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Article

Factors Associated with Anxiety and Depression among Elite Collegiate Badminton Players in Japan: Exploratory Analysis

by
Yuta Sakamoto
1,*,
Junya Komagata
2,
Atsuya Otsuka
1,
Yukina Shinya
1,3,
Momoka Sendouda
1,3 and
Yujiro Masu
4
1
Department of Rehabilitation, Health Science University, 7187 Kodachi, Fujikawaguchiko-machi, Minamitsuru-gun, Yamanashi 401-0380, Japan
2
Department of Physical Therapy, Nagoya Women’s University, 3-40 Shioji-cho, Mizuho-Ku, Nagoya 467-8610, Japan
3
Department of Rehabilitation, Isawa Onsen Hospital, 330-5 Hatta, Isawa-cho, Fuefuki-shi 406-0023, Japan
4
Department of Human Communication, Health Science University, 7187 Kodachi, Fujikawaguchiko-machi, Minamitsuru-gun, Yamanashi 401-0380, Japan
*
Author to whom correspondence should be addressed.
Psychiatry Int. 2024, 5(3), 470-481; https://doi.org/10.3390/psychiatryint5030033
Submission received: 1 July 2024 / Revised: 5 August 2024 / Accepted: 15 August 2024 / Published: 21 August 2024
(This article belongs to the Topic Health Questionaries)
Browse Figure
Versions Notes

Abstract

:
This study focused on mental health and fatigue in elite university student-athletes competing in badminton at the national level, comparing them with control university students and examining related factors. Among university athletes, anxiety and depression showed a moderately negative correlation with life satisfaction outside of sports, as determined by partial correlation tests adjusted for fatigue. Athletes demonstrated a 47% rate of anxiety and a 30% rate of depression. These values showed no significant difference from those of the anxiety (29%) and depression (21%) rates in a non-athlete university student sample. In addition, this study suggested that the evaluation of fatigue using a checklist of individual strength might produce low reliability and validity for elite university student-athletes in badminton. These exploratory findings highlight the importance of focusing on athletes’ overall life satisfaction and suggest the potential need for effective mental health interventions beyond sports. However, because of the exploratory nature of this study and the small sample size, further research is necessary to confirm these results.

