research title about stress of students

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• Published: 17 April 2024

Deciphering the influence: academic stress and its role in shaping learning approaches among nursing students: a cross-sectional study

• Rawhia Salah Dogham 1 ,
• Heba Fakieh Mansy Ali 1 ,
• Asmaa Saber Ghaly 3 ,
• Nermine M. Elcokany 2 ,
• Mohamed Mahmoud Seweid 4 &
• Ayman Mohamed El-Ashry   ORCID: orcid.org/0000-0001-7718-4942 5  

BMC Nursing volume  23 , Article number:  249 ( 2024 ) Cite this article

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Nursing education presents unique challenges, including high levels of academic stress and varied learning approaches among students. Understanding the relationship between academic stress and learning approaches is crucial for enhancing nursing education effectiveness and student well-being.

This study aimed to investigate the prevalence of academic stress and its correlation with learning approaches among nursing students.

Design and Method

A cross-sectional descriptive correlation research design was employed. A convenient sample of 1010 nursing students participated, completing socio-demographic data, the Perceived Stress Scale (PSS), and the Revised Study Process Questionnaire (R-SPQ-2 F).

Most nursing students experienced moderate academic stress (56.3%) and exhibited moderate levels of deep learning approaches (55.0%). Stress from a lack of professional knowledge and skills negatively correlates with deep learning approaches (r = -0.392) and positively correlates with surface learning approaches (r = 0.365). Female students showed higher deep learning approach scores, while male students exhibited higher surface learning approach scores. Age, gender, educational level, and academic stress significantly influenced learning approaches.

Academic stress significantly impacts learning approaches among nursing students. Strategies addressing stressors and promoting healthy learning approaches are essential for enhancing nursing education and student well-being.

Nursing implication

Understanding academic stress’s impact on nursing students’ learning approaches enables tailored interventions. Recognizing stressors informs strategies for promoting adaptive coping, fostering deep learning, and creating supportive environments. Integrating stress management, mentorship, and counseling enhances student well-being and nursing education quality.

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Introduction

Nursing education is a demanding field that requires students to acquire extensive knowledge and skills to provide competent and compassionate care. Nursing education curriculum involves high-stress environments that can significantly impact students’ learning approaches and academic performance [ 1 , 2 ]. Numerous studies have investigated learning approaches in nursing education, highlighting the importance of identifying individual students’ preferred approaches. The most studied learning approaches include deep, surface, and strategic approaches. Deep learning approaches involve students actively seeking meaning, making connections, and critically analyzing information. Surface learning approaches focus on memorization and reproducing information without a more profound understanding. Strategic learning approaches aim to achieve high grades by adopting specific strategies, such as memorization techniques or time management skills [ 3 , 4 , 5 ].

Nursing education stands out due to its focus on practical training, where the blend of academic and clinical coursework becomes a significant stressor for students, despite academic stress being shared among all university students [ 6 , 7 , 8 ]. Consequently, nursing students are recognized as prone to high-stress levels. Stress is the physiological and psychological response that occurs when a biological control system identifies a deviation between the desired (target) state and the actual state of a fitness-critical variable, whether that discrepancy arises internally or externally to the human [ 9 ]. Stress levels can vary from objective threats to subjective appraisals, making it a highly personalized response to circumstances. Failure to manage these demands leads to stress imbalance [ 10 ].

Nursing students face three primary stressors during their education: academic, clinical, and personal/social stress. Academic stress is caused by the fear of failure in exams, assessments, and training, as well as workload concerns [ 11 ]. Clinical stress, on the other hand, arises from work-related difficulties such as coping with death, fear of failure, and interpersonal dynamics within the organization. Personal and social stressors are caused by an imbalance between home and school, financial hardships, and other factors. Throughout their education, nursing students have to deal with heavy workloads, time constraints, clinical placements, and high academic expectations. Multiple studies have shown that nursing students experience higher stress levels compared to students in other fields [ 12 , 13 , 14 ].

Research has examined the relationship between academic stress and coping strategies among nursing students, but no studies focus specifically on the learning approach and academic stress. However, existing literature suggests that students interested in nursing tend to experience lower levels of academic stress [ 7 ]. Therefore, interest in nursing can lead to deep learning approaches, which promote a comprehensive understanding of the subject matter, allowing students to feel more confident and less overwhelmed by coursework and exams. Conversely, students employing surface learning approaches may experience higher stress levels due to the reliance on memorization [ 3 ].

Understanding the interplay between academic stress and learning approaches among nursing students is essential for designing effective educational interventions. Nursing educators can foster deep learning approaches by incorporating active learning strategies, critical thinking exercises, and reflection activities into the curriculum [ 15 ]. Creating supportive learning environments encouraging collaboration, self-care, and stress management techniques can help alleviate academic stress. Additionally, providing mentorship and counselling services tailored to nursing students’ unique challenges can contribute to their overall well-being and academic success [ 16 , 17 , 18 ].

Despite the scarcity of research focusing on the link between academic stress and learning methods in nursing students, it’s crucial to identify the unique stressors they encounter. The intensity of these stressors can be connected to the learning strategies employed by these students. Academic stress and learning approach are intertwined aspects of the student experience. While academic stress can influence learning approaches, the choice of learning approach can also impact the level of academic stress experienced. By understanding this relationship and implementing strategies to promote healthy learning approaches and manage academic stress, educators and institutions can foster an environment conducive to deep learning and student well-being.

Hence, this study aims to investigate the correlation between academic stress and learning approaches experienced by nursing students.

Study objectives

Assess the levels of academic stress among nursing students.

Assess the learning approaches among nursing students.

Identify the relationship between academic stress and learning approach among nursing students.

Identify the effect of academic stress and related factors on learning approach and among nursing students.

Materials and methods

Research design.

A cross-sectional descriptive correlation research design adhering to the STROBE guidelines was used for this study.

A research project was conducted at Alexandria Nursing College, situated in Egypt. The college adheres to the national standards for nursing education and functions under the jurisdiction of the Egyptian Ministry of Higher Education. Alexandria Nursing College comprises nine specialized nursing departments that offer various nursing specializations. These departments include Nursing Administration, Community Health Nursing, Gerontological Nursing, Medical-Surgical Nursing, Critical Care Nursing, Pediatric Nursing, Obstetric and Gynecological Nursing, Nursing Education, and Psychiatric Nursing and Mental Health. The credit hour system is the fundamental basis of both undergraduate and graduate programs. This framework guarantees a thorough evaluation of academic outcomes by providing an organized structure for tracking academic progress and conducting analyses.

Participants and sample size calculation

The researchers used the Epi Info 7 program to calculate the sample size. The calculations were based on specific parameters such as a population size of 9886 students for the academic year 2022–2023, an expected frequency of 50%, a maximum margin of error of 5%, and a confidence coefficient of 99.9%. Based on these parameters, the program indicated that a minimum sample size of 976 students was required. As a result, the researchers recruited a convenient sample of 1010 nursing students from different academic levels during the 2022–2023 academic year [ 19 ]. This sample size was larger than the minimum required, which could help to increase the accuracy and reliability of the study results. Participation in the study required enrollment in a nursing program and voluntary agreement to take part. The exclusion criteria included individuals with mental illnesses based on their response and those who failed to complete the questionnaires.

socio-demographic data that include students’ age, sex, educational level, hours of sleep at night, hours spent studying, and GPA from the previous semester.

Tool two: the perceived stress scale (PSS)

It was initially created by Sheu et al. (1997) to gauge the level and nature of stress perceived by nursing students attending Taiwanese universities [ 20 ]. It comprises 29 items rated on a 5-point Likert scale, where (0 = never, 1 = rarely, 2 = sometimes, 3 = reasonably often, and 4 = very often), with a total score ranging from 0 to 116. The cut-off points of levels of perceived stress scale according to score percentage were low < 33.33%, moderate 33.33–66.66%, and high more than 66.66%. Higher scores indicate higher stress levels. The items are categorized into six subscales reflecting different sources of stress. The first subscale assesses “stress stemming from lack of professional knowledge and skills” and includes 3 items. The second subscale evaluates “stress from caring for patients” with 8 items. The third subscale measures “stress from assignments and workload” with 5 items. The fourth subscale focuses on “stress from interactions with teachers and nursing staff” with 6 items. The fifth subscale gauges “stress from the clinical environment” with 3 items. The sixth subscale addresses “stress from peers and daily life” with 4 items. El-Ashry et al. (2022) reported an excellent internal consistency reliability of 0.83 [ 21 ]. Two bilingual translators translated the English version of the scale into Arabic and then back-translated it into English by two other independent translators to verify its accuracy. The suitability of the translated version was confirmed through a confirmatory factor analysis (CFA), which yielded goodness-of-fit indices such as a comparative fit index (CFI) of 0.712, a Tucker-Lewis index (TLI) of 0.812, and a root mean square error of approximation (RMSEA) of 0.100.

Tool three: revised study process questionnaire (R-SPQ-2 F)

It was developed by Biggs et al. (2001). It examines deep and surface learning approaches using only 20 questions; each subscale contains 10 questions [ 22 ]. On a 5-point Likert scale ranging from 0 (never or only rarely true of me) to 4 (always or almost always accurate of me). The total score ranged from 0 to 80, with a higher score reflecting more deep or surface learning approaches. The cut-off points of levels of revised study process questionnaire according to score percentage were low < 33%, moderate 33–66%, and high more than 66%. Biggs et al. (2001) found that Cronbach alpha value was 0.73 for deep learning approach and 0.64 for the surface learning approach, which was considered acceptable. Two translators fluent in English and Arabic initially translated a scale from English to Arabic. To ensure the accuracy of the translation, they translated it back into English. The translated version’s appropriateness was evaluated using a confirmatory factor analysis (CFA). The CFA produced several goodness-of-fit indices, including a Comparative Fit Index (CFI) of 0.790, a Tucker-Lewis Index (TLI) of 0.912, and a Root Mean Square Error of Approximation (RMSEA) of 0.100. Comparative Fit Index (CFI) of 0.790, a Tucker-Lewis Index (TLI) of 0.912, and a Root Mean Square Error of Approximation (RMSEA) of 0.100.

Ethical considerations

The Alexandria University College of Nursing’s Research Ethics Committee provided ethical permission before the study’s implementation. Furthermore, pertinent authorities acquired ethical approval at participating nursing institutions. The vice deans of the participating institutions provided written informed consent attesting to institutional support and authority. By giving written informed consent, participants confirmed they were taking part voluntarily. Strict protocols were followed to protect participants’ privacy during the whole investigation. The obtained personal data was kept private and available only to the study team. Ensuring participants’ privacy and anonymity was of utmost importance.

Tools validity

The researchers created tool one after reviewing pertinent literature. Two bilingual translators independently translated the English version into Arabic to evaluate the applicability of the academic stress and learning approach tools for Arabic-speaking populations. To assure accuracy, two additional impartial translators back-translated the translation into English. They were also assessed by a five-person jury of professionals from the education and psychiatric nursing departments. The scales were found to have sufficiently evaluated the intended structures by the jury.

Pilot study

A preliminary investigation involved 100 nursing student applicants, distinct from the final sample, to gauge the efficacy, clarity, and potential obstacles in utilizing the research instruments. The pilot findings indicated that the instruments were accurate, comprehensible, and suitable for the target demographic. Additionally, Cronbach’s Alpha was utilized to further assess the instruments’ reliability, demonstrating internal solid consistency for both the learning approaches and academic stress tools, with values of 0.91 and 0.85, respectively.

Data collection

The researchers convened with each qualified student in a relaxed, unoccupied classroom in their respective college settings. Following a briefing on the study’s objectives, the students filled out the datasheet. The interviews typically lasted 15 to 20 min.

Data analysis

The data collected were analyzed using IBM SPSS software version 26.0. Following data entry, a thorough examination and verification were undertaken to ensure accuracy. The normality of quantitative data distributions was assessed using Kolmogorov-Smirnov tests. Cronbach’s Alpha was employed to evaluate the reliability and internal consistency of the study instruments. Descriptive statistics, including means (M), standard deviations (SD), and frequencies/percentages, were computed to summarize academic stress and learning approaches for categorical data. Student’s t-tests compared scores between two groups for normally distributed variables, while One-way ANOVA compared scores across more than two categories of a categorical variable. Pearson’s correlation coefficient determined the strength and direction of associations between customarily distributed quantitative variables. Hierarchical regression analysis identified the primary independent factors influencing learning approaches. Statistical significance was determined at the 5% (p < 0.05).

Table  1 presents socio-demographic data for a group of 1010 nursing students. The age distribution shows that 38.8% of the students were between 18 and 21 years old, 32.9% were between 21 and 24 years old, and 28.3% were between 24 and 28 years old, with an average age of approximately 22.79. Regarding gender, most of the students were female (77%), while 23% were male. The students were distributed across different educational years, a majority of 34.4% in the second year, followed by 29.4% in the fourth year. The students’ hours spent studying were found to be approximately two-thirds (67%) of the students who studied between 3 and 6 h. Similarly, sleep patterns differ among the students; more than three-quarters (77.3%) of students sleep between 5- to more than 7 h, and only 2.4% sleep less than 2 h per night. Finally, the student’s Grade Point Average (GPA) from the previous semester was also provided. 21% of the students had a GPA between 2 and 2.5, 40.9% had a GPA between 2.5 and 3, and 38.1% had a GPA between 3 and 3.5.

Figure  1 provides the learning approach level among nursing students. In terms of learning approach, most students (55.0%) exhibited a moderate level of deep learning approach, followed by 25.9% with a high level and 19.1% with a low level. The surface learning approach was more prevalent, with 47.8% of students showing a moderate level, 41.7% showing a low level, and only 10.5% exhibiting a high level.

Nursing students? levels of learning approach (N=1010)

Figure  2 provides the types of academic stress levels among nursing students. Among nursing students, various stressors significantly impact their academic experiences. Foremost among these stressors are the pressure and demands associated with academic assignments and workload, with 30.8% of students attributing their high stress levels to these factors. Challenges within the clinical environment are closely behind, contributing significantly to high stress levels among 25.7% of nursing students. Interactions with peers and daily life stressors also weigh heavily on students, ranking third among sources of high stress, with 21.5% of students citing this as a significant factor. Similarly, interaction with teachers and nursing staff closely follow, contributing to high-stress levels for 20.3% of nursing students. While still significant, stress from taking care of patients ranks slightly lower, with 16.7% of students reporting it as a significant factor contributing to their academic stress. At the lowest end of the ranking, but still notable, is stress from a perceived lack of professional knowledge and skills, with 15.9% of students experiencing high stress in this area.

Nursing students? levels of academic stress subtypes (N=1010)

Figure  3 provides the total levels of academic stress among nursing students. The majority of students experienced moderate academic stress (56.3%), followed by those experiencing low academic stress (29.9%), and a minority experienced high academic stress (13.8%).

Nursing students? levels of total academic stress (N=1010)

Table  2 displays the correlation between academic stress subscales and deep and surface learning approaches among 1010 nursing students. All stress subscales exhibited a negative correlation regarding the deep learning approach, indicating that the inclination toward deep learning decreases with increasing stress levels. The most significant negative correlation was observed with stress stemming from the lack of professional knowledge and skills (r=-0.392, p < 0.001), followed by stress from the clinical environment (r=-0.109, p = 0.001), stress from assignments and workload (r=-0.103, p = 0.001), stress from peers and daily life (r=-0.095, p = 0.002), and stress from patient care responsibilities (r=-0.093, p = 0.003). The weakest negative correlation was found with stress from interactions with teachers and nursing staff (r=-0.083, p = 0.009). Conversely, concerning the surface learning approach, all stress subscales displayed a positive correlation, indicating that heightened stress levels corresponded with an increased tendency toward superficial learning. The most substantial positive correlation was observed with stress related to the lack of professional knowledge and skills (r = 0.365, p < 0.001), followed by stress from patient care responsibilities (r = 0.334, p < 0.001), overall stress (r = 0.355, p < 0.001), stress from interactions with teachers and nursing staff (r = 0.262, p < 0.001), stress from assignments and workload (r = 0.262, p < 0.001), and stress from the clinical environment (r = 0.254, p < 0.001). The weakest positive correlation was noted with stress stemming from peers and daily life (r = 0.186, p < 0.001).

