Abstract
This study aimed to determine the prevalence and risk factors of poor subjective sleep quality in elite judo athletes. A subjective cross-sectional questionnaire survey was conducted with 106 elite judo athletes who participated in the training camp of the Japanese national team. Eighty-six respondents (men: 52.3%; average age: 22.9 ± 3.1 years) with complete responses were included in the analysis (valid response rate: 81.1%). Subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The prevalence of poor sleep quality (PSQI score ≥ 5.5), the mean PSQI score, and subscale scores were investigated. Relationships between poor sleep quality and attributes, lifestyle habits, competition-based activities, and psychological distress were explored using Fisher’s exact tests and multivariate logistic regression analysis. Thirty-five respondents (40.7%) reported poor sleep quality. The percentage and subscale scores of the respondents for sleep latency, sleep duration, and daytime dysfunction were higher than those of the population of Japanese national-level athletes. The mean PSQI score of the respondents was similar to that of some elite athlete populations but higher than those of others. Multivariate logistic regression analysis revealed that psychological distress was associated with poor sleep quality. In conclusion, the prevalence of poor subjective sleep quality in elite judo athletes was suggested to be similar or higher among elite athlete population. Sleep latency, sleep duration, and daytime dysfunction status were worse in elite judo athletes than in Japanese national-level athletes. Psychological distress was a risk factor for poor subjective sleep quality in elite judo athletes.
Supplementary Information
The online version contains supplementary material available at 10.1007/s41105-023-00444-6.
Keywords: Judokas, Sleep disturbances, Mental health, Determinants
Introduction
Sleep plays an important role in the mental and physical recovery of athletes who train hard daily [1]. Multiple recent systematic reviews have suggested that sleep loss not only decreases an athlete’s physical performance (e.g., speed and endurance) and cognitive performance (e.g., attention and memory) but also increases the risk of illness or injury [2, 3]. High-quality sleep is especially important for elite athletes in order to enhance their condition and performance and win high-level competitions.
Previous studies have reported sleep problems in elite athletes, such as national-level and professional athletes. A study using the Pittsburgh Sleep Quality Index (PSQI) showed that 28.0% of national-level athletes (candidates for the Asian games) in Japan had poor sleep quality [4]. Another study reported that athletes who were representative of nine countries at either national- or international-level competitions had a mean PSQI score of 5.1 ± 2.5 [5]. Furthermore, several studies also reported the mean PSQI scores of athletes engaged in specific sports disciplines: 3.6 ± 2.4 points in professional soccer players at the highest soccer league in the Netherlands [6], 4.3 ± 1.6 points in professional Australian football players in Australia [7], 5.1 ± 3.2 points in sprinters and hurdlers at the highest Dutch competition levels [6], and 5.6 ± 2.1 points in professional soccer players in Qatar [8].
Several studies on athletes of various disciplines have identified lifestyle habits, the status of competition-based activities, and psychological distress as risk factors for poor sleep quality. A study on Japanese national-level athletes reported that short time in bed, skipping breakfast, the use of electronic devices (PC, smartphone, etc.) just before bedtime, depressive mood, and thinking about troubles while in bed were risk factors for poor sleep quality [4]. A previous study of student-athletes reported similar lifestyle habits such as late bedtime, early wake time, late-night part-time jobs, and use of smartphones/cellphones after lights out; competition-based activities such as morning practices and motivation loss stressors; and psychological distress were related to poor sleep quality [9]. However, no study has investigated the discipline-specific risk factors of poor sleep quality in elite athletes.
Among athletes engaged in various sports, addressing sleep problems is extremely important for judo athletes. Competitive judo can be described as a high-intensity intermittent combat sport, and competitive judo athletes require high-level dynamic strength, muscular endurance, anaerobic power, and capacity [10]. Several studies have reported the impact of sleep conditions on physiological performance, such as muscle strength [11] and anaerobic performance [11, 12] in judo athletes. Therefore, appropriate measures to prevent poor sleep quality are essential for judo athletes.
Because judo has weight categories, most judo athletes reduce their body weight a few days before the competition to gain a competitive advantage over lighter opponents [13]. High training demands and weight loss can induce muscle damage and negatively impact the immune system [14], especially as a large number of judo athletes use extreme methods of weight reduction [15], which negatively affect physiological and psychological performance [16]. Rapid weight reduction has been reported to worsen depressive mood in judokas who participated in the Brazilian judo championship [17]. Additionally, some of them suffered from long term psychological impacts of repeated weight loss [18]. Since psychological distress induced by weight deduction is a major issue, it is implied that sleep conditions in elite judo athletes may be worse compared to elite athletes in other sports.
However, no study has investigated sleep conditions and related factors in elite judo athletes. Several studies on judo athletes have reported that the training load changes did not substantially alter sleep quality [19], and the use of electronic devices (e.g., PC and phones) was not related to sleep duration, sleep efficiency, and sleep latency [20], but were not examined in elite judo athletes. The knowledge of elite athletes is valuable because it can contribute to enhancing international competitiveness. Thus, the present study aimed to clarify the prevalence and risk factors for poor subjective sleep quality in elite judo athletes.
