influence of music in mental health essay

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• Published: 30 August 2019

The effects of playing music on mental health outcomes

• Laura W. Wesseldijk 1 , 2 ,
• Fredrik Ullén 1   na1 &
• Miriam A. Mosing 1 , 3   na1  

Scientific Reports volume  9 , Article number:  12606 ( 2019 ) Cite this article

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• Behavioural genetics
• Psychiatric disorders
• Risk factors

The association between active musical engagement (as leisure activity or professionally) and mental health is still unclear, with earlier studies reporting contrasting findings. Here we tested whether musical engagement predicts (1) a diagnosis of depression, anxiety, schizophrenia, bipolar or stress-related disorders based on nationwide patient registers or (2) self-reported depressive, burnout and schizotypal symptoms in 10,776 Swedish twins. Information was available on the years individuals played an instrument, including their start and stop date if applicable, and their level of achievement. Survival analyses were used to test the effect of musical engagement on the incidence of psychiatric disorders. Regression analyses were applied for self-reported psychiatric symptoms. Additionally, we conducted co-twin control analyses to further explore the association while controlling for genetic and shared environmental confounding. Results showed that overall individuals playing a musical instrument (independent of their musical achievement) may have a somewhat increased risk for mental health problems, though only significant for self-reported mental health measures. When controlling for familial liability associations diminished, suggesting that the association is likely not due to a causal negative effect of playing music, but rather to shared underlying environmental or genetic factors influencing both musicianship and mental health problems.

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Introduction

The high suicide rate among famous musicians over the last few years, e.g. Soundgarden’s Chris Cornell, Linkin Park’s Chester Bennington, Avicii and the Prodigy’s Keith Flint, has received a lot of media attention and raised the question about a possible relationship between mental health problems and musicianship. In line with that, a recent survey among 2,211 British self-identified professional musicians found musicians to be up to three times more likely to report depressive problems than individuals in the general population 1 . Furthermore, several famous people engaged in creative professions other than musicianship were also known for their psychiatric illnesses, like Vincent van Gogh, Ernest Hemingway or John Nash. It has been shown that unaffected relatives of individuals with bipolar disorder or schizophrenia have higher levels of creativity 2 , 3 , 4 , 5 . Overall, such findings suggest that creativity and musicianship are risk factors for mental health problems.

On the other hand, there are many studies that report positive relationships between musical engagement and indicators of mental health, thus suggesting the opposite, namely that engagement in music could be protective against psychiatric problems. Although epidemiological studies investigating the association between music and the risk of mental health problems are rare – for a review, see 6 – the few existing ones all tend to suggest a positive effect of music 7 . For example, singing or playing music has been reported to be have a positive influence on various subjective health outcomes, including anxiety and depression 8 . Singing in a choir is related to higher self-rated quality of life and satisfaction with health 9 , and playing an instrument, and singing or performing in theater, tend to be associated with increased self-rated health in women, but decreased all-cause mortality in men and not vice versa 10 . Hours of music practice has been shown to be associated with lower alexithymia (i.e., a dysfunction in emotional awareness, social attachment, and interpersonal relating) 11 . Finally, in 50,797 Norwegian males, but not in females, it was found that active participation in music, singing or theater predicted significantly lower depressive symptoms 12 . It is important to note that the measures of health outcomes in these studies are retrospective self-reports. Therefore, the outcomes could partly reflect characteristics of the rater and may be subject to a recall bias.

Furthermore, there are numerous reviews on the effect of music interventions, both active (e.g. performing) and passive (e.g. listening), on individuals in clinical settings, e.g. during medical procedures or in mental health clinics (for reviews in children, see 13 , 14 , 15 , 16 , 17 ; for reviews in adults, see 18 , 19 , 20 ). The majority of reviews conclude that music interventions have a positive effect on pain, mood, and anxious or depressive symptoms in both children and adults in clinical settings. This suggests not only a positive association in line with the epidemiological research, but also potentially a causal relationship. It is important to note that most of the music interventions described in these studies have been tailored to address individually assessed needs of a client by a music therapist, which differs significantly from self-initiated musical engagement in daily life. Furthermore, as pointed out in most of these reviews, it is difficult to draw firm conclusions about protective effect of music due to the mixed quality of many of the conducted studies, i.e., studies had small samples, suffered from bias due to methodological issues, and there was great variability among the results of the studies.

In sum, the direction of the association between musical engagement and mental health is still unclear with powerful population based research still failing to establish a relation unequivocally. Furthermore, it seems that differentiating between active amateur and professional musicians might explain the discrepancy between, on the one hand research reporting beneficial effects of music in everyday life on mental health, and on the other hand the high rate of depression and suicides among professional musicians. This view is in line with findings from the recent study of Bonde, et al . 21 in which active professional musicians reported more health problems than active amateur musicians, while active amateur musicians reported significantly better self-reported health than non-musicians. Possibly, the strain and pressure experienced by professional musicians may override a possible overall positive effect of musical engagement. Furthermore, an association between engagement in music and mental health problems on a population level does not necessarily reflect causal effects; it could also reflect reverse causation or underlying shared genetic or shared environmental factors that influence both the choice to engage in music and the development of psychiatric problems. It is well known that genetic factors play a role both in mental health problems 22 and in individual variation in music-related abilities 23 . In line with that, there is evidence that the association between creativity and psychiatric disorders is largely driven by underlying shared genetic factors 24 . Studying twins can reduce genetic and shared environmental confounding and strengthen causal inferences.

Here, using a large genetically informative sample of Swedish twins, we aim to investigate whether there is an association between active musical engagement defined by whether an individual plays an instrument, on an amateur and professional level, and mental health and if so, whether the relationship is consistent with a causal hypothesis, i.e., that musical engagement truly affects mental health. We use data from the Swedish nationwide in-patient and outpatient registers for psychiatric diagnoses (i.e., diagnosis of depression, anxiety disorder, schizophrenia, bipolar, stress disorder) as well as self-reports on mental health problems (depressive, burnout and schizotypal symptoms). As the association between playing sport and mental health is already well established, we conducted sensitivity analyses investigating a protective effect of sport against psychiatric problems in this sample.

Participants

Data for the present study was collected as part of “the Study of Twin Adults: Genes and Environment” (STAGE), a sub-study in a cohort of approximately 32,000 adult twins registered with the Swedish Twin Register (STR). The STAGE study sent out a web survey in 2012–2013 inquiring about, musical engagement and musical achievement and other potentially music related traits. The 11,543 responders were aged between 27 and 54 years and data were available for 10,776 individuals on musical engagement and for 6,833 on musical achievement.

The National Patient Register (NPR) records the use of the health care system in Sweden, which has nationwide coverage ensuring equal access to health care for all residents, using a 10-digit personal identification number assigned to all Swedish residents 25 . The NPR includes an in-patient register (IPR) and out-patient register (OPR). The IPR contains information about hospitalizations since 1964 (with full national coverage since 1977), while the OPR covers outpatient visits since 2001 26 . The Cause of Death Register (CDR) contains information from death records since 1961 27 . The Swedish twins from the STAGE study were linked to records from the IPR, OPR and CDR.

Informed consent was obtained from all participants. The study was approved by the Regional Ethics Review Board in Stockholm (Dnr 2011/570-31/5, 2012/1107-32, 2018/866-32). All research methods were performed in accordance with relevant guidelines and regulations.

Musical engagement

Participants were asked whether they ever played an instrument. Those who responded positively were asked at what age they started to play, whether they still played an instrument and, if not, at what age they stopped playing. From these questions, a music status variable was created (0: does not play, 1: used to play, 2: plays).

Sport engagement

Participants reported on whether they ever actively trained a sport (excluding exercise training or physical activity in general). Information on age they started training a sport, whether they still played and at what age they stopped playing resulted in a sport status variable with 0 ‘does not play’, 1 ‘used to play’ and 2 ‘plays sport’.

Musical achievement

Musical achievement was measured with a Swedish version of the Creative Achievement Questionnaire (CAQ) that assesses different domains of creativity, including music 28 , 29 . Individuals were asked to rate their musical achievement on a seven-point scale: 1 ‘I am not engaged in music at all’, 2’I have played or sang privately, but I have never played, sang or showed my music to others’, 3’I have taken music lessons, but I have never played, sang or showed my music to others’, 4 ‘I have played or sung, or my music has been played in public concerts in my home town, but I have not been paid for this’, 5 ‘I have played or sung, or my music has been played in public concerts in my home town, and I have been paid for this’, 6 ‘I am professionally active as a musician’ and 7 ‘I am professionally active as a musician and have been reviewed/featured in national or international media and/or have received an award for my musical activities’. To differentiate between amateur and professional musicians, we converted the scale to three groups: 1 ‘no engagement in music’, 2–4 ‘making music on an amateur level’, and 5–7 ‘professionally active in music’.

Registry-based mental health outcomes

For each individual we derived information (diagnosis and date of first diagnosis) on incidence of depression, anxiety disorder, schizophrenia, bipolar disorder, or stress disorder based on clinical diagnoses after any inpatient or outpatient visit, or underlying cause of death registered in the national registers according to the International Classification of Diseases (ICD) codes as reported in Table  1 . We created an ‘any psychiatric diagnosis’ variable indicating whether the participant has ever been diagnosed with any of the five categories of clinical diagnoses above. For this variable, we selected the earliest date of diagnosis in case of comorbidity.

Questionnaire-based self-reported mental health

In addition, self-reports on mental health outcomes (i.e., depressive, burnout and schizotypal symptoms) obtained in the web survey were analyzed. Depressive symptoms were measured with the depression scale of the Hopkins Symptom Checklist 30 . This scale contains of six items all ranging from 0 to 4 (0 ‘not at all’ to 4 ‘extremely’), measuring depressive symptoms in a work-related context, with higher scores indicating more depressive symptoms. Burn-out symptoms related to work were measured with the Emotional exhaustion subscale of the Maslach Burnout Inventory-General Survey 31 . This scale consists of five items that range from 1 (every day) to 6 (a few times per year or less/never). Therefore, as higher scores reflect less burnout symptoms, we reversed this scale so that higher scores indicate more burnout symptoms in line with the other mental health outcomes. Schizotypal symptoms were measured with the “Positive Dimension Frequency Scale” of the Community Assessment of Psychic Experiences (CAPE) questionnaire 32 . The score is based on 20 positive symptom items that can be answered with four different symptom frequency levels, from 1 ‘never’ to 4 ‘almost always’. Higher scores indicate more schizotypal symptoms. The Cronbach alpha reliability in present study was 0.89 for the depressive symptom scale, 0.87 for the burnout symptom scale and 0.79 for the schizotypal symptom scale.

Level of education

Educational achievement was dichotomized into ‘low and intermediate’ (1 to 7; unfinished primary school to bachelor education) and ‘high’ (8 to 10; master education to PhD).

Statistical analyses

All analyses were conducted in STATA 15.