Table  3 outlines the association between the socio-demographic characteristics of nursing students and their deep and surface learning approaches. Concerning age, statistically significant differences were observed in deep and surface learning approaches (F = 3.661, p = 0.003 and F = 7.983, p < 0.001, respectively). Gender also demonstrated significant differences in deep and surface learning approaches (t = 3.290, p = 0.001 and t = 8.638, p < 0.001, respectively). Female students exhibited higher scores in the deep learning approach (31.59 ± 8.28) compared to male students (29.59 ± 7.73), while male students had higher scores in the surface learning approach (29.97 ± 7.36) compared to female students (24.90 ± 7.97). Educational level exhibited statistically significant differences in deep and surface learning approaches (F = 5.599, p = 0.001 and F = 17.284, p < 0.001, respectively). Both deep and surface learning approach scores increased with higher educational levels. The duration of study hours demonstrated significant differences only in the surface learning approach (F = 3.550, p = 0.014), with scores increasing as study hours increased. However, no significant difference was observed in the deep learning approach (F = 0.861, p = 0.461). Hours of sleep per night and GPA from the previous semester did not exhibit statistically significant differences in deep or surface learning approaches.

Table  4 presents a multivariate linear regression analysis examining the factors influencing the learning approach among 1110 nursing students. The deep learning approach was positively influenced by age, gender (being female), educational year level, and stress from teachers and nursing staff, as indicated by their positive coefficients and significant p-values (p < 0.05). However, it was negatively influenced by stress from a lack of professional knowledge and skills. The other factors do not significantly influence the deep learning approach. On the other hand, the surface learning approach was positively influenced by gender (being female), educational year level, stress from lack of professional knowledge and skills, stress from assignments and workload, and stress from taking care of patients, as indicated by their positive coefficients and significant p-values (p < 0.05). However, it was negatively influenced by gender (being male). The other factors do not significantly influence the surface learning approach. The adjusted R-squared values indicated that the variables in the model explain 17.8% of the variance in the deep learning approach and 25.5% in the surface learning approach. Both models were statistically significant (p < 0.001).

Nursing students’ academic stress and learning approaches are essential to planning for effective and efficient learning. Nursing education also aims to develop knowledgeable and competent students with problem-solving and critical-thinking skills.

The study’s findings highlight the significant presence of stress among nursing students, with a majority experiencing moderate to severe levels of academic stress. This aligns with previous research indicating that academic stress is prevalent among nursing students. For instance, Zheng et al. (2022) observed moderated stress levels in nursing students during clinical placements [ 23 ], while El-Ashry et al. (2022) found that nearly all first-year nursing students in Egypt experienced severe academic stress [ 21 ]. Conversely, Ali and El-Sherbini (2018) reported that over three-quarters of nursing students faced high academic stress. The complexity of the nursing program likely contributes to these stress levels [ 24 ].

The current study revealed that nursing students identified the highest sources of academic stress as workload from assignments and the stress of caring for patients. This aligns with Banu et al.‘s (2015) findings, where academic demands, assignments, examinations, high workload, and combining clinical work with patient interaction were cited as everyday stressors [ 25 ]. Additionally, Anaman-Torgbor et al. (2021) identified lectures, assignments, and examinations as predictors of academic stress through logistic regression analysis. These stressors may stem from nursing programs emphasizing the development of highly qualified graduates who acquire knowledge, values, and skills through classroom and clinical experiences [ 26 ].

The results regarding learning approaches indicate that most nursing students predominantly employed the deep learning approach. Despite acknowledging a surface learning approach among the participants in the present study, the prevalence of deep learning was higher. This inclination toward the deep learning approach is anticipated in nursing students due to their engagement with advanced courses, requiring retention, integration, and transfer of information at elevated levels. The deep learning approach correlates with a gratifying learning experience and contributes to higher academic achievements [ 3 ]. Moreover, the nursing program’s emphasis on active learning strategies fosters critical thinking, problem-solving, and decision-making skills. These findings align with Mahmoud et al.‘s (2019) study, reporting a significant presence (83.31%) of the deep learning approach among undergraduate nursing students at King Khalid University’s Faculty of Nursing [ 27 ]. Additionally, Mohamed &Morsi (2019) found that most nursing students at Benha University’s Faculty of Nursing embraced the deep learning approach (65.4%) compared to the surface learning approach [ 28 ].

The study observed a negative correlation between the deep learning approach and the overall mean stress score, contrasting with a positive correlation between surface learning approaches and overall stress levels. Elevated academic stress levels may diminish motivation and engagement in the learning process, potentially leading students to feel overwhelmed, disinterested, or burned out, prompting a shift toward a surface learning approach. This finding resonates with previous research indicating that nursing students who actively seek positive academic support strategies during academic stress have better prospects for success than those who do not [ 29 ]. Nebhinani et al. (2020) identified interface concerns and academic workload as significant stress-related factors. Notably, only an interest in nursing demonstrated a significant association with stress levels, with participants interested in nursing primarily employing adaptive coping strategies compared to non-interested students.

The current research reveals a statistically significant inverse relationship between different dimensions of academic stress and adopting the deep learning approach. The most substantial negative correlation was observed with stress arising from a lack of professional knowledge and skills, succeeded by stress associated with the clinical environment, assignments, and workload. Nursing students encounter diverse stressors, including delivering patient care, handling assignments and workloads, navigating challenging interactions with staff and faculty, perceived inadequacies in clinical proficiency, and facing examinations [ 30 ].

In the current study, the multivariate linear regression analysis reveals that various factors positively influence the deep learning approach, including age, female gender, educational year level, and stress from teachers and nursing staff. In contrast, stress from a lack of professional knowledge and skills exert a negative influence. Conversely, the surface learning approach is positively influenced by female gender, educational year level, stress from lack of professional knowledge and skills, stress from assignments and workload, and stress from taking care of patients, but negatively affected by male gender. The models explain 17.8% and 25.5% of the variance in the deep and surface learning approaches, respectively, and both are statistically significant. These findings underscore the intricate interplay of demographic and stress-related factors in shaping nursing students’ learning approaches. High workloads and patient care responsibilities may compel students to prioritize completing tasks over deep comprehension. This pressure could lead to a surface learning approach as students focus on meeting immediate demands rather than engaging deeply with course material. This observation aligns with the findings of Alsayed et al. (2021), who identified age, gender, and study year as significant factors influencing students’ learning approaches.

Deep learners often demonstrate better self-regulation skills, such as effective time management, goal setting, and seeking support when needed. These skills can help manage academic stress and maintain a balanced learning approach. These are supported by studies that studied the effect of coping strategies on stress levels [ 6 , 31 , 32 ]. On the contrary, Pacheco-Castillo et al. study (2021) found a strong significant relationship between academic stressors and students’ level of performance. That study also proved that the more academic stress a student faces, the lower their academic achievement.

Strengths and limitations of the study

This study has lots of advantages. It provides insightful information about the educational experiences of Egyptian nursing students, a demographic that has yet to receive much research. The study’s limited generalizability to other people or nations stems from its concentration on this particular group. This might be addressed in future studies by using a more varied sample. Another drawback is the dependence on self-reported metrics, which may contain biases and mistakes. Although the cross-sectional design offers a moment-in-time view of the problem, it cannot determine causation or evaluate changes over time. To address this, longitudinal research may be carried out.

Notwithstanding these drawbacks, the study substantially contributes to the expanding knowledge of academic stress and nursing students’ learning styles. Additional research is needed to determine teaching strategies that improve deep-learning approaches among nursing students. A qualitative study is required to analyze learning approaches and factors that may influence nursing students’ selection of learning approaches.

According to the present study’s findings, nursing students encounter considerable academic stress, primarily stemming from heavy assignments and workload, as well as interactions with teachers and nursing staff. Additionally, it was observed that students who experience lower levels of academic stress typically adopt a deep learning approach, whereas those facing higher stress levels tend to resort to a surface learning approach. Demographic factors such as age, gender, and educational level influence nursing students’ choice of learning approach. Specifically, female students are more inclined towards deep learning, whereas male students prefer surface learning. Moreover, deep and surface learning approach scores show an upward trend with increasing educational levels and study hours. Academic stress emerges as a significant determinant shaping the adoption of learning approaches among nursing students.

Implications in nursing practice

Nursing programs should consider integrating stress management techniques into their curriculum. Providing students with resources and skills to cope with academic stress can improve their well-being and academic performance. Educators can incorporate teaching strategies that promote deep learning approaches, such as problem-based learning, critical thinking exercises, and active learning methods. These approaches help students engage more deeply with course material and reduce reliance on surface learning techniques. Recognizing the gender differences in learning approaches, nursing programs can offer gender-specific support services and resources. For example, providing targeted workshops or counseling services that address male and female nursing students’ unique stressors and learning needs. Implementing mentorship programs and peer support groups can create a supportive environment where students can share experiences, seek advice, and receive encouragement from their peers and faculty members. Encouraging students to reflect on their learning processes and identify effective study strategies can help them develop metacognitive skills and become more self-directed learners. Faculty members can facilitate this process by incorporating reflective exercises into the curriculum. Nursing faculty and staff should receive training on recognizing signs of academic stress among students and providing appropriate support and resources. Additionally, professional development opportunities can help educators stay updated on evidence-based teaching strategies and practical interventions for addressing student stress.

Data availability

The datasets generated and/or analysed during the current study are not publicly available due to restrictions imposed by the institutional review board to protect participant confidentiality, but are available from the corresponding author on reasonable request.

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Acknowledgements

Our sincere thanks go to all the nursing students in the study. We also want to thank Dr/ Rasha Badry for their statistical analysis help and contribution to this study.

The research was not funded by public, commercial, or non-profit organizations.

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Ayman M. El-Ashry & Rawhia S. Dogham: conceptualization, preparation, and data collection; methodology; investigation; formal analysis; data analysis; writing-original draft; writing-manuscript; and editing. Heba F. Mansy Ali & Asmaa S. Ghaly: conceptualization, preparation, methodology, investigation, writing-original draft, writing-review, and editing. Nermine M. Elcokany & Mohamed M. Seweid: Methodology, investigation, formal analysis, data collection, writing-manuscript & editing. All authors reviewed the manuscript and accept for publication.

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Dogham, R.S., Ali, H.F.M., Ghaly, A.S. et al. Deciphering the influence: academic stress and its role in shaping learning approaches among nursing students: a cross-sectional study. BMC Nurs 23 , 249 (2024). https://doi.org/10.1186/s12912-024-01885-1

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Predicting stress in first-year college students using sleep data from wearable devices

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected] ; [email protected]

Affiliations Gund Institute for Environment, University of Vermont, Burlington, Vermont, United States of America, Department of Mathematics & Statistics, University of Vermont, Burlington, Vermont, United States of America, Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America

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

Affiliations Department of Mathematics & Statistics, University of Vermont, Burlington, Vermont, United States of America, Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America

Roles Project administration

Affiliation Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America

Roles Funding acquisition, Writing – review & editing

Roles Conceptualization, Writing – review & editing

Affiliations Department of Social Science and Health Policy, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America, Center for Remote Patient and Participant Monitoring, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America

Affiliations Center for Remote Patient and Participant Monitoring, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America, Department of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America

Affiliations Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America, Department of Psychological Science, University of Vermont, Burlington, Vermont, United States of America

Affiliations Gund Institute for Environment, University of Vermont, Burlington, Vermont, United States of America, Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, Vermont, United States of America

Roles Conceptualization, Funding acquisition, Writing – review & editing

Affiliations Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America, Department of Computer Science, University of Vermont, Burlington, Vermont, United States of America

Roles Conceptualization, Funding acquisition, Supervision, Writing – review & editing

• Laura S. P. Bloomfield, 
• Mikaela I. Fudolig, 
• Julia Kim, 
• Jordan Llorin, 
• Juniper L. Lovato, 
• Ellen W. McGinnis, 
• Ryan S. McGinnis, 
• Matt Price, 
• Taylor H. Ricketts, 

• Published: April 11, 2024
• https://doi.org/10.1371/journal.pdig.0000473
• Peer Review
• Reader Comments

Consumer wearables have been successful at measuring sleep and may be useful in predicting changes in mental health measures such as stress. A key challenge remains in quantifying the relationship between sleep measures associated with physiologic stress and a user’s experience of stress. Students from a public university enrolled in the Lived Experiences Measured Using Rings Study (LEMURS) provided continuous biometric data and answered weekly surveys during their first semester of college between October-December 2022. We analyzed weekly associations between estimated sleep measures and perceived stress for participants (N = 525). Through mixed-effects regression models, we identified consistent associations between perceived stress scores and average nightly total sleep time (TST), resting heart rate (RHR), heart rate variability (HRV), and respiratory rate (ARR). These effects persisted after controlling for gender and week of the semester. Specifically, for every additional hour of TST, the odds of experiencing moderate-to-high stress decreased by 0.617 or by 38.3% ( p <0.01). For each 1 beat per minute increase in RHR, the odds of experiencing moderate-to-high stress increased by 1.036 or by 3.6% ( p <0.01). For each 1 millisecond increase in HRV, the odds of experiencing moderate-to-high stress decreased by 0.988 or by 1.2% ( p <0.05). For each additional breath per minute increase in ARR, the odds of experiencing moderate-to-high stress increased by 1.230 or by 23.0% ( p <0.01). Consistent with previous research, participants who did not identify as male (i.e., female, nonbinary, and transgender participants) had significantly higher self-reported stress throughout the study. The week of the semester was also a significant predictor of stress. Sleep data from wearable devices may help us understand and to better predict stress, a strong signal of the ongoing mental health epidemic among college students.

Author summary

College students are at high-risk for mental-health related morbidity and mortality. Determining which objective sleep measures are associated with stress provides an opportunity to identify who is at risk and intervene in real time. We enrolled a large cohort of first-year college students to assess the relationship between self-reported stress and sleep estimates from wearable devices. We show that nightly averages of total sleep time, resting heart rate, heart rate variability, and respiratory rate are significantly associated with perceived stress during the first semester of college, controlling for gender and week of the semester. These findings establish the potential importance of physiologic estimates from wearable devices to predict stress in first-year college students.

Citation: Bloomfield LSP, Fudolig MI, Kim J, Llorin J, Lovato JL, McGinnis EW, et al. (2024) Predicting stress in first-year college students using sleep data from wearable devices. PLOS Digit Health 3(4): e0000473. https://doi.org/10.1371/journal.pdig.0000473

Editor: Raquel Simões de Almeida, Polytechnic Institute of Porto: Instituto Politecnico do Porto, PORTUGAL

Received: July 16, 2023; Accepted: February 16, 2024; Published: April 11, 2024

Copyright: © 2024 Bloomfield 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: We have provided data as supplementary information and with which results are replicable. We have removed all data that could breach compliance with our ethics board to maintain confidentiality of participants.

Funding: LSP Bloomfield was supported by the Gund Fellowship and partial salary from the Mass Mutual Insurance Wellness Initiative (Grant # FP2860). JK, JL, and KS salaries are funded by the Mass Mutual Insurance Wellness Initiative (Grant # FP2860). EWM was supported by the U.S. National Institute of Health under Grant MH123031. This project has been funded as part of the Lived Experience Measured Using Rings Study (LEMURS) through the Mass Mutual Insurance Wellness Initiative (Grant # FP2860). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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

Introduction

Chronic stress has been linked to behavioral changes and adverse health outcomes [ 1 – 4 ]. Recent work has sought to connect measures of sleep with markers of mental health, including stress [ 5 , 6 ]. Specifically, elevated stress affects sleep quality and quantity [ 7 – 9 ]. The transition to college is considered a stressful life transition for many [ 10 ]. Coincident with the onset of common mental health disorders, such as anxiety and depression, college is a period marked by insufficient sleep and irregular sleep patterns [ 11 ]. A recent multi-university study found that more than 60% of college students met the criteria for poor sleep and mental health symptoms were associated with decreased sleep quality [ 12 ]. There is a growing literature showing that sleep is an important predictor for success in college [ 13 , 14 ], daily measures of mental health [ 15 , 16 ], and health outcomes later in life [ 17 , 18 ].