Methods
Procedure and participants
A subjective survey using a self-administered questionnaire was conducted between December 2017 and January 2018 in Japan. This study targeted 106 elite judo athletes who participated in the training camp of the Japanese national team. Ultimately, 12 qualified to compete in the Olympic Games of Tokyo 2020 and won medals. All participants responded to the survey (response rate: 100.0%). Among them, 86 respondents with complete responses were included in the analysis (valid response rate: 81.1%).
This study was approved by the Research Ethics Committee of the Faculty of Health and Sports Sciences of the University of Tsukuba, Japan (Reference No: Tai 29-44). All the respondents provided written informed consent to participate in the study.
Survey items
The questionnaire assessed attributes, subjective sleep quality, lifestyle habits, competition-based activities, and psychological distress.
Attributes included age, sex, height, and weight. The body mass index (BMI) was also calculated based on the participants’ height and weight; a BMI of more than 25 was considered obese, 18.5–25 as normal weight, and less than 18.5 as underweight.
Subjective sleep quality was assessed using the Japanese version of the Pittsburgh Sleep Quality Index (PSQI) [21, 22], which consists of 18 questions regarding an individual’s sleep habits during the previous month. Seven component scores were calculated from these questions: sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. Each of these components was scored on a scale of 0–3 points, with higher scores indicating poorer sleep conditions. The total score ranged from 0 to 21 points. The cutoff value was 5.5 points, and scores of at least 5.5 points indicated poor sleep quality. When used for screening insomnia, the PSQI had a sensitivity of 85.7% and a specificity of 86.6% [22].
Lifestyle habits included bedtime, wake-up time, drinking alcohol, meals (regularity of mealtimes; skipping breakfast, lunch, or dinner; taking meals, alcoholic drinks, caffeinated drinks, and supplements before going to bed), and use of electronics after lights out (e.g., television, smartphone/cellphone, and gaming devices).
Competition status, activity contents, and competition stressors were used to assess competition-based activities. Competition status included the length of athletic career (years) and performance level (top three winners of international games, participating in international competitions, prizes at national games, and others). The survey also included questions on sports time and the presence or absence of morning (9:00 a.m. or earlier) and evening practices (9:00 p.m. or later) each day to evaluate activity content. Based on these responses, we calculated the sports time per week and determined the presence or absence of morning and evening practice.
We used the Competition Stressor Scale developed by Asanuma et al. to assess competition stressors [23]. The 28-item scale measures the frequency of stress exposure over the past month. Each item is rated on a 4-point scale, with 0 indicating “not at all” and 3 indicating “very often.” It comprises five factors, and the score range for each component is as follows: interpersonal relationships, 0–24 points; competition results, 0–9 points; evaluations from one’s surroundings, 0–15 points; expectations and pressure from others, 0–15 points; and motivation loss, 0–21 points. Higher scores indicated higher stress levels, and the relevance of the scale has been demonstrated in previous studies [23]. Cronbach’s α values for our respondents were as follows: interpersonal relationships, 0.82; competition results, 0.85; evaluations from one’s surroundings, 0.85; expectations and pressure from others, 0.85; and motivation loss, 0.85.
The Japanese version of the K6 scale was used to assess psychological distress [24] and was robust for screening this condition [25]. All six items were rated on a 5-point Likert scale, with scores ranging from 0 to 4 points. A higher total score indicates poor mental health. The cut-off value was 5 points, and a score of at least 5 points indicated psychological distress. When used for screening mood and anxiety disorders, the detection sensitivity was 100.0%, while the specificity was 68.7% [24]. The Japanese version of the K6 was validated [26], and the internal consistency reliability (Cronbach’s α) of this scale in this study was 0.84.
Statistical analysis
All statistical analyses were conducted using SPSS Statistics 25.0 J for Windows. Before conducting the main analysis, each variable was compared between eligible and excluded respondents. The prevalence of poor sleep quality (scores ≥ 5.5 points or more in the PSQI), mean PSQI score, and score of each PSQI component were investigated. Second, the relationships between poor sleep quality and attributes, lifestyle habits, competition-based activities, and psychological distress were examined using Fisher’s exact tests. Finally, multivariate logistic regression analysis of poor sleep quality was performed. In this analysis, only the variables that had a significant association with poor sleep quality in Fisher’s exact test were used as independent variables, and attributes were adjusted. Prior to this analysis, we confirmed that multicollinearity had not occurred.
For the analyses involving poor sleep quality, absence (scores < 5.5 points in the PSQI) was coded as 0, while presence (scores ≥ 5.5 points in the PSQI) was coded as 1. In addition, for independent variables, the category with the lowest non-zero prevalence of poor sleep quality was set as the reference category. Bedtime and wake time were divided into the following three groups: before 11:00 p.m., 11:00–11:59 p.m., and 0:00 a.m. or later for bedtime, and before 7:00 a.m., 7:00–7:59 a.m. and 8:00 a.m. or later for wake time. Performance level was classified into international competition level (including top 3 winners of international games and participants of international competitions) and national competition level (including prizes at national games and others). Age, length of athletic career, sports time per week, and factors of competition stressors were divided by the median value. The statistical level of significance was set at 5%.
