-analyses of higher quality compared to those of lower quality. Similarly, mean effects were larger but not significantly so, where reported effects in the original studies were based on interventional rather than correlational designs. This trend only applied to hypothesized positive effects because none of the original studies in the meta-analyses related to hypothesized negative effects used interventional designs.

https://doi.org/10.1371/journal.pone.0263408.t003

In this systematic review of meta-analyses, we synthesized the available evidence regarding effects of sport psychology interventions/constructs on sport performance. We aimed to consolidate the literature, evaluate the potential for meta-analysis quality to influence the results, and suggest recommendations for future research at both the single study and quantitative review stages. During the systematic review process, several meta-analysis characteristics came to light, such as the number of meta-analyses of sport psychology interventions (experimental designs) compared to those summarizing the effects of psychological constructs (correlation designs) on performance, the number of meta-analyses with exclusively athletes as participants, and constructs featuring in multiple meta-analyses, some of which (e.g., cohesion) produced very different effect size values. Thus, although our overall aim was to evaluate the strength of the evidence base for use of psychological interventions in sport, we also discuss the impact of these meta-analysis characteristics on the reliability of the evidence.

When seen collectively, results of our review are supportive of using sport psychology techniques to help improve performance and confirm that variations in psychological constructs relate to variations in performance. For constructs hypothesized to have a positive effect on performance, the mean effect strength was moderate ( d = 0.51) although there was substantial variation between constructs. For example, the beneficial effects on performance of task cohesion ( d = 1.00) and self-efficacy ( d = 0.82) are large, and the available evidence base for use of mindfulness interventions suggests a very large beneficial effect on performance ( d = 1.35). Conversely, some hypothetically beneficial effects (2 of 36; 5.6%) were in the negligible-to-small range (0.15–0.20) and most beneficial effects (19 of 36; 52.8%) were in the small-to-moderate range (0.22–0.49). It should be noted that in the world of sport, especially at the elite level, even a small beneficial effect on performance derived from a psychological intervention may prove the difference between success and failure and hence small effects may be of great practical value. To put the scale of the benefits into perspective, an authoritative and extensively cited review of healthy eating and physical activity interventions [ 49 ] produced an overall pooled effect size of 0.31 (compared to 0.51 for our study), suggesting sport psychology interventions designed to improve performance are generally more effective than interventions designed to promote healthy living.

Among hypothetically negative effects (e.g., ego climate, cognitive anxiety, depression), the mean detrimental effect was small ( d = -0.21) although again substantial variation among constructs was evident. Some hypothetically negative constructs (5 of 24; 20.8%) were found to actually provide benefits to performance, albeit in the negligible range (0.02–0.12) and only two constructs (8.3%), both from Lochbaum and colleagues’ POMS meta-analysis [ 21 ], were shown to negatively affect performance above a moderate level (depression: d = -0.64; total mood disturbance, which incorporates the depression subscale: d = -0.84). Readers should note that the POMS and its derivatives assess six specific mood dimensions rather than the mood construct more broadly, and therefore results should not be extrapolated to other dimensions of mood [ 50 ].

Mean effects were larger among higher quality than lower quality meta-analyses for both hypothetically positive ( d = 0.54 vs d = 0.45) and negative effects ( d = -0.25 vs d = 0.17), but in neither case were the differences significant. It is reasonable to assume that the true effects were derived from the higher quality meta-analyses, although our conclusions remain the same regardless of study quality. Overall, our findings provide a more rigorous evidence base for the use of sport psychology techniques by practitioners than was previously available, representing a significant contribution to knowledge. Moreover, our systematic scrutiny of 30 meta-analyses published between 1983 and 2021 has facilitated a series of recommendations to improve the quality of future investigations in the sport psychology area.

Recommendations

The development of sport psychology as an academic discipline and area of professional practice relies on using evidence and theory to guide practice. Hence, a strong evidence base for the applied work of sport psychologists is of paramount importance. Although the beneficial effects of some sport psychology techniques are small, it is important to note the larger performance benefits for other techniques, which may be extremely meaningful for applied practice. Overall, however, especially given the heterogeneity of the observed effects, it would be wise for applied practitioners to avoid overpromising the benefits of sport psychology services to clients and perhaps underdelivering as a result [ 1 ].

The results of our systematic review can be used to generate recommendations for how the profession might conduct improved research to better inform applied practice. Much of the early research in sport psychology was exploratory and potential moderating variables were not always sufficiently controlled. Terry [ 51 ] outlined this in relation to the study of mood-performance relationships, identifying that physical and skills factors will very likely exert a greater influence on performance than psychological factors. Further, type of sport (e.g., individual vs. team), duration of activity (e.g., short vs. long duration), level of competition (e.g., elite vs. recreational), and performance measure (e.g., norm-referenced vs. self-referenced) have all been implicated as potential moderators of the relationship between psychological variables and sport performance [ 51 ]. To detect the relatively subtle effects of psychological effects on performance, research designs need to be sufficiently sensitive to such potential confounds. Several specific methodological issues are worth discussing.

The first issue relates to measurement. Investigating the strength of a relationship requires the measured variables to be valid, accurate and reliable. Psychological variables in the meta-analyses we reviewed relied primarily on self-report outcome measures. The accuracy of self-report data requires detailed inner knowledge of thoughts, emotions, and behavior. Research shows that the accuracy of self-report information is subject to substantial individual differences [ 52 , 53 ]. Therefore, self-report data, at best, are an estimate of the measure. Measurement issues are especially relevant to the assessment of performance, and considerable measurement variation was evident between meta-analyses. Some performance measures were more sensitive, especially those assessing physical performance relative to what is normal for the individual performer (i.e., self-referenced performance). Hence, having multiple baseline indicators of performance increases the probability of identifying genuine performance enhancement derived from a psychological intervention [ 54 ].

A second issue relates to clarifying the rationale for how and why specific psychological variables might influence performance. A comprehensive review of prerequisites and precursors of athletic talent [ 55 ] concluded that the superiority of Olympic champions over other elite athletes is determined in part by a range of psychological variables, including high intrinsic motivation, determination, dedication, persistence, and creativity, thereby identifying performance-related variables that might benefit from a psychological intervention. Identifying variables that influence the effectiveness of interventions is a challenging but essential issue for researchers seeking to control and assess factors that might influence results [ 49 ]. A key part of this process is to use theory to propose the mechanism(s) by which an intervention might affect performance and to hypothesize how large the effect might be.

A third issue relates to the characteristics of the research participants involved. Out of convenience, it is not uncommon for researchers to use undergraduate student participants for research projects, which may bias results and restrict the generalization of findings to the population of primary interest, often elite athletes. The level of training and physical conditioning of participants will clearly influence their performance. Highly trained athletes will typically make smaller gains in performance over time than novice athletes, due to a ceiling effect (i.e., they have less room for improvement). For example, consider runner A, who takes 20 minutes to run 5km one week but 19 minutes the next week, and Runner B who takes 30 minutes one week and 25 minutes the next. If we compare the two, Runner A runs faster than Runner B on both occasions, but Runner B improved more, so whose performance was better? If we also consider Runner C, a highly trained athlete with a personal best of 14 minutes, to run 1 minute quicker the following week would almost require a world record time, which is clearly unlikely. For this runner, an improvement of a few seconds would represent an excellent performance. Evidence shows that trained, highly motivated athletes may reach performance plateaus and as such are good candidates for psychological skills training. They are less likely to make performance gains due to increased training volume and therefore the impact of psychological skills interventions may emerge more clearly. Therefore, both test-retest and cross-sectional research designs should account for individual difference variables. Further, the range of individual difference factors will be context specific; for example, individual differences in strength will be more important in a study that uses weightlifting as the performance measure than one that uses darts as the performance measure, where individual differences in skill would be more important.

A fourth factor that has not been investigated extensively relates to the variables involved in learning sport psychology techniques. Techniques such as imagery, self-talk and goal setting all require cognitive processing and as such some people will learn them faster than others [ 56 ]. Further, some people are intuitive self-taught users of, for example, mood regulation strategies such as abdominal breathing or listening to music who, if recruited to participate in a study investigating the effects of learning such techniques on performance, would respond differently to novice users. Hence, a major challenge when testing the effects of a psychological intervention is to establish suitable controls. A traditional non-treatment group offers one option, but such an approach does not consider the influence of belief effects (i.e., placebo/nocebo), which can either add or detract from the effectiveness of performance interventions [ 57 ]. If an individual believes that, an intervention will be effective, this provides a motivating effect for engagement and so performance may improve via increased effort rather than the effect of the intervention per se.