1. Introduction

Sports are currently experiencing a peak in popularity in Japan, and the country has recently hosted the Rugby World Cup in 2019, the Tokyo Olympics and Paralympics in 2020, and the FIBA Basketball World Cup in 2023. Japan is scheduled to host additional significant international competitions, which is expected to result in increased interest in sports. Additionally, in March 2022, the Japan Sports Agency established its third Basic Plan for Sports to promote sports as a means of social coexistence and to spread sports more widely among the populace [1]. Sports are a global aspect of culture and are capable of addressing social issues. However, while the positive effects of sports on individuals and society have been frequently reported, issues related to athlete health remain unaddressed.
Athletes who strive for excellence in a competitive environment are at a higher risk of anxiety and depression [2]. Studies conducted in Australia, European countries, the United States, and South Africa have reported rates of anxiety and depression symptoms in athletes of 10–43%, despite variations in the type of sport, comparison groups, and assessment methods [3,4,5]. However, in Japan, the belief prevails that athletes, having endured long periods of rigorous training and significant pressure during competitions, are mentally strong [6]. The understanding of athletes’ mental health in our country therefore lags behind that of other nations.
Internationally, an increasing focus has been placed on athletes’ mental health and psychological support for them, but research on Japanese athletes’ mental health is scarce. A 2021 study of Japanese rugby athletes reported that 32% experienced psychological stress and 10% showed tendencies or disorders related to anxiety and depression [7]. It is only recently that there has been a focus on the high degree of mental health risk among Japanese athletes. Thus, many questions regarding risk factors and related issues for Japanese athletes’ mental health remain unanswered, posing a significant challenge.
The fields of sports psychology and clinical sports psychology have a strong association with psychosomatic problems. However, the scope of clinical sports psychology is narrower in Japan than in Europe because it focuses on the experiences and expressions of athletes [6]. Moreover, the usefulness of psychological approaches in sports is widely recognized in Japan, and most support for them comes from an academic perspective, which highlights the need for insights into athletes’ mental health from a psychosomatic standpoint. Cultural aspects significantly influence psychology, and it may not be appropriate to blindly apply international research. Thus, research on the mental health of Japanese athletes is needed.
One psychosomatic issue that athletes face is mental health challenges, especially those of anxiety and depression. Depression in athletes can be observed as burnout syndrome, overtraining, social phobia, and anorexia [8]. Anxiety is a common mental health symptom in young athletes, and it can lead to the onset of depression [8].
Another issue is fatigue, which, like depression, plays a role in overtraining, chronic fatigue, and burnout syndrome in athletes. Fatigue is a subjective phenomenon characterized by overwhelming tiredness and a lack of energy [9]. However, fatigue is generally divided into the following types: subjective fatigue, which is the personal experience of tiredness, and performance fatigue, which refers to decreased physical performance. This distinction arises because of the implicit assumption that neuromuscular fatigue and associated sensations are independent, where symptoms arise in their interaction [10,11]. There is no consensus on the definition of fatigue, and its assessment in clinical settings involves evaluating multifaceted symptoms using subjective rating scales or assessing changes in exercise performance [9,12]. Because overtraining, chronic fatigue, and burnout syndrome have symptoms centered around fatigue and have a significant impact on mental health, it is crucial to address athlete fatigue [13,14].
Despite the risk to their mental health, athletes tend not to seek help because of biases such as stigma and concern regarding the impact on their performance; this can result in significant harm if these issues are overlooked [15]. Therefore, understanding what factors are associated with anxiety and depression in elite athletes and how mental health and chronic fatigue are involved can provide crucial insight into essential care for athletes. Based on these considerations, we believe that it is necessary to identify the risk factors for mental health challenges among Japanese athletes.
The research questions addressed in this study are as follows:
  • Do elite collegiate badminton players have higher levels of mental health issues (anxiety and depression) compared to healthy individuals?
  • What factors are associated with mental health issues in elite collegiate badminton players?
  • Is chronic fatigue a contributing factor to mental health issues in elite collegiate badminton players?
This study aims to address these research questions by examining factors related to mental health within this limited population of university elite athletes.

2. Materials and Methods

2.1. Subsection Study Design and Selection of Participants

This study employed a retrospective cross-sectional design using questionnaires. Analyses were conducted using evaluation forms provided at a health survey booth set up at the 2022 national badminton tournament. The total population for this study consisted of 223 participants from the singles division of the tournament, representing the universe of elite university badminton players in Japan. From this population, athletes who voluntarily applied to participate at the survey booth were selected as the subjects. The participants with experience competing in national tournaments were designated the athlete group. Male university students without regular sports practice were randomly approached for participation and designated as the healthy control group. For the control group, we targeted healthy male university students in Japan who were not engaged in competitive sports. According to the e-stat of Japan, the population of male university students in 2022 was reported to be 1,431,224 [16]. Based on recent reports indicating that approximately 6% of university students participate in competitive sports, the estimated population of male university students not engaged in competitive sports is approximately 1,345,350 [17]. At the time of the survey, the male university students who participated were provided with an oral explanation of the instrument, and written informed consent was obtained.
Male university athletes without experience in national tournaments and controls who were national tournament participants or had missing responses were excluded from this study.