Results
Table 1 shows the respondents’ characteristics. The respondents included 45 men (52.3%), and the mean age was 22.9 ± 3.1 years (range: 17–32 years). Based on BMI, 48.8% of the respondents were obese, 51.2% had normal BMI, and none were categorized as underweight. The participants had an average athletic career length of 16.8 ± 3.5 years (range 10–27 years), and 86.0% had an international competition level. A comparison of each variable between eligible and excluded respondents is presented in Supplementary Table 1. The excluded respondents were likelier to be obese and have worse daytime dysfunction than the eligible respondents.
Table 1.
Respondents’ characteristics
| M ± SD or n (%) | |
|---|---|
| Attributes | |
| Age | 22.9 ± 3.1 |
| Max | 32 |
| Min | 17 |
| Sex | |
| Men | 45 (52.3) |
| Women | 41 (47.7) |
| Body mass index | |
| Normal weight | 44 (51.2) |
| Obese | 42 (48.8) |
| Lifestyle habits | |
| Bedtime | |
| Before 11:00 p.m | 11 (12.8) |
| 11:00–11:59 p.m | 44 (51.2) |
| After 0:00 a.m | 31 (36.0) |
| Wake–up time | |
| Before 7:00 a.m | 38 (44.2) |
| 7:00–7:59 a.m | 38 (44.2) |
| After 8:00 a.m | 10 (11.6) |
| Drinking alcohol | |
| Yes | 50 (58.1) |
| Meals | |
| Regular mealtimes | |
| Yes | 69 (80.2) |
| Skipping breakfast | |
| Yes | 42 (48.8) |
| Skipping lunch | |
| Yes | 5 (5.8) |
| Skipping dinner | |
| Yes | 4 (4.7) |
| Taking meals before bed | |
| Yes | 60 (69.8) |
| Taking alcoholic drinks before bed | |
| Yes | 37 (43.0) |
| Taking caffeinated drinks before bed | |
| Yes | 33 (38.4) |
| Taking supplements before bed | |
| Yes | 48 (55.8) |
| Use of electronics after lights out | |
| Television | |
| Yes | 75 (87.2) |
| Smartphone/cellphone | |
| Yes | 77 (89.5) |
| Gaming devices | |
| Yes | 9 (10.5) |
| Competition activities | |
| Competition status | |
| Athletic career (years) | 16.8 ± 3.5 |
| Max | 27 |
| Min | 10 |
| Performance level | |
| Top 3 of international games | 66 (76.7) |
| International | 8 (9.3) |
| Prizes at national games | 11 (12.8) |
| Others | 1 (1.2) |
| Activities contents | |
| Sports time per week (minutes) | 1261.4 ± 376.6 |
| Morning practices (9:00 a.m. or earlier) | |
| Yes | 62 (72.1) |
| Evenings practices (9:00 p.m. or later) | |
| Yes | 8 (9.3) |
| Competition stressors | |
| Interpersonal relationships (points) | 5.8 ± 4.4 |
| Competition results (points) | 4.7 ± 2.6 |
| Evaluations from one’s surroundings (points) | 2.3 ± 3.1 |
| Expectations and pressure from others (points) | 6.0 ± 4.0 |
| Motivation loss (points) | 5.5 ± 4.7 |
| Psychological distress | |
| Presence | 29 (33.7) |
M mean, SD standard deviation
Table 2 presents the proportion of respondents with poor sleep quality, mean PSQI score, and distribution of each PSQI component. Among all respondents, 35 (40.7%) had poor sleep quality, and the mean PSQI score was 5.3 ± 2.1 points.
Table 2.
Respondents’ sleep status
| M ± SD or n (%) | |
|---|---|
| PSQI global score | 5.3 ± 2.1 |
| Poor sleep quality | |
| Absence | 51 (59.3) |
| Presence | 35 (40.7) |
| PSQI component score | |
| Sleep quality | |
| 0 points | 4 (4.7) |
| 1 point | 55 (64.0) |
| 2 points | 26 (30.2) |
| 3 points | 1 (1.2) |
| Sleep latency | |
| 0 points | 17 (19.8) |
| 1 point | 31 (36.0) |
| 2 points | 25 (29.1) |
| 3 points | 13 (15.1) |
| Sleep duration | |
| 0 points | 25 (29.1) |
| 1 point | 41 (47.7) |
| 2 points | 20 (23.3) |
| 3 points | 0 (0.0) |
| Habitual sleep efficiency | |
| 0 points | 74 (86.0) |
| 1 point | 9 (10.5) |
| 2 points | 3 (3.5) |
| 3 points | 0 (0.0) |
| Sleep disturbances | |
| 0 points | 21 (24.4) |
| 1 point | 65 (75.6) |
| 2 points | 0 (0.0) |
| 3 points | 0 (0.0) |
| Use of sleep medication | |
| 0 points | 86 (100.0) |
| 1 point | 0 (0.0) |
| 2 points | 0 (0.0) |
| 3 points | 0 (0.0) |
| Daytime dysfunction | |
| 0 points | 28 (32.6) |
| 1 point | 48 (55.8) |
| 2 points | 9 (10.5) |
| 3 points | 1 (1.2) |
M mean, SD standard deviation, PSQI Pittsburgh Sleep Quality Index
Table 3 shows the proportion of respondents with poor sleep quality based on attribute status, lifestyle habits, competition-based activities, and psychological distress. The results of Fisher’s exact tests showed that poor sleep quality were significantly related to the length of athletic career (p < 0.05) and psychological distress (p < 0.01). The prevalence of poor sleep quality was higher in respondents with an athletic career length of 16 years or less than in those with an athletic career length of 17 years or more. The prevalence of poor sleep quality was also higher in respondents with psychological distress than in those without psychological distress.