Survival analyses , i.e., Cox proportional hazard regression, were conducted to explore the effect of musical engagement and musical achievement on the risk to receive a registry-based diagnosis of a psychiatric disorder 33 . Survival analysis is a method to analyze data where the outcome variable is the time until an event happens. The time (years) from the age of twelve to either the date of first receiving a psychiatric diagnosis or to the date of censoring (i.e., date of death or end of follow-up at January 1, 2015) were used as the time scale (i.e., the survival time). For the analyses on the effect of musical engagement , we had to take into account that some individuals had not yet started playing an instrument at the age of twelve (i.e., would start at a later age), or stopped playing at some stage. Therefore, years were split on whether the individual did not play, stopped or started playing, or currently played a musical instrument using the stsplit statement to differentiate between the three levels of musical engagement. We used Cox proportional hazard regressions, a method that assumes the effect upon survival to be constant over time, to calculate hazard ratios (HRs) with 95% confidence intervals. The HRs represent the effects of 1) playing an instrument versus never having played an instrument or 2) having played an instrument (but stopped before diagnosis) versus never having played an instrument on the baseline risk for a mental health diagnosis (independent of playing status) during the follow-up period. A HR value greater than one indicates an increased risk, while a value below one indicates a protective effect. Additionally, we conducted the survival analyses to estimate the effect of musical achievement in a lifetime on the risk of a mental health diagnosis, in which the HRs represent 1) the effect of having performed music as an amateur versus not being involved in music, or 2) the effect of having performed music professionally versus not being involved in music. As we analyzed the three level musical achievement in a lifetime, we did not split years on age (assuming that individuals have been on a lifelong ‘achievement’ trajectory). To correct for relatedness in the twin sample, the robust standard error estimator for clustered observations was used 34 . We fitted separate survival models for each of the five psychiatric disorder diagnoses as well as for the ‘any psychiatric diagnosis’ variable. Thus, first, we in total fitted six models for the effect of musical engagement and another six models for musical achievement. All models included sex as a covariate. Additionally, we fitted all models corrected for level of education, resulting in a small loss of data due to missing information for some individuals, therefore reducing the power. For each model, the proportional hazards assumption was tested using Schoenfeld residuals. No evidence for deviation from the proportional hazards assumption was found for any of the models (all p values > 0.01). As a sensitivity analysis, the above-described models for musical engagement (in which we used the stsplit statement) were repeated with sport engagement as the exposure variable instead, to estimate the effect of playing sport on registry-based psychiatric disorder diagnoses.

Self-reported mental health outcomes

Linear regression analyses were performed to explore the effect of musical engagement and musical achievement on the self-rated continuous measures of depressive symptoms, burnout symptoms and schizotypal symptoms. To correct for relatedness in the twin sample, we used the robust standard error estimator for clustered observations. We included sex as a covariate. Additionally, we ran the analyses corrected for level of education. As a sensitivity analysis, we estimated the effect of sport engagement on depressive, burnout and schizotypal symptoms using linear regression analyses.

Co-twin control analyses (within-pair analyses)

Within-pair analyses in identical twins were conducted to further explore the association between musical engagement and receiving a mental health diagnosis when controlling for genetic and shared environmental factors. As monozygotic (MZ) twins are genetically identical and share their family environment, studying identical twins excludes confounding in case a genetic predisposition or shared environmental influence affects both outcome (mental health problems), and exposure (music engagement). Therefore, if music engagement truly causes a lower/higher risk for receiving a mental health diagnosis, we would expect the MZ twin that plays music to have a lower/higher risk of psychiatric problems than his or her co-twin that does not play music. Conditional Cox regression models, with the strata statement to stratify by pair identifier, were fitted for the mental health diagnoses to estimate HRs with 95% confidence intervals. Notably, only complete identical twin pairs discordant for exposure (i.e., music engagement) and outcome (i.e., the psychiatric disorder diagnosis) contribute to the within-pair analyses. The conditional logistic regression estimates the effect of the difference between the two observations in the strata. Twins are regarded as discordant for the outcome when the time of the psychiatric diagnosis differs. Due to the low prevalence of schizophrenia and bipolar disorder in the complete twin pairs, these phenotypes were excluded from the within-pair analyses.

Additionally, to explore further the effect of music engagement on the self-rated continuous measures of depressive symptoms, burnout symptoms and schizotypal symptoms, we conducted within-pair linear regression analyses using the xtreg fe statement to stratify by twin pair. In within-pair analyses in identical twins correcting for sex is not required as each twin is matched to his or her co-twin. To increase power, we also included data from same-sex dizygotic (DZ) twins (who share on average 50% of their genetic makeup and 100% of their family environment).

Descriptives

Information on mental health outcomes and musical engagement was available for 9,816 individuals [2,212 complete twin pairs (1,055 MZ, 661 dizygotic same-sex (DZ), 496 dizygotic opposite-sex (DOS) twins) and 5,392 individual twins]. Among these individuals, data on musical achievement were available for 6,295 individuals [1,208 complete twin pairs (627 MZ, 342 DZ, 239 DOS) and 3,879 individual twins]. Characteristics of the participants are reported in Table  2 .

Women were more likely to initiate playing an instrument than men (37.7% of men versus 20.5% of women), while roughly the same amount of men and women remained actively involved in music in adulthood (23.3% of men and 21.9% of women). More men (8.5%) than women (5%) played music professionally.

Although overall, there was an overall trend towards a somewhat elevated risk for psychiatric disease in those engaged with music, neither playing music nor having played music in the past (Fig.  1 ), nor professional musicianship (Fig.  2 ) was significantly associated with the risk for any of the psychiatric disorders. The analyses adjusted for level of education showed similar results (see Table  S1 for musical engagement and Table  S2 for musical achievement, in the supplementary material), with the exception that individuals who played an instrument had a significantly higher risk (39%) of being diagnosed with an anxiety disorder (HR 1.39, CI 1.01–1.92) compared to those who never played an instrument. In terms of covariates, we found females to have a higher risk for depression (92%), anxiety disorder (92%), and stress-related disorders (58%) (Table  S1 ). Additionally, individuals with higher levels of education had a significantly lower risk for psychiatric disorders, depression, anxiety disorder, schizophrenia or bipolar disorder (Table  S1 ).

Music engagement and registry-based mental health outcomes. Sex is included as covariate.

Music achievement and registry-based mental health outcomes. Sex is included as a covariate.

Self-reported mental health

Results of the regression analyses with self-reported mental health symptoms indicated that playing an instrument was significantly associated with more schizotypal symptoms and depressive and burnout symptoms in a work context (see left part of Table  3 ). Having played an instrument in the past did not significantly influence any of the self-rated mental health outcomes. Furthermore, even though professional and amateur musicians report more burnout and schizotypal symptoms than non-players, individuals who played music professionally did not experience significantly more depressive, burnout or schizotypal symptoms than individuals who play music on an amateur level (see right part of Table  3 ). When analyses were repeated adjusting for level of education (results not shown) all results remained the same.

Sensitivity sport analyses

Results of the sensitivity analyses on the registry-based mental health outcomes showed that individuals who actively played sports were less likely to develop any psychiatric disorder, as well as depression, anxiety, and bipolar disorder (see Fig.  S1 ). There was no sustained beneficial effect of past sports engagement after stopping with exercise. The analyses adjusted for level of education showed the same results.

Regression analyses on the self-reported mental health outcomes showed that individuals who actively play sports were significantly less likely to report depressive symptoms (β = −0.23, p < 0.001) and burnout symptoms (β = −0.20, p < 0.001), but not schizotypal symptoms (β = 0.00, p = 0.96). Past sport activities were unrelated to the self-reported mental health outcomes (p values range between 0.08 and 0.20). Including level of education in the analyses did not affect the results.

Co-twin control analyses

Results of the co-twin control analyses for both the registry-based and self-reported mental health measures are shown in Table  4 . None of the within-pair estimates were significant. However, overall, the effect sizes (HR or beta) moved closer to zero with increased controlling of shared liability.

We aimed to investigate the association between musical engagement in everyday life and mental health in a large cohort of Swedish twins. Although the findings were somewhat mixed, overall results suggest that individuals who actively play a musical instrument (but not necessarily professionally) may have a somewhat increased risk for mental health problems. However, when controlling for familial liability these associations became weaker and non-significant suggesting that the association is likely explained by underlying shared factors influencing both musicianship and mental health problems.

While analyses using registry-based mental health diagnoses showed no significant association between music playing or professional musical engagement and psychiatric diagnoses, the direction of the effect was trending towards a somewhat increased risk for psychiatric diagnoses for those actively engaged with music. Results from the self-reported mental health outcomes further supported this; individuals playing an instrument report more depressive, burnout and schizotypal symptoms. This is in contrast with previous epidemiological and clinical studies reporting positive effects of musical engagement on anxious and depressive symptoms 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 . Further, a recent study by Fancourt and Steptoe 35 found cultural engagement to decrease the development of depression in older ages. However, it appears likely that it is important to distinguish between general cultural engagement, i.e., visits to the theatre, concerts or opera, the cinema or an art gallery, exhibition or museum) and active playing of a musical instrument, which is the focus of the present study. Playing a musical instrument is much more narrowly defined behavior and involves many (cognitive and physical) processes different from engaging in cultural musical activities or listening to music. On the other hand, our findings are in line with results from the survey among British professional musicians 1 and with previous findings of associations between creativity and mental health problems, i.e., that people engaging in creative activities tend to experience more psychiatric problems 4 . It is important to note that the previous epidemiological studies on mental health, the British musicians study, but also our continuous mental health outcomes, were based on self-report. An explanation could be that results of self-report reflect a different attitude towards mental health among more creative individuals, with higher acceptance and awareness of mental health problems, possibly resulting in over-reporting in the field.

Further, there is evidence that the association between creativity and psychiatric disorders can be largely attributed to underlying shared genetic factors 24 , 36 . This is in line with present results of our co-twin control analyses, which showed that the association between musicianship and mental health was attenuated when controlling for genetic and shared environmental confounding (although all analyses were non-significant). This suggests that the observed associations would partly be explained by a shared underlying etiology, (i.e., genetic or family environmental factors which affect both, individuals differences in music playing and mental health) and not by a causal effect of playing music. The within-pair results, however, should be interpreted with caution as only discordant twin pairs contribute to the co-twin control analyses, which reduced the power to find significant associations.

We found significant differences between professional or amateur musicians and non-players in self-rated health outcomes, which are in line with our findings on playing music in general. However, in neither self-rated nor registry-based data, we observed any significant differences in mental health problems between professional musicians compared to amateur musicians. This is in contrast to findings from the study of Bonde, et al . 21 in which active professional musicians reported higher numbers of overall health problems than active amateur musicians, while active amateur musicians reported significantly better self-reported health than non-musicians did. Whilst this was also a large population-based sample, this study analyzed general health instead of mental health, which likely contributes to the difference in findings.

