{"title":"由于运动员的训练时间与睡眠困难评分有关,因此可能会对临床睡眠问题产生影响。","authors":"","doi":"10.1016/j.sleh.2024.02.006","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><p>Sleep is a key component of athletic recovery, yet training times could influence the sleep of athletes. The aim of the current study was to compare sleep difficulties in athletes across different training time groups (early morning, daytime, late evening, early morning plus late evening) and to investigate whether training time can predict sleep difficulties.</p></div><div><h3>Methods</h3><p><span>Athletes from various sports who performed at a national-level (n = 273) answered the Athlete Sleep Screening Questionnaire (ASSQ) along with several other questionnaires related to demographics, exercise training, and mental health. From the ASSQ, a Sleep Difficulty Score (SDS) was calculated. Transformed SDS (tSDS) was compared across different training time categories using multiple one-way </span>ANOVAs. A stepwise regression was then used to predict tSDS from various sleep-related factors.</p></div><div><h3>Results</h3><p>SDSs ranged from none (31%), mild (38%), moderate (22%), and severe (9%). However, the one-way ANOVAs revealed training earlier or later vs. training daytime shifted the tSDS in a negative direction, a trend toward increased sleep difficulty. In particular, athletes training in the late evening (>20:00 or >21:00) had a significantly higher tSDS when compared to daytime training (<em>p</em> = .03 and <em>p</em> < .01, respectively). The regression model (<em>p</em><span> < .001) explained 27% of variance in the tSDS using depression score, age, training time, and chronotype score.</span></p></div><div><h3>Conclusion</h3><p>Among a heterogeneous sample of national-level athletes, 31% displayed moderate to severe SDSs regardless of their training time. However, when athletes trained outside daytime hours there was a tendency for the prevalence of sleep difficulties to increase.</p></div>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":"10 4","pages":"Pages 449-454"},"PeriodicalIF":3.4000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The training times of athletes could play a role in clinical sleep problems due to their associations with sleep difficulty scores\",\"authors\":\"\",\"doi\":\"10.1016/j.sleh.2024.02.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objectives</h3><p>Sleep is a key component of athletic recovery, yet training times could influence the sleep of athletes. The aim of the current study was to compare sleep difficulties in athletes across different training time groups (early morning, daytime, late evening, early morning plus late evening) and to investigate whether training time can predict sleep difficulties.</p></div><div><h3>Methods</h3><p><span>Athletes from various sports who performed at a national-level (n = 273) answered the Athlete Sleep Screening Questionnaire (ASSQ) along with several other questionnaires related to demographics, exercise training, and mental health. From the ASSQ, a Sleep Difficulty Score (SDS) was calculated. Transformed SDS (tSDS) was compared across different training time categories using multiple one-way </span>ANOVAs. A stepwise regression was then used to predict tSDS from various sleep-related factors.</p></div><div><h3>Results</h3><p>SDSs ranged from none (31%), mild (38%), moderate (22%), and severe (9%). However, the one-way ANOVAs revealed training earlier or later vs. training daytime shifted the tSDS in a negative direction, a trend toward increased sleep difficulty. In particular, athletes training in the late evening (>20:00 or >21:00) had a significantly higher tSDS when compared to daytime training (<em>p</em> = .03 and <em>p</em> < .01, respectively). The regression model (<em>p</em><span> < .001) explained 27% of variance in the tSDS using depression score, age, training time, and chronotype score.</span></p></div><div><h3>Conclusion</h3><p>Among a heterogeneous sample of national-level athletes, 31% displayed moderate to severe SDSs regardless of their training time. However, when athletes trained outside daytime hours there was a tendency for the prevalence of sleep difficulties to increase.</p></div>\",\"PeriodicalId\":48545,\"journal\":{\"name\":\"Sleep Health\",\"volume\":\"10 4\",\"pages\":\"Pages 449-454\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sleep Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352721824000317\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sleep Health","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352721824000317","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
The training times of athletes could play a role in clinical sleep problems due to their associations with sleep difficulty scores
Objectives
Sleep is a key component of athletic recovery, yet training times could influence the sleep of athletes. The aim of the current study was to compare sleep difficulties in athletes across different training time groups (early morning, daytime, late evening, early morning plus late evening) and to investigate whether training time can predict sleep difficulties.
Methods
Athletes from various sports who performed at a national-level (n = 273) answered the Athlete Sleep Screening Questionnaire (ASSQ) along with several other questionnaires related to demographics, exercise training, and mental health. From the ASSQ, a Sleep Difficulty Score (SDS) was calculated. Transformed SDS (tSDS) was compared across different training time categories using multiple one-way ANOVAs. A stepwise regression was then used to predict tSDS from various sleep-related factors.
Results
SDSs ranged from none (31%), mild (38%), moderate (22%), and severe (9%). However, the one-way ANOVAs revealed training earlier or later vs. training daytime shifted the tSDS in a negative direction, a trend toward increased sleep difficulty. In particular, athletes training in the late evening (>20:00 or >21:00) had a significantly higher tSDS when compared to daytime training (p = .03 and p < .01, respectively). The regression model (p < .001) explained 27% of variance in the tSDS using depression score, age, training time, and chronotype score.
Conclusion
Among a heterogeneous sample of national-level athletes, 31% displayed moderate to severe SDSs regardless of their training time. However, when athletes trained outside daytime hours there was a tendency for the prevalence of sleep difficulties to increase.
期刊介绍:
Sleep Health Journal of the National Sleep Foundation is a multidisciplinary journal that explores sleep''s role in population health and elucidates the social science perspective on sleep and health. Aligned with the National Sleep Foundation''s global authoritative, evidence-based voice for sleep health, the journal serves as the foremost publication for manuscripts that advance the sleep health of all members of society.The scope of the journal extends across diverse sleep-related fields, including anthropology, education, health services research, human development, international health, law, mental health, nursing, nutrition, psychology, public health, public policy, fatigue management, transportation, social work, and sociology. The journal welcomes original research articles, review articles, brief reports, special articles, letters to the editor, editorials, and commentaries.