When there are positive beliefs that an intervention will work, it becomes important to distinguish belief effects from the proposed mechanism through which the intervention should be successful. Research has shown that field studies often report larger effects than laboratory studies, a finding attributed to higher motivation among participants in field studies [ 58 ]. If participants are motivated to improve, being part of an active training condition should be associated with improved performance regardless of any intervention. In a large online study of over 44,000 participants, active training in sport psychology interventions was associated with improved performance, but only marginally more than for an active control condition [ 59 ]. The study involved 4-time Olympic champion Michael Johnson narrating both the intervention and active control using motivational encouragement in both conditions. Researchers should establish not only the expected size of an effect but also to specify and assess why the intervention worked. Where researchers report performance improvement, it is fundamental to explain the proposed mechanism by which performance was enhanced and to test the extent to which the improvement can be explained by the proposed mechanism(s).

Limitations

Systematic reviews are inherently limited by the quality of the primary studies included. Our review was also limited by the quality of the meta-analyses that had summarized the primary studies. We identified the following specific limitations; (1) only 12 meta-analyses summarized primary studies that were exclusively intervention-based, (2) the lack of detail regarding control groups in the intervention meta-analyses, (3) cross-sectional and correlation-based meta-analyses by definition do not test causation, and therefore provide limited direct evidence of the efficacy of interventions, (4) the extensive array of performance measures even within a single meta-analysis, (5) the absence of mechanistic explanations for the observed effects, and (6) an absence of detail across intervention-based meta-analyses regarding number of sessions, participants’ motivation to participate, level of expertise, and how the intervention was delivered. To ameliorate these concerns, we included a quality rating for all included meta-analyses. Having created higher and lower quality groups using a median split of quality ratings, we showed that effects were larger, although not significantly so, in the higher quality group of meta-analyses, all of which were published since 2015.

Conclusions

Journals are full of studies that investigate relationships between psychological variables and sport performance. Since 1983, researchers have utilized meta-analytic methods to summarize these single studies, and the pace is accelerating, with six relevant meta-analyses published since 2020. Unquestionably, sport psychology and performance research is fraught with limitations related to unsophisticated experimental designs. In our aggregation of the effect size values, most were small-to-moderate in meaningfulness with a handful of large values. Whether these moderate and large values could be replicated using more sophisticated research designs is unknown. We encourage use of improved research designs, at the minimum the use of control conditions. Likewise, we encourage researchers to adhere to meta-analytic guidelines such as PRISMA and for journals to insist on such adherence as a prerequisite for the acceptance of reviews. Although such guidelines can appear as a ‘painting by numbers’ approach, while reviewing the meta-analyses, we encountered difficulty in assessing and finding pertinent information for our study characteristics and quality ratings. In conclusion, much research exists in the form of quantitative reviews of studies published since 1934, almost 100 years after the very first publication about sport psychology and performance [ 2 ]. Sport psychology is now truly global in terms of academic pursuits and professional practice and the need for best practice information plus a strong evidence base for the efficacy of interventions is paramount. We should strive as a profession to research and provide best practices to athletes and the general community of those seeking performance improvements.

Supporting information

S1 checklist..

https://doi.org/10.1371/journal.pone.0263408.s001

Acknowledgments

We acknowledge the work of all academics since Koch in 1830 [ 2 ] for their efforts to research and promote the practice of applied sport psychology.

• 1. Terry PC. Applied Sport Psychology. IAAP Handbook of Applied Psychol. Wiley-Blackwell; 2011 Apr 20;386–410.
• 2. Koch CF. Die Gymnastik aus dem Gesichtspunkte der Diätetik und Psychologie [Callisthenics from the Viewpoint of Dietetics and Psychology]. Magdeburg, Germany: Creutz; 1830.
• 3. Chroni S, Abrahamsen F. History of Sport, Exercise, and Performance Psychology in Europe. Oxford Research Encyclopedia of Psychology. Oxford: Oxford University Press; 2017 Dec 19. https://doi.org/10.1093/acrefore/9780190236557.013.135
• 4. Rieger K. Der Hypnotismus: Psychiatrische Beiträge zur Kenntniss der Sogenannten Hypnotischen Zustände [Hypnotism: Psychiatric Contributions to the Knowledge of the So-called Hypnotic States]. Würzburg, Germany: University of Würzburg; 1884.
• 5. Mosso, A. La fatica [Fatigue]. Milan, Italy: Treves; 1891 [trans. 1904].
• View Article
• Google Scholar
• 9. Hanrahan SJ, Andersen MB, editors. Routledge Handbook of Applied Sport Psychology. London: Routledge; 2010.
• 10. Schinke RJ, McGannon KR, Smith B, editors. Routledge International Handbook of Sport Psychology. London: Routledge; 2016.
• 11. Bertollo M, Filho E, Terry PC. Advancements in Mental Skills Training: International Perspectives on Key Issues in Sport and Exercise Psychology. London: Routledge; 2021.
• PubMed/NCBI
• 17. Lochbaum M. Understanding the meaningfulness and potential impact of sports psychology on performance. In: Milanović D, Sporiš G, Šalaj S, Škegro D, editors, Proceedings book of 8th International Scientific Conference on Kinesiology, Opatija. Zagreb, Croatia: University of Zagreb, Faculty of Kinesiology; 2017. pp. 486–489.
• 24. Cohen J. Statistical Power Analysis for the Behavioral Sciences. New York: Routledge Academic; 1988.
• 50. Ekkekakis P. The Measurement of Affect, Mood, and Emotion. Cambridge: Cambridge University Press; 2013.

• Search by keyword
• Search by citation

Page 1 of 16

Effects of Creatine Supplementation on the Performance, Physiological Response, and Body Composition Among Swimmers: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Although recent studies have increasingly focused on examining the potential benefits of creatine supplementation to improve performance in swimming events, the impact of creatine supplementation on swimming p...

• View Full Text

Fine Tuning ECG Interpretation for Young Athletes: ECG Screening Using Z-score-based Analysis

Electrocardiograms (ECGs) in athletes commonly reveal findings related to physiologic adaptations to exercise, that may be difficult to discern from true underlying cardiovascular abnormalities. North American...

Cardiorespiratory Fitness and Sleep, but not Physical Activity, are Associated with Functional Connectivity in Older Adults

Aging results in changes in resting state functional connectivity within key networks associated with cognition. Cardiovascular function, physical activity, sleep, and body composition may influence these age-...

Effect of Programed Walking Exercise Using Bot Fit in Younger Adults

Physical inactivity and sedentary behavior both increase the risk of chronic disease and mortality. Regular participation in physical activity and reducing sedentary behavior play important roles in maintainin...

Advancing Pediatric Sports Medicine: A Review of the 4th Edition of the Oxford Textbook of Children’s Sport and Exercise Medicine, Edited by Neil Armstrong and Willem Van Mechelen and Published by Oxford University Press

The longitudinal effects of resisted and assisted sprint training on sprint kinematics, acceleration, and maximum velocity: a systematic review and meta-analysis.

Sprinting is important for both individual and team sports, and enhancing performance is often done through resisted, assisted, or combined sprint training. However, the effectiveness of these methods compared...

Agreement Between Heart Rate Variability - Derived vs. Ventilatory and Lactate Thresholds: A Systematic Review with Meta-Analyses

Determining thresholds by measuring blood lactate levels (lactate thresholds) or gas exchange (ventilatory thresholds) that delineate the different exercise intensity domains is crucial for training prescripti...

Can Foot Orthoses Benefit Symptomatic Runners? Mechanistic and Clinical Insights Through a Scoping Review

Running is a widely practiced sport worldwide associated with a host of benefits on cardiovascular, metabolic, musculoskeletal, and mental health, but often leads to musculoskeletal overuse injuries. The presc...

Sport and Autism: What Do We Know so Far? A Review

Autism, or autism spectrum disorders, is a neurodevelopmental condition characterized by limitations in social interaction, communication skills, and repetitive behaviors. Although motor disorders were previou...

