Athletic Training and Sports Health Care

Original Research 

Mental Health in Student Athletes: Associations With Sleep Duration, Sleep Quality, Insomnia, Fatigue, and Sleep Apnea Symptoms

Michael A. Grandner, PhD, MTR; Christine Hall, BS; Anjelica Jaszewski, BS; Pamela Alfonso-Miller, MD; Jo-Ann Gehrels, MS; William D. S. Killgore, PhD; Amy Athey, PsyD

Abstract

Purpose:

To quantify the relationship between sleep difficulties and poor mental health among student athletes using validated measures.

Methods:

Data were collected from 190 National Collegiate Athletic Association Division I student athletes. Sleep assessments included measures of sleep duration, sleep quality, insomnia, fatigue, and sleep apnea symptoms. Mental well-being was assessed as depression, anxiety, mental health days, stress, and social support from family, friends, significant other, and teammates.

Results:

Shorter sleep duration, poor sleep quality, insomnia, and fatigue were consistently and independently associated with stress, depression, anxiety, mental health days, and social support. Sleep apnea symptoms were associated with stress, depression, and social support.

Conclusions:

Short sleep duration, poor sleep quality, and daytime fatigue in student athletes are all associated with depression, anxiety, stress, poor mental health days, and decreased social support. These associations are not accounted for solely by stress.

[Athletic Training & Sports Health Care. 20XX;X(X):XX–XX.]

Abstract

Purpose:

To quantify the relationship between sleep difficulties and poor mental health among student athletes using validated measures.

Methods:

Data were collected from 190 National Collegiate Athletic Association Division I student athletes. Sleep assessments included measures of sleep duration, sleep quality, insomnia, fatigue, and sleep apnea symptoms. Mental well-being was assessed as depression, anxiety, mental health days, stress, and social support from family, friends, significant other, and teammates.

Results:

Shorter sleep duration, poor sleep quality, insomnia, and fatigue were consistently and independently associated with stress, depression, anxiety, mental health days, and social support. Sleep apnea symptoms were associated with stress, depression, and social support.

Conclusions:

Short sleep duration, poor sleep quality, and daytime fatigue in student athletes are all associated with depression, anxiety, stress, poor mental health days, and decreased social support. These associations are not accounted for solely by stress.

[Athletic Training & Sports Health Care. 20XX;X(X):XX–XX.]

Sleep is an emerging area of interest in the context of athletics.1–4 Sleep loss impairs cognitive performance5–7 and physical performance,8–10 which can lead to reduced athletic performance. Notably, sleep deprivation and/or insufficient sleep are associated with reduced athletic performance among elite athletes and improvements in sleep have been associated with corresponding improvements in athletic performance.9,11 The topic of sleep health in collegiate athletes was recently reviewed12 in the context of position statements from the National Collegiate Athletic Association (NCAA)13 and the International Olympic Committee.14,15

In addition to cognitive functioning and physical performance, sleep plays a particularly important role in mental health. Sleep disturbance is a prominent feature in nearly all psychiatric conditions, including depression, bipolar disorder, post-traumatic stress disorder, other anxiety disorders, attention deficit disorders, and many others. Insomnia is a well-recognized risk factor for the development of depression16–18 and the recurrence of depressive episodes among remitted depressed individuals.19 Insomnia is also a known risk factor for suicide20 and may interact with short sleep duration.21 Regarding general stress and mental well-being, several studies have shown that poor sleep quality is strongly associated with higher levels of stress and overall poorer mental health.22–24 Although the causal direction of sleep and mental health issues is not firmly established, it is clear that these two factors are inextricably linked.

Mental health remains an important factor for student athletes. Student athletes are at a high risk of depression and anxiety and often operate under conditions of high physical and/or emotional stress.25–27 Social support could possibly serve as a protective factor, mitigating some of the impact of stressful situations on mental health. However, few studies have examined the relationship between sleep and mental health among athletes, particularly using validated sleep screening measures.

Accordingly, the current study investigated the relationship between several relevant sleep variables (sleep duration, sleep quality, insomnia, fatigue, and sleep apnea symptoms) on a wide range of mental health variables (stress, depression, anxiety, mental well-being, and social support) among college athletes, using established, validated measures where possible. It was hypothesized that (1) poor sleep would be associated with poor mental health among student athletes and (2) some, but not all, of these relationships would be mediated by stress.