However, the relationship between stress and sleep responses does not follow a uniform dose-response due to between and within individual differences over time [ 19 ]. The chronicity of stressors and individual coping behaviors also influence the impact of stress on sleep [ 20 – 22 ]. Additionally, demographic, and psychological differences, including mental health diagnosis and exposure to adverse life events in childhood influence the magnitude of the impact of stress on sleep measures, particularly during transitional periods [ 23 – 25 ]. Previous evidence for the relationship between stress and sleep often lacks information on previous psychological history, are carried out in laboratory settings, are based on self-reported sleep data or are small sample sizes [ 26 , 27 ]. Absent experimental protocols, repeated measures of sleep and stress across a large population are needed to observe sufficient variation within and between individuals to assess whether sleep measures can be used to infer changes in mental health measures.

The widespread use of consumer-grade wearables makes it possible to rigorously estimate physiological and sleep measures in large-scale studies [ 13 , 28 – 30 ]. These studies have provided insight into the mechanistic and temporal relationships between sleep and stress. Previous work using machine learning on wearable sleep and mental health data has shown that sleep abnormalities are associated with the probability of mental illness onset [ 29 ]. Specifically, stress has been linked to reduced total sleep time (TST), increased sleep onset latency (SOL), and lower sleep efficiency [ 21 , 22 , 31 , 32 ]. Physiological indices measured during sleep, such as lower average nightly heart rate variability (HRV) [ 33 – 35 ] increased resting heart rate (RHR) [ 27 ], and variation in average nightly respiratory rate (ARR) [ 36 , 37 ] have also been linked to stressors. Recent work using skin conductance and temperature from wearable sensor data, has shown accuracy in classifying college students as high or low stress [ 30 ].

The Oura ring is a multi-sensor wearable device that has been validated for accurate sleep measurement [ 38 – 40 ]. In a 2021 validation study comparing the Oura ring to polysomnography (PSG), the Oura ring was 94% accurate in detecting sleep and wake periods when using an accelerometer-based model and 96% accurate with the inclusion of circadian features [ 28 ]. The Oura ring uses photoplethysmography (PPG) [ 41 ], which measures arterial pulses, to derive RHR, HRV, and ARR [ 42 ]. Night-time measurements are shown to be the most consistent due to day-time factors that can influence the accuracy of these measurements and introduce noise [ 43 ].

In the present longitudinal study, we investigated whether sleep measures from biometric data taken continuously with an Oura ring could be used to predict subjective measures of stress (PSS) in first-year college students. We hypothesized that reduced TST, higher RHR, lower HRV, and greater variation in ARR would be associated with higher PSS. We selected this critical window for evaluating the relationship because it is a major life transition associated with heightened stress and during which sleep behaviors change for many young adults. Given the health implications of prolonged stress and sleep disruptions, utilizing continuous biometric data to predict periods of heightened stress in young adults offers the potential for rapid assessment and targeted, preventative interventions.

Materials and methods

All participants were enrolled during the fall semester of their first year of university. Participants were recruited during orientation, through student mailing lists, and in-person events. After expressing interest in the study, participants were asked to complete basic demographic questionnaires, which were used to screen for eligibility. Inclusion criteria included being a first-year student between the ages of 18–24 years, being full-time (enrolled in at least 12 credits), and owning a smartphone. Interested participants who did not meet these criteria were excluded and not enrolled. After eligibility screening, participants were invited to attend a lecture which provided in-depth information about the study. Participants were required to complete a comprehension assessment with completely correct answers before being able to provide written informed consent through REDCap, a HIPPA-compliant online application. This study protocol was reviewed and approved by the University of Vermont Institutional Review Board (Protocol #2126).

After enrollment, each participant was assigned a unique study identifier. Participants then attended an in-person event to complete sizing for their Oura ring. The Oura ring automatically collected body response data during sleep and daily activity. That data was uploaded to Oura Cloud via the Oura mobile app and was accessed using the Oura mobile app or Oura on the web. When participants were enrolled in Oura Teams, all identifying information was removed and each participant was manually coded with their unique study identifier. Oura Teams data was only accessed by those approved by the UVM IRB. Additionally, Oura uses administrative, organizational, technical, and physical safeguards to protect the personal data that was collected and processed.

After receiving their Oura ring, participants were asked to complete a baseline survey and fill out weekly surveys. There were six additional weekly surveys that were distributed to participants. Responses to questions from electronic questionnaires were stored in REDCap. All data collected by this study was stored on a secure virtual machine on a drive that had restricted access to those who are approved by the UVM IRB.

Weekly surveys

Stress measure..

The PSS-10 is a ten-item measurement tool that assesses the degree to which individuals perceive of situations in their lives as uncontrollable, unpredictable, and overloaded relative to their subjective coping abilities (e.g., how often could a person not cope with activities and events in their life) [ 44 ]. Items were rated on a 5-point Likert-type scale (0 = never to 4 = very often) ( S1 Text ). Six items were considered the negativity subscale and four items related to the positivity subscale. The PSS-10 has internal consistency, with α of 0.91, and has also been widely validated across cultures [ 45 ]. The PSS-10 is not a diagnostic instrument, and there are not any clinically established cut-offs. However, it has been used as a screening tool, and scores above 14 have been considered a moderate-to-high level of stress [ 46 ]. Consistent with previous studies, we converted this score to a binary outcome variable at the threshold of 14 for moderate-to-high stress.

Sleep measures.

To quantify sleep, the Oura ring uses a combination of accelerometer data, heart rate, heart rate variability, and pulse wave amplitude variability with machine learning models to calculate sleep duration, including those for deep sleep (N3), light sleep (N1+N2), rapid-eye-movement sleep (REM), and proportion of time a user is in bed awake [ 28 ]. The Oura ring has a high association with PSG for measuring TST, SOL, and wake after sleep onset (WASO) [ 35 ].

For each night, we used information recorded by the Oura ring for the sleep period with the longest duration (i.e., naps were not included). The measures from the Oura ring that we used in our models are given in the Supporting Information ( S1 Table ). In addition to the raw values, we also computed mean-adjusted values for participants. For a given individual, the adjusted measurements are x dev, k = x k − mean({ x 1 , x 2 , …, x n }) where k = 1, 2, …, n is the k th night measurement of measure x .

To compare the weekly survey measures to the daily Oura sleep data, we aggregated the daily sleep measurements at a weekly level. For every user, we considered weeks where there were at least three days where sleep data was recorded. For each week, we computed the following statistics for the values in that week: minimum, the 5 th , 25 th , 50 th (mean), 75 th , 95 th percentiles, and the maximum. By using these summary statistics as inputs to our model, we input a reduced representation of the sleep measures distribution for each participant for each week. We performed the same aggregation procedure on the adjusted daily values to adjust for within-individual variation.

Compliance.

We observed a high level of compliance from participants who were eligible and enrolled in the study (N = 603) ( S1 Fig ). We filtered out participants who had less than three surveys to maintain integrity of the repeated measures analysis. 92.4% (557/603) of participants who enrolled in the study, completed at least three surveys. From the raw Oura data, 94.5% of user-week combinations (3530 out of 3735) had three or more Oura data points per week which corresponds to 98.7% (595/603) of enrolled participants with any days of Oura data. When weekly surveys were matched to weeks of Oura data with at least three nights of sleep data, 94.3% (525/557) of participants with at least three surveys remained in the sample ( S2 and S3 Tables).

Statistical analysis

Mixed-effects models..

We used longitudinal mixed-effects models, also known as multilevel models, hierarchical linear models, or random effects models, due to the nested structure of panel data where repeated measures were taken [ 47 ]. These models handle missing and unbalanced data more effectively than traditional regression methods and can account for within-individual and between-individual variability [ 48 ]. The fixed effects represent the average relationship between time-invariant traits and stress across the entire population [ 49 ]. We explored multiple model forms, but our final model was a mixed-effects linear regression model with random and fixed effects for week of the semester to account for differences in stress associated with the structure of the school year. The model included gender, week, and sleep measures as fixed effects which were not highly correlated ( S4 Table ). Participant identifier and week were included as random effects. This approach allowed us to control for within-subject variability across the weeks of the study, providing an estimate of the effect of these predictors on PSS. We used these models to predict PSS as a continuous and binary outcome measure. We also calculated weekly fluctuations in PSS with two additional outcome measures: 1) Change in PSS from previous measure (Δ PSS) and 2) Deviation of PSS from each participant mean (σ PSS). The equation of our model can be found in the Supplemental Information ( S5 Table ). We also explored mixed-effects models with nonlinear components to investigate Oura sleep measures as predictors of PSS ( S2 Text ).

Our data included weekly surveys and biometrics from a first-year college cohort (N = 525) ( Table 1 ). 87% (525/603) of enrolled participants who had completed at least three weekly surveys had Oura ring data for at least three nights in the same week as their completed survey ( N = 3,112). First-year college students slept, on average, 7.41 hours per night ( SD = 0.83 hours). Participants had a mean individual variance of 5.15 hours of TST on weekdays during the study ( SD = 1.49 hours) and an average variance of 2.72 hours (SD = 1.40 hours) in a single week ( Table 1 ). Participants had an average RHR of 62.75 bpm ( SD = 8.64 bpm). At the participant level, RHR varied by 18.90 bpm ( SD = 8.38 bpm) over the course of the study and 7.89 bpm within a given week ( SD = 5.62 bpm). Participants had an average HRV of 68.24 ms ( SD = 33.09 ms) during the study. Participants had a mean individual variance in HRV of 57.95 ms ( SD = 32.36 ms) over the course of the study and an average variance of 26.84 ms ( SD = 20.64 ms) per week. Participants had a mean individual variance of ARR of 2.42 breaths per minute ( SD = 1.03 breaths per minute) over the course of the study and an average variance of 1.02 breaths per minute ( SD = 0.65 breaths per minute) per week ( Table 1 ).

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Proportions, averages, and standard deviations of sleep measures with perceived stress scores (PSS).

https://doi.org/10.1371/journal.pdig.0000473.t001

Weekly surveys revealed that the average Perceived Stress Score (PSS) for participants was 15.85 ( SD = 7.33). 64.14% (1,996/3,112) of weekly survey responses indicated moderate-to-high stress (PSS> = 14). As far as fluctuations in stress, the average change in PSS between week was -0.48 ( SD = 5.90) and the participant variance over the study was 12.07 ( SD = 7.88). We also calculated the average PSS per participant and calculated their deviation from their average from week to week. On average, participants deviated from their average PSS by an average -1.15e-08 ( SD = 4.11), or on average by 0 ( Table 1 ). Participants who did not identify as male (i.e., female, nonbinary, and transgender students) had significantly higher PSS than male participants ( S6 Table ).

We calculated the intraclass correlation coefficients for TST, RHR, HRV, and ARR to assess the portion of variation attributable to within-subject variability. TST was the only predictor with a substantial portion of its variation attributable to within-subject variation ( S7 Table ). Conversely, more than 80% of the variation in RHR, HRV, and ARR was attributable to differences between participant measures rather than within participant measures. When added as predictors, these sleep measures did not have significant contributions to total variance in PSS attributable to between-individual differences ( S7 Table ). However, in univariate regression models, TST, RHR, HRV, and ARR were significant explanatory variables for PSS ( S6 Table ).

A relationship between PSS and sleep estimates (TST, RHR, HRV, and ARR) was observed across covariate-adjusted mixed-effects regression models for PSS as both a continuous and binary outcome (Tables 2 and 3 ). In modeling PSS as a continuous outcome, TST, RHR, HRV, and ARR were significant predictors), controlling for gender and week of the semester ( Table 2 ). In model 1b, an additional hour of sleep was associated with a 0.877 decrease in PSS ( p <0.01). In model 1c, an increase of 1 bpm in RHR was associated with a 0.055 increase in PSS ( p <0.01). In model 1d, an increase of 1 ms in HRV was associated with a 0.012 decrease in PSS ( p <0.05). In model 1e, an increase of 1 breath per minute in ARR was associated with a 0.270 increase in PSS ( p <0.05). In addition to being significant predictors of PSS, the addition of TST, RHR, HRV, and ARR improved the model fit. The addition of TST having the greatest improvement in model fit ( Table 2 ).

In this model the fixed effects are gender, week, and sleep measures TST, RHR, HRV, and ARR. The random effects are participant and week of study. The likelihood ratio (LR) compares the model to the previous model fit.

https://doi.org/10.1371/journal.pdig.0000473.t002

We also present the results from models with PSS as a binary outcome, moderate-to-high stress (PSS> = 14), due to its clinical relevance. In modeling stress as a binary outcome, TST, RHR, HRV, and ARR were significant predictors of participants reporting symptoms of moderate-to-high stress, controlling for gender and week of the semester ( Table 3 ). For every additional hour of sleep (model 2b), the odds of reporting moderate-to-high symptoms of stress decreased by 0.617 ( p <0.01). For every 1 bpm increase in RHR (model 2c), the odds of reporting symptoms of moderate-to-high stress increased by 1.036 ( p <0.05). For every 1 ms increase in HRV (model 2d), the odds of reporting symptoms of moderate-to-high of stressed decreased by 0.988 ( p <0.05). For each additional breath per minute (model 2e), the odds of reporting symptoms of moderate-to-high stress increased by 1.230 ( p <0.01).

In this model the fixed effects are gender, week, and mean sleep measures TST, RHR, HRV, and ARR. The random effects are participant and week of study. The likelihood ratio (LR) compares the model to the previous model fit.

https://doi.org/10.1371/journal.pdig.0000473.t003

Lastly, we investigated the association between changes in stress with changes in sleep estimates ( Table 4 ). There was a significant relationship between average TST and change in participant PSS between weeks of the study ( p <0.01). There was also a significant relationship between deviation in TST from a participant’s study average and change in PSS between weeks ( p <0.01), deviation in RHR from a participant’s study average and change in PSS ( p <0.01), and deviation in HRV from a participant’s study average and change in PSS ( p <0.01).

In this model the fixed effects are gender, week, and the sleep measures TST, RHR, HRV, and ARR. The random effects are participant and week of study. The likelihood ratio (LR) compares the model to the previous model fit.

https://doi.org/10.1371/journal.pdig.0000473.t004

Additionally, there was a significant relationship between TST and deviation in PSS from a participant’s study mean ( p <0.01) as well as between deviation in TST from a participant’s study average and deviation in PSS from a participant’s study mean ( p <0.01). There were no significant associations between weekly variance in sleep measures and change in PSS nor between weekly variance in sleep measures and deviation in PSS.

To check the robustness of our results from mixed-effects models, we also explored mixed effects models that use gradient-boosted trees to assess dominant predictors of stress in our sample ( S2 Text ). Results were consistent with the results of our mixed-effects multilevel regression models ( S8 Table ).

Young adults are at risk for concerning mental health symptoms [ 50 , 51 ], especially those undergoing major life transitions like the start of college [ 52 ]. Mounting evidence has shown that the mental health of college students was severely affected by the COVID-19 pandemic [ 53 – 55 ], and that the rise in mental health burden has remained high in this population [ 56 ]. There has been much discussion about how to address the growing need for mental health support, particularly on college campuses [ 57 ]. Researchers and health professionals have long suspected that stress plays a role in sleep, yet prior work has primarily relied upon cross-sectional, retrospective, and self-report assessments of sleep to assess the relationship between these measures. Subjective accounts of sleep duration are not reliable or objective measures of sleep duration; single time point assessment is also vulnerable to bias and has validity concerns.

Wearable devices estimating sleep have been suggested as a potential mechanism for identifying changes in mental health status in college students and prompting interventions [ 30 ] because they provide a more consistent picture of vital sign measures that are linked to health [ 58 ]. Recent work has shown that sleep abnormalities may be useful for predicting changes in mental health [ 29 ], however, many epidemiologic studies using biometric wearables have been limited by small sample sizes or short durations. To address these limitations, we enrolled a large cohort of college students and collected surveys and continuous biometric monitoring during the first semester of college. In our cohort, 64% of perceived stress scores were above the threshold for moderate-to-high stress. The average TST for the survey period was 7.41 hours ( SD = 0.83 hours); however, the average minimum night of sleep for our cohort was 5.75 hours ( SD = 1.14 hours) which is well below the recommended guidelines for young adults. Furthermore, 32% of our sample slept, on average, less than 7 hours. While these distributions of sleep may seem insufficient, they are higher than other comparable collegiate samples pointing to the widespread disrupted sleep for undergraduate students.