2.2. Outcome Measures

The questionnaire collected anonymous self-report data. Basic demographic information such as age, part-time job status, competitive history, participation in competitions (international and national), and awards in competitions (international and national) was collected. Additionally, sports-related parameters, such as practice duration, rest periods, and total weekly practice hours, were analyzed. Furthermore, the questionnaires collected information on sports satisfaction, life satisfaction, exercise habits, and pain.
Sports satisfaction and life satisfaction were assessed on an 11-point numerical rating scale ranging from 0 to 10. Life satisfaction was defined as satisfaction outside sports.
The main outcome assessment used the Hospital Anxiety Depression Scale (HADS) to evaluate mental health parameters, specifically anxiety and depression. HADS is a 14-item scale with responses on a 4-point scale. The two subscales are calculated by summing the scores of their respective 7 items. Because HADS does not include physical symptoms, it allows for assessments excluding physical conditions. A cut-off value of 8 or above was considered indicative of the presence of symptoms for both anxiety and depression [18]. Additionally, the HADS has been validated for use in the general population, not just in patient groups [19].
Fatigue was assessed using the Checklist Individual Strength (CIS), a multidimensional measure of subjective fatigue. The CIS consists of 20 items answered on a 7-point Likert scale, calculated for four subscales (fatigue severity, concentration, motivation, and activity). The CIS is calculated from the sum of 8 items for fatigue severity, 5 items for concentration, 4 items for motivation, 3 items for activity, and the total of all these items. Higher scores on any subscale indicate greater severity of fatigue. CIS has been validated for reliability and validity in chronic fatigue syndrome and neurological disorders, and the validity of the Japanese version has also been reported for chronic fatigue patients [20]. On this instrument, a total score of 76 or higher indicates a risk of sick leave or work disability, and a subscale score of 35 or higher for fatigue severity indicates severe fatigue [21,22].

2.3. Statistical Analyses

HADS and CIS scores for the athlete and control groups were examined for internal validity using Cronbach’s alpha. Given the exploratory nature of this study, variables with a Cronbach’s alpha below the minimum threshold of 0.6 were considered to have low internal validity and were excluded from further analysis [23]. To compare measured outcomes between groups, the Student’s t-test or Mann–Whitney U test was used, depending on the results of the Shapiro–Wilk test for normality. Furthermore, within the athlete and control groups, the relationships among anxiety, depression, fatigue, and measured variables were analyzed using correlation tests. Variables were subjected to the Shapiro–Wilk test, and, depending upon the results, the Pearson test was applied for normally distributed data, or the Spearman test was used for data that did not follow a normal distribution. In addition, partial correlation analysis was conducted on the results of the correlation tests. Comparisons of nominal scales were made using the solution-square test. Basic statistical analyses were performed using EZR [24], and partial correlation analysis was conducted using the ppcor package in R [25,26]. The significance threshold was set to p < 0.05. The interpretation of correlation coefficients varies among researchers; however, in this study, a range of absolute values of 0–0.3 was defined as weak, 0.3–0.7 as moderate, and 0.7–1 as strong correlation [27]. The post hoc power analysis for the correlation test was conducted using the pwr.r.test function from the pwr package in R [28]. Additionally, when expressing basic statistical measures, parametric data were shown as mean ± SD (standard deviation), while non-parametric data were shown as median (quartile).

3. Results

3.1. Selection of Participants and Their Characteristics

The number of participants is depicted in Figure 1. After the data from 40 athlete respondents and 41 control respondents who met exclusion criteria were removed, there were responses from 29 athletes and 37 controls.
The basic characteristics of the athletes and healthy persons are presented in Table 1. Additionally, the distributions of age and life satisfaction were non-parametric. The median ages were 20 years for athletes and 21 years for controls, with a significant 1-year difference in age. Significant differences were also observed between the groups in terms of part-time employment status and the presence of hobbies.

3.2. Intergroup Comparison of Mental Health and Fatigue

The results of the intergroup comparison of evaluations between the athlete and control groups and Cronbach’s alpha coefficients are shown in Table 2. The Cronbach’s alpha for the CIS motivation and activity items was below 0.6, indicating low internal validity. Therefore, these items were excluded from further analysis. Additionally, the distributions of anxiety and depression were non-parametric. No significant differences were found in anxiety (p = 0.24) or depression (p = 0.07) between the groups. For anxiety, 14 (47%) athletes and 11 (29%) controls were symptomatic, with no significant differences observed between the groups in the number of symptomatic individuals (p = 0.20) or in severity (p = 0.60). For depression, nine (30%) athletes and eight (21%) controls were symptomatic, with no significant differences between the groups found in the number of symptomatic individuals (p = 0.24) or in severity (p = 1). Athletes scored significantly higher in CIS total value (p < 0.001) and concentration (p = 0.033).