The discrepancy in findings between registry-based mental health diagnoses and self-reported mental health could be due to an influence of rater and recall biases captured in the self-reported mental health outcomes, as discussed above. However, another explanation could be less power in the analyses with the registry-based mental health diagnoses to detect an existing effect. The power of a method to analyze survival time data depends partly on the number of psychiatric diagnoses rather than on the total sample size. In the present sample, observed post-hoc power for the survival analyses to detect a HR of 0.8 for music engagement is 88% for the incidence of a psychiatric disorder, 67% for depression, 61% for anxiety, 7% for schizophrenia, 18% for bipolar and 45% for stress disorder, reflecting the different incident rates of the disorders. As the self-reported mental health problems were measured on a continuous scale, these analyses have higher power (i.e., no cut-off score needs to be reached to obtain a full diagnosis). Nevertheless, our sensitivity analyses in the registry-based outcomes on the effect of sport did show a significant protective effect of sport against the risk of receiving a diagnosis of a psychiatric disorder, depression, anxiety and bipolar disorder in this sample, suggesting that an association can be found with the present distribution of the data if existent. Therefore, we conclude that a lack of power is not a likely explanation for our null findings in the registry-based health outcomes, and that if there truly were an effect, it would be very small.

There are some limitations of this study in addition to the ones we already touched upon. We analyzed data on psychiatric diagnoses obtained from the Swedish nationwide in-patient and outpatient registers. However, the outpatient register only reached full coverage in 2001 and it is therefore possible that some individuals were not classified with a psychiatric disorder, although they did experience mental health problems before 2001. The same holds for individuals with mental health problems who did not visit a doctor. In addition, the dichotomous rather than dimensional nature of psychiatric diagnoses excludes large parts of the continuous variation among individuals in psychiatric problems. The continuous symptom scales increase the power to detect an effect of engagement in music or sports, but may be somewhat biased. Furthermore, our study explored potential effects of active musical engagement (i.e., making music) in everyday life and therefore our findings do not allow for any conclusions about the potential effect of (personalized) musical interventions on mental health problems. Lastly, as mentioned earlier, the sample of discordant twin pairs contributing to the co-twin control analyses was small, resulting in low power to detect effects.

To our knowledge, the present population-based study is the only genetically informative large-scale study to investigate associations between active engagement in music (both as a leisure activity and professionally) and registry-based as well as self-reported mental health outcomes. Rather than a protective effect of music engagement in everyday life as often suggested, our findings suggest that individuals actively engaged in music playing, but not only professional musicians, may have a somewhat elevated risk for mental health problems. This association may at least partly be due to shared underlying etiology and it is unlikely that it reflects a causal effect of playing music.

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Acknowledgements

The present work was supported by the Marcus and Amalia Wallenberg Foundation (MAW 2018.0017), and the Bank of Sweden Tercentenary Foundation (M11-0451:1). We acknowledge The Swedish Twin Registry for access to data. The Swedish Twin Registry is managed by the Karolinska Institutet and receives funding through the Swedish Research Council under the grant no 2017-00641. Open access funding provided by Karolinska Institute.

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Fredrik Ullén and Miriam A. Mosing jointly supervised this work.

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Department of Neuroscience, Karolinska Institutet, Solnavägen 9, SE-171 77, Stockholm, Sweden

Laura W. Wesseldijk, Fredrik Ullén & Miriam A. Mosing

Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ, Amsterdam, The Netherlands

• Laura W. Wesseldijk

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels v 12A, 171 77, Stockholm, Sweden

• Miriam A. Mosing

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F.U., M.M. and L.W. developed the study design. L.W. performed the data analysis and interpretation under the supervision of F.U., M.M. L.W. and M.M. drafted the manuscript, and F.U. provided critical revisions. All authors approved the final version of the manuscript for submission.

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Wesseldijk, L.W., Ullén, F. & Mosing, M.A. The effects of playing music on mental health outcomes. Sci Rep 9 , 12606 (2019). https://doi.org/10.1038/s41598-019-49099-9

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How Listening to Music Can Have Psychological Benefits

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Steven Gans, MD is board-certified in psychiatry and is an active supervisor, teacher, and mentor at Massachusetts General Hospital.

Listening to music can be entertaining, and some research suggests that it might even make you healthier. Music can be a source of pleasure and contentment, but there are many other psychological benefits as well. Music can relax the mind, energize the body, and even help people better manage pain.

The notion that music can influence your thoughts, feelings, and behaviors probably does not come as much of a surprise. If you've ever felt pumped up while listening to your favorite fast-paced rock anthem or been moved to tears by a tender live performance, then you easily understand the power of music to impact moods and even inspire action.

The psychological effects of music can be powerful and wide-ranging. Music therapy is an intervention sometimes used to promote emotional health, help patients cope with stress, and boost psychological well-being. Some research even suggests that your taste in music can provide insight into different aspects of your personality .

Music Can Improve Cognitive Performance

Eternity in an Instant / Getty Images

Research suggests that background music, or music that is played while the listener is primarily focused on another activity, can improve performance on cognitive tasks in older adults. One study found that playing more upbeat music led to improvements in processing speed, while both upbeat and downbeat music led to benefits in memory.

So the next time you are working on a task, consider turning on a little music in the background if you are looking for a boost in your mental performance. Consider choosing instrumental tracks rather than those with complex lyrics, which might end up being more distracting.

Music Can Reduce Stress

It has long been suggested that music can help reduce or manage stress. Consider the trend centered on meditative music created to soothe the mind and inducing relaxation.

Fortunately, this is one trend supported by research. Listening to music can be an effective way to cope with stress.

In one 2013 study, participants took part in one of three conditions before being exposed to a stressor and then taking a psychosocial stress test. Some participants listened to relaxing music, others listened to the sound of rippling water, and the rest received no auditory stimulation.

The results suggested that listening to music had an impact on the human stress response , particularly the autonomic nervous system . Those who had listened to music tended to recover more quickly following a stressor.

Music Can Help You Eat Less

One of the most surprising psychological benefits of music is that it might be a helpful weight-loss tool. If you are trying to lose weight, listening to mellow music and dimming the lights might help you achieve your goals .

According to one study, people who ate at low-lit restaurants where soft music was played consumed 18% less food than those who ate in other restaurants.  

The researchers suggest that music and lighting help create a more relaxed setting. Since the participants were more relaxed and comfortable, they may have consumed their food more slowly and have been more aware of when they began to feel full.

You might try putting this into practice by playing soft music at home while you eat dinner. By creating a relaxing setting, you may be more likely to eat slowly and, therefore, feel fuller sooner.

Music Can Improve Your Memory

Lots of students enjoy listening to music while they study, but is that such a great idea? Some feel like listening to their favorite music as they study improves memory , while others contend that it simply serves as a pleasant distraction.

Research suggests that it may help. But it depends upon a variety of factors, including the type of music, the listener's enjoyment of that music, and even how musically well-trained the listener may be.

In one study, musically naive students learned better when listening to positive music, possibly because these songs elicited more positive emotions without interfering with memory formation.

However, musically trained students tended to perform better on learning tests when they listened to neutral music, possibly because this type of music was less distracting and easier to ignore. If you tend to find yourself distracted by music, you may be better off learning in silence or with neutral tracks playing in the background.

Another study found that participants learning a new language showed improvement in their knowledge and abilities when they practiced singing new words and phrases versus just regular speaking or rhythmic speaking.  

Music Can Help Manage Pain

Research has shown that music can be very helpful in the management of pain. One study of fibromyalgia patients found that those who listened to music for just one hour a day experienced a significant reduction in pain compared to those in a control group .  

At the end of the four-week study period, participants who had listened to music each day experienced significant reductions in feelings of pain and depression. Such results suggest that music therapy could be an important tool in the treatment of chronic pain.

A 2015 review of research on the effects of music on pain management found that patients who listened to music before, during, or even after surgery experienced less pain and anxiety than those who did not listen to music.  

While listening to music at any point in time was effective, the researchers noted that listening to music pre-surgery resulted in better outcomes. The review looked at data from more than 7,000 patients and found that music listeners also required less medication to manage their pain.

There was also a slightly greater, though not statistically significant, improvement in pain management results when patients were allowed to select their own music.

Music May Help You Sleep Better

Insomnia is a serious problem that affects people of all age groups. While there are many approaches to treating this problem, research has demonstrated that listening to relaxing classical music can be a safe, effective, and affordable remedy.​

In a study looking at college students, participants listened to classical music, an audiobook, or nothing at all at bedtime for three weeks. Researchers assessed sleep quality both before and after the intervention.

The study found that participants who had listened to music had significantly better sleep quality than those who had listened to the audiobook or received no intervention.  

Music Can Improve Motivation

There is a good reason why you find it easier to exercise while you listen to music. Researchers have found that listening to fast-paced music motivates people to work out harder.

One experiment designed to investigate this effect tasked 12 healthy male students with cycling on a stationary bike at self-paced speeds. On three different trials, the participants biked for 25 minutes at a time while listening to a playlist of six different popular songs of various tempos.

Unknown to the listeners, the researchers made subtle differences to the music and then measured performance. The music was left at a normal speed, increased by 10%, or decreased by 10%.

Speeding up the tracks resulted in increased performance in terms of distance covered, the speed of pedaling, and power exerted. Conversely, slowing down the music's tempo led to decreases in all of these variables .

So if you are trying to stick to a workout routine, consider loading up a playlist filled with fast-paced tunes that will help boost your motivation and enjoyment of your exercise regimen.

Music Can Improve Mood

Another of the science-backed benefits of music is that it just might make you happier.

In one examination of the reasons why people listen to music, researchers discovered that music played an important role in relating arousal and mood. Participants rated music's ability to help them achieve a better mood and become more self-aware as two of the most important functions of music.

Another study found that intentionally trying to boost moods by listening to positive music could have an impact within two weeks. Participants were instructed to purposefully attempt to improve their mood by listening to positive music each day for two weeks.

Other participants listened to music but were not directed to become happier intentionally. When participants were later asked to describe their own levels of happiness, those who had intentionally tried to improve their moods reported feeling happier after just two weeks.

Music May Reduce Symptoms of Depression

Researchers have also found that music therapy can be a safe and effective treatment for a variety of disorders, including depression .

One study found that music therapy was a safe, low-risk way to reduce depression and anxiety in patients suffering from neurological conditions such as dementia, stroke, and Parkinson's disease.

While music can certainly have an impact on mood, the type of music is also important. Classical and meditation music offer the greatest mood-boosting benefits, while heavy metal and techno music are ineffective and even detrimental.

Music Can Improve Endurance and Performance

Another important psychological benefit of music lies in its ability to boost performance. While people have a preferred step frequency when walking and running, scientists have discovered that the addition of a strong, rhythmic beat, such as fast-paced musical track, could inspire people to pick up the pace.  

Runners are not only able to run faster while listening to music; they also feel more motivated to stick with it and display greater endurance. The ideal tempo for workout music is somewhere between 125 and 140 beats per minute.

While research has found that synchronizing body movements to music can lead to better performance and increased stamina, the effect tends to be the most pronounced in cases of low to moderate intensity exercise. In other words, the average person is more likely to reap the rewards of listening to music more than a professional athlete might.

So why does music boost workout performance? Listening to music while working out lowers a person's perception of exertion. You're working harder, but it doesn't seem like you're putting forth more effort.

Because your attention is diverted by the music, you are less likely to notice the obvious signs of exertion such as increased respiration, sweating, and muscle soreness.

A Word From Verywell

Music can inspire and entertain, but it also has powerful psychological effects that can improve your health and well-being.