We show that estimates of sleep measures from a consumer wearable in first-year college students were significantly associated with weekly PSS, a marker of mental health and well-being. Decreased TST, increased RHR, decreased HRV, and increased ARR were significantly associated with higher PSS and the likelihood of reporting symptoms consistent with a moderate-to-high level of stress (Tables 2 and 3 ). Gender explained some of the variance in stress measures. As expected from previous studies [ 59 , 60 ], participants who did not identify as male (i.e., female, nonbinary, and transgender students) had significantly higher levels of perceived stress than male participants ( S2 Table ). The inclusion of sleep measures as predictors in mixed-effects models significantly improved model fit and the explanatory value of our models (Tables 2 and 3 ). In our models, TST had the most substantial improvement in model fit measured by model fit estimates (i.e., AIC, BIC, and likelihood ratio) (Tables 2 and 3 ). These associations provide evidence that there is a relationship between changes in stress and changes in sleep measures, particularly TST ( Table 4 ). However, the practical significance of these relationships is important to note.

Our study adds to the growing literature utilizing sleep and cardiorespiratory markers to identify changes in health [ 36 , 61 , 62 ]. Mechanistically there is a relationship between stress and decreased parasympathetic regulation [ 63 ] which modulates the neural pathways affecting heart rate, heart rate variability, and respiratory rate [ 64 ]. When an individual is under physical or mental stress, parasympathetic activity decreases and sympathetic activity increases resulting in increased RHR and decreased HRV. HRV has been linked to sleep stages and higher night-time HRV has been linked to better sleep quality [ 63 , 65 ]. Importantly, cardiovascular mortality has been associated with low HRV [ 43 ]. Changes in these cardiorespiratory measures have been detected in college students following stressful exposures [ 36 ].

The inclusion of ARR as a predictor of stress in our study is unique in the literature, where a growing number of studies have pointed to TST, HRV, RHR, and sleep stages as sleep measures that are associated with stress. Stress has also been associated with increased respiratory rate and respiratory variability [ 66 ]. ARR has been referred to as a neglected vital sign due to its importance in health assessment, but relatively minimal focus in the literature [ 67 ]. The stability of nightly ARR within healthy individuals, particularly the low internight variability in ARR [ 68 ], makes it a potentially useful metric for tracking changes in wellness and has been used to assess stress reactivity [ 69 – 71 ]. ARR has gained attention due to its relationship to COVID-19 infection [ 68 ] and increases in 3–5 breaths/min can signal health deterioration [ 72 ]. However, the low variance of this measure and the potential for measurement error exists in our data. In our analysis 93% of the variation in ARR was due to differences between individuals limiting its ( S7 Table ). A large study validating the respiratory estimates from Oura with PSG is needed to further understand this potentially useful measure.

Longer term studies with further investigation of temporal correspondence between stress and sleep measure deviations may provide better understanding of causal relationships as well as how individual factors affect these relationships. Further analysis of the onset of stress, its duration, and the temporal relationship to sleep disturbances may provide greater clarity on whether sleep measures associated with stress can be used to predict stress in this population. During exploratory analyses, we detected significant differences in sleep and stress measures during the Thanksgiving break. Utilizing school breaks as a quasi-experimental study for the influence of reduced academic stressors on sleep is a worthwhile area for future study. To our knowledge, there is no published evidence of large, randomized control trials of long-term behavioral interventions targeting stress in college students with continuous wearable data. These studies could provide more insight into whether reductions in stress are associated with changes in sleep measures over longer time periods. Future research could also evaluate the potential impact of mobile app-based interventions following the detection of sleep disturbances.

There are limitations to the present study. The current study focused on raw sleep measures that could be extracted from the Oura ring’s longest nightly sleep period. It will be important for future studies to evaluate additional sleep variables, such as daytime naps, which have been associated with mental health in college students [ 30 ]. While sleep data was taken nightly, surveys were collected on a weekly basis; aggregation of an individual’s sleep measures by week could have introduced bias. Second, we do not have stress or sleep data before participants moved to college and therefore cannot assess the influence of beginning college on stress and sleep measures and how these health behaviors may have shifted at the start of college. Expanding this window of analysis may identify whether the link between sleep measures and PSS holds prior to the beginning of college and throughout the college experience. Third, our sample was predominantly female, white, and were not first-generation college students ( Table 1 ). Future work would benefit from inclusion of additional cohorts to assess the influence of these traits and applicability of these results to a broader population. Compared to previous studies on first-year college students [ 11 – 13 ], this cohort got more sleep pointing to potential differences in this population from other college-aged groups. Fourth, potential confounders also exist in our data. In our analysis, we did not account for some factors that may influence sleep measures such as psychotropic medications, sleep disorders, physical activity, or the use of substances (e.g., caffeine, marijuana, and alcohol use).

The first year of college is a particularly important period for understanding sleep patterns and stress. As students transition to a time during which they have more autonomy, they establish sleep habits in the context of increased academic pressure, changes in their social milieu, and the development of adult coping behaviors. The present work highlights the potential utility of monitoring sleep, suggesting that these measures may identify within individual changes that are concerning for stress. As the demand for mental health services grows, determining which wearable-derived sleep estimates provide information about well-being and can predict worsening mental health in young adults is an important area of study.

Conclusions

In their first semester of college, students are experiencing a big life change that has been associated with both sleep dysregulation and increased stress. The present work provides support for the use of sleep estimates from wearable devices in the prediction of perceived stress in first-year college students. Over 500 first-year students had an average of 7 hours and 26 minutes of sleep per night and showed elevated perceived stress scores over the course of their fall semester of college. The major strength of the present work is that after considering multiple factors that are well-known to influence stress in young adults, there was a persistent significant relationship between perceived stress and indices of physiologic stress–reduced sleep duration, increased resting heart rate, decreased night-time heart rate variability, and increased night-time average respiratory rate. Findings from the Oura ring suggest that decreased sleep, increased resting heart rate, decreased night-time heart rate variability, and increased night-time respiratory rate are predictive of increased perceived stress and the likelihood of experiencing symptoms consistent with moderate-to-high levels of stress, measured at weekly intervals after accounting for gender and week of the semester. The present findings call for more research on the utility of wearable data to identify which young adults are at greatest risk for elevated stress given the implications for increased morbidity and mortality associated with mental health for this population.

Supporting information

S1 text. stress assessment..

https://doi.org/10.1371/journal.pdig.0000473.s001

S2 Text. Additional Methods: Nonlinear Models.

https://doi.org/10.1371/journal.pdig.0000473.s002

S1 Data. Sleep Measures Data.

https://doi.org/10.1371/journal.pdig.0000473.s003

S1 Fig. Participants with survey and Oura data.

https://doi.org/10.1371/journal.pdig.0000473.s004

S1 Table. Oura Ring measures, descriptions and units.

https://doi.org/10.1371/journal.pdig.0000473.s005

S2 Table. Distributions of outcome variables and sleep measures by dataset inclusion and exclusion criteria for participants with at least 3 nights of Oura data per week.

https://doi.org/10.1371/journal.pdig.0000473.s006

S3 Table. Distributions of outcome variables and sleep measures by dataset inclusion and exclusion criteria for participants with at least 1 night of Oura data per week.

https://doi.org/10.1371/journal.pdig.0000473.s007

S4 Table. Correlation between predictor variables and PSS.

https://doi.org/10.1371/journal.pdig.0000473.s008

S5 Table. Single variable sleep mixed-effects MLR models (N = 3,112) with 525 participants.

Model Y ij =   β 0  +  β 1 X sleep measure ij +  β 2 X weeknum ij  +  u j   +  ε ij .

https://doi.org/10.1371/journal.pdig.0000473.s009

S6 Table. Demographic variables as predictors of PSS.

https://doi.org/10.1371/journal.pdig.0000473.s010

S7 Table. Proportion of variance in outcome and predictor variables attributable to differences between subjects.

https://doi.org/10.1371/journal.pdig.0000473.s011

S8 Table. Nonlinear predictive models in GPBoost for PSS outcome.

https://doi.org/10.1371/journal.pdig.0000473.s012

Acknowledgments

We want to thank MassMutual for supporting our research focused on the health and well-being of college students. This work was made possible by MassMutual under Grant Number FP 2860.

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Stress among higher education students: towards a research agenda

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• Volume 56 , pages 735–746, ( 2008 )

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This article has two primary aims. Firstly, it provides a critical review of previous studies into student stress and identifies several important issues that, as yet, have not been explored. There has been no consideration of the effect of students maturing during their studies on the stress that they experience and how they cope with that stress. Secondly, the article highlights limitations in the past and present literature base, where there has been a concentration on a quantitative approach, and focus on a narrow range of subject groups. There is also a need to undertake longitudinal research to investigate individuals’ stress experiences during the period they study at university. Overall the key assertion here is that thus far research into student stress has not offered a complete account and explanation of students’ stress experiences.

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Robotham, D. Stress among higher education students: towards a research agenda. High Educ 56 , 735–746 (2008). https://doi.org/10.1007/s10734-008-9137-1