Chronic Effects of Static Stretching Exercises on Skeletal Muscle Hypertrophy in Healthy Individuals: A Systematic Review and Multilevel Meta-Analysis

The chronic effect of static stretching (SS) on muscle hypertrophy is still unclear. This study aimed to examine the chronic effects of SS exercises on skeletal muscle hypertrophy in healthy individuals.

Effects of Holistically Conceptualised School-Based Interventions on Children’s Physical Literacy, Physical Activity, and Other Outcomes: A Systematic Review

Schools are a key setting for promoting children’s physical literacy development. This review aimed to identify school-based interventions that adopted a holistic conceptualisation of physical literacy and exa...

What do we Know about Complex-Contrast Training? A Systematic Scoping Review

The complex-contrast training (CCT) method utilizes two exercises with different loads and movement velocities in a set-by-set fashion to induce multiple neuromuscular adaptations. The speculated primary mecha...

Role of Cardiorespiratory Fitness, Aerobic, Exercise and Sports Participation in Female Cognition: A Scoping Review

The impact of cardiorespiratory fitness (CRF) on cognition is thought to be mediated by brain-derived neurotrophic factor. Aerobic exercise can increase CRF through various activities, including sports partici...

Potential of Soft-Shelled Rugby Headgear to Lower Regional Brain Strain Metrics During Standard Drop Tests

The growing concern for player safety in rugby has led to an increased focus on head impacts. Previous laboratory studies have shown that rugby headgear significantly reduces peak linear and rotational acceler...

On-water Rowing Biomechanical Assessment: A Systematic Scoping Review

Biomechanical parameters can distinguish a skilled rower from a less skilled rower and can provide coaches with meaningful feedback and objective evidence to inform coaching practices on rowing technique. Ther...

Upper Extremity Stress Fractures

Stress injuries are often missed secondary to their insidious onset, milder symptoms, and subtle or initially absent findings when imaged.

Metabolic Phenotyping from Whole-Blood Responses to a Standardized Exercise Test May Discriminate for Physiological, Performance, and Illness Outcomes: A Pilot Study in Highly-Trained Cross-Country Skiers

This study used metabolic phenotyping to explore the responses of highly-trained cross-country skiers to a standardized exercise test, which was part of the athletes’ routine testing, and determine whether met...

Effects of High-Intensity Interval Training on the Parameters Related to Physical Fitness and Health of Older Adults: A Systematic Review and Meta-Analysis

As a novel and time-efficient exercise form, high-intensity interval training (HIIT) has shown great potential in improving health-related physical fitness among diverse populations. However, empirical evidenc...

Training Intensity Distribution of a 7-Day HIIT Shock Microcycle: Is Time in the “Red Zone” Crucial for Maximizing Endurance Performance? A Randomized Controlled Trial

Various studies have shown that the type of intensity measure affects training intensity distribution (TID) computation. These conclusions arise from studies presenting data from meso- and macrocycles, while m...

The Prevalence of Low Vitamin D in Elite Para-Athletes: A Systematic Review

Vitamin D insufficiency (25OHD, 50–75 nmolˑl − 1 ) is a common issue within healthy adults and elite athletes and is associated with decreased musculoskeletal health and performance. However, few studies have ident...

The Discrepancy Between External and Internal Load/Intensity during Blood Flow Restriction Exercise: Understanding Blood Flow Restriction Pressure as Modulating Factor

Physical exercise induces acute psychophysiological responses leading to chronic adaptations when the exercise stimulus is applied repeatedly, at sufficient time periods, and with appropriate magnitude. To max...

Effects of In-Season Strength Training on Physical Fitness and Injury Prevention in North African Elite Young Female Soccer Players

Strength training (ST) primarily enhances physical fitness (e.g., muscle strength, power, speed) and bone density in female soccer players. Less information is available on the injury preventive effects of ST ...

Arachnoid Cysts in Athletes with Sports-Related Concussion: A Case Series and Literature Review

Arachnoid cysts (AC) are associated with a risk of rupture or haemorrhage following head impact and pose a potential predisposing factor for significant complications of sport-related concussion. Despite a rec...

Effect of Advanced Footwear Technology Spikes on Sprint Acceleration: A Multiple N-of-1 Trial

In contrast with Advanced Footwear Technology-AFT running shoes for long-distance, little is known about AFT sprint spikes on performance and acceleration parameters. However, their use has become widespread s...

Bibliometric Review of the Step Test: A Comprehensive Analysis of Research Trends and Development

The step test provides valuable information on cardiorespiratory parameters such as maximal oxygen uptake and heart rate. Cardiorespiratory capacity is critical to health-related fitness, with heart rate recov...

Biopsychosocial and Environmental Correlates of Children’s Motor Competence: An Exploratory Study

Given the significance of motor competence (MC) for healthy development and as a cornerstone for lifelong physical activity (PA), it is crucial to understand the manifold factors that are associated with MC. T...

Stressing the Relevance of Differentiating between Systematic and Random Measurement Errors in Ultrasound Muscle Thickness Diagnostics

The majority of studies that explore changes in musculature following resistance training interventions or examine atrophy due to immobilization or sarcopenia use ultrasound imaging. While most studies assume ...

Patient’s Perception of the Role of Gym Activity in Abdominal Wall Herniation in Adults: A Prospective Study

Despite significant changes in healthcare, work practices, and leisure activity, the proposed precipitating factors for abdominal wall hernias have remained largely unchanged for almost two centuries. We aimed...

Why should the Next Generation of Youth Guidelines Prioritize Vigorous Physical Activity?

The health benefits of regular physical activity (PA) in youth are well-documented. Yet the adherence rate to PA guidelines among youth worldwide is alarmingly deficient with only 19% of youth worldwide adheri...

Associations of Sex and Sport Contact-Level with Recovery Timelines Among Collegiate Athletes with Sport-Related Concussion

Growing interest has motivated recent studies to examine differences in recovery after sport-related concussion (SRC) by sex. However, heterogeneity in study design, participants, and recovery outcomes has led...

Response to “Comment on: Machine Learning for Understanding and Predicting Injuries in Football”

The original article was published in Sports Medicine - Open 2024 10 :84

The Leading Article to this article has been published in Sports Medicine - Open 2022 8 :73

Comment on: Machine Learning for Understanding and Predicting Injuries in Football

The original article was published in Sports Medicine - Open 2022 8 :73

The Letter to this article has been published in Sports Medicine - Open 2024 10 :85

The Biomechanical Influence of Step Width on Typical Locomotor Activities: A Systematic Review

Step width is a spatial variable in the frontal plane, defined as the mediolateral distance between the heel (forefoot during sprinting) of bilateral feet at initial contact. Variations in step width may impac...

Solving the High-Intensity Multimodal Training Prescription Puzzle: A Systematic Mapping Review

High-Intensity Multimodal Training (HIMT) refers to all styles of high-intensity combined aerobic, resistance and/or bodyweight exercise. Previous heterogeneity in exercise prescription and reporting in HIMT r...

Interplay of Muscle Architecture, Morphology, and Quality in Influencing Human Sprint Cycling Performance: A Systematic Review

This systematic review aimed to discern the relationships between muscle morphology, architecture, and quality with sprint cycling performance while considering the multifaceted nature of these relationships a...

The Essential and Optimal Analgesic and Anti-Inflammatory Medicines for Athletes at the Olympic Games

In 2019, the International Olympic Committee published the first Olympic and Paralympic Model Formulary (OPF), which defined the standardised set of medications required at every Olympic and Paralympic Games for ...

Health Problems of Professional Ballet Dancers: an Analysis of 1627 Weekly Self-Reports on Injuries, Illnesses and Mental Health Problems During One Season

Several studies have investigated injuries of (pre-)professional ballet dancers, however most used a medical-attention and/or time-loss definition and did not analyse the prevalence of all health problems. The...

Peak Oxygen Uptake is Slope Dependent: Insights from Ground Reaction Forces and Muscle Oxygenation in Trained Male Runners

The aim of this study is to explore the effect of treadmill slope on ground reaction forces and local muscle oxygenation as putative limiting factors of peak oxygen uptake in graded maximal incremental running...