Methods

Sample

Data were collected from surveys administered to 190 NCAA Division I athletes over the summer and during the first 2 weeks of the Fall 2016 semester. To be eligible for the survey, students had to be at least 18 years of age. Selection favored returning students. Students were recruited through flyers, in-person solicitations at training facilities, and word of mouth among students and athletics staff. All surveys were administered online, using the student's phone, tablet, or computer or a study-provided tablet. Participants were paid for completing surveys. This study was approved by the Institutional Review Board of the University of Arizona.

Measures

Mental health–depression was assessed with the Center for Epidemiological Studies Depression Scale (CESD),28 a well-validated screening tool for depression. Scores range from 0 to 60, with values greater than 16 considered high risk for a depressive disorder. The CESD was originally developed to assess depression symptoms as they are experienced in the general population, and it has been used in young adult populations.29,30 It is generally accepted as a reliable and valid depression screener.28,31

Anxiety was assessed using the Generalized Anxiety Disorder (GAD) questionnaire,32 a standard screening tool for anxiety disorders. Scores range from 0 to 21. It was originally developed to assess generalized anxiety disorder symptoms, but has since become a standard screening tool for anxiety disorder in general.33

Stress was measured with the Perceived Stress Scale (PSS),34 a standard and well-validated measure of global perceived levels of stress. This questionnaire has since become a standard measure in stress research.35,36 Higher scores reflect greater experiences of life stresses.

Mental well-being was assessed by asking, “Now thinking about your mental health, which includes stress, depression, and problems with emotions, for how many days during the past 30 days was your mental health not good?” Responses were 0 to 30. This item is based on the Measuring Healthy Days survey items developed by the Centers for Disease Control and Prevention.37

Social support was assessed with the Multidimensional Scale of Perceived Social Support (MSPSS),38 a well-validated measure that includes subscales for family, friends, and significant other. A fourth scale for teammates was created by taking the items from the “friends” scale and substituting the word “teammates” for “friends.” This scale has demonstrated strong psychometric properties across a wide range of populations.39–42

Overall sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI), a well-validated global measure of poor sleep.43 Scores range from 0 to 21, with a cutoff value of 5 indicating poor sleep. One item in the PSQI asks, “How many hours of actual sleep did you get at night? (This may be different than the number of hours you spend in bed.)” This item was used to estimate habitual sleep duration.

Insomnia severity was assessed with the Insomnia Severity Index (ISI), a well-validated and standard tool for the assessment of insomnia symptoms.44 Scores range from 0 to 28, with 0 to 7 usually indicating no insomnia, 8 to 14 usually indicating mild insomnia, 15 to 21 indicating moderate insomnia, and 22 to 28 indicating severe insomnia. The ISI has demonstrated strong psychometric properties and is considered a gold standard assessment of the experience of insomnia.45–47

Fatigue was assessed with the Fatigue Severity Scale (FSS), a well-validated, standard measure of general fatigue.48 This scale has scores ranging from 0 to 63, with 36 representing a cutoff for pathological fatigue. Sleep apnea symptoms that were assessed included loud snoring and snorting/gasping during sleep. These were assessed from the validated Multivariable Apnea Prediction (MAP) index,49 which asks, “During the past month, on how many nights or days per week have you had or been told you had the following.” Those who indicated “loud snoring” at least 1 night per week were coded as “Yes” and those who indicated any “snorting/gasping” were coded as “Yes.” The MAP has been used as a valid sleep apnea screener in multiple contexts.49–53

Statistical Analyses

All variables were examined for outliers and physiologically implausible values. Continuous variables were reported as mean and standard deviation, and categorical variables were reported as percentages. Linear regression analyses, with mental health variable as outcome and sleep variable as predictor, were adjusted for age, sex, and year in school. Unstandardized regression coefficients (B) and 95% CIs were calculated. To determine whether these relationships are accounted for by stress, PSS score was entered as an additional covariate in all models for which stress was not the outcome assessed. All analyses were performed using STATA software version 14.0 (STATA Corp).

Results

Sample Characteristics

Characteristics of the sample are reported in Table 1. The mean age of the sample was 19 years, and the sample was 46% female. Most participants were second, third, and fourth year college students. The sports represented were football (24%), track and field (16%), swimming (15%), softball (8%), baseball (7%), soccer (6%), golf (5%), gymnastics (5%), volleyball (4%), basketball (4%), tennis (4%), cheer (2%), and diving (1%). The mean self-reported sleep duration of the sample was 7 hours, with a mean sleep quality rating of 8, which is in the “poor sleep” range. Mean ISI score was 8, which is in the range of “mild” insomnia. Mean fatigue score was 29, which is moderately high. Loud snoring was prevalent in 17% of the sample and snorting/gasping was prevalent in 18%. Mean CESD depression score was 11 and mean GAD score was 5. Mean number of poor mental health days in the past month was 5. Social support scores were moderately high in all categories except teammates, where scores were lower.