Instead of thinking of music as pure entertainment, consider some of the major mental benefits of incorporating music into your everyday life. You might find that you feel more motivated , happy, and relaxed as a result.

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By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Understanding the Influence of Music on People’s Mental Health Through Dynamic Music Engagement Model

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Research shows that music helps people regulate and process emotions to positively impact their mental health, but there is limited research on how to build music systems or services to support this. We investigated how engagement with music can help the listener support their mental health through a case study of the BTS ARMY fandom. We conducted a survey with 1,190 BTS fans asking about the impact BTS’ music has on their mental health and wellbeing. Participants reported that certain songs are appropriate for specific types of mood regulations, attributed largely to lyrics. Reflection, connection, and comfort were the top three experiences listeners shared during and after listening to BTS’ music. External factors like knowledge about the context of a song’s creation or other fans’ reactions to a song also influenced people’s feelings toward the music. Our research suggests an expanded view of music’s impact on mental health beyond a single-modal experience to a dynamic, multi-factored experience that evolves over time within the interconnected ecosystem of the fandom. We present the Dynamic Music Engagement Model which represents the complex, multifaceted, context-dependent nature of how music influences people’s mental health, followed by design suggestions for music information systems and services.

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Bhattacharya, A., Backonja, U., Le, A., Antony, R., Si, Y., Lee, J.H. (2023). Understanding the Influence of Music on People’s Mental Health Through Dynamic Music Engagement Model. In: Sserwanga, I., et al. Information for a Better World: Normality, Virtuality, Physicality, Inclusivity. iConference 2023. Lecture Notes in Computer Science, vol 13971. Springer, Cham. https://doi.org/10.1007/978-3-031-28035-1_8

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MINI REVIEW article

Influence of music on the hearing and mental health of adolescents and countermeasures.

• Hubei Provincial Committee of the Chinese Communist Youth League, Wuhan, China

This review elaborates on the influence of music on the psychological well-being of adolescents, covering the potential advantages, drawbacks, and necessary strategic interventions associated with music exposure. Initially, we characterize music and delve into a multifaceted classification system. Music, as a pervasive art form, is categorized based on regional and national parameters, and it also distinguishes through the assorted genres and traits. The mental well-being of adolescents is significantly influenced by music through mechanisms such as the facilitation of emotional expression and regulation, fortification of social bonds and the sense of belonging, as well as the fostering of creativity and cognitive development. Nonetheless, music, if misused or associated with inappropriate content, could elicit a spectrum of issues ranging from auditory impairment, diversion of attention, addiction tendencies, to the induction of negative emotions. To counteract these potential hazards, we propose several mitigation strategies including the selection of appropriate music styles, the establishment of a wholesome music environment, the promotion of the constructive role of music education, and fostering active participation in music activities among the youth. In conclusion, we underscore the necessity of a collaborative endeavor from all sectors of society to ensure a healthy music environment for the youth, which in turn would enhance the positive influence of music on the mental health development of this population.

1. Introduction

Music, as an immersive and broad artistic medium, plays a pivotal role in the lives of adolescents. This stage of life, commonly known as adolescence, is viewed as a crucial period for psychological, social, and cognitive development; the role of music within this framework is significant. As per the research conducted by Ouergui et al. (2023) , youth display a high frequency of interaction and deep engagement with music. In the contemporary digital age, music is ubiquitous. Whether via streaming services, social media platforms, or traditional radio and television, music is woven into the fabric of young people’s lives. This pervasive presence of music provides adolescents with a means to express themselves and articulate their emotions; furthermore, it has emerged as a crucial avenue for their social interactions.

Numerous adolescents opt to convey their identities and emotions by curating and sharing music playlists ( Taruffi, 2021 ; Feneberg et al., 2023 ). This behavior extends beyond the expression of their musical esthetics; it mirrors their quest for resonance and the establishment of social relationships through music. For instance, a melancholic playlist might communicate an adolescent’s low mood, whereas an energetic playlist can depict their elation and positivity. Moreover, sharing these playlists encourages youth to find shared interests among friends and peers, thereby enhancing social connections. Concurrently, music plays a key role in shaping adolescents’ identity and self-perception ( McFerran et al., 2010 ; Haeyen and Noorthoorn, 2021 ). During this phase, adolescents engage in the process of discovering and molding their identities; the music they select and appreciate often reflects their values, beliefs, and self-concepts. This journey of self-recognition and self-expression through music significantly affects adolescents’ mental health and development.

In recent years, there has been an escalating focus on research exploring the influence of music on adolescents’ mental health. For example, Knoerl R and Neal-Barnett A discovered that youth frequently utilize music as a coping mechanism for their emotions, such as alleviating stress and enhancing mood ( Neal-Barnett et al., 2019 ; Knoerl et al., 2022 ). Further, several studies have indicated that collaborative musical activities (like choir participation or orchestra) can boost adolescents’ social skills and self-esteem ( Porter et al., 2017 ). However, some research has also highlighted potential risks associated with music, including hearing damage and distraction ( Halevi-Katz et al., 2015 ). These studies collectively underscore the profound influence of music on the mental health of adolescents.

The aim of this article is to review the existing research on the effect of music on the psychological health of adolescents, with a specific emphasis on the benefits and potential hazards of music and strategies for ensuring that adolescents can safely enjoy the psychological benefits of music. This review hopes to offer practical suggestions for parents, educators, and community workers and to guide future research in this domain.

2. Definition and classification of music

2.1. definition of music.

Music, as a universal form of human expression, has a well-known definition, but it has multiple interpretations in terms of substance and artistic features. In its essence, music is a conscious and organized expression of sound and silence ( Tervaniemi, 2023 ). It involves elements such as melody (a musical phrase formed by a series of notes), rhythm (the organization and duration of notes), harmony (two or more notes sound simultaneously), and color (the characteristics and sensations of music, often contributed by specific instruments or sound sources).

In terms of artistic features, music is regarded as a universal human language that can convey emotions, express ideas, provide comfort, and cross cultural boundaries. It is an art form with high expressiveness and depth, through which we can experience various aspects of life ( Mastnak, 2016 ).

2.2. Classification of music

The diversity of music is reflected in its broad classification. Classified by region and country, music from different regions reflects their respective cultural characteristics and traditions. For example, Chinese music is famous for its unique pentatonic scale, strong expressiveness, and rich variety of instruments ( Wang et al., 2021 ; Su and Kong, 2023 ). The characteristics of Indian music are complex rhythmic structures, such as Tala, and improvisation based on the scale (Raga; Fletcher, 1915 ; Sharma et al., 2021 ). Western classical music is known for its rigorous formal structure, rich harmony, and complex note textures ( Georges, 2017 ; Lepping et al., 2019 ).

Another classification method is based on the genre and characteristics of music. Classical music usually refers to music created between 1650 and 1900, with carefully crafted compositions and rich expressive power. Pop music is the most common type of music since the mid-20th century, characterized by simple melodies, easily accepted lyrics, and strong rhythms ( Ren, 2021 ). Jazz originated in the early 20th century in the United States and is known for its unique rhythm (such as swing rhythm) and extensive improvisation ( Roe and Lysaker, 2023 ). Rock music originated in the United States in the 1950s, and it has had a widespread impact worldwide due to its strong rhythm and gripping guitar solos ( Bogt et al., 2021 ).

Each type of music has its unique characteristics and forms of expression, providing people with various ways of expression and experience. The richness and diversity of music not only reflect human creativity but also provide a powerful tool that can influence and shape our psychological state.

3. Benefits of music

3.1. facilitates expression and regulation of emotions.

Music has long been recognized as a potent medium for expressing emotions. It enables individuals to convey a wide spectrum of complex emotions. For instance, fast-paced, high-intensity music may signify happiness and excitement, whereas slow-paced, low-key music can indicate sadness and frustration ( Dovorany et al., 2023 ). Through creating and listening to music, adolescents can easily comprehend and manage their emotions. Moreover, music serves as an instrument for emotional regulation, assisting individuals in alleviating stress, mitigating anxiety, and bolstering self-confidence ( Aalbers et al., 2017 ). Research indicates that listening to music can lower cortisol levels (a stress hormone), thereby reducing stress ( Emami et al., 2023 ). The theory of self-efficacy suggests that participation in music activities (such as learning an instrument or singing) can enhance individual self-confidence and self-esteem ( Paolantonio et al., 2020 ).

3.2. Enhances social connections and sense of belonging

Music also provides social benefits, as it serves as a shared interest and experience and fosters a sense of connection and belonging. For instance, sharing musical tastes can strengthen friendships among young people and promote the formation of social identity ( Yifan Zou and Wang, 2021 ). Additionally, participation in group music activities (such as orchestra or choir) can help adolescents develop teamwork skills and provide a robust sense of belonging and shared accomplishment ( Cores-Bilbao et al., 2019 ).

3.3. Fuels creative and intellectual development

Music is considered a vital source of creativity. Through music composition and improvisation, teenagers can freely explore and express their thoughts, emotions, and imagination ( Xia et al., 2023 ). Moreover, studies have shown that music training can positively affect intellectual development, particularly improvements in musical training correlated with mathematical, logical, and spatial intelligence ( Kim and Chung, 2023 ). Although the specific influence of music on intellectual development continues to be studied, evidence suggests that adolescents involved in music activities perform better academically than those who are not.

4. Potential drawbacks of music

Despite the widely researched and acknowledged benefits of music, its potential disadvantages, particularly when improperly used, must be recognized.

4.1. Inappropriate usage of music

Excessive and improper use of music may contribute to hearing damage. Long-term exposure to high-volume music, especially through headphones or earbuds, increases the risk of harmful noise exposure, potentially resulting in temporary or permanent hearing damage ( Hanson and Fearn, 1975 ). As a result of their limited self-regulation, adolescents may unconsciously listen to loud music, endangering their hearing health. Consequently, teenagers must be educated on safe music listening habits, including reducing volume, limiting listening duration, and using safe listening devices ( Gopal et al., 2019 ).

Additionally, excessive music listening may distract attention, thereby affecting academic and work performance ( Chen et al., 2023 ). Some argue that music enhances work efficiency, but research suggests that listening to lyrical music can distract attention, particularly when performing tasks requiring language processing ( Vasilev et al., 2018 ). Furthermore, overreliance on music might lead to habitual addiction, which is characterized by an uncontrollable urge to listen to music, potentially affecting daily life negatively.

4.2. Potential negative effect of music content

The content of music may induce or exacerbate negative emotions and behaviors. For instance, lyrics containing violence, sex, discrimination, and negativity may negatively influence adolescents ( Wang and Jiang, 2022 ). Studies have demonstrated that young people often interpret and internalize lyrics more than adults do; thus, the youth are more susceptible to these negative influences than adults ( Martino et al., 2006 ).

The emotional tone of music may influence the listeners’ emotional state. Some studies have indicated that listening to melancholic and intense music may induce or exacerbate negative emotions ( Hahn et al., 2022 ). Though young individuals may use such music to regulate or express their emotions, in the long run, excessive exposure to such music may detrimentally affect their mental health ( Figure 1 ).

Figure 1 . Schematic of music on the mental health of youth.