Table 3.
Relationships between poor sleep quality and attributes, lifestyle habits, competition-based activities, and psychological distress
| Poor sleep quality | |||
|---|---|---|---|
| Absence | Presence | p valuea | |
| n (%) | n (%) | ||
| Attributes | |||
| Age | |||
| 23 years or more | 29 (65.9) | 15 (34.1) | 0.273 |
| 22 years or less | 22 (52.4) | 20 (47.6) | |
| Sex | |||
| Male | 27 (60.0) | 18 (40.0) | 1.000 |
| Female | 24 (58.5) | 17 (41.5) | |
| Body mass index | |||
| Obese | 28 (66.7) | 14 (33.3) | 0.194 |
| Normal weight | 23 (52.3) | 21 (47.7) | |
| Lifestyle habits | |||
| Bedtime | |||
| Before 11:00 p.m | 8 (72.7) | 3 (27.3) | 0.321 |
| 11:00–11:59 p.m | 28 (63.6) | 16 (36.4) | |
| 0:00 a.m. or later | 15 (48.4) | 16 (51.6) | |
| Wake up time | |||
| Before 7:00 a.m | 23 (60.5) | 15 (39.5) | 1.000 |
| 7:00–7:59 a.m | 22 (57.9) | 16 (42.1) | |
| 8:00 a.m. or later | 6 (60.0) | 4 (40.0) | |
| Drinking alcohol | |||
| Yes | 31 (62.0) | 19 (38.0) | 0.657 |
| No | 20 (55.6) | 16 (44.4) | |
| Meals | |||
| Regular mealtimes | |||
| Yes | 43 (62.3) | 26 (37.7) | 0.281 |
| No | 8 (47.1) | 9 (52.9) | |
| Skipping breakfast | |||
| No | 30 (68.2) | 14 (31.8) | 0.124 |
| Yes | 21 (50.0) | 21 (50.0) | |
| Skipping lunch | |||
| No | 49 (60.5) | 32 (39.5) | 0.393 |
| Yes | 2 (40.0) | 3 (60.0) | |
| Skipping dinner | |||
| No | 49 (59.8) | 33 (40.2) | 1.000 |
| Yes | 2 (50.0) | 2 (50.0) | |
| Taking meals before going to bed | |||
| No | 19 (73.1) | 7 (26.9) | 0.100 |
| Yes | 32 (53.3) | 28 (46.7) | |
| Taking alcoholic drinks before going to bed | |||
| Yes | 22 (59.5) | 15 (40.5) | 1.000 |
| No | 29 (59.2) | 20 (40.8) | |
| Taking caffeinated drinks before going to bed | |||
| No | 33 (62.3) | 20 (37.7) | 0.506 |
| Yes | 18 (54.5) | 15 (45.5) | |
| Taking supplements before going to bed | |||
| Yes | 30 (62.5) | 18 (37.5) | 0.516 |
| No | 21 (55.3) | 17 (44.7) | |
| Use of electronics after lights-out | |||
| Television | |||
| No | 45 (62.5) | 27 (37.5) | 0.236 |
| Yes | 6 (42.9) | 8 (57.1) | |
| Smartphone/cellphone | |||
| No | 9 (81.8) | 2 (18.2) | 0.187 |
| Yes | 42 (56.0) | 33 (44.0) | |
| Computer | |||
| No | 48 (62.3) | 29 (37.7) | 0.150 |
| Yes | 3 (33.3) | 6 (66.7) | |
| Competition-based activities | |||
| Competition status | |||
| Length of athletic career | |||
| 17 years or more | 32 (69.6) | 14 (30.4) | 0.049 |
| 16 years or less | 19 (47.5) | 21 (52.5) | |
| Performance level | |||
| National competition level | 8 (66.7) | 4 (33.3) | 0.754 |
| International competition level | 43 (58.1) | 31 (41.9) | |
| Activities contents | |||
| Sports time per week | |||
| 1260 min or more | 26 (60.5) | 17 (39.5) | 1.000 |
| 1259 min or less | 25 (58.1) | 18 (41.9) | |
| Morning practices (9:00 a.m. or earlier) | |||
| Yes | 38 (61.3) | 24 (38.7) | |
| No | 13 (54.2) | 11 (45.8) | 0.627 |
| Evenings practices (9:00 p.m. or later) | |||
| Yes | 5 (62.5) | 3 (37.5) | |
| No | 46 (59.0) | 32 (41.0) | 1.000 |
| Competition stressors | |||
| Interpersonal relationships | |||
| 5 points or less | 29 (67.4) | 14 (32.6) | 0.188 |
| 6 points or more | 22 (51.2) | 21 (48.8) | |
| Competition results | |||
| 4 points or less | 24 (60.0) | 16 (40.0) | 1.000 |
| 5 points or more | 27 (58.7) | 19 (41.3) | |
| Evaluations from one’s surroundings | |||
| 1 point or less | 31 (64.6) | 17 (35.4) | 0.279 |
| 2 points or more | 20 (52.6) | 18 (47.4) | |
| Expectations and pressure from others | |||
| 7 points or more | 27 (62.8) | 16 (37.2) | 0.661 |
| 6 points or less | 24 (55.8) | 19 (44.2) | |
| Motivation loss | |||
| 5 points or less | 30 (65.2) | 16 (34.8) | 0.275 |
| 6 points or more | 21 (52.5) | 19 (47.5) | |
| Psychological distress | |||
| Absence | 40 (70.2) | 17 (29.8) | 0.005 |
| Presence | 11 (37.9) | 18 (62.1) | |
aFisher’s exact test
Table 4 presents the results of multivariate logistic regression analysis for predicting poor sleep quality. The results showed a significant relationship between psychological distress and poor sleep quality, and the presence of psychological distress had a 3.38 odds ratio of causing poor sleep quality compared with the absence of this condition (AOR 3.38, 95% CI 1.26–9.08, p < 0.05).