Characteristics of the Sample

Table 1:

Characteristics of the Sample

Sleep and Stress in Student Athletes

Table 2 displays results of regression analyses examining relationships between sleep-related variables and stress, operationalized as PSS score, adjusted for age, sex, and year in school. Each additional hour of sleep duration was associated with a 1-point reduction on the PSS. Each 1-point worsening of the PSQI or ISI score was associated with approximately 1 additional point on the PSS. Each 1-point increase on the FSS was associated with a 0.25-point increase on the PSS. Although snoring was not associated with the PSS score, the presence of snorting/gasping was associated with 3.6 additional points on the PSS.

Relationships Between Sleep Variables and PSS Stress Score, Adjusted for Age, Sex, and Year in School

Table 2:

Relationships Between Sleep Variables and PSS Stress Score, Adjusted for Age, Sex, and Year in School

Sleep and Depression, Anxiety, and Mental Well-being

Table 3 displays results of regression analyses examining relationships between sleep-related variables and depression (CESD score), anxiety (GAD score), and mental well-being (poor mental health days per month), adjusted for age, sex, and year in school. Additionally, stress (PSS score) was added to these models to determine whether the associations are mediated by stress. Each additional hour of sleep duration was associated with a lower CESD score and a lower GAD score, but no significant association with mental health days. The relationship with CESD score remained when stress was added to the model. Each additional point on the PSQI or the ISI was associated with a higher CESD score, a higher GAD score, and more poor mental health days. All of these relationships were maintained when stress was added to the model for both sleep variables. Similarly, each point on the FSS was associated with higher depression and anxiety scores and more poor mental health days. The relationships with depression and anxiety were maintained when stress was added to the model, but the relationship with poor mental health days was not. Both snoring and snorting/gasping were associated with a higher depression score, but this was not significant after stress was added to the model.

Relationships Between Sleep Variables and Depression (CESD Score), Anxiety (GAD Score), and Mental Well-being (Healthy Days), Adjusted for Age, Sex, and Year in School

Table 3:

Relationships Between Sleep Variables and Depression (CESD Score), Anxiety (GAD Score), and Mental Well-being (Healthy Days), Adjusted for Age, Sex, and Year in School

Sleep and Social Support From Family, Friends, Significant Other, and Teammates

Table 4 displays results of regression analyses examining relationships between sleep-related variables and social support from family, friends, significant other (MSPSS scores), aand teammates, adjusted for age, sex, and year in school. Additionally, stress (PSS score) was added to these models to determine whether the associations are mediated by stress. Each additional hour of sleep duration was associated with more social support from family, and this was maintained when stress was added to the model. Higher PSQI scores were associated with decreased social support from friends, significant other, and teammates, although these relationships were not significant when stress was added to the model. Higher ISI scores were associated with decreased social support from family, friends, significant other, and teammates, although only the relationship with support from family and teammates was still significant after including stress in the model. Higher FSS scores were associated with decreased support from teammates, although this was no longer significant after including stress in the model. Snoring was not associated with social support. However, snorting/gasping was related to decreased support from family, friends, significant other, and teammates, and the relationship with support from friends remained significant after including stress in the model.

Relationships Between Sleep Variables and Social Support, Adjusted for Age, Sex, and Year in School

Table 4:

Relationships Between Sleep Variables and Social Support, Adjusted for Age, Sex, and Year in School

Discussion

Overall, as expected, most sleep variables were related to most mental health variables, and although stress mediated many relationships, most were independent of the effects of stress.

The students demonstrated overall poor sleep quality and sleep hygiene. This is likely due to late night social activity, socialization, examination preparation, studying, early morning responsibilities, travel for competition, and other factors. It is not clear whether student athletes' sleep is worse than that of their non-athlete counterparts; future research could examine whether these patterns are different for athletes and non-athletes. It is possible that increased time demands would lead to worse sleep among athletes; it is also possible that increased access to support services and other qualities often found in athletes (eg, resilience) may lead to better sleep overall. It should be noted that college students in general experience poor sleep hygiene, with a multitude of causes.54–58 It is possible that this contributes to mental health on college campuses in general, irrespective of athlete status.