5. Implementing effective coping strategies

5.1. selecting appropriate music genres.

For adolescents, the choice of an appropriate music genre is critical, as it can satisfy both their personal preferences and psychological needs. This selection process should prioritize the adolescents’ preferences and psychological needs and consider the esthetic value and educational significance of music. For instance, according to Maslow’s hierarchy of needs theory, music can fulfill physiological needs (such as relaxation and stress relief), safety needs (like fostering a sense of security), social needs (enhancing belongingness and interpersonal relationships), esteem needs (expressing oneself and receiving acknowledgment), and self-actualization needs (such as creation and performance; Healy, 2016 ).

Furthermore, the esthetic value and educational implications of music should not be overlooked. Esthetic studies illustrate that music can trigger profound emotional experiences and spiritual exchanges and offer beauty appreciation. Education research suggests that music education can enhance holistic adolescent development, including intellectual, emotional, social, and moral dimensions ( Ouergui et al., 2023 ). Thus, we should motivate teenagers to choose music of high esthetic and educational value, including classical music, ethnic music, and world music.

5.2. Establishing a healthy music environment

To safeguard adolescents’ auditory health, parents must monitor volume and duration and avoid prolonged exposure to loud music. In addition, the content of music, particularly those expressing negative emotions, violence, discrimination, and other harmful elements, should be regulated. These responsibilities require the collaborative efforts of families, schools, and society at large. The home, being a teenager’s first classroom, should see parents educating adolescents about the appropriate use of music, including volume control, time management, and selection of positive and healthy music content. Schools, as the secondary classroom, should guide adolescents toward appreciating high-quality music, thereby positively impacting music education. The society, being the broader classroom, should offer abundant music resources and services to cultivate a healthy musical environment for adolescents ( Kortesoja et al., 2023 ).

5.3. Advocating positive music education

Music education plays a pivotal role in fostering adolescents’ mental health. First, we should prioritize the design and teaching methods of music courses. Music syllabi should encompass diverse facets of music, including music theory, instrumental performance, vocal training, music appreciation, and music creation. Teaching methods should emphasize student-centric approaches and inspire active participation, exploration, and creative thinking. Innovative teaching techniques, such as project-based learning, problem-based learning, and cooperative learning can pique adolescents’ interest and enhance their learning efficacy ( Lei, 2022 ). Second, we should expand the accessibility of music education resources. This expansion includes providing a plethora of resources like music books, music software, and music websites and organizing a variety of music activities such as concerts, music competitions, and music festivals.

5.4. Encouraging active participation in music activities

Music activities offer an excellent platform for teenagers to hone their musical skills, showcase their talents, and relish the joy of music. Adolescents should be encouraged to actively participate in various music activities, like learning musical instruments, partaking in performances, and organizing music clubs. These activities not only enhance the music literacy of adolescents but also boost their social, organizational, and leadership skills. Moreover, the innovative spirit in adolescents must be stimulated, and they should be encouraged to engage in music creation, adaptation, and research. These activities allow adolescents to comprehend music profoundly, express music freely, and actively engage in music, thereby enhancing their mental health ( Perkins et al., 2016 ).

6. Conclusion

In this systematic review, we explored the intricate relationship between music and the mental health of adolescents. The influence of music on adolescent mental health is significant, encompassing areas such as emotional expression and regulation, fostering social connections and a sense of belonging, and promoting creativity and intellectual growth. Music offers adolescents an avenue to articulate their identity and emotions while assisting in the development of their social networks, creativity, and cognitive abilities. Conversely, the mental health status of adolescents influences their interaction with and perception of music. Adolescents may select different music genres in alignment with their emotional state and psychological requirements. For instance, during periods of stress or unhappiness, they may gravitate toward music that provides comfort or reflects their current emotional state.

This bi-directional relationship underscores the significance of music in the realm of adolescent psychological health, and it contributes fresh perspectives and ideas for future research. Possible future research areas could include studying how adolescents utilize music to manage their psychological stress or investigating ways to enhance their mental health through music education ( Wang et al., 2022 ). Although music confers a multitude of benefits on adolescent mental health, inappropriate utilization of music may have detrimental effects. High-volume music can lead to auditory damage, and excessive music engagement may cause attention dispersion or contribute to addictive tendencies. Moreover, some music content can instigate negative emotional responses in adolescents, encompassing themes of violence and discrimination ( Wang and Jiang, 2022 ). Thus, adolescents should enjoy music in moderation and proactively mitigate possible risks. Parents and teachers bear the responsibility of instructing adolescents on appropriate music consumption, including adjusting suitable volume, managing listening duration, and selecting positive and health-promoting music content. These strategies can help adolescents evade the negative implications of music while maximizing its positive influences, thereby enhancing their mental health status.

The establishment of a healthy music environment is pivotal in promoting adolescent mental health; this goal can be achieved through the collective efforts of families, schools, and society. Homes should provide safe and inviting music environments for adolescents. Schools should be equipped with music education resources and opportunities. Society should facilitate music activities and services to cater to adolescents’ musical needs. Further, adolescents should be encouraged to actively engage in music activities, such as learning instruments and partaking in musical performances. These activities not only foster adolescents’ musical aptitude and knowledge but also hone their social skills, boost self-confidence, and stimulate creativity ( Phillips et al., 2019 ). In this process, the role of music educators is paramount. They bear the responsibility of imparting not only musical knowledge and skills to the adolescents but also helping them understand the spiritual value of music. They should facilitate the understanding of how music affects their emotions and mental states, as well as how to employ music as a tool to enhance their mental health ( Steele and Young, 2011 ).

In conclusion, music significantly influences adolescent mental health. A concerted effort at all levels is required to cultivate a healthy musical environment for adolescents to optimally harness the positive influence of music and avert its potential negative effects.

Author contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Conflict of interest

The author declares 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.

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Keywords: adolescents, mental health, music influence, hearing, review

Citation: Chen L (2023) Influence of music on the hearing and mental health of adolescents and countermeasures. Front. Neurosci . 17:1236638. doi: 10.3389/fnins.2023.1236638

Received: 08 June 2023; Accepted: 17 July 2023; Published: 03 August 2023.

Reviewed by:

Copyright © 2023 Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Li Chen, [email protected]

Disclaimer: 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.

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Music Can Be a Great Mood Booster

7 tips for using the power of music to help you feel happier.

Sarah Elizabeth Adler,

Your favorite album doesn’t just sound good — it may also be good for your mental health.

That’s according to a report from the Global Council on Brain Health (GCBH), an AARP-founded working group of scientists, health care professionals and other experts. Their report, “Music on Our Minds,” highlights research showing music’s positive effect on emotional well-being, including improving mood, decreasing anxiety and managing stress.

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“There are so many mechanisms which explain the powerful impact that listening to a piece of music can have,” says report contributor Suzanne Hanser, president of the International Association for Music & Medicine (IAMM) and a professor of music therapy at Berklee College of Music.

As the report details, that impact starts in the brain where music activates many regions, including those associated with emotion and memory . “The music that was played at your wedding or in a religious service, or even at a concert you attended or a dance you were at — that music remains preserved for those neuropathways, which connect that music with really positive feelings,” Hanser says.

Research shows that music can have a beneficial effect on brain chemicals such as dopamine, which is linked to feelings of pleasure, and oxytocin, the so-called “love hormone.” And there is evidence that music can help lower levels of the stress hormone cortisol. ​

How music can keep your brain healthy

The report also includes findings from the 2020 AARP Music and Brain Health Survey, a nationally representative survey of 3,185 adults, which found that listening to music — whether in the background, by focused listening to recordings or at musical performances — had a small positive impact on mental well-being, depression and anxiety.

“In times when people feel sad, stressed, anxious or lonely, listening to or making music can often help people boost their mental well-being,” says GCBH Executive Director Sarah Lenz Lock, AARP’s senior vice president for policy.

To boost music’s mental-health benefits in your life, Hanser says anyone can adapt some of the techniques used by trained music therapists. One of them is what she calls “deep” or active listening — instead of putting on music as background noise, set aside time to concentrate on what you hear, taking note of the feelings, memories and bodily sensations (whether that’s a slowing of your heart rate or the urge to get up and dance) that arise as you listen.

“We can do that even when we’re feeling at our most isolated and sad,” she says. “We can take control, we can be empowered by the music to feel differently.”

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How to use music to provide a mental boost

1. Explore technology that can enable you to listen to music across multiple devices, such as your phone or television. Try music apps, such as Spotify or Pandora, which will suggest new music you might enjoy based on algorithms identifying music similar to your current selections.

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2. Enjoy listening to familiar music that comforts you and evokes positive memories and associations.

3. If you are unhappy, try listening to or making music to improve your mood or relieve feelings of depression.

4. Dance , sing or move to music. These activities not only provide physical exercise but can also relieve stress and build social connections — and they’re fun ways to stimulate your brain.

5. While listening to music that you know and like tends to cause the strongest brain response and dopamine release, try listening to new music. Unfamiliar melodies may stimulate your brain, while providing a new source of pleasure as you get used to hearing them.

6. Make music yourself! Music making includes singing and playing an instrument . Learning to play a musical instrument can offer a sense of mastery and self-esteem, while enhancing brain activity. Singing may be the simplest way to get started.

7. Listen to fun music when you exercise. Music can help motivate you to move. “And it can hasten clearance of lactic acid buildup during recovery from vigorous exercise, according to the GCBH report. ​

Editor’s note: This story, originally published June 30, 2020, was updated to reflect new information.  

Sarah Elizabeth Adler joined aarp.org as a writer in 2018. Her pieces on science, art and culture have appeared in  The Atlantic , where she was previously an editorial fellow,  California  magazine and elsewhere.

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Home — Essay Samples — Nursing & Health — Music Therapy — The Impact of Music on Our Health

The Impact of Music on Our Health

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Published: Feb 12, 2019

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Analysis and research on the influence of music on students’ mental health under the background of deep learning

Associated data.

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

This paper makes a detailed analysis and discussion on the impact of music appreciation on college students’ mental health and the influence of music appreciation on students’ mental health, mental energy and mental structure. There has long been the idea of music promoting people’s mental health, as well as related research in the field of music psychology. For this specific group of primary and secondary school students, it should be said that it is relatively rare to consider using music education to promote their mental health. This paper summarizes the advantages of deep learning over shallow learning, explains the necessity of introducing deep learning, and describes the data representation of deep learning and several typical deep learning models. This study adopts the method of multi-evidence to conduct in-depth research and analysis. On the basis of in-depth study and research, this paper analyzes and studies the impact of music on students’ mental health, so as to lay a foundation for future research on students’ mental health. In terms of influencing factors and strategies to promote students’ in-depth learning, we should apply the research results to specific teaching situations with the help of advanced digital technology, and strive to combine theory with practice. The research shows that college students’ mental health is an important part of quality education in Colleges and universities, and music education plays an important role in the implementation of quality education.