3.3. Correlation Analysis of Mental Health and Fatigue within Each Group

The correlation tests between mental health and the measurement values for each group are presented in Table 3. In the athlete group, anxiety showed a moderately negative correlation with life satisfaction, though not a significant one (r = −0.37, p = 0.051), and weak correlations were seen with fatigue and sports parameters, showing no significant differences. In the control group, anxiety showed a significant moderately positive correlation with fatigue severity (r = −0.33, p = 0.04). Only weak correlations were found with other fatigue or satisfaction parameters, and no significant differences were noted.
In the athlete group, depression showed a significant moderately negative correlation with life satisfaction (r = −0.47, p = 0.008) and significant moderately negative correlations with CIS total score (r = −0.41, p = 0.02) and concentration (r = −0.38, p = 0.04). In contrast, depression in the control group showed a significant moderately negative correlation with life satisfaction (r = −0.45, p = 0.005) and a significant moderately positive correlation with the CIS total score (r = 0.34, p = 0.04). A notable feature of the correlation tests for depression was that while the control group showed a positive correlation with fatigue, the athlete group showed a negative correlation.
The results of the correlation tests for fatigue, satisfaction, and sports parameters in each group are presented in Table 4. In the athlete group, concentration (r = −0.37, p = 0.04) showed significant moderately negative correlations with life satisfaction, but other measurements showed only weak correlations, with no significant differences. In the control group, life satisfaction showed weak correlations, with no significant differences.

3.4. Partial Correlation Analysis in the Athlete Group

The results of the partial correlation tests in the athlete group are shown in Table 5. These tests were conducted to elucidate the detailed relationships among variables that showed significant differences in the correlation tests in the athlete group. The variables selected included anxiety and depression (measures of mental health), life satisfaction, and concentration.
Depression showed a significant moderately negative correlation with life satisfaction, even when adjusted for concentration (p = 0.043). Although the correlation with anxiety was not significant, a moderate negative correlation was observed (p = 0.088). Concentration showed a weak correlation when adjusted for mental health, reversing the sign of the correlation test results, indicating that these were spurious correlations mediated by life satisfaction (p = 0.18).

4. Discussion

This exploratory study conducted a cross-sectional survey of elite university student-athletes who competed in badminton at the national level and control students, focusing on factors affecting mental health (anxiety and depression) and fatigue.

4.1. Participant Characteristics

The athlete group in this exploratory study consisted entirely of participants who had competed in national tournaments, including elite university badminton players having competed at the world championship level. One significant difference that appeared between the athlete group and the control group was age. This study targeted university students participating in national tournaments, encompassing a wide age range of 18–22 years, producing a bias toward upperclassmen in the control group by the survey method. Surveys of mental health among university students are becoming increasingly more common, finding more significant mental health issues in specific subgroups in relation to gender, economic background, and social support, but not in relation to age [29]. For instance, one survey of Japanese university student-athletes found no difference in the levels of depression across academic years [30]. Furthermore, as the median age difference found in that study was only 1 year, it was considered not to have a severe impact.
The proportion of part-time employment also differed between groups. Previous research has shown that work can negatively impact university students’ mental health through poor workplace relationships [31], and part-time employment itself has a minor negative effect on mental health [32]. Furthermore, the results of inquiries regarding the presence or absence of hobbies (activities or interests) suggested that athletes had hobbies more rarely than controls. Recreational sports have been shown to mitigate stress-related anxiety [33], and the number of hobbies that a person has was reported to affect anxiety and depression during the COVID-19 lockdowns [34]. Significant differences in work and hobbies suggest that factors influencing mental health may vary.
Additionally, this study was conducted in 2022, and Japanese university students have been affected by the COVID-19 pandemic. Surveys of the mental health impacts of COVID-19 on Japanese university students have shown that the incidence of depression doubled between before and after the pandemic. The findings of this study may thus reflect the mental health and fatigue of elite badminton university student-athletes against the backdrop of a generation that was affected by the pandemic [35]. Therefore, caution is required in interpreting the results of this exploratory study with regard to the mental health of elite badminton players.