Effects of Mitoquinone (MitoQ) Supplementation on Aerobic Exercise Performance and Oxidative Damage: A Systematic Review and Meta-analysis

Contracting skeletal muscle produces reactive oxygen species (ROS) originating from both mitochondrial and cytosolic sources. The use of non-specific antioxidants, such as vitamins C and E, during exercise has...

Effects of a Preseason Neuromuscular Training Program vs. an Endurance-Dominated Program on Physical Fitness and Injury Prevention in Female Soccer Players

The pre-season preparatory period is considered key for optimizing the physical fitness levels needed to withstand congested match periods and preventing injuries during the regular soccer season. This study c...

Epidemiology of Non-Contact Muscle Injuries in the Italian Male Elite Under-19 Football (Soccer) Championship

While extensive research exists on muscle injuries among adult football players, a notable gap persists in studies concerning younger footballers. The aim of the current study is to provide epidemiological dat...

Accuracy of the 6-Minute Walk Test for Assessing Functional Capacity in Patients With Heart Failure With Preserved Ejection Fraction and Other Chronic Cardiac Pathologies: Results of the ExIC-FEp Trial and a Meta-Analysis

Heart diseases, particularly heart failure, significantly impact patient quality of life and mortality rates. Functional capacity assessment is vital for predicting prognosis and risk in these patients. While ...

Expertise and Deceptive Movements in Sport

Deceptive movements occur when an actor seeks to fake, hide or delay kinematic information about their true movement outcomes. The purpose of deceptive movements is to impair the perception of opponents (the ‘...

The Effect of Endurance Exercise on Semen Quality in Male Athletes: A Systematic Review

Endurance exercise has the potential to affect reproductive function, with amenorrhea in female athletes. However, most studies focus on women. Evidence on the association between endurance exercise and male f...

Rating of Perceived Exertion: A Large Cross-Sectional Study Defining Intensity Levels for Individual Physical Activity Recommendations

Physical inactivity is a growing risk factor worldwide, therefore getting people into sports is necessary. When prescribing physical activity, it is essential to recommend the correct training intensities. Car...

Balance Control is Sequentially Correlated with Proprioception, Joint Range of Motion, Strength, Pain, and Plantar Tactile Sensation Among Older Adults with Knee Osteoarthritis

Patients with knee osteoarthritis (KOA) are at high risk for falls, which is attributed to their impaired balance control. Identifying factors associated with balance control facilitates the development of pre...

Effect of Exercise Prior to Sedentary Behavior on Vascular Health Parameters: A Systematic Review and Meta-Analysis of Crossover Trials

Sedentary behavior has been shown to negatively affect parameters of endothelial function and central hemodynamics, both of which are closely associated with vascular health. Exercise prior to sedentary behavi...

Concussion and the Sleeping Brain

Emerging research has suggested sleep to be a modifier of the trajectory of concussion recovery in adolescent and adult populations. Despite the growing recognition of the relationship between sleep and concus...

Impact of an Ultra-Endurance Marathon on Cardiac Function in Association with Cardiovascular Biomarkers

Participation in ultra-endurance races may lead to a transient decline in cardiac function and increased cardiovascular biomarkers. This study aims to assess alterations in biventricular function immediately a...

The Effect of Palmitoylethanolamide (PEA) on Skeletal Muscle Hypertrophy, Strength, and Power in Response to Resistance Training in Healthy Active Adults: A Double-Blind Randomized Control Trial

Palmitoylethanolamide (PEA) has analgesic/anti-inflammatory properties that may be a suitable alternative to over-the-counter (OTC) non-steroidal analgesics/anti-inflammatories. While OTC pain medications can ...

• Editorial Board
• Sign up for article alerts and news from this journal

Annual Journal Metrics

Citation Impact 2023 Journal Impact Factor: 4.1 5-year Journal Impact Factor: 5.5 Source Normalized Impact per Paper (SNIP): 1.740 SCImago Journal Rank (SJR): 1.446

Speed 2023 Submission to first editorial decision (median days): 16 Submission to acceptance (median days): 216

Usage 2023 Downloads: 1,609,820 Altmetric mentions: 4,288

• More about our metrics
• ISSN: 2198-9761 (electronic)

• Supplements
• Most Read Articles
• Most Cited Articles
• Editorial board
• Authors instructions
• For Reviewers

An official website of the United States government

Official websites use .gov A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

• Publications
• Account settings
• Advanced Search
• Journal List

Sports Specialization in Young Athletes

Evidence-Based Recommendations

Neeru Jayanthi , MD

Courtney pinkham , bs, lara dugas , phd, brittany patrick , mph, cynthia labella , md.

• Author information
• Article notes
• Copyright and License information

Neeru Jayanthi, MD, Associate Professor, Department of Family Medicine and Orthopaedic Surgery and Rehabilitation, Loyola Stritch School of Medicine, 2160 First Avenue, Bldg 54, Rm 260, Maywood, IL 60153 (e-mail: [email protected] )

Issue date 2013 May.

Sports specialization is intense training in 1 sport while excluding others. Sports specialization in early to middle childhood has become increasingly common. While most experts agree that some degree of sports specialization is necessary to achieve elite levels, there is some debate as to whether such intense practice time must begin during early childhood and to the exclusion of other sports to maximize potential for success. There is a concern that sports specialization before adolescence may be deleterious to a young athlete.

Evidence Acquisition:

PubMed and OVID were searched for English-language articles from 1990 to 2011 discussing sports specialization, expert athletes, or elite versus novice athletes, including original research articles, consensus opinions, and position statements.

For most sports, there is no evidence that intense training and specialization before puberty are necessary to achieve elite status. Risks of early sports specialization include higher rates of injury, increased psychological stress, and quitting sports at a young age. Sports specialization occurs along a continuum. Survey tools are being developed to identify where athletes fall along the spectrum of specialization.

Conclusion:

Some degree of sports specialization is necessary to develop elite-level skill development. However, for most sports, such intense training in a single sport to the exclusion of others should be delayed until late adolescence to optimize success while minimizing injury, psychological stress, and burnout.

Keywords: intense training, children, adolescents, overtraining, exercise

Youth sports participation has evolved from child-driven, recreational free play for enjoyment to adult-driven, highly structured, deliberate practice devoted to sports-specific skill development. 12 , 32 Emphasis is placed on developing and attaining sufficient skill levels to excel at many levels of athletics. 35 , 44 This evolution in youth sports may have developed as a result of society’s increasing regard for successful athletes, who enjoy significant recognition and financial rewards for their achievements. Consequently, many children and adolescents participating in sports now aspire to achieve elite levels. 44 , 46

The amount of training necessary to develop elite-level sports skills has long been debated. Ericsson et al defined the necessary components for expert skill acquisition in musicians, and these concepts have been extrapolated to sports. 16 To achieve expertise, musicians must practice 10 000 hours over 10 years. This intense practice is more likely to be successful if begun during the early years of development. Lesser practice and a delayed start resulted in less expertise. In contrast, others believe that fewer hours are needed to achieve elite-level skills and that intense specialized training is more effective during later stages of development. 42

A survey of elite young athletes (Training of Young Athletes Study) found that parents were the strongest influence on the initiation of a sport (gymnastics, tennis, swimming, soccer) while coaches were the strongest influence on their decision to perform intense training. 8 Similarly, a survey of 153 high school athletic directors suggested that coaches were the most powerful influence to specialize in a single sport. 23 This may create a disconnect: initially, a parent introduces the child to the sport; successes follow; then the coach encourages specialized training to achieve higher level success. The parent may acknowledge and encourage increased participation, not want to interfere with the child-coach relationship, and/or assume that this path is necessary for continued success. If the child has an injury as a result of training, the medical provider may treat the injury but may not have enough information to provide appropriate training recommendations for injury prevention.