Several findings from this study deserve further comment. First, shorter sleep duration was associated with higher levels of stress, depression, and anxiety, more poor mental health days, and decreased social support from family. Several previous studies have shown that population levels of short sleep duration are associated with poor mental health. Similarly, laboratory studies have demonstrated that experimentally induced sleep deprivation in healthy young individuals is associated with increased symptoms of depression, anxiety, somatic complaints, and feelings of persecution,59 and leads to poorer emotional coping60 and degraded ability to deal effectively with frustration.61 In addition, the combination of short sleep duration and insomnia may be particularly detrimental.62 Short sleep duration has also been associated with decreased social support in the general population,63 supporting the findings of this study. Several recent position statements suggest that healthy adults need at least 7 hours of sleep,64–68 although young adults and/or athletes may require more, up to 9 hours.66,69

Similar to the findings regarding sleep duration, poor sleep quality and insomnia severity were also associated with higher levels of stress, depression, and anxiety, more poor mental health days, and decreased social support from family, friends, significant other, and teammates. Many previous studies have shown that poor sleep quality and insomnia in the general population are associated with depression, anxiety, stress, and poor mental health days.16–18,70–72 Some evidence also suggests decreased social support.73 Insomnia is prevalent in the general population, and was prevalent in the current sample. Although some basic techniques may be helpful for the amelioration of minor sleep problems when student athletes report significant difficulties falling asleep or maintaining sleep, the diagnosis of Insomnia Disorder should be considered and referrals for appropriate treatment should be made. According to recent position statements by the American Academy of Sleep Medicine74 and American College of Physicians,75 pharmacologic therapy for insomnia is not recommended as a first-line treatment. Rather, cognitive behavioral therapy for insomnia is recommended in that it has equal or better efficacy, better long-term outcomes, and fewer adverse effects. As an additional benefit for athletes, most hypnotic medications produce psychomotor slowing and increase risk for accidents and injuries, which further supports the use of cognitive behavioral therapy for insomnia, which avoids these adverse side effects.

Consistent with our expectations, sleep apnea symptoms (particularly snorting/gasping) were also associated with increased stress and depression, and decreased social support from family, friends, significant other, and teammates. Sleep apnea is a condition that is often undiagnosed, especially in young adults in good health. Anatomical features can predispose to risk of sleep apnea, even in lean athletes. Risk is even higher among football players, especially linemen.76,77 There are several available screening instruments for sleep apnea (eg, the STOP-BANG questionnaire78) and screening measures for daytime sleepiness,79 which is a common daytime symptom of sleep apnea. These are also published in the NCAA Mental Health Best Practices document.80 Undiagnosed sleep apnea can lead to increased fatigue and many other health problems caused by excessive sleep fragmentation, increased oxidative stress, and intermittent hypoxia during the night.81

From the current findings, it is clear that sleep plays an important role in mental health among student athletes and should be considered as a potentially modifiable factor for poor mental health for this population. The NCAA recently published Mental Health Best Practices guidelines80 that include sleep screening as part of a mental health program. In addition, resources such as the accompanying handbook82 and guide83 may be helpful in addressing sleep problems among student athletes.

Limitations

There were several limitations to our methods. First, no objective measures of sleep were available, so all responses were obtained from self-report instruments. However, most of the instruments included in the study were well-validated measures that have been used extensively in sleep research. Second, because this was a cross-sectional study, no inferences of causality could be made. It is likely that sleep and mental health exist in a bidirectional relationship. Although it is not possible to disentangle the causal association from these data, prior controlled laboratory research has demonstrated that sleep deprivation and restriction lead to worsening of mental health symptoms such as depression and anxiety.59 Third, the sample consisted of individuals from a single university and may not completely generalize to all institutions. Although replication of these findings will be necessary to establish their applicability to the broader population, the results of this research are consistent with the extant literature on the role of sleep in mental health, attesting to the likely veracity and applicability of these findings more broadly. Another important limitation of this study was that there was no non-athlete comparison group. The scope of this study was exclusively athletes, which precluded the ability to examine whether mental health or sleep variables systematically differed between athletes and non-athletes, and/or whether the relationship between these was different. It is plausible that all three of these (sleep, mental health, and the relationship) may be different among athletes for multiple reasons.

Implications for Clinical Practice

The current study investigated the relationship between sleep and mental health in a sample of Division I student athletes. Overall, sleep duration, sleep quality, insomnia severity, fatigue, and sleep apnea symptoms were generally associated with increased stress, depression, and (in most cases) anxiety. They were also associated with a higher number of poor mental health days and decreased perception of social support. Athletics programs should consider sleep screening among student athletes to identify those at risk, promote healthy sleep practices (as much as is possible given scheduling demands), and develop relationships with sleep physicians and behavioral sleep medicine specialists for the purpose of referral and treatment. The current study was unable to explore the mechanisms of these relationships; future studies could better identify the causal pathways at play, which would be useful for refining interventions. Future studies should also explore the degree to which modification of sleep improves mental health among student athletes, and whether these changes can result in more distal changes in athletic performance and better quality of life.