4.2. Intergroup Comparisons of Mental Health and Fatigue and Measurement Reliability

In this exploratory study, no clear difference was found between elite athlete university students and control university students in terms of mental health. This was indicated by an intergroup comparison of actual values and prevalence rates of anxiety and depression in this study, where, although the figures were slightly higher for university athletes, the differences were not significant. Researchers have previously reported that compared with the general population, athletes’ levels of depression and anxiety are either comparable or slightly lower [8]. Although the direction of the numbers differs, this study showed parallel results for Japanese athlete university students as those found in previous research.
The prevalence rates of mental health issues among athletes in this study were 47% for anxiety and 30% for depression, aligning with the range (10–43%) cited in the Introduction for international top athletes and showing higher values than a survey of top Japanese athletes (10%). Further investigation of mental health risks among Japanese athletes is necessary.
The evaluation of fatigue using the CIS showed that all items except for fatigue severity were significantly higher in the athlete group, but caution is necessary concerning the results for athletes’ motivations and activities. Evaluation of fatigue is important for athletes. However, despite the abundance of the literature, comparisons are not straightforward because of the ambiguity and variation in the definition of fatigue [10]. Fatigue is generally divided into subjective fatigue and decreased physical performance, but most studies on athlete fatigue focus only on physical performance or on the relationship between mental fatigue and performance. Understanding this duality is essential for a comprehensive assessment of athlete fatigue. Moreover, although top athletes have a risk of overuse syndrome and chronic fatigue syndrome, it is not clear which of the available questionaries is optimal for quantitatively evaluating fatigue. The ambiguity of the definition of fatigue also affects the measurement of athlete mental or subjective fatigue. The CIS that was used in this study was confirmed to have high reliability and validity in the assessment of symptomatic individuals who have chronic fatigue syndrome and multiple sclerosis [9]. Cronbach’s alpha coefficient is conventionally considered to designate reliability at 0.7 or above, and in some research, it is considered to show reliability at 0.6 or above. However, in this study, Cronbach’s alpha coefficients for motivation and activity in athletes were found to be too low to indicate reliability [23]. The interpretation of CIS evaluations for elite university student-athletes must, therefore, be carefully considered.