Defining Sports Specialization

Sports specialization is defined as intense, year-round training in a single sport with the exclusion of other sports. 29 , 35 Variations on this general theme exist, with disagreement on what volume of training constitutes “intense” and whether year-round participation or exclusion of all other sports is essential for classifying an athlete as specialized. Some advocate that a minimum volume of training is required to meet the definition, 16 , 42 while others define specialization as simply limiting participation to a single sport on a year-round basis, regardless of training volume. 23 Ericsson et al proposed 3 stages in becoming a specialist or expert musician: (1) start at an early age, (2) specialize and increase participation, and (3) dedicate full-time commitment. 16 Côté et al further characterizes the intense training as the ultimate purpose of improving performance (“deliberate practice”) as opposed to enjoyment of the activity (“deliberate play”). 14 Soberlak and Côté developed a different approach when evaluating elite hockey players: sampling (ages 6-12 years), specializing (ages 13-15 years), and investment (ages 16+ years). 42 The distinction of sports specialization should really be focused on children who commit exclusively to a sport during the early-to-middle elementary school years, since later specialization is very common and almost standard in today’s society. 46

These definitions exclude athletes who perform a large volume of intense training in a single sport throughout the year but still compete in others concomitantly and those who train intensely in a single sport during parts of the year with variable year-round participation. As a result, sports specialization may be better defined along a continuum.

In an ongoing study, the rates of sports specialization in young athletes (8-18 years old) presenting to a pediatrician or family physician for sports physicals were compared with those presenting for an injury. 29 Based on questions about their sports participation, a sports specialization score was tabulated for each athlete. Preliminary data suggest that the most relevant question is whether they have quit other sports to focus on 1 sport. This factor accounted for 38% of the variance in the sport specialization score. 29 The second-most relevant question (32% of the variance) was whether the child had spent more than 3 quarters of their training time in 1 sport. Year-round and/or out-of-state training and competition were also relevant in determining level of specialization.

Trends in Sports Specialization

In the United States, participation in organized sport has increased from approximately 9% of children 6 years and younger in 1997 to 12% in 2008. 35 A majority (77.7%) of high school athletic directors reported an increasing trend in sports specialization. 23 Further evidence for early sports specialization is the growing number of travel leagues at 7 or 8 years of age 37 and an increase in young Olympic athletes. 46

Rates of sports specialization appear to increase with age. A study of 519 US Tennis Association junior tennis players found that 70% began specializing at an average age of 10.4 years old. 28 Specialization rate gradually increased after 14 years, with 95% of players by age 18 years. However, enjoyment and satisfaction ratings decreased in players older than 14 years old ( P < 0.01).

The reality is that few athletes achieve the elite or professional level. 35 Less than 1% of young athletes 6 to 17 years of age achieve elite status in basketball, soccer, baseball, softball, or football. 35 The data are similar for Germany 21 and Australia. 39

Does Early Specialization Promote Success in Sports?

There is general agreement that the number of hours spent in deliberate practice and training positively correlates with level of achievement in both individual and team sports; whether this intense practice must begin during early childhood and to the exclusion of other sports is a matter of debate. There are relatively few data to validate these theories. Professional medical organizations have published position statements on sports specialization and intense training in young people but have limited data upon which to base their recommendations and thus rely on expert opinion. 2 , 3 , 17 , 26 , 36

Early vs Late Intense Training

The best musicians spent over 10 000 hours practicing alone, while their less successful peers had accumulated 7000 hours or less, coinciding with critical periods of biological and cognitive development. Musicians began training around 5 years of age; those who began after age 5 years were unable to catch up.

Research in athletes has not consistently demonstrated that early intense training is essential for attaining an elite level in all sports ( Table 1 ). 5 , 6 , 13 , 21 , 22 , 24 , 25 , 30 , 31 , 38 , 42 , 45 Data from these studies are limited by a subset of sports, small samples sizes, and retrospective design; few included athletes who began intense training before 12 years. Two studies demonstrated that accomplished elite athletes were more likely to initiate intense training in early and middle childhood; both were women’s rhythmic gymnastics. In gymnastics, peak performance occurs before full maturation, requiring intense training before puberty. 25 , 30

Evidence for and against early sports specialization to achieve elite status

Plus sign (+) indicates “evidence for.”

Begin intense training.

Specialize in sport.

Diversify early, specialize in sport.

Canoeing/kayak, cycling, orienteering, rowing, sailing, skiing, swimming, track and field, triathalon, weight lifting.

In contrast, elite athletes in other sports were more likely to initiate intense training later in adolescence. World-class athletes were more likely to start competing at a later age, competed in other sports, and were typically selected for a sport federation program at an older age than those at the national level. 44 A recent survey of 148 elite and 95 near-elite Danish athletes (mean age, 24.5 years; track and field, weightlifting, cycling, rowing, swimming, skiing) found that the elite group began intense training at a later age and spent fewer hours practicing its main sport up to the age of 15 years compared to the near-elite group.38 By 18 years of age, the 2 groups had accumulated a similar number of practice hours, but by 21 years, elites had accumulated more practice hours.38 Involvement in other sports was not different between the groups and did not predict success. These sports require a high physical and aerobic capacity and lower technical or tactical requirement relative to ball and performance sports (gymnastics 11 and figure skating 43 ). While some physiologic adaptations to aerobic training occur in childhood, they are much less pronounced than adaptations in adolescence.

Early vs Late Specialization

For most sports, early diversification is more likely to lead to success ( Table 1 ). 5 , 6 , 13 , 21 , 22 , 24 , 31 , 38 , 42 , 45 A survey of 376 female Division 1 intercollegiate athletes found that the majority had their first organized sports experiences in other sports. 35 Only 17% had previously participated exclusively in their current sport; the majority simultaneously participated in individual sports (swimming, track and field, diving, tennis, and golf). 35

Early diversification provides the young athlete with valuable physical, cognitive, and psychosocial environments and promotes motivation. 1 , 2 , 36 , 38 , 46

Among high-level athletes of basketball, netball, and field hockey, the greater the number of activities that the athletes experienced and practiced in their developing years (ages 0-12 years), the less sports-specific practice was necessary to acquire expertise in their sport. 4 , 5 This is transfer of pattern recall skills from one sport to another, most pronounced during the early stages of involvement. 1 Early diversification followed by specialization may lead to more enjoyment, fewer injuries, and longer participation, contributing to the chances of success. 6 , 20 , 45

Other Factors Promoting Success in Sports

Early participation differences between elite youth soccer players who progressed to professional status at age 16 years and those who did not revealed that those who progressed had accumulated more hours per year in unstructured soccer activities between the ages of 6 and 12 years. There was no difference in soccer practice, soccer competition, or other sports in that time frame. 19 This suggests that elites sought more unstructured soccer during free time. This is supported by data that show that enjoyment of the sport and intrinsic motivation predict attainment. 20 , 25 , 31 Successful elite tennis players often have good long-term relationships with the same coach, access to tennis courts, and less overall demands for success compared with age-matched controls. 13

Risks of Single-Sport Intense Training

The risks of single-sport intense training include adverse psychological stress and premature withdrawal from competitive sport. Current data suggest that intense training and specialization may be independent risk factors. 28 , 29

The risks of intense training in elite young athletes in the United Kingdom was relatively low (rates of injury < 1/1000 hours of training) with few serious consequences. 7 , 34 Training volumes were often < 16 hours per week; lower than for other intensely trained athletes. 29 , 41 A 10-year follow-up suggests that injury incidence is significantly higher for athletes competing at an international level (87.5%) and a regional/country level (64.0%) compared with those competing at a national level (16.7%) or recreational level (47.1%). 33

Higher training volumes may increase risk for injury in a variety of sports. 41 In 2721 high school athletes, increased exposure was the most important risk factor for injury. 41 There was a linear relationship between exposure and risk of injury (odds ratio, 8.28), showing significantly elevated risk once training volume exceeded 16 hours per week ( Figure 1 ). Cumulative match (or competition) exposure also carries a significant risk: medical withdrawals increased in national tennis players after playing > 5 matches per year in supernational tournaments. 27 Players who specialized only in tennis were 1.5 times more likely to report an injury. 28 A 10-year prospective analysis of 481 youth baseball pitchers (9-14 years old) found that those who pitched more than 100 innings per year were 3.5 times more likely to be injured. 18 Others have found a significantly increased risk (odds ratio, 5.05) for shoulder or elbow surgery if pitching more than 8 months per year. 40

Relationship of injury to exposure hours in high school athletes. 41

The risk of injury from intense training and specialization may be affected by age, competitive level, growth rate, and pubertal maturation stage. Higher rates of injury were found in athletes older than 13 years of age and those at higher competitive levels. 15 Peripubertal gymnasts are more likely injured during periods of rapid growth (Tanner stages 2 and 3). 11 Fracture risk is also higher during peak height velocity. 9 , 29