References

  1. Silva A, Queiroz SS, Winckler C, et al. Sleep quality evaluation, chronotype, sleepiness and anxiety of Paralympic Brazilian athletes: Beijing 2008 Paralympic Games. Br J Sports Med. 2012;46(2):150–154. doi:10.1136/bjsm.2010.077016 [CrossRef]
  2. 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 [CrossRef]
  3. Juliff LE, Halson SL, Peiffer JJ. Understanding sleep disturbance in athletes prior to important competitions. J Sci Med Sport. 2015;18(1):13–18. doi:10.1016/j.jsams.2014.02.007 [CrossRef]
  4. Nédélec M, Halson S, Delecroix B, Abaidia AE, Ahmaidi S, Dupont G. Sleep hygiene and recovery strategies in elite soccer players. Sports Med. 2015;45(11):1547–1559. doi:10.1007/s40279-015-0377-9 [CrossRef]
  5. Ma N, Dinges DF, Basner M, Rao H. How acute total sleep loss affects the attending brain: a meta-analysis of neuroimaging studies. Sleep (Basel). 2015;38(2):233–240. doi:10.5665/sleep.4404 [CrossRef]
  6. Goel N, Basner M, Rao H, Dinges DF. Circadian rhythms, sleep deprivation, and human performance. Prog Mol Biol Transl Sci. 2013;119:155–190. doi:10.1016/B978-0-12-396971-2.00007-5 [CrossRef]
  7. Lim J, Dinges DF. A meta-analysis of the impact of short-term sleep deprivation on cognitive variables. Psychol Bull. 2010;136(3):375–389. doi:10.1037/a0018883 [CrossRef]
  8. Abe T, Mollicone D, Basner M, Dinges DF. Sleepiness and safety: where biology needs technology. Sleep Biol Rhythms. 2014;12(2):74–84. doi:10.1111/sbr.12067 [CrossRef]
  9. Reyner LA, Horne JA. Sleep restriction and serving accuracy in performance tennis players, and effects of caffeine. Physiol Behav. 2013;120:93–96. doi:10.1016/j.physbeh.2013.07.002 [CrossRef]
  10. Bougard C, Davenne D. Effects of sleep deprivation and time-of-day on selected physical abilities in off-road motorcycle riders. Eur J Appl Physiol. 2012;112(1):59–67. doi:10.1007/s00421-011-1948-6 [CrossRef]
  11. Mah CD, Mah KE, Kezirian EJ, Dement WC. The effects of sleep extension on the athletic performance of collegiate basketball players. Sleep (Basel). 2011;34(7):943–950. doi:10.5665/SLEEP.1132 [CrossRef]
  12. Brauer AA, Athey AB, Ross MJ, Grandner MA. Sleep and health among collegiate student athletes. Chest. 2019;156(6):1234–1245. doi:10.1016/j.chest.2019.08.1921 [CrossRef]
  13. Kroshus E, Wagner J, Wyrick D, et al. Wake up call for collegiate athlete sleep: narrative review and consensus recommendations from the NCAA Interassociation Task Force on Sleep and Wellness. Br J Sports Med. 2019;53(12):731–736. doi:10.1136/bjs-ports-2019-100590 [CrossRef]
  14. Reardon CL, Hainline B, Aron CM, et al. Infographic. Sleep disorders in athletes. Br J Sports Med. 2020;54(3):188–189. doi:10.1136/bjsports-2019-101107. [CrossRef]
  15. Reardon CL, Hainline B, Aron CM, et al. Mental health in elite athletes: International Olympic Committee consensus statement (2019). Br J Sports Med. 2019;53(11):667–699. doi:10.1136/bjs-ports-2019-100715 [CrossRef]
  16. Spiegelhalder K, Regen W, Nanovska S, Baglioni C, Riemann D. Comorbid sleep disorders in neuropsychiatric disorders across the life cycle. Curr Psychiatry Rep. 2013;15(6):364. doi:10.1007/s11920-013-0364-5 [CrossRef]
  17. Baglioni C, Riemann D. Is chronic insomnia a precursor to major depression? Epidemiological and biological findings. Curr Psychiatry Rep. 2012;14(5):511–518. doi:10.1007/s11920-012-0308-5 [CrossRef]
  18. Baglioni C, Battagliese G, Feige B, et al. Insomnia as a predictor of depression: a meta-analytic evaluation of longitudinal epidemiological studies. J Affect Disord. 2011;135(1–3):10–19. doi:10.1016/j.jad.2011.01.011 [CrossRef]