Table 4.
Multivariate logistic regression analysis of poor sleep quality
| Multivariate logistic regression analysisa | |||
|---|---|---|---|
| AOR | 95% CI | p value | |
| Length of athletic career | |||
| 17 years or more | 1.00 | ||
| 16 years or less | 3.00 | 0.86–10.48 | 0.086 |
| Psychological distress | |||
| Absence | 1.00 | ||
| Presence | 3.38 | 1.26–9.08 | 0.016 |
AOR adjusted odds ratio, CI confidence interval
aAdjusted for attributes
Discussion
The present study investigated the prevalence and risk factors of poor subjective sleep quality in elite judo athletes. The results showed that 40.7% of respondents who participated in the training camp of the Japanese national judo team had poor sleep quality, as assessed by the PSQI, which was higher than 28.0% of Japanese national-level athletes of 36 disciplines who were candidates for the Asian games [4] (see Supplementary Fig. 1). Furthermore, the mean PSQI score of our respondents was 5.3 ± 2.1 points, which was worse than that of Japanese national-level athletes as described above [4], professional soccer players in the Netherlands [6], and professional Australian football players in Australia [7] (see Supplementary Fig. 2). However, it was not significantly different from elite athletes of 18 disciplines in 9 countries [5], national-level athletes of sprinters and hurdlers in the Netherlands [6], and professional soccer players in Qatar [8]. Taken together, the sleep conditions of elite judo athletes tended to be similar to or worse than those of other elite athletes.
The component scores of our respondents for sleep latency, sleep duration, and daytime dysfunction were worse than those of Japanese national-level athletes (candidates for the Asian games) [4] (see Supplementary Table 2). These factors would contribute to our respondents’ poorer sleep quality. The respondents’ shorter sleep duration may be caused by morning practices (72.1%) and evening practices (9.3%), both of which were more prevalent than in national-level athletes of various sports events (48.4 and 4.0% for morning and evening practices, respectively) [4]. The higher daytime dysfunction of our respondents is consistent with the fact that heavyweight-class judo athletes suffer from sleep-disordered breathing and excessive daytime sleepiness [27]. Furthermore, our results support that daytime dysfunction is caused by low sleep quality and inadequate sleep duration [28, 29].
Our respondents showed no sex differences in subjective sleep quality. One reason for this may be that this study was conducted during the training camp in which all respondents lived in similar environments. As for differences between in sleep quality, the results of previous studies were inconsistent. For example, some reported differences between sexes, such as poorer sleep quality in women than in men [4, 30, 31]. Conversely, men had poorer sleep quality than women [32], and others reported no sex difference [33, 34], making further studies are necessary.
Multivariate logistic regression analysis showed that poor sleep quality in elite judo athletes was related to psychological distress only, but not competition-based activities as well as lifestyle habits. This supports previous findings on judo athletes that the training load changes did not alter sleep quality [19] and the use of electronic devices (e.g., PC and phones) was not related to sleep duration, sleep efficiency, and sleep latency [20]. On the other hand, previous studies that targeted athletes of various disciplines [4, 9] reported that competition-based activities and various lifestyle habits were also related to poor sleep quality. Since our study targeted elite judo athletes during the training camp of the Japanese national team, respondents had comparable competition levels, and it is considered that their competition-based activities as well as lifestyle habits were even similar. This homogeneity of competition-based activities and lifestyle habits may have resulted in no statistical relationship of these variables with poor sleep quality. Further studies are necessary to clarify risk factors of poor sleep quality in single discipline elite athletes.