Psychological Stress and Dropping Out of Sports

Early sports specialization may contribute to burnout and dropping out of sports ( Table 1 ). 5 , 6 , 13 , 22 , 24 , 25 , 30 , 38 , 42 , 45 Swimmers who specialized early spent less time on the national team and retired earlier than athletes who specialized later. 6 Minor league ice hockey players (boys) that dropped out of the sport started off-ice training earlier and spent more time in off-ice training than those who continued to compete. 45

In a retrospective 10-year review, 1 out of 5 of the most competitive elite athletes reported injury as the reason for quitting one’s sport. 10 Rhythmic gymnasts, those who specialized earlier and spent more hours training from age 4 to 16 years, rated their health lower and experienced less fun. 30 Junior tennis players who burned out early had less input in their training, higher perceived parental criticism and expectations, and lower levels of extrinsic motivation. 20 Elite Russian swimmers who dropped out reported that the main reasons for leaving the sport were psychological fatigue, general health, and difficult loads. 6

Some degree of sports specialization is necessary to attain elite-level skill. 2 , 3 , 17 , 26 , 36 However, for most sports, intense training in a single sport to the exclusion of others should be delayed until late adolescence to optimize success while minimizing risk for injury and psychological stress. 5 , 6 , 13 , 22 , 24 , 25 , 30 , 38 , 42 , 45

The following authors declared potential conflicts of interest: Neeru Jayanthi, MD, received a grant from the American Medical Society for Sports Medicine, and received honoraria and travel/expenses from United States Tennis Assocation (Player Development) for lectures and expenses and travel/expenses for serving on the American Medical Society for Sports Medicine Board of Directors; Brittany Patrick received a grant from the American Medical Society for Sports Medicine; Cynthia LaBella, MD, received a grant from the American Medical Society for Sports Medicine, and received honoraria for lectures given at AAP NCE, received royalties for published work, and received AAP COSMF executive committee travel expenses.

• 1. Abernethy B, Baker J, Côté J. Transfer of pattern recall skills may contribute to the development of sport expertise. Appl Cognit Psychol. 2005;19:705-718 [ Google Scholar ]
• 2. American Academy of Pediatrics Committee on Sports Medicine and Fitness. Intense training and sports specialization in young athletes. Pediatrics. 2000;106:154-157 [ PubMed ] [ Google Scholar ]
• 3. American College of Sports Medicine The prevention of sport injuries of children and adolescents. Med Sci Sport. 1993;25(8):1-7 [ PubMed ] [ Google Scholar ]
• 4. Baker J, Côté J, Abernethy B. Learning from the experts: practice activities of expert decision-makers in sport. Res Q Exerc Sport. 2003;74:342-347 [ DOI ] [ PubMed ] [ Google Scholar ]
• 5. Baker J, Côté J, Abernethy B. Sport-specific practice and the development of expert decision-making in team ball sports. J Appl Sport Psychol. 2003;15:12-25 [ Google Scholar ]
• 6. Barynina II, Vaitsekhovskii SM. The aftermath of early sports specialization for highly qualified swimmers. Fitness Sports Rev Int. 1992;27:132-133 [ Google Scholar ]
• 7. Baxter-Jones A, Maffulli N, Helms P. Low injury rates in elite athletes. Arch Dis Child. 1993;68:130-132 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 8. Baxter-Jones AD, Maffulli N; TOYA Study Group Parental influence on sport participation in elite young athletes. J Sports Med Phys Fitness. 2003;43(2):250-255 [ PubMed ] [ Google Scholar ]
• 9. Blimkie CJ, Lefevre J, Beunen GP, Renson R, Dequeker J, Van Damme P. Fractures, physical activity, and growth velocity in adolescent Belgian boys. Med Sci Sports Exerc. 1993;25(7):801-808 [ DOI ] [ PubMed ] [ Google Scholar ]
• 10. Butcher J, Lindner KJ, Johns DP. Withdrawal from competitive youth sport: a retrospective ten-year study. J Sport Behav. 2002;25(2):145-163 [ Google Scholar ]
• 11. Caine D, Cochrane B, Caine C, Zemper E. An epidemiologic investigation of injuries affecting young competitive female gymnasts. Am J Sports Med. 1989;17(6):811-820 [ DOI ] [ PubMed ] [ Google Scholar ]
• 12. Caine D, Maffulli N, Caine C. Epidemiology of injury in child and adolescent sports: injury rates, risk factors, and prevention. Clin Sports Med. 2008;27:19-50 [ DOI ] [ PubMed ] [ Google Scholar ]
• 13. Carlson R. The socialization of elite tennis players in Sweden: an analysis of the players’ backgrounds and development. Sociol Sport J. 1988;5:241-256 [ Google Scholar ]
• 14. Côté J, Lidor R, Hackfort D. ISSP position stand: to sample or to specialize? Seven postulates about youth sport activities that lead to continued participation and elite performance. Int J Sport Exerc Psychol. 2009;9:7-17 [ Google Scholar ]
• 15. Emery C. Risk factors for injury in child and adolescent sport. Clin J Sport Med. 2003;13(4):256-268 [ DOI ] [ PubMed ] [ Google Scholar ]
• 16. Ericsson KA, Krampe RT, Tesch-Romer C. The role of deliberate practice in the acquisition of expert performance. Psychol Rev. 1993;100(3):363-406 [ Google Scholar ]
• 17. FIMS/WHO Ad Hoc Committee on Sports and Children Sports and children: consensus statement on organized sports for children. Bull World Health Organ. 1998;76(5):445-447 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 18. Fleisig GS, Andrews JR, Cutter GR, et al. Risk of serious injury for young baseball pitchers: a 10-year prospective study. Am J Sports Med. 2011;39(2):253-257 [ DOI ] [ PubMed ] [ Google Scholar ]
• 19. Ford PR, Ward P, Hodges N, Williams AM. The role of deliberate practice and play in career progression in sport: the early engagement hypothesis. High Ability Studies. 2009;20(1):65-75 [ Google Scholar ]
• 20. Gould D, Udry E, Tuffey S, Loehr J. Burnout in competitive junior tennis players: pt. 1. A quantitative psychological assessment. Sport Psychol. 1996;10:322-340 [ Google Scholar ]
• 21. Gullich A, Emrich E. Evaluation of the support of young athletes in the elite sports system. Eur J Sport Soc. 2006;3:85-108 [ Google Scholar ]
• 22. Helsen WF, Starkes JL, Hodges NJ. Team sports and the theory of deliberate practice. J Sport Exerc Psychol. 1998;20:12-34 [ Google Scholar ]
• 23. Hill G, Simons J. A study of the sport specialization on high school athletics. J Sport Social Iss. 1989;13(1):1-13 [ Google Scholar ]
• 24. Hodges NJ, Starkes JL. Wrestling with the nature of expertise: a sport specific test of Ericsson, Krampe, and Tesh-Romer’s (1993) theory of “deliberate practice.” Int J Sport Psychol. 1996;27:400-424 [ Google Scholar ]
• 25. Hume PA, Hopkins WG, Robinson DM, Robinson SM, Hollings SC. Predictors of attainment in rhythmic sportive gymnastics. J Sports Med Phys Fitness. 1994;33(4):367-377 [ PubMed ] [ Google Scholar ]
• 26. Hughson R. Children in competitive sports: a multi-disciplinary approach. Can J Appl Sport Sci. 1986;11(4):162-172 [ PubMed ] [ Google Scholar ]
• 27. Jayanthi N, O’Boyle J, Durazo-Arvizu R. Risk factors for medical withdrawals in United States tennis association junior national tennis tournaments: a descriptive epidemiologic study. Sports Health. 2009;1(3):231-235 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 28. Jayanthi NA, Dechert A, Durazo R, Luke A. Training and specialization risks in junior elite tennis players J Med Sci Tennis. 2011;16(1):14-20 [ Google Scholar ]
• 29. Jayanthi NA, Pinkham C, Durazo-Arivu R, Dugas L, Luke A. The risks of sports specialization and rapid growth in young athletes. Clin J Sports Med. 2011;21(2):157 [ Google Scholar ]
• 30. Law M, Côté J, Ericsson KA. Characteristics of expert development in rhythmic gymnastics: a retrospective study. Int J Exerc Sport Psychol. 2007;5:82-103 [ Google Scholar ]
• 31. Lidor R, Lavyan Z. A retrospective picture of early sport experiences among elite and near-elite Israeli athletes: developmental and psychological perspectives. Int J Sport Psychol. 2002;33:269-289 [ Google Scholar ]
• 32. Maffulli N. The growing child in sport. Br Med Bull. 1992;48(3):561-568 [ DOI ] [ PubMed ] [ Google Scholar ]
• 33. Maffulli N, Baxter-Jones AD, Grieve A. Long-term sport involvement and sports injury rate in elite athletes. Arch Dis Child. 2005;90:525-527 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 34. Maffulli N, King J, Helms P. Training in elite young athletes (the training of young athletes (TOYA) study: injuries, flexibility and isometric strength. Br J Sports Med. 1994;28(2):123-136 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 35. Malina RM. Early sport specialization: roots, effectiveness, risks. Curr Sports Med Rep. 2010;9(6):364-371 [ DOI ] [ PubMed ] [ Google Scholar ]
• 36. McLeod TCV, Decoster L, Loud KJ, et al. National Athletic Trainers’ Association position statement: prevention of pediatric overuse injuries. J Athl Train. 2011;46(2):206-220 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 37. Metzl JD. Expectations of pediatric sport participation among pediatricians, patients, and parents. Pediatr Clin North Am. 2002;49(3):497-504 [ DOI ] [ PubMed ] [ Google Scholar ]
• 38. Moesch K, Elbe AM, Hauge ML, Wikman JM. Late specialization: the key to success in centimeters, grams, or seconds (cgs) sports. Scand J Med Sci Sports. 2011;21(6):e282-e290 [ DOI ] [ PubMed ] [ Google Scholar ]
• 39. Oldenziel KE, Gagne F, Gulbin J. Factors affecting the rate of athlete development from novice to senior elite: how applicable is the 10-year rule? Paper presented at: 2004 Pre-Olympic Congress: Sports Science Through the Ages; August 2004; Thessaloniki, Greece [ Google Scholar ]
• 40. Olsen SJ, Fleisig GS, Shouchen D, Loftice J, Andrews JR. Risk factors for shoulder and elbow injuries in adolescent baseball pitchers. Am J Sports Med. 2006;34:905-912 [ DOI ] [ PubMed ] [ Google Scholar ]
• 41. Rose MS, Emery CA, Meeuwisse WH. Sociodemographic predictors of sport injury in adolescents. Med Sci Sports Exerc. 2008;40(3):444-450 [ DOI ] [ PubMed ] [ Google Scholar ]
• 42. Soberlak P, Côté J. The developmental activities of elite ice hockey players. J Appl Sport Psyc. 2003;15:41-49 [ Google Scholar ]
• 43. Starkes JL, Deakin J, Allard F, Hodges NJ, Hayes A. Deliberate practice in sports: what is it anyway? In: Ericsson KA, ed. The Road to Excellence: The Acquisition of Expert Performance in the Arts and Sciences, Ports, and Games. Mahwah, NJ: Erlbaum; 1996:81-106 [ Google Scholar ]
• 44. Vaeyens R, Gullich A, Warr CR, Philippaerts R. Talent identification and promotion programmes of Olympic athletes. J Sports Sci. 2009;27:1367-1380 [ DOI ] [ PubMed ] [ Google Scholar ]
• 45. Wall M, Côté J. Developmental activities that lead to dropout and investment in sport. Phys Educ Sport Pedagogy. 2007;12:77-87 [ Google Scholar ]
• 46. Wiersma LD. Risks and benefits of youth sport specialization: perspectives and recommendations. Pediatr Exerc Sci. 2000;12:13-22 [ Google Scholar ]
• View on publisher site
• PDF (293.5 KB)
• Collections