  19. Perlis ML, Giles DE, Buysse DJ, Tu X, Kupfer DJ. Self-reported sleep disturbance as a prodromal symptom in recurrent depression. J Affect Disord. 1997;42(2–3):209–212. doi:10.1016/S0165-0327(96)01411-5 [CrossRef]
  20. Pigeon WR, Pinquart M, Conner K. Meta-analysis of sleep disturbance and suicidal thoughts and behaviors. J Clin Psychiatry. 2012;73(9):e1160–e1167. doi:10.4088/JCP.11r07586 [CrossRef]
  21. Chakravorty S, Siu HY, Lalley-Chareczko L, et al. Sleep duration and insomnia symptoms as risk factors for suicidal ideation in a nationally representative sample. Prim Care Companion CNS Disord. 2015;17(6). doi:10.4088/PCC.13m01551 [CrossRef]
  22. Grandner MA, Jackson NJ, Izci-Balserak B, et al. Social and behavioral determinants of perceived insufficient sleep. Front Neurol. 2015;6:112. doi:10.3389/fneur.2015.00112 [CrossRef]
  23. Benitez A, Gunstad J. Poor sleep quality diminishes cognitive functioning independent of depression and anxiety in healthy young adults. Clin Neuropsychol. 2012;26(2):214–223. doi:10.1080/13854046.2012.658439 [CrossRef]
  24. Franzen PL, Buysse DJ, Rabinovitz M, Pollock BG, Lotrich FE. Poor sleep quality predicts onset of either major depression or subsyndromal depression with irritability during interferon-alpha treatment. Psychiatry Res. 2010;177(1–2):240–245. doi:10.1016/j.psychres.2009.02.011 [CrossRef]
  25. Sudano LE, Miles CM. Mental health services in NCAA Division I athletics: a survey of head ATCs. Sports Health. 2017;9(3):262–267. doi:10.1177/1941738116679127 [CrossRef]
  26. Sudano LE, Collins G, Miles CM. Reducing barriers to mental health care for student-athletes: an integrated care model. Fam Syst Health. 2017;35(1):77–84. doi:10.1037/fsh0000242 [CrossRef]
  27. Rao AL, Hong ES. Understanding depression and suicide in college athletes: emerging concepts and future directions. Br J Sports Med. 2016;50(3):136–137. doi:10.1136/bjsports-2015-095658 [CrossRef]
  28. Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1(3):385–401. doi:10.1177/014662167700100306 [CrossRef]
  29. Chelminski I, Ferraro FR, Petros TV, Plaud JJ. An analysis of the “eveningness-morningness” dimension in “depressive” college students. J Affect Disord. 1999;52(1–3):19–29. doi:10.1016/S0165-0327(98)00051-2 [CrossRef]
  30. Knight AM, Trupin L, Katz P, Yelin E, Lawson EF. Depression risk in young adults with juvenile- and adult-onset lupus: twelve years of followup. Arthritis Care Res (Hoboken). 2018;70(3):475–480. doi:10.1002/acr.23290 [CrossRef]
  31. Nabbe P, Le Reste JY, Guillou-Landreat M, et al. Which DSM validated tools for diagnosing depression are usable in primary care research? A systematic literature review. Eur Psychiatry. 2017;39:99–105. doi:10.1016/j.eurpsy.2016.08.004 [CrossRef]
  32. Spitzer RL, Kroenke K, Williams JB, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166(10):1092–1097. doi:10.1001/archinte.166.10.1092 [CrossRef]
  33. Plummer F, Manea L, Trepel D, McMillan D. Screening for anxiety disorders with the GAD-7 and GAD-2: a systematic review and diagnostic metaanalysis. Gen Hosp Psychiatry. 2016;39:24–31. doi:10.1016/j.genhosppsych.2015.11.005 [CrossRef]
  34. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385–396. doi:10.2307/2136404 [CrossRef]
  35. Nielsen MG, Ørnbøl E, Vestergaard M, et al. The construct validity of the Perceived Stress Scale. J Psychosom Res. 2016;84:22–30. doi:10.1016/j.jpsychores.2016.03.009 [CrossRef]
  36. Taylor JM. Psychometric analysis of the Ten-Item Perceived Stress Scale. Psychol Assess. 2015;27(1):90–101. doi:10.1037/a0038100 [CrossRef]
  37. Centers for Disease Control and Prevention. Measuring Healthy Days. Centers for Disease Control and Prevention; 2000.