4.3. Factors Related to Mental Health and Fatigue

In the correlation analysis for mental health and fatigue in the athlete and control groups, as well as in the partial correlation analysis among athletes, several notable findings were observed. The most distinctive of these was that in the partial correlation analysis adjusted for concentration in the athlete group, depression and life satisfaction had a significant moderately negative correlation. However, no large effect-size correlations were found between the athletes’ competition satisfaction or sports parameters and mental health. These results suggest that factors outside sports, rather than satisfaction with the sport itself or the composition of practice, may be closely related to mental health.
However, in surveys on psychological support and mental health in athletes, reports on how life outside sports is related to mental health are limited. Excessive stress behavior due to the discrepancy between targeted sports achievements or performance and reality is well documented in the context of depression and chronic fatigue among athletes [36]. Of course, it is not unrealistic to posit a relationship between performance and depression, but according to the results of this study, life satisfaction outside of competition is a factor that affects mental health. Previous research has reported that athletes’ hobby activities contribute to reducing dropouts, and there are reports on athletes with physical limitations regarding subjective life satisfaction and quality of life (QOL) [37,38,39]. In the study examining the factors of athletes’ quality of life, it was shown that an athlete’s QOL improves with a positive mental state [38]. However, the discussion of the quality of life in athletes often encompasses their lives in terms of sports, and the perspective that athletes’ mental health is related to their life satisfaction outside of sports remains minimal. The findings of this exploratory study indicate a potential new approach to athlete mental health measures, emphasizing the importance of enriching their lives outside sports.
There are several reasons to consider the factors related to athletes’ fatigue carefully. First, the low internal consistency indicated by Cronbach’s alpha coefficients of 0.5 or below for athletes’ motivations and activities suggests that these measures may not be suitable. Moreover, the correlation tests between athletes’ mental health and the items of the CIS showed inverse positive and negative correlations relative to those shown for the control group, suggesting that the CIS may not have high validity for evaluating athlete fatigue. Indeed, concentration, which showed a moderately negative correlation with mental health for athletes, showed a weaker correlation with mental health in the partial correlation analysis, adjusted by life satisfaction, and the results were not significant. Thus, the CIS measurement in this study, with its parameters positively correlated with motivation and life satisfaction, suggests that it did not capture fatigue related to mental health. Thus, the CIS may not be a reliable or valid assessment for evaluating fatigue in university athlete students in terms of reliability and external validity.
Finally, one notable characteristic was the moderately negative correlation between depression and life satisfaction in the control group. No clear differences were seen for anxiety and depression in the intergroup comparison to athletes. Similarly, the correlation coefficients between the athlete and control groups showed similar patterns. In Japan, athletes are widely perceived to be mentally robust [6]. However, this exploratory study did not demonstrate that athletes are mentally tougher than controls, and it found that life satisfaction affects mental health in athletes, just as it does in other individuals. These exploratory findings reinforce the notion that mental health risks in athletes need to be addressed.

4.4. Study Limitations

Several research limitations must be considered when interpreting the results of this exploratory study. First, its design was that of a cross-sectional observational study performed with a questionnaire, which does not permit conclusions to be drawn regarding causality. In addition, the methods for soliciting participants for the athlete and control groups were different, potentially introducing bias. Furthermore, the participant athletes were all badminton players, suggesting that the low reliability and external validity of the CIS may result from an influence of the specific characteristics of the sport, limiting the generalizability of the findings. Moreover, because of the limited number of participants, it was not possible to apply methods of modeling analysis, such as structural equation modeling or multiple regression analysis. Finally, life satisfaction is a broad concept, and further analysis is needed to determine which aspects of life influence it for the study population.
Despite these limitations, the strengths of this exploratory study lie in its focus on mental health in the limited population of elite university student-athletes in badminton, discussion of evaluation methods for subjective fatigue, and elucidation of the relationship between mental health and life satisfaction among these student-athletes.
Future research should include larger sample sizes and consider longitudinal designs to better understand the dynamic relationships among life satisfaction, mental health, and fatigue in athletes. Additionally, further studies are needed to develop and validate appropriate tools for measuring mental and subjective fatigue in athletes, taking into account the specific characteristics of different sports and the ambiguity in the current definitions of fatigue. Such studies would help confirm these exploratory findings and provide a more comprehensive understanding of the factors affecting mental health in elite athletes.

5. Conclusions

This exploratory study focused on the mental health and fatigue of elite university student-athletes who compete at the national level in badminton, examining related factors and identifying several key findings. First, it was found that among university elite athlete students in badminton, anxiety and depression form a moderately negative correlation with life satisfaction outside sports. This suggests the need to explore the association between athletes’ lives and mental health rather than in the context of decreased mental health due to sports parameters, as has traditionally been performed. Next, the prevalence of anxiety and depression among athletes showed no significant difference from that of the control group, and the relationship between life satisfaction and depression was similar. Finally, the evaluation of fatigue using the CIS may have low reliability and validity for elite university student-athletes in badminton.
The findings of this exploratory study suggest the necessity of intervening in life outside sports as a measure to support mental health. Furthermore, it is necessary to conduct additional research to identify the factors that constitute life satisfaction and develop effective mental health prevention programs in more detail. Future studies should consider larger sample sizes and longitudinal designs to confirm these exploratory findings and to better understand the dynamic relationships among life satisfaction, mental health, and fatigue in elite athletes.