Introduction

With the gradual advancement of quality education concept in schools, more and more attention has been paid to the influence of music on students’ mental health in teaching. Music becomes a channel for students to go to mental health, which allows them to cultivate students’ aesthetic sentiment, enlighten their wisdom, enhance their psychological quality, enhance their aesthetic taste and construct their own spiritual framework during their growth. With the deepening of research, deep learning has not only increased a lot of related research, such as neural network, learning process, classroom teaching, etc., but also the interdisciplinary research on deep learning has developed rapidly, such as pedagogy, physics, mathematics and other disciplines. Under the background of core literacy-oriented curriculum reform, a large number of primary and secondary schools are putting in-depth learning into specific curriculum teaching practice. With the popularization of higher education, music, as an important aspect of quality education, gets more and more attention. Many colleges and universities include music appreciation in humanistic quality education courses, and put forward higher requirements for music appreciation courses. Music, as a kind of culture, has a long history in the longitudinal direction, and is vast in the horizontal direction. It plays an extremely important role in the quality of talents ( Awais et al., 2020 ). Mental health, as an important index reflecting personal health, has been paid more and more attention in social functional departments, such as education, life and production, and has been vigorously publicized and popularized as an important part of humanistic care. The mental health of college students is one of the focuses of the current society. It is a way worth exploring to use music to adjust the mental state of college students. The mental health of college students is one of the focuses of the current society. Using music to adjust the mental state of college students is a way worth exploring ( Nachmani et al., 2018 ). With the deepening of research, deep learning has attracted the attention of researchers in the field of education. Educational researchers have found that “learning can also be divided into depth and depth” and that deep learning is an effective way to deeply process knowledge and information and improve learning efficiency. Therefore, developing deep learning has become an important measure of contemporary learning science. At the same time, society requires citizens to master accurate information and have the ability to deal with it, so as to serve the contemporary society. Deep learning means that on the basis of understanding, learners learn new ideas and knowledge critically, integrate them with the original cognitive structure, connect many ideas with each other, and transfer existing knowledge to new situations, so as to make decisions and solve problems. At present, digital, networked and mobile new learning methods have emerged one after another and become popular. Even because of the misuse of new learning tools and technologies, some learning activities only stay at the shallow learning level, so the network is even considered as a hotbed for shallow learning, which is not suitable for deep learning activities. At present, the rapid development of economy and the fierce competition in the information society also bring great social pressure to their lives. For the current college students, they cannot bear such great pressure. This invisible pressure makes them prone to excessive self-esteem, stronger self-inferiority, easy self-centeredness, emotional, weak sense of responsibility and other psychological problems, which lead them to commit crimes easily ( Kaluarachchi et al., 2021 ).

The early study of in-depth learning showed concern for the learning process, learning methods and learning results. At the same time, from the perspective of psychological research, the concept of learning quality with “understanding” as the core was put forward, and it was tried to describe it in a measurable way. Under the background at that time, the research trend of learning process, learning methods, learning results and quality and teaching effectiveness was a positive and concrete attempt to respond to the educational problems in the social change from the micro-level of classroom teaching, taking the educational process as the research foothold. In terms of computational complexity of network structure, when a network structure with depth k can express a certain function compactly, when a network structure with depth less than k is used to express the function, it may be necessary to increase the number of computational factors of exponential scale, which greatly increases the computational complexity. Generally speaking, for a given number of training samples, if there is a lack of other prior knowledge, people prefer to use a small number of computing units to establish the “tight expression” of the objective function to obtain better generalization ability. When the network depth is not enough, this tight expression may not be established at all. Because theoretical research shows that the function that can be compactly expressed by the network with depth K sometimes requires exponential growth of computing units when expressed by the network with depth k – 1.

In this paper, the corresponding research methods are established to analyze and explain it. In the research of deep learning, the corresponding model diagram and algorithm formula are established. In the research of music’s influence on students’ mental health, data graph and other methods are established to analyze it.

The main contribution of this paper is to conduct in-depth research and analysis of its research by using multi-evidence method. And use the method of demonstration to study and explain its research. On the basis of in-depth study, this paper analyzes and studies the impact of music on students’ mental health. Lay a foundation for the future study of students’ mental health. This paper summarizes the advantages of deep learning over shallow learning, explains the necessity of introducing deep learning, describes the data representation of deep learning and several typical deep learning models, such as convolutional neural network, DBN, and stack self-coding network, explains the reasons that may lead to the difficulties of deep learning training, introduces effective training methods, and from the aspects of initialization method, the selection of network layer and activation function, model structure This paper summarizes the new progress of deep learning research in recent years from four aspects: learning algorithm and practical application.

This paper is divided into five sections. The first section of this paper expounds the research background of the influence of music teaching on students’ mental health. The second section makes an empirical analysis of how to use network technology to support and promote deep learning. The third section studies the basic connotation of deep learning. The content of deep learning algorithm is described. Section “results and analysis” studies the influence of music on students’ mental health, and describes the research on the influence of music appreciation on students’ mental health. Section “summary” summarizes the full text. This paper summarizes the advantages of deep learning over shallow learning, and explains the necessity of introducing deep learning.

Related work

At present, the importance of education informatization is insufficient, and there is no in-depth understanding of the positive role of university informatization construction on the development of higher education. The traditional management concept and mode of thinking have seriously restricted the construction and development of university informatization. Theoretical research results are divorced from reality. This is mainly because most of the technical personnel engaged in design are not the front-line personnel of education, which leads to the disconnection between the designed works and education. The speed of information technology updating is fast. To give full play to the benefits, we must have high-quality information management personnel. Education informatization requires technical personnel who can be responsible for the design and maintenance of information systems, as well as the integration and development of various management software. Although there are many talents in this field in ordinary colleges and universities of science and technology, most of them are in teaching posts and do not engage in business management. How to avoid the complementary connection of information systems and avoid the phenomenon of “information fortress.” How to correctly and reasonably apply information technology to the process of education informatization has not been well solved. In view of many problems in the current process of educational informatization, learning research groups have conducted descriptive empirical research on how to use network technology to support and promote deep learning. However, with the increasing attention paid to this problem, with various new learning methods constantly emerging, faced with worries and doubts about superficial and impetuous learning caused by fast-food, fragmentation and miniaturization of learning, It is necessary to deeply analyze and understand the essential connotation of deep learning, and further explore the theoretical basis of deep learning from the perspective of learning science and learning psychology, which has practical theoretical significance for understanding and understanding deep learning, revealing its mechanism and forming promotion strategies. Deep learning is more expressive than shallow learning, and the increase of depth makes the local optimal solution of non-convex objective function the main factor causing learning difficulties. From the perspective of the relevance and complexity of research topics, there are differences in the starting time of deep learning research, as well as the disciplines involved in early research (educational psychology and higher education were the earliest in countries, and educational technology was the first to introduce deep learning research in China), and the relevance and complexity of research topics are quite different. From any angle, we can see that deep learning puts forward new requirements for students’ learning. It emphasizes that learning is a kind of learning different from the past. It is no longer aimed at exams, nor is it limited to simple and mechanical copying of knowledge. Instead, it requires learners to grasp, apply, synthesize, analyze and evaluate, and be able to solve practical problems in life situations and form higher-order thinking goals.

In the research, Kresovich et al. think that the potential psychological adjustment of music is very crucial, which not only edifies students’ sentiment, but also promotes the emotional communication among students, makes the interpersonal relationship among students more harmonious, cultivates the ability of mutual assistance and assistance, and promotes the healthy development of students’ mind and body ( Kresovich et al., 2021 ). Hense et al. think that music education is not only a means of art teaching, but also plays a significant role in psychological adjustment and treatment. Therefore, music education should play an active role and value in disease treatment in college music education. Colleges and universities should proceed from the reality of students’ mental health, endow colorful music teaching activities with the function of psychological adjustment, and widely apply them to the practice of college students’ mental health work ( Hense et al., 2018 ). Kegelaers et al. think that music itself has a power that other arts cannot match and surpass, and this power contains very powerful emotions. This is also a very clear affirmation of the function of music in numerous literatures ( Kegelaers et al., 2021 ). Wang et al. thinks that the “anxiety” caused by the pressure of study, employment and competition has become a major psychological problem that plagues higher vocational students ( Wang and Agius, 2018 ). According to Terry et al. the psychological adjustment function of music for students cannot be realized only by passive appreciation. On the contrary, passive music appreciation must be expanded into active music rhythm and interactive and cooperative music-themed activities, so that students can rediscover their own values and abilities, reconfirm themselves and accept themselves in the process of listening, discussing and expressing music, so that they can play music effectively ( Terry et al., 2020 ). Sharma et al. thinks that the stimulation provided by music satisfies the “id”. The “ID” is the primitive instinct, the most inaccessible part of the personality, and the powerful one, which includes the survival drive and sexual drive of human instinct. When the ID is not satisfied, the individual will breed anxiety and produce a tense state. The satisfaction that the ID needs can eliminate the tension and make the individual feel happy ( Sharma et al., 2020 ). Wang et al. think that learning is the process of learners’ complex information processing activities and cognitive construction. In essence, deep learning is a process of constructing the meaning of structural and non-structural knowledge, and it is also a complex information processing process. It is necessary to effectively and finely process the activated prior knowledge and the acquired new knowledge, that is, from awareness and analysis to synthesis, application and assimilation ( Wang et al., 2020 ). The purpose of in-depth learning is to develop higher-order thinking ability and realize meaningful learning. Its core idea embodies important concepts in cognitive science such as understanding, construction, transfer, problem solving and reflection. Ballenberger et al. think that deep learning is no longer just the similarities and differences of learning methods and strategies, but that there are significant differences in the understanding and criticism of meaning, the connection and construction of knowledge, and the migration and application of learning. The understanding of this difference has also prompted researchers to explore the essential characteristics of deep learning from the perspectives of memory mode, knowledge system, focus and learning motivation ( Ballenberger et al., 2018 ).

Deep learning research

Research on the basic connotation of deep learning.

In the 1990s, the deep learning research continued from the earlier research, which was reflected in the concern for learning results and learning process. The research at this stage mainly focuses on the topics of education, academic performance, learning strategies, learning perception and learning outcomes from the perspective of self-construction of psychological learning, while the research topics such as students, knowledge, motivation, science, classroom, mode and differences in learning quality also frequently appear. In the process of problem-solving learning, learners still pay attention to the explanation of functional level, but it includes a wider range of explanatory information, as well as more structured information and internal mechanisms. They try to understand the causal relationship between phenomena through the qualitative relationship between parts and recall association. Deep learning method tries to find the internal structure of data and the real relationship between variables. A large number of studies have shown that the way of data representation has a great influence on the success of training and learning. Good representation can eliminate the influence of changes in input data that have nothing to do with learning tasks on learning performance, while retaining useful information for learning tasks ( Ascenso et al., 2018 ; Jensen and Bonde, 2018 ). Among the views on self-construction and social construction of learning, it is worth paying attention to the debate between the two research camps of symbolic processing and situational cognition for nearly 20 years. The cognitive theory of symbol processing is an important research of modern cognitive psychology. The cognitive theory of orientation symbol processing emphasizes the decisive role of knowledge on behavior and cognitive activities. It emphasizes the holistic study of cognitive processes. And “mental activity like computer” is taken as its metaphorical basis. With the method of computer simulation, a large number of simulation studies have been carried out on cognitive problems such as perceptual attention, memory and problem solving. Important progress has been made in revealing the nature and mechanism of human cognition. However, due to the limitations of metaphor itself, there are serious deficiencies in this study. The former pays attention to the processing structure of brain and thinking symbol representation, emphasizes the understanding of people’s inner mental process and the transformation characteristics of individual input and output, and pays no attention to the external environment; The latter pays attention to the structure of the external world and how it constrains and guides human behavior, emphasizing the role of history, social interaction, culture and environment, while weakening the importance of internal cognition. In order to show the overall research situation of deep learning in recent years more clearly and grasp the development trend of deep learning research, this research is based on the full-text database of Chinese academic journals in CNKI database, and adopts the method of literature analysis. Deep learning is a learning process characterized by the mental state of advanced thinking. Therefore, this paper focuses on the deep learning methods, deep learning motivation and deep learning strategies adopted by learners in the learning process. Through the statistical analysis of the frequency of high-frequency keywords, the co-cited matrix is generated, and through the advanced statistical processing such as cluster analysis, multi-dimensional scale analysis, factor analysis and social network analysis, different forms of visual graphics are drawn. According to its research, the corresponding model diagrams are established for analysis, as shown in Figures 1 , ​ ,2 2 .