Similar articles

Cited by other articles, links to ncbi databases.

• Download .nbib .nbib
• Format: AMA APA MLA NLM

Add to Collections

• Browse All Articles
• Newsletter Sign-Up

• 26 Apr 2024

Deion Sanders' Prime Lessons for Leading a Team to Victory

The former star athlete known for flash uses unglamorous command-and-control methods to get results as a college football coach. Business leaders can learn 10 key lessons from the way 'Coach Prime' builds a culture of respect and discipline without micromanaging, says Hise Gibson.

• 29 Feb 2024

Beyond Goals: David Beckham's Playbook for Mobilizing Star Talent

Reach soccer's pinnacle. Become a global brand. Buy a team. Sign Lionel Messi. David Beckham makes success look as easy as his epic free kicks. But leveraging world-class talent takes discipline and deft decision-making, as case studies by Anita Elberse reveal. What could other businesses learn from his ascent?

• 28 Feb 2023
• Cold Call Podcast

Muhammad Ali: A Case Study in Purpose-Driven Decision Making

Muhammad Ali, born Cassius Marcellus Clay Jr., rose from a poor family in segregated Louisville, Kentucky to international fame, winning three heavyweight boxing titles and becoming a civil rights leader and role model for millions of people around the world. How did he do it? Early in his career, Ali’s creativity and hard work helped him overcome significant obstacles. Rather than letting his fear of flying keep him from competing in the 1960 Olympics, he traveled to Italy wearing a parachute -- and easily won the gold medal in boxing. When he returned to the U.S. as a gold medalist, Ali used his growing fame to bring attention to racism and humanitarian causes he supported, including his then-controversial decision to refuse to fight in the Vietnam War. Professor Robert Simons discusses how Ali made decisions throughout his life and career to leave a lasting impact on the world in his case, “Muhammad Ali: Changing the World.”

• 25 Oct 2022
• Research & Ideas

Is Baseball Ready to Compete for the Next Generation of Fans?

With its slower pace and limited on-field action, major league baseball trails football in the US, basketball, and European soccer in revenue and popularity. Stephen Greyser discusses the state of "America's pastime."

• 01 Nov 2021

Team Success Starts with the Individual—and with Love

Many leaders see teams as collective units, but helping individual members reach their potential—personally and professionally—can open new opportunities. Ranjay Gulati looks at the philosophy of famed football coach Pete Carroll. Open for comment; 0 Comments.

• 12 Oct 2021

What Actually Draws Sports Fans to Games? It's Not Star Athletes.

Team owners think they need marquee names or slick stadiums to prosper, but research by Karim Lakhani and Patrick Ferguson suggests that fans want something far simpler: suspense. Open for comment; 0 Comments.

• 27 Jul 2021

Mixing Sports and Money: Adidas and the Commercialization of the Olympics

Horst Dassler, the son of the founder of Adidas, cultivated relationships with athletes and national associations—with the aim of expanding his family’s sports apparel business. In doing so, he created the first sports sponsorships for the Olympics, and ultimately became a key force behind the commercialization of sports today. Professor Geoffrey Jones explores the pros and cons of the globalization and commercialization of sport in his case, spanning from the 1930s to the 1970s, “Horst Dassler, Adidas, and the Commercialization of Sport.” Open for comment; 0 Comments.

• 17 Mar 2021
• Working Paper Summaries

Consuming Contests: Outcome Uncertainty and Spectator Demand for Contest-based Entertainment

Analysis of Australian Football League data shows that the uncertainty of game outcomes has a large, positive causal effect on stadium attendance. These findings show how competitive balance is important for contest designers in general and sports leagues in particular.

• 24 Apr 2020

Lessons from the NFL: Virtual Hiring, Leadership, Building Teams and COVID-19

The National Football League player draft this year is challenging for the league, players, fans and, in particular, talent evaluators, reports Boris Groysberg and colleagues. What can business learn? Open for comment; 0 Comments.

• 08 Jan 2020

NFL Head Coaches Are Getting Younger. What Can Organizations Learn?

Football team owners are hiring younger head coaches, hoping to unleash innovation and fresh thinking. How's that working out? Research by Boris Groysberg and colleagues. Open for comment; 0 Comments.

• 23 Jan 2019
• Sharpening Your Skills

Sports: Lessons for Managers

When people look to illustrate a great business idea or accomplishment, a sports metaphor usually isn't far away. Why Harvard Business School researchers look for teaching gold on the playing fields of the world. Open for comment; 0 Comments.