Several situations induced psychological distress in our respondents. First, this survey was conducted during the training camp of the Japanese national team. Because our respondents were those who aspired to be representatives of Japan, they could have high pressure. In fact, the mean score of expectations and pressure from others in our respondents was higher than that in student athletes [9], which may have induced their psychological distress. Second, most judo athletes suffer long-term psychological distress due to repeated weight loss [18]. Many judo athletes use extreme methods of weight reduction [15], which negatively effect on psychological performance [16]. Rapid weight reduction has been reported to worsen depressive mood in judo athletes who participated in the Brazilian judo championship [17].
This study had several limitations. First, because this was a cross-sectional study, we could not evaluate the causal relationships between lifestyle habits, competition-based activities, psychological distress, and poor sleep quality. Hence, a longitudinal study is necessary to verify the causal relationships among these variables. Second, the PSQI questionnaire assesses subjective sleep quality and has high sensitivity and specificity in the detection of insomnia [22]. However, additional objective measures of sleep are required to gain insight into the nature of sleep problems, including some symptoms of sleep disorders (e.g., apnea and periodic body movement) among judo athletes. In addition, some items, such as body composition and competition-based activity, should be measured objectively to avoid reporting bias. Third, the sample size of the present study was relatively small for multivariate analysis. Thus, it would be better to conduct future studies with larger sample sizes and involving other countries. Research in other countries is important for international comparisons because judo is globally popular. More than 200 countries and territories are members of the International Judo Federation [35], but there are regional, cultural, and religious differences among these places. Fourth, although the response rate in our present study was adequate, approximately 20% of participants were excluded from the analysis due to incomplete responses. A comparison of each variable between eligible and excluded respondents showed that excluded respondents were more likely to be obese and to have worse daytime dysfunction than eligible respondents. Thus, selection bias might have occurred. Fifth, this survey was conducted during the training camp of the Japanese national team. The PSQI is supposed to assess the respondents’ sleep condition in the previous month, but that situation might have led to reporting bias to some extent, even though the duration of the training was short.
Despite these limitations, this is a valuable study as it reports the prevalence of poor sleep quality and its risk factors in elite judo athletes. The respondents of this study were participants of the training camp of the Japanese national team and included medalists at the Tokyo 2020 Summer Olympics. Our findings will contribute to maintaining sleep conditions and enhancing athletic performance in the highest level of judo athletes.
Conclusions
The prevalence of poor subjective sleep quality (40.7%) assessed by the PSQI score ≥ 5.5 and the mean PSQI score in elite judo athletes were tended to be similar or higher compared other elite athlete populations. Sleep latency, sleep duration, and daytime dysfunction status were worse in elite judo athletes than in Japanese national-level athletes. Psychological distress has been found to be a risk factor for poor subjective sleep quality in elite judo athletes.
Supplementary Information
Below is the link to the electronic supplementary material.
Author contributions
TMo was involved in data collection, analysis, interpretation and writing the manuscript. TMa, KI, KM, TO, MT, TI, and MS were involved in data collection and reviewing the manuscript. KT was involved in reviewing the manuscript and funding acquisition. FT was involved in design of the work, data collection, interpretation, and funding acquisition. All authors approved the manuscript to be published, and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of our work are appropriately investigated and resolved.
Funding
This study was supported in part by a grant from Japan Sports Agency’s Sports Research Innovation Project (SRIP).
Declarations
Conflict of interest
The authors declare that they have no conflicts of interest.
Ethical approval
This study was approved by the Research Ethics Committee of the Faculty of Health and Sports Sciences of the University of Tsukuba, Japan (Reference No: Tai 29-44).