  38. Zimet GD, Dahlem NW, Zimet SG, Farley GK. The multidimensional scale of perceived social support. J Pers Assess. 1988;52(1):30–41. doi:10.1207/s15327752jpa5201_2 [CrossRef]
  39. Hardan-Khalil K, Mayo AM. Psychometric properties of the Multidimensional Scale of Perceived Social Support. Clin Nurse Spec. 2015;29(5):258–261. doi:10.1097/NUR.0000000000000148 [CrossRef]
  40. De Maria M, Vellone E, Durante A, Biagioli V, Matarese M. Psychometric evaluation of the Multidimensional Scale of Perceived Social Support (MSPSS) in people with chronic diseases. Ann Ist Super Sanita. 2018;54(4):308–315.
  41. Canty-Mitchell J, Zimet GD. Psychometric properties of the Multidimensional Scale of Perceived Social Support in urban adolescents. Am J Community Psychol. 2000;28(3):391–400. doi:10.1023/A:1005109522457 [CrossRef]
  42. Zimet GD, Powell SS, Farley GK, Werkman S, Berkoff KA. Psychometric characteristics of the Multidimensional Scale of Perceived Social Support. J Pers Assess. 1990;55(3–4):610–617. doi:10.1080/00223891.1990.9674095 [CrossRef]
  43. Buysse DJ, Reynolds CF III, 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 [CrossRef]
  44. Bastien CH, Vallières A, Morin CM. Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Med. 2001;2(4):297–307. doi:10.1016/S1389-9457(00)00065-4 [CrossRef]
  45. Alsaadi SM, McAuley JH, Hush JM, et al. Detecting insomnia in patients with low back pain: accuracy of four self-report sleep measures. BMC Musculoskelet Disord. 2013;14(1):196. doi:10.1186/1471-2474-14-196 [CrossRef]
  46. Morin CM, Belleville G, Bélanger L, Ivers H. The Insomnia Severity Index: psychometric indicators to detect insomnia cases and evaluate treatment response. Sleep (Basel). 2011;34(5):601–608. doi:10.1093/sleep/34.5.601 [CrossRef]
  47. Schutte-Rodin S, Broch L, Buysse D, Dorsey C, Sateia M. Clinical guideline for the evaluation and management of chronic insomnia in adults. J Clin Sleep Med. 2008;4(5):487–504. doi:10.5664/jcsm.27286 [CrossRef]
  48. Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD. The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol. 1989;46(10):1121–1123. doi:10.1001/archneur.1989.00520460115022 [CrossRef]
  49. Maislin G, Pack AI, Kribbs NB, et al. A survey screen for prediction of apnea. Sleep. 1995;18(3):158–166. doi:10.1093/sleep/18.3.158 [CrossRef]
  50. Bourjeily G, El Sabbagh R, Sawan P, et al. Epworth sleepiness scale scores and adverse pregnancy outcomes. Sleep Breath. 2013;17(4):1179–1186. doi:10.1007/s11325-013-0820-9 [CrossRef]
  51. Fülöp T, Hickson DA, Wyatt SB, et al. Sleep-disordered breathing symptoms among African-Americans in the Jackson Heart Study. Sleep Med. 2012;13(8):1039–1049. doi:10.1016/j.sleep.2012.06.005 [CrossRef]
  52. Sharwood LN, Elkington J, Stevenson M, et al. Assessing sleepiness and sleep disorders in Australian long-distance commercial vehicle drivers: self-report versus an “at home” monitoring device. Sleep (Basel). 2012;35(4):469–475. doi:10.5665/sleep.1726 [CrossRef]
  53. Balk EM, Moorthy D, Obadan NO, et al. Diagnosis and Treatment of Obstructive Sleep Apnea in Adults. Agency for Healthcare Research and Quality; 2011.
  54. Todd J, Mullan B. The role of self-regulation in predicting sleep hygiene in university students. Psychol Health Med. 2013;18(3):275–288. doi:10.1080/13548506.2012.701756 [CrossRef]
  55. Kor K, Mullan BA. Sleep hygiene behaviours: an application of the theory of planned behaviour and the investigation of perceived autonomy support, past behaviour and response inhibition. Psychol Health. 2011;26(9):1208–1224. doi:10.1080/08870446.2010.551210 [CrossRef]
  56. Marhefka JK. Sleep deprivation: consequences for students. J Psychosoc Nurs Ment Health Serv. 2011;49(9):20–25. doi:10.3928/02793695-20110802-02 [CrossRef]