Model diagram of deep learning system.

Deep learning operation model diagram. (A) Model distillation and (B) privileged features distillation.

In-depth study has stepped into the fast lane, the research results have gradually increased, and the research contents have become richer and richer. Build a virtual learning community in cyberspace, use instructional video resources or other software tools for visual learning, or conduct simulation experiments in virtual situations. Online collaborative learning, blended learning, mobile learning, and ubiquitous learning have become possible. Information-based teaching is a bilateral educational activity that educators use the current educational media, information resources and educational technology methods. The whole teaching process adheres to the teaching concept of taking learners as the main body and taking ability as the standard, “learning by doing and teaching by doing”. Information-based teaching design refers to, in order to achieve certain teaching goals, according to the characteristics of students, the theme of course content and environmental conditions. Make full use of modern information technology and resources, take learning as the center, and scientifically arrange each link and element in the teaching process, so as to realize the optimization of the teaching process. Based on the theoretical analysis and practical consensus of deep learning, it can be seen that deep learning is to solve the problems related to learning in the increasingly complex environment from the perspective of integration in explaining the rationality and experience of learning essence. Deep learning emphasizes the essence of learning. When deep learning becomes the consensus and normal state of educational practice and the essence of learning returns, the name of “deep learning” may return to “learning” instead of emphasizing “depth”. It is worth mentioning that deep learning is relative to false learning and mechanical learning, and the latter two are not what school teaching should be ( Sakalle et al., 2021 ; Sundaresan et al., 2021 ). Each computing layer of the network is composed of multiple feature maps, and each feature map exists in the form of a two-dimensional plane. The neurons in the plane share the same weight set under constraints. Deep learning is a new multi-layer neural network learning algorithm. This paper analyzes the advantages of this algorithm, and on the basis of summarizing the current research situation, puts forward the existing problems in the current research. On the basis of the analysis model of deep learning constructed by the latter, the research status is summarized. As the process of deep learning mainly includes situation creation, knowledge construction, problem solving and reflective evaluation, correspondingly, these four cognitive theories also explain deep learning from these four angles. Although each has its own emphasis, it is not absolutely independent. At the same time, there are some connections among these four cognitive theories. Constructivism theory comprehensively expounds deep learning from the perspectives of learning process, results, conditions, etc. Situational cognitive theory, distributed cognitive theory and metacognitive theory also enrich and develop the related research of constructivism from many aspects. The idea of metacognition runs through all the processes of deep learning, and is involved in constructivism theory, situational cognition theory and metacognition theory. In the research, a corresponding model diagram is established to analyze it, as shown in Figure 3 .

Model diagram of deep learning level.

Human’s learning activity is an extremely complex system, and the study of human learning phenomenon and its essential law has always been the focus of human attention for a long time. Looking back at the long course of study and research, human beings’ exploration of learning phenomena has experienced three changes: the tradition of philosophical research, the tradition of scientific psychology based on laboratory and the tradition of multidisciplinary integration research that focuses on natural situations. A systematic and scientific learning theory has gradually formed, and gradually turned to the study and scientific research that pays more attention to complex learning phenomena in real situations. In the research of deep learning, the corresponding data tables are established for analysis, such as Tables 1 , ​ ,2 2 .

Data sheet of deep learning research.

Deep learning specific analysis data table.

The deep learning method research includes four aspects: strategy research, teaching mode, environment design and model design. Among them, strategy research refers to various strategies and methods to promote deep learning, including information technology support strategy, learning evaluation strategy and blank space strategy. In order to meet the needs of their own development, deep learners will actively learn knowledge and skills. However, shallow learners only accept information passively in order to complete the task.

Research on deep learning algorithm

In-depth study is interwoven with people’s way of understanding things based on rationality and experience. In the debate between self-construction and social construction of learning, cognitive objectivism moves toward the opposite side, and the irrational, socialized and contextualized parts of learning activities are gradually discovered. It can be seen from the main co-cited researchers in deep learning research that during this period, the key researchers not only include the teaching field, but also the research in multimedia learning, Computer Supported Cooperative Learning (CSCL) and other fields have received sudden attention. While discussing the advantages of information technology in promoting deep learning, people also found some problems such as learners’ cognitive load in this process. Deep learning has become a hot field in modern education. In the early stage of its development, it did not pay enough attention to it, and there is still a certain gap between the interpretation and practical application of deep learning in countries. The integration of information technology and deep learning is not high. Scholars pay more and more attention to the integration of information technology and deep learning. Improving classroom efficiency and realizing deep learning through information technology has become a hot topic ( Babini et al., 2020 ; Cheah et al., 2020 ). Content analysis refers to a scientific research method that objectively, systematically and quantitatively describes the research content of a certain field, so as to deeply grasp the research status and content of the research field. Cite Space is an application software developed based on Java platform. Because it is suitable for multivariate, time-sharing and dynamic complex network analysis, it has become the most distinctive and influential information visualization software in the field of information analysis. Scientific and reasonable teaching strategies are the foundation and guarantee to make deep learning a reality. Deep learning teaching strategy is a suggestion to adjust teachers’ ideas and teaching behaviors based on the problems existing in deep learning. The research scope of deep learning mainly focuses on formal learning field and well-structured problem field. The formal field of study mainly refers to the classroom. However, learning also happens in most areas of informal learning. Informal learning, as an extension of formal learning, plays an important role in understanding and supplementing the knowledge learned in class. In the deep learning model, the convolutional neural network limits the network structure by using the local connection of the receiving domain. Another feature of convolutional neural networks is the sharing of weights. There are a lot of connected weights in the graph, but because the neurons in the same hidden layer share the same weight set, the number of free parameters is greatly reduced. The feature detection layer of convolutional neural network learns through training data, avoiding explicit feature extraction, but implicitly learning features from training data. Moreover, the neurons on the same feature mapping surface have the same weights, and the network can learn in parallel, which is also an advantage of convolutional neural network over other neural networks. The network structure of convolutional neural network is closer to the actual biological neural network, and it has unique advantages in speech recognition and image processing, especially in the field of visual image processing, and good results have been obtained. In the research, the corresponding algorithm formulas are established for analysis, such as formulas (1) – (4) plus (5) , (6) .

The method of random initialization is adopted for the deep neural network. The gradient-based optimization makes the training result fall into the local extreme value, but the global optimal value cannot be found. The numerical optimal solution (minimum value) trained by gradient descent method is almost equal to the analytical solution. When the parameter x to be optimized is initialized to different values, the final corresponding optimal solution (minimum value) is also different. This shows that the position of the optimal solution (local minimum) obtained by the iteration of the gradient descent algorithm is closely related to the initial value of the parameters to be optimized. With the deepening of the network structure, it is more difficult to get good generalization performance, which makes the learning result of the deep neural network after random initialization even worse than that of the shallow structure neural network with only one or two hidden layers. For deep learning, unsupervised learning and semi-supervised learning are the key components of a successful learning algorithm. Unsupervised learning makes the parameters of supervised learning enter a suitable preset area, and a good solution can be obtained by gradient descent in this area. Unsupervised learning is used in each layer of deep structured neural network to decompose a problem into several sub-problems related to the extraction of multiple representation levels, and visual learning support is provided at appropriate stages. From the perspective of visualization, the teaching process has gone through two stages, namely, the process of concretizing abstract knowledge and the process of expressing concrete knowledge in abstract concepts ( Dang et al., 2020 ; Fang, 2021 ). The subject of the former is mainly teachers (learners may also participate in it), that is, teachers create a learning environment including information technology to provide visual learning support for learners; The main body of the latter is learners, that is, learners abstract the concrete content into concepts and models, and express them visually. In the interpersonal field, relevant strategies include: setting up cooperative research groups, and in most schools, the research groups are carried out continuously and daily; providing internship opportunities is a way for students to strengthen and cooperate their skills in off-campus situations. Because both of them focus on the cognitive level of learning, they pay less attention to the emotional level and social and cultural attributes of learning. Especially from the perspective of “complex learning environment” it is still necessary to deeply integrate the cognitive, social and technical aspects of learning. Therefore, it is still worth further discussion to apply the above two classification theories to the evaluation of deep learning. In the research, the corresponding algorithm formulas are established for analysis, such as formulas (7) – (10) plus (11) .

The deep neural network has a deep non-local learning structure, and it can learn the features in the data set with great changes from fewer samples, showing stronger feature recognition ability than the kernel method. At the same time, the learning process of RDFM method solves the over-fitting problem caused by too strong learning ability due to the introduction of regularization factors. According to Fisher’s criterion, the depth structured neural network is used to improve the discrimination of features. Deep neural network has a deep nonlocal learning structure and learns the characteristics of data sets with great changes from fewer samples. It shows stronger feature recognition ability than kernel method. At the same time, due to the introduction of regularization factor in the learning process of rdfm method, the problem of over-fitting caused by strong learning ability is solved. Experiments are carried out on various types of data sets, and the results show the necessity of using unsupervised regularization in the fine-tuning stage of deep learning. Experiments on image classification and learning low-dimensional representation of images with the depth unsupervised self-coding model realized by this nonlinear transformation method show that these transformations are helpful to learn the depth structure neural network with at least five hidden layers, which proves the effectiveness of the transformation, improves the speed of the basic random gradient learning algorithm, and helps to find a better generalized classifier. Deep neural networks such as convolution DBN and stack self-coding network have been used in speech and audio data processing, such as music artist genre classification, speaker identification, speaker gender classification and speech classification, etc., and very good learning results have been obtained ( Koops and Kuebel, 2021 ). DBN and stack self-coding network have shown good performance in a single image recognition task, successfully used to generate a compact and meaningful image retrieval representation, and have been used in large-scale image retrieval tasks with very good results.

Results and analysis

Study on the influence of music appreciation on students’ mental health.