Author Contributions

Conceptualization, Y.S. (Yuta Sakamoto) and J.K.; methodology, Y.S. (Yuta Sakamoto); software, Y.S. (Yuta Sakamoto), Y.S. (Yukina Shinya) and M.S.; validation, Y.S. (Yuta Sakamoto), Y.S. (Yukina Shinya) and M.S.; formal analysis, Y.S. (Yuta Sakamoto), J.K., A.O., Y.S. (Yukina Shinya) and M.S.; investigation, J.K., A.O., Y.S. (Yukina Shinya), M.S. and Y.M.; resources, Y.S. (Yuta Sakamoto), J.K. and Y.M.; data curation, Y.S. (Yuta Sakamoto), Y.S. (Yukina Shinya) and M.S.; writing—original draft preparation, Y.S. (Yuta Sakamoto), Y.S. (Yukina Shinya) and M.S.; writing—review and editing, J.K., A.O. and Y.M.; visualization, Y.S. (Yukina Shinya) and M.S.; supervision, Y.S. (Yuta Sakamoto); project administration, Y.S. (Yuta Sakamoto) and J.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and received approval from the approval of the Health Sciences University Ethics Committee (Approval Number: R4-018).

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Acknowledgments

We express our gratitude to the members of the Health Sciences University Trainer Club for their cooperation in conducting the survey and to Professor Tatsuya Kasuyama for coordination. Additionally, we used ChatGPT (4.0) for English translation. Thank you very much.

Conflicts of Interest

The authors declare no conflicts of interest.