Informed consent
All respondents provided a written informed consent to participate in this study.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Leeder J, Glaister M, Pizzoferro K, Dawson J, Pedlar C. Sleep duration and quality in elite athletes measured using wristwatch actigraphy. J Sports Sci. 2012;30(6):541–545. doi: 10.1080/02640414.2012.660188. [DOI] [PubMed] [Google Scholar]
- 2.Fullagar HH, Skorski S, Duffield R, Hammes D, Coutts AJ, Meyer T. Sleep and athletic performance: the effects of sleep loss on exercise performance, and physiological and cognitive responses to exercise. Sports Med. 2015;45(2):161–186. doi: 10.1007/s40279-014-0260-0. [DOI] [PubMed] [Google Scholar]
- 3.Simpson NS, Gibbs EL, Matheson GO. Optimizing sleep to maximize performance: implications and recommendations for elite athletes. Scand J Med Sci Sports. 2017;27(3):266–274. doi: 10.1111/sms.12703. [DOI] [PubMed] [Google Scholar]
- 4.Hoshikawa M, Uchida S, Hirano Y. A subjective assessment of the prevalence and factors associated with poor sleep quality amongst elite Japanese athletes. Sports Med Open. 2018;4(1):10. doi: 10.1186/s40798-018-0122-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Driller MW, Mah CD, Halson SL. Development of the athlete sleep behavior questionnaire: a tool for identifying maladaptive sleep practices in elite athletes. Sleep Sci. 2018;11(1):37–44. doi: 10.5935/1984-0063.20180009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Rijken NH, Soer R, de Maar E, Prins H, Teeuw WB, Peuscher J, Oosterveld FG. Increasing performance of professional soccer players and elite track and field athletes with peak performance training and biofeedback: a pilot study. Appl Psychophysiol Biofeedback. 2016;41(4):421–430. doi: 10.1007/s10484-016-9344-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Van Ryswyk E, Weeks R, Bandick L, O'Keefe M, Vakulin A, Catcheside P, Barger L, Potter A, Poulos N, Wallace J, Antic NA. A novel sleep optimisation programme to improve athletes' well-being and performance. Eur J Sport Sci. 2017;17(2):144–151. doi: 10.1080/17461391.2016.1221470. [DOI] [PubMed] [Google Scholar]
- 8.Khalladi K, Farooq A, Souissi S, Herrera CP, Chamari K, Taylor L, El Massioui F. Inter-relationship between sleep quality, insomnia and sleep disorders in professional soccer players. BMJ Open Sport Exerc Med. 2019;5(1):e000498. doi: 10.1136/bmjsem-2018-000498. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Monma T, Ando A, Asanuma T, Yoshitake Y, Yoshida G, Miyazawa T, Ebine N, Takeda S, Omi N, Satoh M, Tokuyama K, Takeda F. Sleep disorder risk factors among student athletes. Sleep Med. 2018;44:76–81. doi: 10.1016/j.sleep.2017.11.1130. [DOI] [PubMed] [Google Scholar]
- 10.Franchini E, Del Vecchio FB, Matsushigue KA, Artioli GG. Physiological profiles of elite judo athletes. Sports Med. 2011;41(2):147–166. doi: 10.2165/11538580-000000000-00000. [DOI] [PubMed] [Google Scholar]
- 11.Souissi N, Chtourou H, Aloui A, Hammouda O, Dogui M, Chaouachi A, Chamari K. Effects of time-of-day and partial sleep deprivation on short-term maximal performances of judo competitors. J Strength Cond Res. 2013;27(9):2473–2480. doi: 10.1519/JSC.0b013e31827f4792. [DOI] [PubMed] [Google Scholar]
- 12.HajSalem M, Chtourou H, Aloui A, Hammouda O, Souissi N. Effects of partial sleep deprivation at the end of the night on anaerobic performances in judokas. Biol Rhythm Res. 2013;44(5):815–821. doi: 10.1080/09291016.2012.756282. [DOI] [Google Scholar]
- 13.Artioli GG, Franchini E, Nicastro H, Sterkowicz S, Solis MY, Lancha AH., Jr The need of a weight management control program in judo: a proposal based on the successful case of wrestling. J Int Soc Sports Nutr. 2010;7:15. doi: 10.1186/1550-2783-7-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Franchini E, Brito CJ, Fukuda DH, Artioli GG. The physiology of judo-specific training modalities. J Strength Cond Res. 2014;28(5):1474–1481. doi: 10.1519/JSC.0000000000000281. [DOI] [PubMed] [Google Scholar]
- 15.Artioli GG, Gualano B, Franchini E, Scagliusi FB, Takesian M, Fuchs M, Lancha AH., Jr Prevalence, magnitude, and methods of rapid weight loss among judo competitors. Med Sci Sports Exerc. 2010;42(3):436–442. doi: 10.1249/MSS.0b013e3181ba8055. [DOI] [PubMed] [Google Scholar]
- 16.Degoutte F, Jouanel P, Bègue RJ, Colombier M, Lac G, Pequignot JM, Filaire E. Food restriction, performance, biochemical, psychological, and endocrine changes in judo athletes. Int J Sports Med. 2006;27(1):9–18. doi: 10.1055/s-2005-837505. [DOI] [PubMed] [Google Scholar]
- 17.Fortes LS, Lira HAAS, Andrede J, Oliveira SFM, Paes PP, Vianna JM, Vieira LM. Mood response after two weeks of rapid weight reduction in judokas. Arch of Budo. 2018;14:125–132. [Google Scholar]