The form of music appreciation teaching is mainly characterized by listening and appreciating, and the music works, because of its own structural style, are in the form of tension, which causes the conscious person to have a specific psychological reaction. Interpersonal relationship refers to the relationship between people established and developed in interpersonal communication, which reflects the contact degree of people in the depth, closeness, coordination and other psychological aspects. The vast majority of contemporary college students are only children, and they have developed the habit of self-centered thinking and dealing with problems. They show no cooperative spirit, no broad mind, and haggle over every ounce when dealing with others. Even though they are aware of the importance of interpersonal relationships, they often find it difficult to get along with others for various reasons. Music maintains mental health by promoting harmonious interpersonal relationships. Every one of us lives in the society, not an isolated existence, and personal mental health is inseparable from the society. The comprehensive functions of music appreciation are reflected in picture appreciation, field appreciation, self-appreciation and creative appreciation. Music appreciation can promote individuals’ mental health and alleviate their negative emotions. This conclusion has been confirmed by many psychological studies. In modern society, a large number of people are in a tense state of life, so physical and mental relaxation plays a great role in mental health. However, not every kind of music can make people relax. Music that can make people relax should generally meet the following requirements: the rhythm is less than the heartbeat, and the rhythm changes little. Music can include flutes, strings, guitars, etc., preferably concertos with soft melodies. With the formation of human self, there is a need to be cared for by others, that is, in one’s life, one hopes to feel warmth, care, sympathy, respect, recognition, etc. from related people. Listening to music can cultivate students’ sentiment, make them have noble spiritual realm, broader vision and mind, cultivate their image memory, creativity, imagination and observation, improve their understanding, perception, emotion and other abilities, and form a correct aesthetic view. Psychological energy is the psychological power, which can make people realize their subjectivity and needs, the courage, impulse willpower, feelings and emotions with various characteristics, etc. Psychological energy can affect the balanced and coordinated development of the dynamic system of human psychology, and it is the key. The psychological energy of college students exists in the form of tension, and the sound of music also stimulates the appreciators in the form of tension. The two kinds of tension combine and influence each other, so that students’ psychological energy can move and play smoothly. The sound of music forms a complete musical work through its constituent elements, such as loudness, pitch and timbre. Music stimulates human sensory organs through various elements of sound. In the teaching of music appreciation, teachers guide students to have emotional experience of music, and guide students to comprehend and feel through all kinds of information and details in music, so that students can integrate their emotions into music. At present, college students are full of energy, rich in knowledge and mature in physiology, and their emotional world is very colorful.

This paper investigates a vocational and technical college and a conservatory of music. These schools are representative, objective and universal, and they are all higher vocational colleges. The investigation lasted 4 months. Thousand questionnaires were distributed to the students of the above four schools, and 900 were recovered, with a recovery rate of 90%. Among them, there are 900 valid questionnaires, with an effective rate of 100%. In the study, the corresponding data graphs are established for analysis, as shown in Figures 4 – 6 .

Data map of music appreciation influence.

Music appreciation data map.

Data map of music appreciation research.

From the above data graph, it can be known that music appreciation has a great influence on psychological activities, up to about 54.3%. Personality is composed of three parts: id, ego and superego. I am the original self, which refers to the original self, including all the basic desires, vitality and impulses required for production. As the source of psychological energy, the ID only needs to be happy and avoid suffering. Happiness is the fundamental principle of the ID’s behavior, completely outside the social moral norms. The psychological energy of self is mostly consumed in the suppression and control of id. Anything that can become conscious is in the self, but it also exists in the unconscious in the self. It is the existence and awakening of self-consciousness. Self can separate desire from fantasy, endure tension and compromise, and change with time. In music appreciation, the appreciator’s self will be strengthened. Music appreciation teaching is a way to further deepen the influence of personality. On the basis of the original value of music, the harmonious development of people’s psychology can be further realized. Idealized personality must be the result of highly harmonious development of internal psychology. Pursuing truth, goodness and beauty also points out the direction for realizing the harmony of internal psychology. Superego is an ideal part of personality structure and a perfect self. I strive for perfection, and it does not care about reality or happiness. Because of the guidance of the superego, the heart will achieve a harmonious state, thus enabling people to live better in real life. Music appreciation can provide a beneficial direction for college students’ superego. Music appreciation is an important part of aesthetic education. To complete music appreciation education with high quality, the most direct thing is to have an excellent music appreciation teacher. An excellent music teacher should have all the excellent qualities of all teachers, including solid basic music skills and professional accomplishment. We should also have many other excellent qualities, such as innovative spirit, profound knowledge, correct aesthetics, etc. Teachers who have graduated from music colleges are more concentrated in their professional fields, and lack relevant knowledge of psychology. Teachers who have graduated from local comprehensive universities and normal colleges also have the same problems to varying degrees. Music psychology is based on general psychological phenomena, and constantly evolves in the process of the emergence, occurrence and development of music consciousness. Music psychology is not innate. It needs to gradually form music consciousness and psychological process with personality characteristics in the actual music activities and education, and in the process of continuous improvement of the brain. The process of continuous learning and acceptance in the growth stage is also the process of the formation of musical psychology. From infancy to adulthood and then to old age, it has experienced the whole process of occurrence, development and decline. Teachers of music majors should master and understand certain knowledge of psychology if they want to improve the mental health of higher vocational college students through music. Under the guidance of the syllabus of music education, corresponding teaching plans and requirements should be formulated for higher vocational college students of the same grade or different grades, so that students can study systematically in a planned way. In the teaching of music appreciation, we should learn from the advanced music ideas, and integrate the most advanced teaching ideas in the world into our own teaching methods, so as to enrich our teaching content and make our teaching methods more vivid. Music appreciation teachers can get the latest music ideas and know the latest research results by reading the latest professional music journals and magazines, so as to serve their own music appreciation teaching.

The psychological impact of music education on students

To study students’ mental health, we have to talk about psychology. Psychology is a subject with many branches. Psychology and music psychology provide theoretical basis for music education to solve students’ mental health problems from different angles. In the early stage, young people can not only look at themselves objectively, but also express themselves clearly, defend themselves sensitively, and cherish themselves, forming a rational self-consciousness. The ideal self and the realistic self are still facing the crisis of division, and self-affirmation and self-denial often conflict. Chronic anxiety symptoms develop slowly, but persist, usually for a long time. In terms of emotional disorders: I often feel distressed, self-reproached, always think of the disadvantages and exaggerate the difficulties when something happens. No moaning, often accompanied by fatigue, chest tightness, shortness of breath, irritability, sensitivity, frequent anxiety, loss of hands and feet, upset, restless, rubbing hands and feet, an unbearable discomfort, anxiety about one’s health, head swelling, face fever, etc. The fierce competition for talents in modern society often leads to college students’ involuntary study pressure and employment pressure, which gather in their hearts and cause obvious anxiety. Accordingly, college students will have the need to seek to relieve their inner pressure and anxiety. Music education is undoubtedly a “good medicine” to relieve college students’ psychological pressure. Music teaching can teach students about the height, intensity, timbre, melody, harmony, rhythm and other aspects of music, so that students can have a more comprehensive understanding of music, and then they can choose their own music independently, and enjoy their body and mind with the help of music. Excellent music plays a positive role in shaping a sound personality. With the help of classroom teaching and extracurricular music activities, music teaching provides a platform for college students to contact and appreciate excellent music works. In the research, the corresponding data graphs are established for analysis, such as Figures 7 – 9 .

Data map of music education impact.

Data map of music education impact effect.

Data map of music education research and analysis.

The beauty of music lies in being able to depict an exciting artistic conception through the intangible emotion of music. Compared with other arts, music is closer to nature, it is easier to express one’s feelings, and it can make the appreciator’s mind deeply moved, which can exert a subtle influence. As an auditory art, music exists through auditory feelings. Let students feel the aesthetic effect in listening, which can better promote students’ imagination beauty, and make music exert great influence on their minds through image, so that students’ body and mind are in a benign and healthy state of development. Because music originated from a long time ago in human society, it was originally for human beings to express their emotions and vent their bad emotions, so music is called “the language of emotions”. Music can penetrate into the deepest part of the soul with the strongest power. If the way of education is suitable, they will infiltrate the soul with beauty and beautify it. If there is no such proper education, the soul will be ugly. Undoubtedly, good music teaching methods can help middle school students enrich their inner feelings and perfect their personality charm. It can also enable middle school students to feel the wonder and beauty of the world. For many middle school students, the emotions conveyed by good music are like guides, leading middle school students’ thoughts to a positive perspective. Listening to good music often can make middle school students calm down and learn cultural knowledge, and can sublimate students’ emotions. Implementing music education is a pleasure in itself, and under its influence, students’ pressure from all sides will be relieved and released, thus reducing their anxiety in learning. One of the standards of mental health is to have good interpersonal relationships. People with mental health can always keep good contact with the society and others, and can correctly know and understand the society and others. Music appreciation teaching is also aesthetic education. Teachers should, according to the characteristics of the times, the age of students and other factors, on the premise of maintaining the richness of classroom teaching content, choose works with strong ideological content and typical representative significance for students to enjoy. Music psychology is a branch of psychology that studies and explains people’s music experience and music behavior from primitive (newborn) to advanced level, based on psychological theory, absorbing physiology, physics, genetics, anthropology, aesthetics and other related theories, and adopting the method of experimental psychology.

Music is closely related to students’ mental health. Music education can promote students’ mental health, enable students to relax themselves, express their feelings, release bad emotions, build harmonious interpersonal relationships, and help students establish a good mental health system. In terms of influencing factors and strategies to promote students’ deep learning, we should apply the research results to specific teaching situations with the help of advanced digital technology, and strive to combine theory with practice. The mental health of college students is an important part of quality education in colleges and universities, and music education plays an important role in the implementation of quality education. It is diversified, multi-faceted, multi-level and repeated to influence and educate people. The effects of music appreciation on college students’ mental health are analyzed and discussed in detail in this paper: the effects on college students’ mental health, mental energy, psychological structure and so on. The idea that music promotes people’s mental health has existed for a long time, and the related researches in the fields of music psychology, music therapy and music education psychology have become quite mature systems. However, for the specific group of primary and secondary school students, it should be said that it is relatively rare to consider using music education to promote their mental health. This paper summarizes the advantages of deep learning over shallow learning, explains the necessity of introducing deep learning, describes the data representation of deep learning and several typical deep learning models, such as convolutional neural network, DBN and stack self-coding network, explains the reasons that may cause difficulties in deep learning training, introduces effective training methods, and summarizes the new progress of deep learning research in recent years from four aspects: initialization method, selection of network layers and activation functions, model structure, learning algorithm and practical application. However, this study lacks large-scale data for training, and obtains a large number of more representative characteristic information. So as to classify and predict the samples, and improve the accuracy of classification and prediction. Therefore, there are certain limitations, and further analysis is needed in the future.

Data availability statement

Author contributions.

TW: conceptualization, methodology, formal analysis, writing—original draft. YZ: conceptualization, validation, data curation, writing—original draft. MY: methodology, validation, data curation, writing—original draft. All authors contributed to the article and approved the submitted version.

Research and practice of general education of Aesthetic Education in Colleges and Universities from the perspective of “Internet +” (SJGZ20210071).

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

The authors thank Mudanjiang Normal University for its help in their work.

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