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Psychiatryint 05 00033 g001
Figure 1. Flow chart for determining the subjects for analysis. The 40 college student-athletes who agreed to participate in the survey were excluded because of the level of competition (n = 8) and response errors (n = 3), resulting in a group of 29 athletes. The 41 healthy college students who agreed to participate in the survey were excluded because of their high level of competition (n = 1) and response errors (n = 3), resulting in a control group of 37 students.
Figure 1. Flow chart for determining the subjects for analysis. The 40 college student-athletes who agreed to participate in the survey were excluded because of the level of competition (n = 8) and response errors (n = 3), resulting in a group of 29 athletes. The 41 healthy college students who agreed to participate in the survey were excluded because of their high level of competition (n = 1) and response errors (n = 3), resulting in a control group of 37 students.
Psychiatryint 05 00033 g001
Table 1. Basic characteristics of each group.
Table 1. Basic characteristics of each group.
AthletesHealthy Personsp
(n = 29)(n = 37)
Age 20 (19–21)21(21–22)<0.001
Part-time jobnone (%)15 (52)6 (16)<0.001
Hobbynone (%)18 (62)31 (84)<0.001
Competition historyyear14 (10–15)
Participation history
  World championshiphave (%)6 (21)
  National championshiphave (%)29 (100)
Experience winning awards
  World championshiphave (%)5 (17)
  National championshiphave (%)22 (76)
Practice timehr/wk22 (±5.9)
Exercise habitshave (%) 18 (47)
Sports satisfaction 7.1 (±2.1)
Life satisfaction 8 (5–9.5)7 (6–8)0.67
Painhave (%)20 (69)26 (70)0.91
Table 2. Groups comparison of mental health and fatigue parameters.
Table 2. Groups comparison of mental health and fatigue parameters.
AthleteHealthy Personp
(n = 29)α A(n = 37)α A
HADS
–Anxiety.Median (quartile)7 (3.5–9)0.745 (3–9)0.810.24
 Mild.Number (%)10 (34) 6 (16) 0.60
 Moderate.Number (%)3 (10) 3 (8)
 Severe.Number (%)1 (3) 2 (5)
–Depression.Median (quartile)5 (3–10)0.803 (2–7)0.690.07
 Mild.Number (%)5 (17) 6 (16) 1
 ModerateNumber (%)3 (10) 2 (5)
 Severe.Number (%)1 (3) 0 (0)
CIS
–Total.Mean ± SD91.2 ± 15.00.8376.6 ± 17.70.84<0.001 ***
–Fatigue Severity.Mean ± SD34.7 ± 6.90.7231.1 ± 10.90.880.13
–Concentration.Mean ± SD22.5 ± 5.30.6519.7 ± 5.20.670.033 *
–Motivation.Mean ± SD19.7 ± 3.90.4414.0 ± 5.40.74<0.001 ***
–Activity.Mean ± SD14.3 ± 2.30.1711.8 ± 3.80.620.003 **
A; Cronbach’s coefficient alpha, HADS; Hospital Anxiety Depression Scale, CIS; Checklist Individual Strength, SD; standard deviation. Parametric data are shown as mean ± SD, non-parametric data as median (quartile), * p < 0.05; ** p <0.01; *** p < 0.001.
Table 3. Correlation analysis of factors associated with mental health parameters.
Table 3. Correlation analysis of factors associated with mental health parameters.
AthleteHealthy Person
AnxietyDepressionAnxietyDepression
CIS
 –Total.  0.01−0.41 *  0.21  0.34 *
 –Fatigue severity.  0.08−0.27  0.33 *  0.29 *
 –Concentration.−0.17−0.38 *−0.08  0.23
Life satisfaction−0.37−0.47 ***−0.16−0.45 ***
Competition satisfaction−0.18−0.16
Practice time (hr/wk)  0.08  0.07
One practice time (min)  0.03  0.21
One break time (min)−0.08  0.03
Mental health parameters include anxiety and depression. Spearman rank correlation was used for anxiety and depression because of non-parametric distributions. CIS; Checklist Individual Strength, * p < 0.05; ***, p < 0.001.
Table 4. Correlation analysis of factors associated with fatigue.
Table 4. Correlation analysis of factors associated with fatigue.
AthleteHealthy Person
Fatigue SeverityConcentrationFatigue SeverityConcentration
Life satisfaction−0.31−0.37 *−0.18−0.47
Competition satisfaction−0.16  0.08
Practice time (hr/wk)−0.04  0.12
One practice time (min)−0.25  0.02
One break time (min)  0.003  0.05
* p < 0.05.
Table 5. Partial correlation analysis in athlete.
Table 5. Partial correlation analysis in athlete.
Variable 1Variable 2ControlPCCPost Hoc Power Analysis
AnxietyLife satisfactionConcentration−0.330.42
DepressionLife satisfactionConcentration−0.38 *0.56
ConcentrationLife satisfactionMental0.260.28
ConcentrationAnxietyLife satisfaction−0.0380.05
ConcentrationDepressionLife satisfaction−0.240.24
Mental; anxiety and depression, PCC; partial correlation coefficient, * p < 0.05.
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MDPI and ACS Style

Sakamoto, Y.; Komagata, J.; Otsuka, A.; Shinya, Y.; Sendouda, M.; Masu, Y. Factors Associated with Anxiety and Depression among Elite Collegiate Badminton Players in Japan: Exploratory Analysis. Psychiatry Int. 2024, 5, 470-481. https://doi.org/10.3390/psychiatryint5030033

AMA Style

Sakamoto Y, Komagata J, Otsuka A, Shinya Y, Sendouda M, Masu Y. Factors Associated with Anxiety and Depression among Elite Collegiate Badminton Players in Japan: Exploratory Analysis. Psychiatry International. 2024; 5(3):470-481. https://doi.org/10.3390/psychiatryint5030033

Chicago/Turabian Style

Sakamoto, Yuta, Junya Komagata, Atsuya Otsuka, Yukina Shinya, Momoka Sendouda, and Yujiro Masu. 2024. "Factors Associated with Anxiety and Depression among Elite Collegiate Badminton Players in Japan: Exploratory Analysis" Psychiatry International 5, no. 3: 470-481. https://doi.org/10.3390/psychiatryint5030033

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