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• Improving Stress Resistance in Agricultural Crops The essay suggests that stress-resistant crops are needed to ensure yield stability under stress conditions and to minimize the environmental impacts of crop production.
• Stress Management at the Workplace This article examines the aspects of stress management at the workplace from the point of view of the position of the manager, and considers collective stress.
• Workplace Stress: The Coping Strategies The research will uncover management-applicable strategies for assisting workers who may experience tension in or outside the workplace.
• Parental Stress and Its Effects on Children In the current paper, the author analyses literature dedicated to parental stress and child development and behavior and tests the previously mentioned hypothesis.
• How Greek Mythology Subdued the Stress of Natural Phenomena The ancient Greeks created numerous engaging stories to explain such natural phenomena as volcanic eruptions, floods, and thunderstorms.
• Mindfulness-Based Stress Reduction The purpose of this work is to investigate one of the mindfulness-based interventions, mindfulness-based stress reduction, and evaluate its efficiency.
• Nurses Stress Reduction Strategies This paper is an implementation plan to eliminate or lessen nurse stress and burnout. The proposed solution entails stress reduction strategies.
• Stress and Happiness in Personal Experience The notion of happiness is quite philosophical and sometimes can be complicated yet it refers to a feeling and a state of partial or complete pleasure.
• Impact of Job Stress on Employee Work-Life Balance Postmodern society is anchored on the emphasis on work to achieve a fulfilling life. This review analyses the center of work-life balance.
• Stress Management and Lifestyle Modification The continued strain on the body from strain over time may lead to serious health problems such as high blood pressure, diabetes, and mental disorders like depression and anxiety.
• Factors of Stress Among Young Adults Stress among young adults is caused by numerous factors, including family problems, work-related issues, health concerns, and psychological trauma.
• Stress and Performance in the Sport Constructive stress is necessary for good mental and physical health. This article will explain the positive and negative pre-performance stressors in sports.
• Biopsychosocial Factors of Stress Stress is a biopsychosocial phenomenon, as it affects a person’s physical well-being, emotional stability, and social interactions.
• Motivation, Job Satisfaction, Involvement, Stress Motivating personnel and the assessment of job satisfaction, including the degree of involvement and stress impact, are the essential aspects of leadership practice in the group.
• Correctional Officer Stress: A Phenomenological Study The current study seeks to expand existing knowledge about the stress of correctional officers. An interview was conducted within the qualitative phenomenological research design.
• Correctional Nursing Stress Theory of Adaptation and Resilience Correctional Nursing Stress Theory guides correctional nurses, improve their knowledge about stress, and help them manage stress with the help of adaptation and inner strength.
• Stress Management in the Work Environment Stress has a severe negative effect on the mental and physical health of employees, and the boss should provide an appropriate system of protection.
• Stress in the Military A study conducted by the Careercast.com in 2013 indicated that the military working environment was characterized by numerous stressors.
• Community Based Stress Management Programs and Interventions Organizations with supportive supervisors’ processes are highly productive. Studies with the best results came from organizations that embrace effective leadership principles.
• Article Synthesis: “Stress” by Simon The effect of stress on the body is disturbing and could affect people in many ways. Pronounced stress initiates speedy changes throughout the body.
• Stress: Causes and Possible Consequences This article has attempted to show that even what we consider to be “minor anomalies” or diseases can be the root cause of stress.
• Stress and Burnout Among Nurses This paper presents research on the connection between stress and burnout syndrome among nurses and patient safety. It provides a review of the relevant literature and an analysis of key findings.
• Stress Level and Work in Team The study is focused on determining differences in people’s productivity, affecting stress levels and attitudes toward working in teams.
• The Chronic Psychological Stress It is proven that chronic psychological stress causes diseases like rheumatoid arthritis, coronary heart disease, diabetes, and cancer.
• Stress Factors: Work, Financial, Social Issues The significant causes of stress identified by scholarly studies are problems at work, financial issues, social pressure, and relationship difficulties.
• How Universities Fail to Help Students Deal with Stress Numerous research studies have found out that a certain amount of stress is inevitable when students make a transition from high school to university.
• Health Psychology and Stress: Correlations Health psychology deals with the enhancement of the whole personality identifying and eliminating the biopsychosocial causes that lead to disease.
• Causes and Management of Stress The paper, defines what stress is, looks on the kinds of biological stress. Stress can be defined as failure of body to respond to demand made on it.
• Stress and Coping: Social Support and Social Ties In this paper, the notions of social ties and social support will be defined, and how social support might depend on the cultural background a person has will be discussed.
• Management of Organizational Stress: Positive or Negative? Organizational stress may be positive or negative depending on presenting circumstances and other contextual variables.
• Post-Traumatic Stress Disorder Diagnosis People who work in risky environments have a high propensity of developing PTSD than their counterparts in safer working environments.
• Psychology Issues: Stress Management Skills Stress management is a skill that is required in everyday life, and that is why it is important. People face stress in almost every part of their life.
• Antisocial Personality Disorder and Post-Traumatic Stress Disorder The patient has an antisocial personality disorder and post-traumatic stress disorder owing to the experience of the brutal murder of his mother at a tender age.
• Occupational Stress Management in Healthcare Occupational stress is one of the most widespread problems that employees face at the workplace. This paper discusses occupational stress in healthcare and its management.
• Benefits of Stress Management and Obstacles of Implementation Stress management strategies are a focal point for people working in the health industry. They are among the most exposed to high levels of stress.
• Real-Life Story of Post-traumatic Stress Disease Philips’s case is an actual representation of the manifestation and intervention of PTSD, a piece of evidence the condition is treatable.
• Stress and Time Management The data is supported by Svedberg’s current information that highlights that an individual can lower the level of anxiety when there is a possibility of sound sleep.
• Stress Affecting First-Year Students The first year at the university is the time when students are most vulnerable to academic failure, as well as most likely to experience social, emotional and financial problems.
• Group Dynamics, Managing Conflict, and Managing Stress and Employee Job Satisfaction This paper discusses of whether a high cohesiveness in a group leads to higher group productivity, or not. Analysis of the effect of the quality of decision-making within the group.
• Stress Reduction Programs for Pregnant Women Mental distress during pregnancy is very common, and it might lead to a wide range of negative consequences for women and their children.
• Post-Traumatic Stress Disorder and Life Quality The paper revolves around post-traumatic stress disorder (PTSD), its primary symptoms, consequences, and approaches to treatment aimed at the improvement of patients’ lives.
• Cumulative Career Traumatic Stress: Law Enforcement CCTS is usually observed among officers and characterized by similar to post-traumatic stress disorder’s symptoms resulted in their constant exposure to traumatic events.
• Potential of Eye Movement Desensitization and Reprocessing Therapy in the Treatment of Post Traumatic Stress Disorder The concept of Eye Movement Desensitization and Reprocessing (EMDR) has the potential to support the needs of different PTSD patients.
• Reducing Stress in Filipino Care Workers in Japan The source will help to explain psychological stressors for Filipino caregivers in Japan and possible ways of improving their experiences.
• Post-Traumatic Stress Disorder in a Raped Girl The patient has a strained connection with her cocaine-addicted mother, who has been emotionally and physically abusive to her since she was three years old.
• Organizational Stress Management: Why It Is Important The concept of stress management, which goes side by side with the problem of coping with stress in the workplace, is now becoming more common.
• The Post-Traumatic Stress Disorder: Case Study The post-traumatic stress disorder is a health condition the patient struggles with when having faced a stressful experience that later affects one’s cognitive-behavioral patterns.
• Stress and Emotional Management While the stress management outlined above has been shown to work on reducing stress, they are only guidelines and cannot work positively on everybody.
• Psychology. Stress Management Approaches There are some unhealthy ways of coping with stress such as excessive smoking, overeating, using sleeping pills or marijuana, or any tranquilizers to relax.
• Stress After Leaving Home in Students Most people perceive stress as a negative emotional state, whereas some consider it to be something that happens to us when we are anxious.
• Alertness, Relaxation, and Stress Correlation This essay explores the correlation between high alpha levels in brains and their states of relaxedness and alertness; the development of low alpha levels in stressful conditions.
• Stress on Law Enforcement Officers and Available Programs Police officers are subject to significant amounts of tension and stress, regardless of the nature and size of the agency for which they work.
• Workplace Stress: Impact on Employee Health and Productivity Workplace stress refers to harmful psychological and physical outcomes occurring when job requirements mismatch with workers’ needs, resources, and capacities.
• Stress Management Memo: Creative Arts Interventions Research and analysis of current scientific research and previous practice experience show several strategies for stress control.
• Post-Traumatic Stress Disorder: A Critical Perspective Post-traumatic stress disorder (PTSD) is a relatively common condition affecting individuals who have experienced severe trauma.
• Case Study for Agnes: Post-Traumatic Stress Disorder According to the case scenario, Agnes is most certainly suffering from post-traumatic stress disorder (PTSD). She was traumatized by the previous account of the storm.
• Bullying and Work-Related Stress in the Irish Workplace One of the best analyses of relationships between workplace stress and bullying has been done in the research study called “Bullying and Work-Related Stress in the Irish Workplace.”
• Stress at the Workplace and Strategies of Its Reduction Job stress has become a growing concern among managers and supervisors in organizations. This is because of the adverse effects on both employees and the company.
• Midlife Crisis and Its Effect on Women’s Stress This paper aims to focus on the psychological problem of stress among this section of the population, its effects on women, and how it can be solved.
• Stress in Nursing Practice Stress can be attributed to many factors in the nursing profession, the principal one being extended work schedules. In the medical field, such errors could be fatal.
• Corrections Officers Stress: Causes and Outcomes This paper analyses the effective ways that can be implemented by the administrators for the prevention and treatment of the stress affecting correction officers.
• Coping Strategies in Job Related Stress in Nurses Job-related stress among nurses is an issue that has raised massive concern among contemporary scholars. Nurses are forced to undergo very traumatizing environmental factors.
• Stress, Adaptation, Coping Methods & Strategies In this paper, the types of stress, adaptation, coping methods, and strategies will be discussed to analyze the patient’s case.
• Organizational Problems: Stress and Burnout of Employees Stress and burnout are the major causes of employee-related problems in organizations. Both stress and burnout have serious effects on the productivity of an organization.
• Case Study: Constant Stress The case study analysis depicts Michael’s stress sufferings at work; being a 40 year old experienced airline pilot, the man completely devoted himself to his work.
• Stress and Wellness – Psychology Stress affects the emotional wellness of an individual. People who are under stress find it difficult to relate with other individuals in a normal manner.
• Psychology Issues: Post-Traumatic Stress Disorder Post-Traumatic Stress Disorder is one of the main challenges that people deal with after a traumatizing event. PTSD should be treated as soon as any of the symptoms start to be recognized.
• The Role of Stress Hormones: Physiology The correct care for youngsters from conception onwards guarantees that the child’s brain develops healthily and to its maximum potential.
• Anxiety, Depression, and Post-Traumatic Stress Disorder Currently, many people experience anxiety, depression, and post-traumatic stress disorder that affect their general health.
• Causes and Management of Stress at Work Stress is a condition that arises when an individual’s resources are inadequate to deal with the responsibilities and pressures of the situation.
• Stress Response Plan for Massachusetts Respondent’s stress is one of the unpleasant consequences of emergency events. People who are the first to experience such crises, feel psychological and physical pressure.
• Parents With Pediatric Terminal Patients: Stress Management Certain family-centered care principles should be used by healthcare providers in order to mitigate parental stress in the situations where their child battles terminal illness.
• Treatment Options for Post-Traumatic Stress Disorder Using psychological interventions as treatment is a productive tool that is used everywhere. Trauma-focused therapy has reduced PTSD symptoms.
• Why Women Experience Stress Throughout Life Females may experience more significant difficulties and anxiety as they age than individuals previously believed.
• Hypnotherapy in the Treatment of Post-Traumatic Stress Disorder Post-traumatic stress disorder refers to a behavioral disorder that occurs as a result of being subject to a shocking event or situation.
• Videogames & Stress Level Reduction Among Students To deal with stress, students do activities that include video games. Video games became available due to technological advances in recent decades.
• Racism, Ethnoviolence, and Post-Traumatic Stress Disorder The paper states that experiencing racism can induce post-traumatic stress disorder. Most people do not draw a link between racism and PTSD.
• Stress and Cognitive Appraisal Cognitive appraisal means the internal interpretation that a person gives to external changes. The role of cognitive appraisal in stress can be significant.
• Stress Reduction Education Targeting the Mental Health Patients with mental health illnesses such as stress and related disorders need to be taught approaches to reduce the latter.
• Epidemiology of Stress in the United Kingdom This report explores the context and current situation related to the prevalence, morbidity, and epidemiology of stress in the UK.
• Stress in Pregnant Women Due to COVID-19 Pandemic Pregnancy is a particularly crucial time for the mental health of a woman. The high levels of stress have been linked to exposure to the pandemic.
• Stress and Stress Management Discussion It is crucial to distinguish acute and chronic stress and the risk factors associated with them to ensure timely intervention to manage stress and prevent long-term damage.
• Impacts of Stress of Low Income on the Risk of Depression in Children Socioeconomic hardships lead to a decline in the quality of parenting and the development of psychological and behavioral problems in children.
• Physiology of Stress and Its Effects on Aging Process Assessment of the biological factors that influence anxiety and resilience might assist in identifying possible neurobiological systems as targets.
• Post-Traumatic Stress Disorder During and After World War I The paper examines the causes and manifestations of PTSD during and after World War I, despite the absence of this term at that time, and how diagnosis and treatment are made.
• Post-Traumatic Stress Disorder’s Treatment The paper present bibliography which review different psychotherapy interventions that can be applied in treating Post Traumatic Stress Disorder among adults.
• Stress and Anxiety and How to Cope With Them The research utilizes a reverse Stroop experiment to evaluate the mental performance of individuals when subjected to either up-regulation or down-regulation.
• Migration Crisis & Post-Traumatic Stress Disorder Trump’s anti-migration actions have significantly affected the psychological state of the people striving to get protection from the US.
• Post-Traumatic Stress Disorder and Substance Addiction Treatment The paper presents the case study of a client struggling with PTSD and substance addiction, including disposition, suggested treatment protocol, and resources for treatment.
• Psychological Post-Traumatic Stress Disorder Traumatized people are more likely to acquire PTSD, a condition in which the victim’s consciousness is dominated by the recollection of the traumatic incident.
• Ways To Cope Emotions and Stress There are several theories on how people experience emotions that have been put forward throughout the years, all attributing emotions to separate causes.
• Oncology: Caregiving Burden, Stress, and Health Effects The illness selected for this paper is cancer, which is a serious disease that sometimes can also be chronic. Caring for cancer patients is difficult.
• Stress: Causes and Consequences from a Sociological Perspective The sociological analysis of stress and the underlying causes of it, as well as its devastating effects, is required as a tool for vulnerable groups.
• Assessing and Treating Post-Traumatic Stress Disorders The paper discusses the treatment of PTSD and the pharmacokinetics of various antidepressants such as fluoxetine, citalopram, paroxetine, and sertraline.
• Discussion of Stress Response in Human The article examines the topic of stress response in humans, and attempt to find an answer to people having to endure traumatic events.
• Stress and Its Negative Influence on Health Current research explores the negative influences of stress on health, accenting neurological, cardiovascular, and immune systems dangers.
• Stress Management on the Job The paper discusses principles in the corporate culture, which help combat stress among employees to bring more value to the company.
• Stress Management Program for Health Workers The paper proposed to use the stress management program for the health workers based on the Mindfulness-Based Stress Reduction (MBSR) technique.
• Stress at the Workplace: Controlling and Preventing Stress at the workplace is inevitable because of workers’ dynamism. Distress in an employment environment can be related or not linked to the job.
• Preventing Workplace Stress: Effective Methods Effective methods of preventing stress in the workplace will help to avoid unpleasant consequences. This paper aims to discuss such methods.
• Posttraumatic Stress Disorder. Diagnostics Posttraumatic stress disorder (PTSD) is a serious mental health condition that needs treatment due to its potential negative implications.
• Combating Stress: Methods for Combating Stress General stress in student life can be caused by anxiety about the future, heavy learning burden, exams, and other factors. This paper discusses methods for combating stress.
• Personal Management Plans: Managing Stress, Nutrition This paper discusses personal management plans: Managing stress, fitness, nutrition, plans for disease prevention, and getting life in order in preparation for dying.
• Prevalence of Combat Post-traumatic Stress Disorder Among Veterans The paper argues combative nature of military personnel contributes to the Post-traumatic Stress disorder experienced by officers.
• Psychophysiological Aspects of Stress Stress has become a serious issue, especially considering the way of life of an average person in the contemporary world, which elevates different disorders.
• Theories in Epidemiology. Stress and Heart Disease The impact of stress on heart diseases is highly controversial among scientists. Various studies support the hypothesis that stress is highly associated with heart disease.
• Post-traumatic Stress and Growth Post-traumatic growth (PTG) refers to positive changes that a person makes after experiencing an extremely disturbing event.
• Maternal Stress in Pregnancy: Effects on Fetal Development The study seeks to find out if the development of the nervous system of the fetus is closely influenced by the psychological wellbeing of the mother.
• Stress and Somatic Symptoms: Healing Environment In summary, a healing environment is vital for modern people since they live in conditions that subject that to stress daily.
• Post-Traumatic Stress Disorder in Military Militants experience a significant number of traumatic events that subject them to PTSD. The culture of the military plays a significant role in promoting veteran mental wellness.
• Post-Traumatic Stress Disorder in Various Populations In this paper, the authors explore the prevalence of post-traumatic stress disorder among different populations. They compare this prevalence between genders and veterans.
• Anxiety and Stress Affect Pain Relief The study aims to reduce pain and monitor patient response in related areas such as relaxation, anxiety. The role of massage in the treatment of pain has been noted successfully.
• Post-Traumatic Stress Disorder: Pharmacological Treatment Approved medications can help treat PTSD symptoms and improve patient outcomes. SSRIs, such as sertraline, have been shown to reduce anxiety and increase concentration.
• Post Traumatic Stress Disorder: Characteristics Central Nervous System associated disorders represent one of the health issues globally. The description is aimed at highlighting research related to Posttraumatic stress disorder
• A Collaborative Stress Management Initiative for Mothers of Cancer Children The article explored the psychological stress experienced by mothers who have cancerous children. The research is current and relevant to contemporary health issues.
• Stress in Law: Reasons and Solutions The paper identifies the factors that result in stress by law enforcers and proposes ways in which the stress and by extension the negative effects it brings, can be mitigated.
• Post-Traumatic Stress Disorder The purpose of this paper is to discuss PTSD. Also, this paper introduces the assessment and factors associated with PTSD.
• Posttraumatic Stress Disorder: Triggers, Clinical Manifestations, and Therapy Posttraumatic stress disorder (PTSD) is a mental condition that originates from experiencing terrifying events and getting haunted by them long after they happened.
• Stress in Women Before and After Myocardial Infarction The study uses two interviews with women suffering an MI; interviews were taken in two different hospitals with a sample size of twenty and 14 respondents, before and after the MI.
• Mindful Meditation as Reducing College Students Stress The study answers the question of what is the reported effect of mindfulness meditation on reducing stress in teenage college students and its overall effectiveness.
• Investigating Post-Traumatic Stress Disorder Most people experience traumatic events during their lifetime. For the first time, the phenomenon of post-traumatic stress disorder was examined among the participants of the wars
• The Post-Traumatic Stress Disorder Many people suffer from post-traumatic stress disorder, and it is very important to know more about its symptoms and treatment.
• Utilization and Effectiveness of Coping Strategies in Job-Related Stress among Nurses Nursing is a discipline that is constantly evolving and requires professionals to use their skills and evidence-based practices to achieve good outcomes in their responsibilities.
• Incidence of Posttraumatic Stress Disorder After Motor Vehicle Accidents In recent years, a global surge in the number of posttraumatic stress disorder (PTSD) occasioned by motor vehicle accidents has been witnessed in the United States of America.
• “Sources of Stress in Nursing Students” by Pulido This is a critique of the paper titled “Sources of stress in nursing students: a systematic review of quantitative studies” by three University of Jaen scholars.
• Strain-Stress Shielding in the Proximal Tibia of a Stemmed Knee Prosthesis In this paper, we review work that has been done about stress shielding and knee prosthesis, compare them and outline the recommendations given in these papers.
• Trends and Issues in Nursing: Workload Stress Stress at the employment place reduces the competence of the employee. In nursing workplace, stress results in deprived service delivery and might affect the fitness of the patient.
• Reducing Stress in Student Nurses: Article Critique In Galbraith and Brown’s quantitative systematic review, “Assessing the intervention effectiveness for reducing stress in student nurses,” the aim is clearly articulated.
• Issue of Stress in Nursing Practice The issues of stress caused by workplace violence in nursing practice require special consideration because of their direct relation to the quality of health care services.
• “Work Stress Among Newly Graduated Nurses” by Blomberg The article by Blomberg et al. is an experimental cross-sectional comparative study aimed to investigate occupational stress among newly graduated nurses.
• My Experiences Handling Stress at High School The most challenging part of implementing my program was self-control. It can be very tempting to “cheat” and reward yourself without making an actual effort.
• Posttraumatic Stress Disorder: Approaches and Symptoms The report presents that several investigations indicate a negative relationship between mindfulness-based approaches and PTSD symptoms acuteness.
• Therapeutic Massage and the Reduction of Overall Stress and Anxiety This paper describes possible biases in conducting a qualitative study of the issue of therapeutic massage and its effect on the human condition.
• Article Summary “Maternal Stress and Sensitivity: Moderating Effect of Positive Affect” The article “Maternal stress and sensitivity: Moderating effect of positive affect” provides insights into the relationship between stress and maternal positive emotions.
• Airport Security Environment and Passenger Stress Most of the measures taken by airport operators to maintain transport security are appropriate and reasonable. Visible signs of safety concerns can cause anxiety to the passenger.
• Research on Stress Levels During Scheduled Sleep Behavior Different studies have revealed that there are several strategies used to reduce stress. Most scholars agree that there is a relationship between sleep and stress.
• The Influence of the Stress on Our Health: How To Cope With Stress To reduce stress and eliminate potential hazards for health, several coping mechanisms have been created—problem-focused coping aims to solve the problem first-hand.
• Janet Tomiyama’s “Stress and Obesity” Summary “Stress and Obesity,” an article by A. Janet Tomiyama, covers the interrelation between the two issues listed in the title and their mutual influence in psychological terms.
• How Depression and Stress in College Have Helped Me Be a Better and Stronger Person?
• How Are Effective Non-monetary Incentives in Relieving Stress?
• How Does Stress Affect Our Health?
• What Are the Causes of Stress at Work?
• How Differently Men and Women Cope With Stress at Work?
• How Does Stress Affect the Immune System?
• What is Post-traumatic Stress Disorder?
• What Triggers Stress and the Importance of Reducing It?
• What Works Stress Management?
• What Are the Health and Emotional Implications of Stress?
• How Different Approaches and Power of Leadership Manage Organizational Stress?
• What Are the Best Treatments for the Posttraumatic Stress Disorders in Veterans?
• How Does Stress Affect Child Development?
• How Ethnic Identity Mediates Acculturation Stress Depending?
• What Are the Causes of School-Related Stress in Student-Athletes?
• How Exercise Helps Reduce Stress?
• How Does Stress Affect the Human Body?
• How Does Burn Out Differ From Stress?
• What Are the Causes and Effects of Students’ Stress?
• What Are the Negative Effects of Stress?
• How Does Blood Pressure Relate to the Level of Stress?
• How Does Stress Affect One‘s Health?
• How Does Stress Make Students Struggle?
• What Are the Causes of Stress for Teenagers?
• How Does Stress Affect Appetite?
• How Does Chronic Stress Affect the Body?
• How Does Stress Affect College Students?
• How Does Stress Help Facilitate Potential Positive?
• How Does the Stress Affect Our Lives?
• How Does Stress Affect a Student’s Life?
• Stress Management: The Holmes and Rahe Stress Scale
• Posttraumatic Stress Disorder Risk Factors
• Dealing With Procrastination: Stress-Related Techniques
• Stress and Its Influence Employees’ Well-Being
• Posttraumatic Stress Disorder Diagnostic Categorization
• Stress Management: Personal Stress Techniques
• Analysis of Pre-Conditions and Ways for Reducing the Stress
• Stress Effects and Management Report
• Stress Has Become One of the Most Serious Health Issues
• Stress Consequences, Causes, and Further Actions
• Stress and Its Effects at the Workplace and Home
• Combat Fatigue or Post-Traumatic Stress Disorder in Soldiers
• Post Traumatic Stress Disorder Symptoms and Causes
• Posttraumatic Stress Disorder in Combat Veterans
• Implications of Educational Attainment on Stress Level in Job
• Combat Stress and Operational Stress Management
• Impact of Stress on Performance
• Post-Traumatic Stress Disorder in Children
• Strategies of Preventing Stress
• Post-Traumatic Stress Disorder in Children After Tsunami
• Psychological Stress and Nicotine Intake
• Relationship Between Critical Thinking, Problem-Solving, Decision-Making, and Stress Management in Nursing
• “Depression and Ways of Coping With Stress” by Orzechowska et al.
• Relationship Between Stress and Nicotine Intake in Middle Age Adults
• Breathe: Stress Management for Nurses Program
• Nursing Stress Solutions: Benefits and Support
• Posttraumatic Stress Disorder in Military Veterans
• Posttraumatic Stress Disorder: Diagnosis and Tratment
• Individuals With Post-Traumatic Stress Disorder
• Training, Stress and Performance: Study Findings
• Holmes & Rahe Stress Inventory and Management
• Strategies in Stress Management
• Stress-Reducing Measures and Activities
• New Life and Stress Factors at High School
• Work Stress and Burnout Among Nurses
• Breast Cancer and Stress Heightening
• The Stress-Buffering Hypothesis Test in a Mexican Sample
• Stress Control Measures to Prevent Nursing Burnout
• The Problem of Nursing Stress
• Shortage-Related Stress in Nursing Workforce
• Posttraumatic Stress Disorder: Definition and Diagnosis
• Humour and Stress in Male and Female Students
• Stress Migraine in Women After Menopause
• Stress Reduction in Healthcare Students
• Work-Related Stress Management in Professional Nurses
• “Job Stress and Burnout in Hospital Employees” by Chou et al.
• Posttraumatic Stress Disorder and Substance Use
• Ontario Post Traumatic Stress Legislation for Employees
• Emotion Perception and Gender Factor in Stress
• Stress as a Fundamental Concept for Nursing
• Stress Control Strategies for Nurses
• Post Traumatic Stress Disorder: Systemic Psychotherapy
• Post Traumatic Stress Disorder Diagnostics
• Combat-Related Posttraumatic Stress Disorder
• The Treatment of Posttraumatic Stress Disorder
• Anti-Stress Workplace Interventions for Nurses
• Post-Traumatic Stress Disorder: Group Therapy
• Stress-Coping Strategies in Nurses
• Posttraumatic Stress Disorder and Treatment Centers
• Post Traumatic Stress Disorder: Case Analysis
• Stress Influence in Emergency Nursing
• Workplace Stress Control Among Nurses
• “Post-Traumatic Stress Disorder” by Bisson et al.
• Women’s Stress Caused by Social Networks
• Veterans’ Post Traumatic Stress Disorder: How a Game Can Help?
• Mitigate Stress Exercise Program at the Work
• Handling Cultural Stress in the United Arab Emirates
• The Tibetan Culture Views on Stress Management
• Stress Impacts on Psychological and Physiological Health
• Social Workers’ Benefits from Stress Management
• Psychological Therapy of Post-Traumatic Stress Disorder
• Posttraumatic Stress Disorder Concept
• Psychological Treatment: Posttraumatic Stress Disorder
• What Is Post-Traumatic Stress Disorder?
• Post-Traumatic Stress Disorder: Cognitive Therapy