• 17 Jul 2016

More Effective Sports Sponsorship—Combining and Integrating Key Resources and Capabilities of International Sports Events and Their Major Sponsors

This field-based study of the Union of European Football Associations and its main international sporting event, the European Championships, explores key organizational capabilities that underlie value creation and enhancement in an event’s portfolio of sponsorship relationships. Developing and employing these capabilities--collaborative, absorptive, adaptive, and learning--have positive results for the event as well as for its sponsors. When effectively undertaken and coordinated, the activities can lead to ongoing renewals of the sponsorship program and open the door for new sponsors. The study’s perspective is that of the event, unusual in research on sponsorship.

• 08 Jan 2016

Is it Worth a Pay Cut to Work for a Great Manager (Like Bill Belichick)?

Few of us want to take less money to move to another organization, but Boris Groysberg and Abhijit Naik point to research that shows hooking up with the right manager—whether in sports or business—can quickly increase your value even if your pay is less. Open for comment; 0 Comments.

• 03 Jan 2016

NFL Black Monday: How Much Do Coaches Really Matter?

Teams planning management changes on "Black Monday" can learn much from academic research on National Football League coaches, say Boris Groysberg and Abhijit Naik. The findings hold value not only for football teams, but for any organization that depends on leadership for success. Open for comment; 0 Comments.

• 26 Oct 2015

What’s the Value of a Win in College Athletics?

As debate continues over whether student-athletes should be paid, professor Doug Chung’s research on the massive money being earned by collegiate football and basketball programs could help guide the answer. Open for comment; 0 Comments.

• 06 Mar 2006

Winners and Losers at the Olympics

We know which athletes won and lost in Turin, but what about the companies and individuals looking for business gold? Professor Stephen A. Greyser looks at the results—and the possibilities ahead in China. Closed for comment; 0 Comments.

Please note: This website has recently moved from www.health.gov to odphp.health.gov. www.health.gov is now the official website of ODPHP’s parent organization, the Office of the Assistant Secretary for Health (OASH). Please update your bookmarks for easy access to all our resources. 

Physical Activity Is Good for the Mind and the Body

Health and Well-Being Matter is the monthly blog of the Director of the Office of Disease Prevention and Health Promotion.

Everyone has their own way to “recharge” their sense of well-being — something that makes them feel good physically, emotionally, and spiritually even if they aren’t consciously aware of it. Personally, I know that few things can improve my day as quickly as a walk around the block or even just getting up from my desk and doing some push-ups. A hike through the woods is ideal when I can make it happen. But that’s me. It’s not simply that I enjoy these activities but also that they literally make me feel better and clear my mind.

Mental health and physical health are closely connected. No kidding — what’s good for the body is often good for the mind. Knowing what you can do physically that has this effect for you will change your day and your life.

Physical activity has many well-established mental health benefits. These are published in the Physical Activity Guidelines for Americans and include improved brain health and cognitive function (the ability to think, if you will), a reduced risk of anxiety and depression, and improved sleep and overall quality of life. Although not a cure-all, increasing physical activity directly contributes to improved mental health and better overall health and well-being.

Learning how to routinely manage stress and getting screened for depression are simply good prevention practices. Awareness is especially critical at this time of year when disruptions to healthy habits and choices can be more likely and more jarring. Shorter days and colder temperatures have a way of interrupting routines — as do the holidays, with both their joys and their stresses. When the plentiful sunshine and clear skies of temperate months give way to unpredictable weather, less daylight, and festive gatherings, it may happen unconsciously or seem natural to be distracted from being as physically active. However, that tendency is precisely why it’s so important that we are ever more mindful of our physical and emotional health — and how we can maintain both — during this time of year.

Roughly half of all people in the United States will be diagnosed with a mental health disorder at some point in their lifetime, with anxiety and anxiety disorders being the most common. Major depression, another of the most common mental health disorders, is also a leading cause of disability for middle-aged adults. Compounding all of this, mental health disorders like depression and anxiety can affect people’s ability to take part in health-promoting behaviors, including physical activity. In addition, physical health problems can contribute to mental health problems and make it harder for people to get treatment for mental health disorders.

The COVID-19 pandemic has brought the need to take care of our physical and emotional health to light even more so these past 2 years. Recently, the U.S. Surgeon General highlighted how the pandemic has exacerbated the mental health crisis in youth .

The good news is that even small amounts of physical activity can immediately reduce symptoms of anxiety in adults and older adults. Depression has also shown to be responsive to physical activity. Research suggests that increased physical activity, of any kind, can improve depression symptoms experienced by people across the lifespan. Engaging in regular physical activity has also been shown to reduce the risk of developing depression in children and adults.

Though the seasons and our life circumstances may change, our basic needs do not. Just as we shift from shorts to coats or fresh summer fruits and vegetables to heartier fall food choices, so too must we shift our seasonal approach to how we stay physically active. Some of that is simply adapting to conditions: bundling up for a walk, wearing the appropriate shoes, or playing in the snow with the kids instead of playing soccer in the grass.

Sometimes there’s a bit more creativity involved. Often this means finding ways to simplify activity or make it more accessible. For example, it may not be possible to get to the gym or even take a walk due to weather or any number of reasons. In those instances, other options include adding new types of movement — such as impromptu dance parties at home — or doing a few household chores (yes, it all counts as physical activity).

During the COVID-19 pandemic, I built a makeshift gym in my garage as an alternative to driving back and forth to the gym several miles from home. That has not only saved me time and money but also afforded me the opportunity to get 15 to 45 minutes of muscle-strengthening physical activity in at odd times of the day.

For more ideas on how to get active — on any day — or for help finding the motivation to get started, check out this Move Your Way® video .

The point to remember is that no matter the approach, the Physical Activity Guidelines recommend that adults get at least 150 minutes of moderate-intensity aerobic activity (anything that gets your heart beating faster) each week and at least 2 days per week of muscle-strengthening activity (anything that makes your muscles work harder than usual). Youth need 60 minutes or more of physical activity each day. Preschool-aged children ages 3 to 5 years need to be active throughout the day — with adult caregivers encouraging active play — to enhance growth and development. Striving toward these goals and then continuing to get physical activity, in some shape or form, contributes to better health outcomes both immediately and over the long term.

For youth, sports offer additional avenues to more physical activity and improved mental health. Youth who participate in sports may enjoy psychosocial health benefits beyond the benefits they gain from other forms of leisure-time physical activity. Psychological health benefits include higher levels of perceived competence, confidence, and self-esteem — not to mention the benefits of team building, leadership, and resilience, which are important skills to apply on the field and throughout life. Research has also shown that youth sports participants have a reduced risk of suicide and suicidal thoughts and tendencies. Additionally, team sports participation during adolescence may lead to better mental health outcomes in adulthood (e.g., less anxiety and depression) for people exposed to adverse childhood experiences. In addition to the physical and mental health benefits, sports can be just plain fun.

Physical activity’s implications for significant positive effects on mental health and social well-being are enormous, impacting every facet of life. In fact, because of this national imperative, the presidential executive order that re-established the President’s Council on Sports, Fitness & Nutrition explicitly seeks to “expand national awareness of the importance of mental health as it pertains to physical fitness and nutrition.” While physical activity is not a substitute for mental health treatment when needed and it’s not the answer to certain mental health challenges, it does play a significant role in our emotional and cognitive well-being.

No matter how we choose to be active during the holiday season — or any season — every effort to move counts toward achieving recommended physical activity goals and will have positive impacts on both the mind and the body. Along with preventing diabetes, high blood pressure, obesity, and the additional risks associated with these comorbidities, physical activity’s positive effect on mental health is yet another important reason to be active and Move Your Way .

As for me… I think it’s time for a walk. Happy and healthy holidays, everyone!

Yours in health, Paul

Paul Reed, MD Rear Admiral, U.S. Public Health Service Deputy Assistant Secretary for Health Director, Office of Disease Prevention and Health Promotion

The Office of Disease Prevention and Health Promotion (ODPHP) cannot attest to the accuracy of a non-federal website.

Linking to a non-federal website does not constitute an endorsement by ODPHP or any of its employees of the sponsors or the information and products presented on the website.

You will be subject to the destination website's privacy policy when you follow the link.