- 18.Gordon Y, Souglis A, Andronikos G. Effect of weight restriction strategies in judokas. J Phys Educ Sport. 2021;21(6):3394–3404. doi: 10.7752/jpes.2021.06460. [DOI] [Google Scholar]
- 19.Ouergui I, Ardigò LP, Selmi O, Levitt DE, Chtourou H, Bouassida A, Bouhlel E, Franchini E. Changes in perceived exertion, well-being, and recovery during specific judo training: impact of training period and exercise modality. Front Physiol. 2020;11:931. doi: 10.3389/fphys.2020.00931. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Dunican IC, Martin DT, Halson SL, Reale RJ, Dawson BT, Caldwell JA, Jones MJ, Eastwood PR. The effects of the removal of electronic devices for 48 hours on sleep in elite judo athletes. J Strength Cond Res. 2017;31(10):2832–2839. doi: 10.1519/JSC.0000000000001697. [DOI] [PubMed] [Google Scholar]
- 21.Buysse DJ, Reynolds CF, 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213. doi: 10.1016/0165-1781(89)90047-4. [DOI] [PubMed] [Google Scholar]
- 22.Doi Y, Minowa M, Uchiyama M, Okawa M, Kim K, Shibui K, Kamei Y. Psychometric assessment of subjective sleep quality using the Japanese version of the Pittsburgh Sleep Quality Index (PSQI-J) in psychiatric disordered and control subjects. Psychiatry Res. 2000;97(2–3):165–172. doi: 10.1016/s0165-1781(00)00232-8. [DOI] [PubMed] [Google Scholar]
- 23.Asanuma T, Takeda F, Monma T, Hotoge S. Relationship between mental health and competitive stressor among collegiate athletes –differences in the level of sense of coherence–. Jpn J Health Promot. 2015;17:7–14. [Google Scholar]
- 24.Furukawa TA, Kawakami N, Saitoh M, Ono Y, Nakane Y, Nakamura Y, Tachimori H, Iwata N, Uda H, Nakane H, Watanabe M, Naganuma Y, Hata Y, Kobayashi M, Miyake Y, Takeshima T, Kikkawa T. The performance of the Japanese version of the K6 and K10 in the World Mental Health Survey Japan. Int J Methods Psychiatr Res. 2008;17(3):152–158. doi: 10.1002/mpr.257. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SL, Walters EE, Zaslavsky AM. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med. 2002;32(6):959–976. doi: 10.1017/s0033291702006074. [DOI] [PubMed] [Google Scholar]
- 26.Sakurai K, Nishi A, Kondo K, Yanagida K, Kawakami N. Screening performance of K6/K10 and other screening instruments for mood and anxiety disorders in Japan. Psychiatry Clin Neurosci. 2011;65(5):434–441. doi: 10.1111/j.1440-1819.2011.02236.x. [DOI] [PubMed] [Google Scholar]
- 27.Wada H, Nagata K, Shirahama R, Tajima T, Kimura M, Ikeda A, Maruyama K, Tamura M, Suzuki K, Tanigawa T. Impact of sleep disordered breathing on performance in judo players. BMJ Open Sport Exerc Med. 2019;5(1):e000418. doi: 10.1136/bmjsem-2018-000418. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Huang YS, Wang CH, Guilleminault C. An epidemiologic study of sleep problems among adolescents in North Taiwan. Sleep Med. 2010;11(10):1035–42. doi: 10.1016/j.sleep.2010.04.009. [DOI] [PubMed] [Google Scholar]
- 29.Pilcher JJ, Ginter DR, Sadowsky B. Sleep quality versus sleep quantity: relationships between sleep and measures of health, well-being and sleepiness in college students. J Psychosom Res. 1997;42(6):583–96. doi: 10.1016/s0022-3999(97)00004-4. [DOI] [PubMed] [Google Scholar]
- 30.Koikawa N, Shimada S, Suda S, Murata A, Kasai T. Sex differences in subjective sleep quality, sleepiness, and health-related quality of life among collegiate soccer players. Sleep Biol Rhythms. 2016;14:377–386. doi: 10.1007/s41105-016-0068-4. [DOI] [Google Scholar]
- 31.Kawasaki Y, Kasai T, Koikawa N, Hanazato N, Suda S, Murata A, Ozaki R, Nagai S, Matsumura Y, Kaneko H, Kubo M, Osawa A, Nojiri S, Ogasawara E, Sakuraba K, Daida H, Kitade M, Itakura A. Sex differences in factors associated with poor subjective sleep quality in athletes. J Sports Med Phys Fitness. 2020;60(1):140–151. doi: 10.23736/S0022-4707.19.09875-X. [DOI] [PubMed] [Google Scholar]
- 32.Mah CD, Kezirian EJ, Marcello BM, Dement WC. Poor sleep quality and insufficient sleep of a collegiate student-athlete population. Sleep Health. 2018;4(3):251–257. doi: 10.1016/j.sleh.2018.02.005. [DOI] [PubMed] [Google Scholar]
- 33.Carter JR, Gervais BM, Adomeit JL, Greenlund IM. Subjective and objective sleep differ in male and female collegiate athletes. Sleep Health. 2020;6(5):623–628. doi: 10.1016/j.sleh.2020.01.016. [DOI] [PubMed] [Google Scholar]
- 34.Halson SL, Johnston RD, Appaneal RN, Rogers MA, Toohey LA, Drew MK, Sargent C, Roach GD. Sleep quality in elite athletes: normative values, reliability and understanding contributors to poor sleep. Sports Med. 2022;52(2):417–426. doi: 10.1007/s40279-021-01555-1. [DOI] [PubMed] [Google Scholar]
- 35.International Judo Federation. Countries. https://www.ijf.org/countries/all/members. Accessed 16 Sep 2022.
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.