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StudyCorgi. (2021, September 9). 261 Stress Topics & Research Questions. https://studycorgi.com/ideas/stress-essay-topics/

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StudyCorgi . "261 Stress Topics & Research Questions." September 9, 2021. https://studycorgi.com/ideas/stress-essay-topics/.

StudyCorgi . 2021. "261 Stress Topics & Research Questions." September 9, 2021. https://studycorgi.com/ideas/stress-essay-topics/.

These essay examples and topics on Stress were carefully selected by the StudyCorgi editorial team. They meet our highest standards in terms of grammar, punctuation, style, and fact accuracy. Please ensure you properly reference the materials if you’re using them to write your assignment.

This essay topic collection was updated on January 21, 2024 .

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Research of College Students Who Work Out at School

College years are a transformative period where students pursue academic excellence and explore various aspects of personal development. Engaging in regular physical activity is a critical part of this developmental phase. Research consistently shows that college students who incorporate workouts into their daily routines experience profound benefits across multiple dimensions of their lives. Discover what previous research has found happens to college students who work out at school and the importance of an on-campus gym.

Mental Clarity and Academic Performance

Regular physical activity can positively affect college students’ mental clarity and cognitive function. Even for short periods, engaging in exercise can boost concentration, memory, and overall brain performance.

Physical activity’s increased blood flow to the brain nourishes brain cells and promotes new neural connections. Consequently, students who maintain an active lifestyle tend to exhibit better academic performance. They can focus more intently during lectures, retain information more effectively, and display enhanced problem-solving skills.

Memory Retention

Exercise significantly impacts college students’ memory retention due to the release of brain-derived neurotrophic factor (BDNF), a protein that supports brain cells’ growth, functionality, and survival. Exercise-induced BDNF production helps form new memories and protects existing ones, improving the ability to retain information over extended periods. Students who maintain regular exercise routines demonstrate a greater capacity to remember lecture material and complex concepts and perform better in exams requiring high memory recall.

Stress Reduction

The pressure to excel academically and socially can be overwhelming for many college students, leading to elevated levels of stress and anxiety. However, regular exercise offers a powerful solution to relieve stress. Physical activity stimulates the release of endorphins, commonly known as the body’s natural stress relievers. These chemicals reduce feelings of anxiety and promote an overall sense of well-being.

Engaging in exercise also provides students with a productive break from study, resetting their minds and decreasing feelings of anxiety. Additionally, the disciplined structure of regular exercise can help students manage their time more effectively, reducing one of the key contributors to stress.

Lifelong Health and Wellness Habits

Many forms of physical activity lead to bountiful health benefits. Running, jogging, or walking on our Alpine Runner Incline Trainer boosts cardiovascular health, strengthening the heart and increasing blood circulation. No matter how they engage in physical activity, regular exercise for college students establishes lifelong health and wellness habits. The college years are critical for setting and solidifying habits that can lead to a healthier, more active lifestyle post-graduation.

Research shows that college students who work out at school reap multiple benefits that impact many aspects of their lives. With a well-equipped on-campus fitness center and TRUE commercial treadmills , your school can contribute to students’ immediate well-being and success.

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Join the discussion about managing academic stress.

April 19, 2024

Discuss academic stress and ways to tackle that stress to enhance your academic success during this Center for Civic Engagement event on Tuesday, April 23, from 6:30-8 p.m. in the Brandt Student Center, Room 115. The discussion will cover different types of stress, recognizing unhealthy levels of stress, and how to change your mindset to lower overall stress levels and increase adaptability in the classroom – all while enjoying some snacks. An opportunity to write positive notes focusing on kindness that will be posted around the BSC will follow the dialogue. Sign up at app.helperhelper.com . Questions? Contact Emily Swartzbaugh at [email protected] .

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MPH student uses public health to amplify holistic fitness approaches

• Caitlin Keough
• April 19, 2024
• Student Life

USF College of Public Health (COPH) MPH student Winston “Cortez” Ward became interested in holistic approaches to health and fitness after being diagnosed with glucose 6 phosphate dehydrogenase deficiency (G6PD).

According to John Hopkins Medicine, G6PD deficiency, which affects about 10% of African American men in the U.S., is an inherited condition that causes hemolytic anemia due to a decreased amount of the enzyme G6PD causing red blood cells break down faster than they are made.

After working as an U.S. Army Reserve Veteran in the 479th Engineer Battalion and later as an IT and customer support manager for Concentrix, Ward decided to follow his passion to pursue a career in health and research how holistic approaches, as a complementary therapy, can aid in reduction of pain and stress on the body. 

“During my career change, I looked to work on myself as well as experience different modalities in this field,” he said. “After an amazing yoga session an epiphany arose to incorporate yoga into a holistic model of health and fitness.”

It was this epiphany that led Ward to open the Cortez Training Center (CTC) in 2021. The non-profit provides the resources and support necessary for integrative approaches to the prevention, treatment and rehabilitation of dysfunction, illnesses, injuries or disabilities. These approaches include healing therapies, personal training, cardio kickboxing, yoga and nutrition coaching.

Ward leading a group of participants in a yoga session at CTC. (Photo courtesy of Ward)

Wanting to pursue research into G6PD and refine processes for CTC, Ward joined the COPH for his MPH in public health practice and public health generalist graduate certificate after earning his BS in biological health sciences and health care administration from USF in 2022.

“My personal health issues are the most motivating factors for obtaining my degree and my aspirations to publish research within the COPH,” he said. “Overcoming many previous experiences and challenges associated with being a minority and a veteran has allowed me to display my resilience and drive towards my degree. I do this for representation, raising awareness and to make an impact in research on understudied public health issues.”

Ward said that he is already seeing the benefits of learning more about public health and is excited to integrate what his has learned into CTC.

 “Public health is already positively influencing and impacting the work that I currently do in the non-profit space,” he said. “A common theme in both public health and holistic health is that the best outcomes, especially for complex issues, come from interprofessional collaboration. This is the direction I am trying to move towards.”

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Family and Academic Stress and Their Impact on Students' Depression Level and Academic Performance

1 School of Mechatronics Engineering, Daqing Normal University, Daqing, China

2 School of Marxism, Heilongjiang University, Harbin, China

Jacob Cherian

3 College of Business, Abu Dhabi University, Abu Dhabi, United Arab Emirates

Noor Un Nisa Khan

4 Faculty of Business Administration, Iqra University Karachi Pakistan, Karachi, Pakistan

Kalpina Kumari

5 Faculty of Department of Business Administration, Greenwich University Karachi, Karachi, Pakistan

Muhammad Safdar Sial

6 Department of Management Sciences, COMSATS University Islamabad (CUI), Islamabad, Pakistan

Ubaldo Comite

7 Department of Business Sciences, University Giustino Fortunato, Benevento, Italy

Beata Gavurova

8 Faculty of Mining, Ecology, Process Control and Geotechnologies, Technical University of Kosice, Kosice, Slovakia

József Popp

9 Hungarian National Bank–Research Center, John von Neumann University, Kecskemét, Hungary

10 College of Business and Economics, University of Johannesburg, Johannesburg, South Africa

Associated Data

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Current research examines the impact of academic and familial stress on students' depression levels and the subsequent impact on their academic performance based on Lazarus' cognitive appraisal theory of stress. The non-probability convenience sampling technique has been used to collect data from undergraduate and postgraduate students using a modified questionnaire with a five-point Likert scale. This study used the SEM method to examine the link between stress, depression, and academic performance. It was confirmed that academic and family stress leads to depression among students, negatively affecting their academic performance and learning outcomes. This research provides valuable information to parents, educators, and other stakeholders concerned about their childrens' education and performance.

Introduction

Higher education institutions (HEIs) are believed to be one of the strongest pillars in the growth of any nation ( 1 ). Being the principal stakeholder, the performance of HEIs mainly relies on the success of its students ( 2 ). To successfully compete in the prevailing dynamic industrial environment, students are not only supposed to develop their knowledge but are also expected to have imperative skills and abilities ( 3 ). In the current highly competitive academic environment, students' performance is largely affected by several factors, such as social media, academic quality, family and social bonding, etc. ( 4 ). Aafreen et al. ( 2 ) stated that students continuously experience pressure from different sources during academic life, which ultimately causes stress among students.

Stress is a common factor that largely diminishes individual morale ( 5 ). It develops when a person cannot handle their inner and outer feelings. When the stress becomes chronic or exceeds a certain level, it affects an individual's mental health and may lead to different psychological disorders, such as depression ( 6 ). Depression is a worldwide illness marked by feelings of sadness and the inability to feel happy or satisfied ( 7 ). Nowadays, it is a common disorder, increasing day by day. According to the World Health Organization ( 8 , 9 ), depression was ranked third among the global burden of disease and predicted to take over first place by 2030.

Depression leads to decreased energy, difficulty thinking, concentrating, and making career decisions ( 6 ). Students are a pillar of the future in building an educated society. For them, academic achievement is a big goal of life and can severely be affected if the students fall prey to depression ( 10 , 11 ). There can be several reasons for this: family issues, exposure to a new lifestyle in colleges and universities, poor academic grades, favoritism by teachers, etc. Never-ending stress or academic pressure of studies can also be a chief reason leading to depression in students ( 12 ). There is a high occurrence of depression in emerging countries, and low mental health literacy has been theorized as one of the key causes of escalating rates of mental illness ( 13 ).

Several researchers, such as ( 6 , 14 , 15 ) have studied stress and depression elements from a performance perspective and reported that stress and depression negatively affect the academic performance of students. However, Aafreen et al. ( 2 ) reported contradictory results and stated that stress sharpens the individual's mind and reflexes and enables workers to perform better in taxing situations. Ardalan ( 16 ) conducted a study in the United States (US). They reported that depression is a common issue among students in the US, and 20 percent of them may have a depressive disorder spanning 12 months or more. It affects students' mental and physical health and limits their social relationships and professional career.

However, the current literature provides mixed results on the relationship between stress and performance. Therefore, the current research investigates stress among students from family and academic perspectives using Lazaru's theory which describes stress as a relation between an individual and his environment and examines how it impacts students' depression level, leading to their academic performance. Most of the available studies on stress and depression are from industrial perspectives, and limited attention is paid to stress from family and institutional perspectives and examines its impact on students' depression level, leading to their academic performance, particularly in Pakistan, the place of the study. Besides, the present study follows a multivariate statistical technique, followed by structural equation modeling (SEM) to examine the relationship between stated variables which is also a study's uniqueness.

This paper is divided into five main sections. The current section provided introduction, theoretical perspective, and background of the study. In the second section, a theoretical framework, a detailed literature review and research hypotheses of the underlying relationships are being proposed. In the third and fourth section, methodology and analysis have been discussed. Finally, in the last section, the conclusion, limitations, implications, and recommendations for future research have been proposed.

Theory and Literature

The idea of cognitive appraisal theory was presented in 1966 by psychologist Richard Lazarus in Psychological Stress and Coping Process. According to this theory, appraisal and coping are two concepts that are central to any psychological stress theory. Both are interrelated. According to the theory, stress is the disparity between stipulations placed on the individuals and their coping resources ( 17 ). Since its first introduction as a comprehensive theory ( 18 ), a few modifications have been experienced in theory later. The recent adaptation states that stress is not defined as a specific incitement or psychological, behavioral, or subjective response. Rather, stress is seen as a relation between an individual and his environment ( 19 ). Individuals appraise the environment as significant for their well-being and try to cope with the exceeding demands and challenges.

Cognitive appraisal is a model based on the idea that stress and other emotional processes depend on a person's expectancies regarding the significance and outcome of an event, encounter, or function. This explains why there are differences in intensity, duration, and quality of emotions elicited in people in response to the environment, which objectively, are equal for all ( 18 ). These appraisals may be influenced by various factors, including a person's goals, values, motivations, etc., and are divided into primary and secondary appraisals, specific patterns of which lead to different kinds of stress ( 20 ). On the other hand, coping is defined as the efforts made by a person to minimize, tolerate, or master the internal and external demands placed on them, a concept intimately related to cognitive appraisal and, therefore, to the stress-relevant person-environment transactions.

Individuals experience different mental and physiological changes when encountering pressure, such as stress ( 21 , 22 ). The feelings of stress can be either due to factors in the external environment or subjective emotions of individuals, which can even lead to psychological disorders such as anxiety and depression. Excess stress can cause health problems. A particularly negative impact has been seen in students due to the high level of stress they endure, affecting their learning outcomes. Various methods are used to tackle stress. One of the methods is trying to pinpoint the causes of stress, which leads us to different terms such as family stress and academic stress. The two factors, stress and depression, have greatly impacted the students' academic performances. This research follows the Lazarus theory based on stress to examine the variables. See the conceptual framework of the study in Figure 1 .

Conceptual framework.

Academic Stress

Academic issues are thought to be the most prevalent source of stress for college students ( 23 ). For example, according to Yang et al. ( 24 ), students claimed that academic-related pressures such as ongoing study, writing papers, preparing for tests, and boring professors were the most important daily problems. Exams and test preparation, grade level competitiveness, and gaining a big quantity of knowledge in a short period of time all contribute to academic pressure. Perceived stress refers to a condition of physical or psychological arousal in reaction to stressors ( 25 , 26 ). When college students face excessive or negative stress, they suffer physical and psychological consequences. Excessive stress can cause health difficulties such as fatigue, loss of appetite, headaches, and gastrointestinal issues. Academic stress has been linked to a variety of negative effects, including ill health, anxiety, depression, and poor academic performance. Travis et al. ( 27 ), in particular, discovered strong links between academic stress and psychological and physical health.

Family Stress

Parental participation and learning effect how parents treat their children, as well as how they handle their children's habits and cognitive processes ( 28 ). This, in turn, shapes their children's performance and behaviors toward them. As a result, the parent-child relationship is dependent on the parents' attitudes, understanding, and perspectives. When parents have positive views, the relationship between them and their children will be considerably better than when they have negative attitudes. Parents respond to unpleasant emotions in a variety of ways, which can be classified as supportive or non-supportive ( 29 ). Parents' supportive reactions encourage children to explore their emotions by encouraging them to express them or by assisting them in understanding and coping with an emotion-eliciting scenario. Non-supportive behaviors, such as downplaying the kid's emotional experience, disciplining the child, or getting concerned by the child's display, transmit the child the message that expressing unpleasant emotions is inappropriate and unacceptable. Supportive parental reactions to unpleasant emotions in children have been linked to dimensions of emotional and social competence, such as emotion comprehension and friendship quality. Non-supportive or repressive parental reactions, on the other hand, have been connected to a child's stored negative affect and disordered behaviors during emotion-evoking events, probably due to an inability or unwillingness to communicate unpleasant sentiments ( 30 , 31 ).

Academic Stress and Students' Depression Levels

Generally, it is believed that mental health improves as we enter into adulthood, and depression disorder starts to decline between the age of 18 and 25. On the other hand, excessive depression rates are the highest pervasiveness during this evolution ( 15 ), and many university students in the particular screen above clinical cut-off scores for huge depression ( 14 , 32 ). Afreen et al. ( 2 ) stated that 30% of high school students experience depression from different perspectives. This means a major chunk of fresh high school graduates are more likely to confront depression or are more vulnerable to encountering depression while enrolling in the university. As the students promote to a higher level of education, there are many factors while calculating the stress like, for example, the syllabus is tough to comprehend, assignments are quite challenging with unrealistic deadlines, and accommodation problems for the students who are shifted from other cities, etc. ( 33 ). Experiences related to university can also contribute while studying depression. The important thing to consider is depression symptoms vary from time to time throughout the academic years ( 34 ); subjective and objective experiences are directly connected to the depression disorder ( 6 ), stress inherent in the university situation likely donates to the difference in university students' depressing experiences.

Stress negatively impacts students' mental peace, and 42.3% of students of Canadian university respondents testified devastating levels of anxiety and stress ( 35 , 36 ). Moreover, there were (58.1%) students who stated academic projects are too tough to handle for them. In Germany, Bulgaria, and Poland, a huge sample of respondents consider assignments a burden on their lives that cannot stand compared to relationships or any other concern in life ( 14 ).

In several countries, university students were studied concerning stress, and results show that depression disorder and apparent anxiety are correlated to educational needs and demands ( 37 ). In their cross-sectional study conducted on a sample of 900 Canadian students, Lörz et al. ( 38 ) concluded that strain confronted due to academic workload relatively has high bleak symptoms even after controlling 13 different risk affecting factors for depression (e.g., demographic features, abusive past, intellectual way, and personality, currently experienced stressful trials in life, societal support). Few have exhibited that students who are tired of educational workload or the students who name them traumatic tend to have more depressing disorders ( 15 ).

These relations can be described by examining the stress and coping behaviors that highlight the role of positive judgments in the stress times ( 39 ), containing the Pancer and colleagues' university modification framework ( 40 , 41 ). The evaluation concept includes examining the circumstances against the available resources, for instance, the effectiveness of coping behavior and societal support. As per these frameworks, if demand is considered unapproachable and resources are lacking, confronted stress and interrelated adverse effects will be high, conceivably giving birth to difficulties in an adjustment like mental instability. Stress triggering situations and the resources in the educational area led to excessive workload, abilities, and study and enhanced time managing skills.

Sketching the overall evaluation frameworks, Pancer et al. ( 40 ) established their framework to exhibit the constructive and damaging adjustment results for the university students dealing with the academic challenges. They stated that while students enroll in the university, they evaluate all the stress-related factors that students confront. They consider them manageable as long as they have sufficient resources. On the other hand, if the available resources do not match the stress factors, it will surely result in a negative relationship, which will lead students to experience depression for sure. Based on the given arguments, the researcher formulates the following hypothesis:

• H1: Increased academic stress results in increased depression levels in students.

Family Stress and Students' Depression Levels

According to Topuzoglu et al. ( 42 ), 3% to 16.9% of individuals are affected by depression worldwide. There are fewer chances for general people to confront depression than university students ( 43 , 44 ). In Mirza et al.'s ( 45 ) study, 1/3 of students encounter stress and depression (a subjective mean occurrence of 30.6%) of all participant students, which suggests students have a 9% higher rate of experiencing depression than general people. Depression can destroy life; it greatly impacts living a balanced life. It can impact students' personal and social relationships, educational efficiency, quality of life, affecting their social and family relationships, academic productivity, and bodily operations ( 46 , 47 ). This declines their abilities, and they get demotivated to learn new things, resulting in unsatisfactory performances, and it can even result in university dropouts ( 48 ). Depression is a continuous substantial risk aspect for committing suicide for university students ( 49 ); thus, it is obliged to discover the factors that can give rise to students' depression.

Seventy-five percentage of students in China of an intermediate school are lucky enough to enroll in higher education. The more students pursue higher education, the more they upsurge for depression (in 2002, the depression rate was 5 to 10%, 2011 it rises 24 to 38%) ( 5 ). Generally, University students' age range is late teens to early twenties, i.e., 18–23 years. Abbas ( 50 ) named the era of university students as “post-adolescence. Risk factors for teenage depression have several and complicated problems of individual characteristics and family and educational life ( 51 ). Amongst the huge depression factors, relationship building with family demands a major chunk of attention and time since factors like parenting and family building play an important role in children's development ( 52 , 53 ). Halonen et al. ( 54 ) concluded that factors like family binding play a major role in development, preservation, and driving adolescent depression. Generally speaking, depressed teenagers tend to have a weaker family relationship with their parents than non-depressed teenagers.

There are two types of family risk factors, soft and hard. Hard factors are encountered in families with a weak family building structure, parents are little to no educated at all, and of course, the family status (economically). Several studies have proved that students of hard risk factors are more likely to encounter depression. Firstly, students from broken families have low confidence in every aspect of life, and they are weak at handling emotional breakdowns compared to students from complete and happy families ( 55 – 57 ). Secondly, the university students born in educated families, especially mothers (at least a college degree or higher degree), are less likely to confront depression than the university students born in families with little to no educated families. Secondly, children born with educated mothers or mothers who at least have a college degree tend to be less depressive than the children of less-educated mothers ( 58 ). However, Parker et al. and Mahmood et al. ( 59 , 60 ) stated a strong relationship between depression and mothers with low literacy levels.

On the other hand, Chang et al. ( 46 ) couldn't prove the authentication of this relationship in university students. Thirdly, university students who belong to lower class families tend to have more unstable mental states and are more likely to witness depression than middle or upper-class families ( 61 ). Jadoon et al. and Abbas et al. ( 62 , 63 ) said that there is no link between depression and economic status. Their irrelevance can be because medical students often come from educated and wealthy families and know their jobs are guaranteed as soon as they graduate. Therefore, the relationship between the hard family environment and depression can be known by targeting a huge audience, and there are several factors to consider while gauging this relationship.

The soft family environment is divided into clear factors (parenting style example, family guidelines, rules, the parent with academic knowledge, etc.) and implied factors (family norm, parent-child relationship, communication within the family, etc.). The soft factor is the key factor within the family that cannot be neglected while studying the teenagers' mental state or depression. Families make microsystems within the families, and families are the reason to build and maintain dysfunctional behavior by multiple functional procedures ( 64 ). Amongst the soft family environmental factors, consistency and struggles can be helpful while forecasting the mental health of teenagers. The youth of broken families, family conflict, weak family relationships, and marital issues, especially unhappy married life, are major factors for youth depression ( 65 ). Ruchkin et al. ( 66 ) stated that African Americans usually have weak family bonding, and their teenagers suffer from depression even when controlling for source bias. Whereas, few researchers have stated, family unity is the most serious factor while foreseeing teenagers' depression. Eaton noted that extreme broken family expressions might hurt emotionality and emotional regulation ( 67 , 68 ).

Social circle is also considered while studying depression in teenagers ( 69 – 71 ). The traditional Pakistani culture emphasizes collectivism and peace and focuses on blood relations and sensitive sentiments. Adolescents with this type of culture opt to get inspired by family, but students who live in hostels or share the room with other students lose this family inspiration. This transformation can be a big risk to encounter depression ( 72 ). Furthermore, in Pakistan securing employment is a big concern for university students. If they want a good job in the future, they have to score good grades and maintain GPA from the beginning. They have to face different challenges all at once, like aggressive educational competition, relationships with peers and family, and of course the biggest employment stress all alone. The only source for coping with these pressures is the family that can be helpful for fundings. If the students do not get ample support the chances are of extreme depression. The following hypothesis is suggested:

• H2: Increased family stress level results in increased depression levels in students.

Students' Depression Levels and Students' Academic Performance

University students denote many people experiencing a crucial conversion from teenagers to adulthood: a time that is generally considered the most traumatic time in one's ( 73 ). This then gets accumulated with other challenges like changes in social circle and exams tension, which possibly puts students' mental health at stake. It has been concluded that one-third of students experience moderate to severe depression in their entire student life ( 74 ). This is the rate that can be increased compared to the general people ( 75 , 76 ). Students with limited social-class resources tend to be more helpless. Additionally, depressed students in attainable-focused environments (for instance, higher academic institutes) are likely to score lower grades with a sense of failure and more insufficient self-assurance because they consider themselves failures, find the world unfair, and have future uncertainties. Furthermore, students with low self-esteem are rigid to take on challenging assignments and projects, hence they are damaging their educational career ( 77 ).

Depression can be defined as a blend of physical, mental, bodily processes, and benightedness which can make themselves obvious by symptoms like, for example, poor sleep schedule, lack of concentration, ill thoughts, and state of remorse ( 78 , 79 ). But, even after such a huge number of depressions in students and the poor academic system, research has not explored the effect of depression on educational performance. A study has shown that the relationship between emotional stability and academic performance in university students and financial status directly results in poor exam performance. As the study further concluded, it was verified depression is an independent factor ( 80 ). Likewise, students suffering from depression score poor grades, but this relationship vanished if their depression got treated. Apart from confidence breaking, depression is a big failure for their academic life. Students with depression symptoms bunk more classes, assessments, and assignments. They drop courses if they find them challenging than non-depressed peers, and they are more likely to drop out of university completely ( 81 ). Students suffering from depression can become ruthless, ultimately affecting their educational performance and making them moody ( 82 ).

However, it has been stated that the association between anxiety and educational performance is even worse and ambiguous. At the same time, some comprehensive research has noted that the greater the anxiousness, the greater the student's performance. On the other hand, few types of research have shown results where there is no apparent relationship between anxiety and poorer academic grades ( 83 ). Ironically, few studies have proposed that a higher anxiety level may improve academic performance ( 84 , 85 ). Current research by Khan et al. ( 86 ) on the undergraduate medical students stated that even though the high occurrence of huge depression between the students, the students GPA is unharmed. Therefore, based on given differences in various research findings, this research is supposed to find a more specific and clear answer to the shared relationship between students' depression levels and academic performance. Based on the given arguments, the researcher formulates the following hypothesis:

• H3: Students' depression level has a significant negative effect on their academic performance.

Methodology

Target population and sampling procedure.

The target audience of this study contains all male and female students studying in the public, private, or semi-government higher education institutions located in Rawalpindi/Islamabad. The researchers collected data from undergraduate and postgraduate students from the management sciences, engineering, and computer science departments. The sampling technique which has been used is the non-probability sampling technique. A questionnaire was given to the students, and they were requested to fill it and give their opinion independently. The questionnaire is based on five points Likert scale.

However, stress and depression are the most common issue among the students, which affects their learning outcomes adversely. A non-probability sampling technique gathered the data from February 2020 to May 2020. The total questionnaires distributed among students were 220, and 186 responses were useful. Of which 119 respondents were females, 66 males, and 1 preferred not to disclose. See Table 1 for detailed demographic information of respondents.

Respondent's demographic profile.

Measurement Scales

We have divided this instrument into two portions. In the first section, there is demographic information of respondents. The second section includes 14 items based on family stress, academic stress, students' depression levels, and students' academic performance. Academic and family stress were measured by 3 item scale for each construct, and students' depression level and academic performance were measured by 4 item scale for each separate construct. The five-point Likert scale is used to measure the items, in which one signifies strongly disagree (S.D), second signifies disagree (D.A), third signifies neither agree nor disagree (N), fourth signifies agree (A.G), and the fifth signifies strongly agree (S.A). The questionnaire has been taken from Gold Berg ( 87 ), which is modified and used in the given questionnaire.

Data Analysis and Results

The researchers used the SEM technique to determine the correlation between stress, depression, and academic performance. According to Prajogo and Cooper ( 88 ), it can remove biased effects triggered by the measurement faults and shape a hierarchy of latent constructs. SPSS v.23 and AMOS v.23 have been used to analyze the collected data. Kaiser-Meyer-Olkin test is used to test the competence of the sample. The value obtained is 0.868, which fulfills the Kaiser et al. ( 89 ), a minimum requirement of 0.6. The multicollinearity factor was analyzed through the variance inflation factor (VIF). It shows the value of 3.648 and meets the requirement of Hair et al. ( 90 ), which is < 4. It also indicates the absence of multicollinearity. According to Schwarz et al. ( 91 ), common method bias (CMB) is quite complex in quantitative studies. Harman's test of a single factor has been used to analyze CMB. The result obtained for the single factor is 38.63%. As stated by Podsakoff et al. ( 92 ), if any of the factors gives value < 50% of the total variance, it is adequate and does not influence the CMB. Therefore, we can say that there is no issue with CMB. Considering the above results are adequate among the measurement and structural model, we ensure that the data is valued enough to analyze the relation.

Assessment of the Measurement and Structural Model

The association between the manifest factors and their elements is examined by measuring model and verified by the Confirmatory Factor Analysis (CFA). CFA guarantees legitimacy and the unidimensional of the measurement model ( 93 ). Peterson ( 94 ) stated that the least required, i.e., 0.8 for the measurement model, fully complies with its Cronbach's alpha value, i.e., 0.802. Therefore, it can confidently be deduced that this measurement model holds satisfactory reliability. As for the psychological legitimacy can be analyzed through factor loading, where the ideal loading is above 0.6 for already established items ( 95 ). Also, according to the recommendation of Molina et al. ( 96 ), the minimum value of the average variance extracted (AVE) for all results is supposed to be >0.5. Table 2 gives detail of the variables and their quantity of things, factor loading, merged consistency, and AVE values.

Instrument reliability and validity.

A discriminant validity test was performed to ensure the empirical difference of all constructs. For this, it was proposed by Fornell and Larcker ( 97 ) that the variance of the results is supposed to be greater than other constructs. The second indicator of discriminant validity is that the square root values of AVE have a greater correlation between the two indicators. Hair et al. ( 90 ) suggested that the correlation between the pair of predictor variables should not be higher than 0.9. Table 3 shows that discriminant validity recommended by Hair et al. ( 90 ) and Fornell and Larcker ( 97 ) was proved clearly that both conditions are fulfilled and indicates that the constructs have adequate discriminant validity.

Discriminant validity analysis.

Acd. Strs, Academic Stress; Fam. Strs, Family Stress; Std. Dep. Lev, Student's Depression Level; Std. Acd. Perf, Student's Academic Performance .

Kaynak ( 98 ) described seven indicators that ensure that the measurement model fits correctly. These indicators include standardized root mean squared residual (SRMR), root means a square error of approximation (RMSEA), comparative fit index (CFI), normative fit index (NFI), adjusted goodness of fit index (AGFI), the goodness of fit index (GFI) and chi-square to a degree of freedom (x 2 /DF). Tucker-Lewis's index (TLI) is also included to ensure the measurement and structural model's fitness. In the measurement model, the obtained result shows that the value of x 2 /DF is 1.898, which should be lower than 2 suggested by Byrne ( 99 ), and this value also meets the requirement of Bagozzi and Yi ( 100 ), i.e., <3. The RMSEA has the value 0.049, which fully meets the requirement of 0.08, as stated by Browne and Cudeck ( 101 ). Furthermore, the SRMR acquired value is 0.0596, which assemble with the required need of < 0.1 by Hu and Bentler ( 102 ). Moreover, according to Bentler and Bonett ( 103 ), McDonald and Marsh ( 104 ), and Bagozzi and Yi ( 100 ), the ideal value is 0.9, and the values obtained from NFI, GFI, AGFI, CFI, and TLI are above the ideal value.

Afterward, the structural model was analyzed and achieved the findings, which give the value of x 2 /DF 1.986. According to Browne and Cudeck ( 101 ), the RMSEA value should not be greater than 0.08, and the obtained value of RMSEA is 0.052, which meets the requirement perfectly. The minimum requirement of Hu and Bentler ( 102 ) should be <0.1, for the structural model fully complies with the SRMR value 0.0616. According to a recommendation of McDonald and Marsh ( 104 ) and Bagozzi and Yi ( 100 ), the ideal value must be up to 0.9, and Table 4 also shows that the values of NFI, GFI, AGFI, CFI, and TLI, which are above than the ideal value and meets the requirement. The above results show that both the measurement and structural models are ideally satisfied with the requirements and the collected data fits correctly.

Analysis of measurement and structural model.

Testing of Hypotheses

The SEM technique is used to examine the hypotheses. Each structural parameter goes along with the hypothesis. The academic stress (Acd. Strs) with the value β = 0.293 while the p -value is 0.003. These outcomes show a significant positive relationship between academic stress (Acd. Strs) and students' depression levels (Std. Dep. Lev). With the β = 0.358 and p = 0.001 values, the data analysis discloses that the family stress (Fam. Strs) has a significant positive effect on the students' depression level (Std. Dep. Lev). However, the student's depression level (Std. Dep. Lev) also has a significant negative effect on their academic performance (Std. Acd. Perf) with the values of β = −0.319 and p = 0.001. Therefore, the results supported the following hypotheses H 1 , H 2 , and H 3 . The sub-hypotheses analysis shows that the results are statistically significant and accepted. In Table 5 , the details of the sub-hypotheses and the principals are explained precisely. Please see Table 6 to review items with their mean and standard deviation values. Moreover, Figure 2 represents the structural model.

Examining the hypotheses.

Description of items, mean, and standard deviation.

Structural model.

Discussion and Conclusion

These findings add to our knowledge of how teenage depression is predicted by academic and familial stress, leading to poor academic performance, and they have practical implications for preventative and intervention programs to safeguard adolescents' mental health in the school context. The outcomes imply that extended academic stress positively impacts students' depression levels with a β of 0.293 and a p -value sof 0.003. However, according to Wang et al. ( 5 ), a higher level of academic stress is linked to a larger level of school burnout, which leads to a higher degree of depression. Satinsky et al. ( 105 ) also claimed that university officials and mental health specialists have expressed worry about depression and anxiety among Ph.D. students, and that his research indicated that depression and anxiety are quite common among Ph.D. students. Deb et al. ( 106 ) found the same results and concluded that depression, anxiety, behavioral difficulties, irritability, and other issues are common among students who are under a lot of academic stress. Similarly, Kokou-Kpolou et al. ( 107 ) revealed that depressive symptoms are common among university students in France. They also demonstrate that socioeconomic and demographic characteristics have a role.

However, Wang et al. ( 5 ) asserted that a higher level of academic stress is associated with a higher level of school burnout, which in return, leads to a higher level of depression. Furthermore, Satinsky et al. ( 105 ) also reported that university administrators and mental health clinicians have raised concerns about depression and anxiety and concluded in his research that depression and anxiety are highly prevalent among Ph.D. students. Deb et al. ( 106 ) also reported the same results and concluded that Depression, anxiety, behavioral problems, irritability, etc. are few of the many problems reported in students with high academic stress. Similary, Kokou-Kpolou et al. ( 107 ) confirmed that university students in France have a high prevalence of depressive symptoms. They also confirm that socio-demographic factors and perceived stress play a predictive role in depressive symptoms among university students. As a result, academic stress has spread across all countries, civilizations, and ethnic groups. Academic stress continues to be a serious problem impacting a student's mental health and well-being, according to the findings of this study.

With the β= 0.358 and p = 0.001 values, the data analysis discloses that the family stress (Fam. Strs) has a significant positive effect on the students' depression level (Std. Dep. Lev). Aleksic ( 108 ) observed similar findings and concluded that many and complicated concerns of personal traits, as well as both home and school contexts, are risk factors for teenage depression. Similarly, Wang et al. ( 109 ) indicated that, among the possible risk factors for depression, family relationships need special consideration since elements like parenting styles and family dynamics influence how children grow. Family variables influence the onset, maintenance, and course of juvenile depression, according to another study ( 110 ). Depressed adolescents are more likely than normal teenagers to have bad family and parent–child connections.

Conversely, students' depression level has a significantly negative impact on their academic performance with β and p -values of −0.319 and 0.001. According ( 111 ), anxiety and melancholy have a negative influence on a student's academic performance. Adolescents and young adults suffer from depression, which is a common and dangerous mental illness. It's linked to an increase in family issues, school failure, especially among teenagers, suicide, drug addiction, and absenteeism. While the transition to adulthood is a high-risk period for depression in general ( 5 ), young people starting college may face extra social and intellectual challenges that increase their risk of melancholy, anxiety, and stress ( 112 ). Students' high rates of depression, anxiety, and stress have serious consequences. Not only may psychological morbidity have a negative impact on a student's academic performance and quality of life, but it may also disturb family and institutional life ( 107 ). Therefore, long-term untreated depression, anxiety, or stress can have a negative influence on people's ability to operate and produce, posing a public health risk ( 113 ).

Theoretical Implications

The current study makes various contributions to the existing literature on servant leadership. Firstly, it enriches the limited literature on the role of family and academic stress and their impact on students' depression levels. Although, a few studies have investigated stress and depression and its impact on Students' academic performance ( 14 , 114 ), however, their background i.e., family and institutions are largely ignored.

Secondly, it explains how the depression level impacts students' academic learning, specifically in the Asian developing countries region. Though a substantial body of empirical research has been produced in the last decade on the relationship between students' depression levels and its impact on their academic achievements, however, the studies conducted in the Pakistani context are scarce ( 111 , 115 ). Thus, this study adds further evidence to prior studies conducted in different cultural contexts and validates the assumption that family and academic stress are key sources depression and anxiety among students which can lead toward their low academic grades and their overall performance.

This argument is in line with our proposed theory in the current research i.e., cognitive appraisal theory which was presented in 1966 by psychologist Richard Lazarus. Lazarus's theory is called the appraisal theory of stress, or the transactional theory of stress because the way a person appraises the situation affects how they feel about it and consequently it's going to affect his overall quality of life. In line with the theory, it suggests that events are not good or bad, but the way we think about them is positive or negative, and therefore has an impact on our stress levels.

Practical Implications

According to the findings of this study, high levels of depressive symptoms among college students should be brought to the attention of relevant departments. To prevent college student depression, relevant departments should improve the study and life environment for students, try to reduce the generation of negative life events, provide adequate social support for students, and improve their cognitive and coping capacities to improve their mental qualities.

Stress and depression, on the other hand, may be managed with good therapy, teacher direction, and family support. The outcomes of this study provide an opportunity for academic institutions to address students' psychological well-being and requirements. Emotional well-being support services for students at Pakistan's higher education institutions are lacking in many of these institutions, which place a low priority on the psychological requirements of these students. As a result, initiatives that consistently monitor and enhance kids' mental health are critical. Furthermore, stress-reduction treatments such as biofeedback, yoga, life-skills training, mindfulness meditation, and psychotherapy have been demonstrated to be useful among students. Professionals in the sector would be able to adapt interventions for pupils by understanding the sources from many spheres.

Counseling clinics should be established at colleges to teach students about stress and sadness. Counselors should instill in pupils the importance of positive conduct and decision-making. The administration of the school should work to create a good and safe atmosphere. Furthermore, teachers should assume responsibility for assisting and guiding sad pupils, since this will aid in their learning and performance. Support from family members might also help you get through difficult times.

Furthermore, these findings support the importance of the home environment as a source of depression risk factors among university students, implying that family-based treatments and improvements are critical in reducing depression among university students.

Limitations and Future Research Implications

The current study has a few limitations. The researcher gathered data from the higher education level of university students studying in Islamabad and Rawalpindi institutions. In the future, researchers are required to widen their region and gather information from other cities of Pakistan, for instance, Lahore, Karachi, etc. Another weakness of the study is that it is cross-sectional in nature. We need to do longitudinal research in the future to authoritatively assert the cause-and-effect link between academic and familial stress and their effects on students' academic performance since cross-sectional studies cannot establish significant cause and effect relationships. Finally, the study's relatively small sample size is a significant weakness. Due to time and budget constraints, it appears that the capacity to perform in-depth research of all firms in Pakistan's pharmaceutical business has been limited. Even though the findings are substantial and meaningful, the small sample size is predicted to limit generalizability and statistical power. This problem can be properly solved by increasing the size of the sample by the researchers, in future researches.

Data Availability Statement

Ethics statement.

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

Author Contributions

All authors contributed to conceptualization, formal analysis, investigation, methodology, writing and editing of the original draft, and read and agreed to the published version of the manuscript.

This work was funded by the 2020 Heilongjiang Province Philosophy and Social Science Research Planning Project on Civic and Political Science in Universities (Grant No. 20SZB01). This work is supported by the Scientific Grant Agency of the Ministry of Education, Science, Research, and Sport of the Slovak Republic and the Slovak Academy Sciences as part of the research project VEGA 1/0797/20: Quantification of Environmental Burden Impacts of the Slovak Regions on Health, Social and Economic System of the Slovak Republic.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

Authors would like to thank all persons who directly or indirectly participated in the completion of this manuscript.

Class of 2024 Master’s Student Ayden Cohn: presenting a better future for nuclear reactors

Ayden Cohn has excelled in the field of nuclear engineering, and his efforts have earned him the title of Outstanding Master's Student in the College of Engineering.

• Alex Parrish

18 Apr 2024

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Ayden Cohn came to Virginia Tech in 2018, after graduating from Granby High School in Norfolk, Virginia. He was the valedictorian of a class of more than 400 peers. He chose to major in Mechanical Engineering and minor in both green engineering and nuclear engineering, blending those disciplines into his interest in the field of nuclear reactors.

Two years after completing his undergraduate studies, Cohn is graduating with a pair of master’s degrees, one from the Pamplin College of Business and another from the College of Engineering , where he has been named the Outstanding Master’s Student. The award was formally presented on March 28 at a reception hosted by the Virginia Tech Graduate School following a nomination and review through the college, reflecting Cohn's excellence in research.

Cohn won a scholarship from the Department of Energy during his junior year at Virginia Tech, which is only given to a small group of students pursuing careers in the nuclear engineering field. He also completed two internships with the Nuclear Regulatory Commission (NRC) in 2022 and 2023, and he gained hands-on experience in Blacksburg nuclear engineering labs as well. 

“When I was a junior, I started getting involved in research,” said Cohn. “I worked with Mark Pierson on small fusion devices that produce neutron output, which first got me involved in nuclear research.” 

He also found his way to the Multi-Phase Flow and Thermal-Hydraulics Lab (MFTL) of Yang Liu during his senior year, eventually becoming a group member for a project funded by the NRC in partnership with Rensselaer Polytechnic Institute (RPI). The work included a study of how fuel rods in nuclear reactors are cooled by water during different boiling conditions. The data will be used to create virtual simulations so future nuclear reactors can be tested for safety before any physical structures are even built.

“The research I conducted in Dr. Liu’s lab produces data that is sent directly to the NRC,” said Cohn. “It will be used to analyze future nuclear reactor designs. I believe it will have a big impact on new reactors and help ensure that any approved reactor is safe. That’s the biggest obstacle to phasing out fossil fuels in favor of nuclear technology, assuring the public that reactors are safe.” 

Liu commented on the value added to his team by Cohn's work.

"Ayden joined our lab with a strong background in reactor thermal hydraulics, which makes him an ideal fit for the project funded by the NRC," Liu said. "Having him on the project has been a tremendous asset.”

In pursuit of his nuclear engineering master’s, Cohn finished his academic studies during his first year of graduate school thanks in large part to the accelerated undergraduate/graduate program in mechanical engineering . His second year included a deep dive into the research he had started with Liu. To make the most of his time in graduate school, he chose to additionally enroll in the Master of Business Administration – Business Analytics through the Pamplin College of Business. The studies in that area gave him a new way to view data, but also taught him how to communicate his data more effectively.

“I’ve learned how to explain my engineering results in ways that are more meaningful,” said Cohn. “Some of the classes in the business program taught me effective strategies to present visuals, and draw your audience’s attention to what’s really important.”

Cohn packed his gear in March and journeyed to the RPI Thermal-Hydraulics Lab’s test facility to conduct a larger-scale version of the tests he performed in Liu’s lab.

He has been active in the Virginia Tech chapter of the American Nuclear Society, and will present his research at their annual conference in June. In July, he starts a job in North Carolina with General Electric where he will work on a team designing nuclear reactors.  

Chelsea Seeber

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