  57. Brick CA, Seely DL, Palermo TM. Association between sleep hygiene and sleep quality in medical students. Behav Sleep Med. 2010;8(2):113–121. doi:10.1080/15402001003622925 [CrossRef]
  58. Majori S, Pasqualetto C, Mantovani W, et al. Self-reported sleep disorders in secondary school students: an epidemiological and risk behavioural analysis. J Prev Med Hyg. 2009;50(2):102–108.
  59. Kahn-Greene ET, Killgore DB, Kamimori GH, Balkin TJ, Killgore WD. The effects of sleep deprivation on symptoms of psychopathology in healthy adults. Sleep Med. 2007;8(3):215–221. doi:10.1016/j.sleep.2006.08.007 [CrossRef]
  60. Killgore WD, Kahn-Greene ET, Lipizzi EL, Newman RA, Kamimori GH, Balkin TJ. Sleep deprivation reduces perceived emotional intelligence and constructive thinking skills. Sleep Med. 2008;9(5):517–526. doi:10.1016/j.sleep.2007.07.003 [CrossRef]
  61. Kahn-Greene ET, Lipizzi EL, Conrad AK, Kamimori GH, Killgore WDS. Sleep deprivation adversely affects interpersonal responses to frustration. Pers Individ Dif. 2006;41(8):1433–1443. doi:10.1016/j.paid.2006.06.002 [CrossRef]
  62. Vgontzas AN, Fernandez-Mendoza J, Liao D, Bixler EO. Insomnia with objective short sleep duration: the most biologically severe phenotype of the disorder. Sleep Med Rev. 2013;17(4):241–254. doi:10.1016/j.smrv.2012.09.005 [CrossRef]
  63. Williams NJ, Grandner MA, Wallace DM, et al. Social and behavioral predictors of insufficient sleep among African Americans and Caucasians. Sleep Med. 2016;18:103–107. doi:10.1016/j.sleep.2015.02.533 [CrossRef]
  64. Watson NF, Badr MS, Belenky G, et al. Recommended amount of sleep for a healthy adult: a joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society. Sleep (Basel). 2015;38(6):843–844. doi:10.5665/sleep.4716 [CrossRef]
  65. Watson NF, Badr MS, Belenky G, et al. Consensus Conference Panel; Non-Participating ObserversAmerican Academy of Sleep Medicine Staff. Recommended amount of sleep for a healthy adult: a joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society. J Clin Sleep Med. 2015;11(6):591–592. doi:10.5664/jcsm.4758 [CrossRef]
  66. Hirshkowitz M, Whiton K, Albert SM, et al. National Sleep Foundation's sleep time duration recommendations: methodology and results summary. Sleep Health. 2015;1(1):40–43. doi:10.1016/j.sleh.2014.12.010 [CrossRef]
  67. Mukherjee S, Patel SR, Kales SN, et al. American Thoracic Society ad hoc Committee on Healthy Sleep. An official American Thoracic Society Statement: the importance of healthy sleep. recommendations and future priorities. Am J Respir Crit Care Med. 2015;191(12):1450–1458. doi:10.1164/rccm.201504-0767ST [CrossRef]
  68. St-Onge MP, Grandner MA, Brown D, et al. Sleep duration and quality: impact on lifestyle behaviors and cardiometabolic health: a scientific statement from the American Heart Association. Circulation. 2016;134(18):e367–e386. doi:10.1161/CIR.0000000000000444 [CrossRef]
  69. Hirshkowitz M, Whiton K, Albert SM, et al. National Sleep Foundation's updated sleep duration recommendations: final report. Sleep Health. 2015;1(4):233–243. doi:10.1016/j.sleh.2015.10.004 [CrossRef]
  70. Baglioni C, Regen W, Teghen A, et al. Sleep changes in the disorder of insomnia: a meta-analysis of polysomnographic studies. Sleep Med Rev. 2014;18(3):195–213. doi:10.1016/j.smrv.2013.04.001 [CrossRef]
  71. Baglioni C, Spiegelhalder K, Lombardo C, Riemann D. Sleep and emotions: a focus on insomnia. Sleep Med Rev. 2010;14(4):227–238. doi:10.1016/j.smrv.2009.10.007 [CrossRef]
  72. Krystal AD. Psychiatric disorders and sleep. Neurol Clin. 2012;30(4):1389–1413. doi:10.1016/j.ncl.2012.08.018 [CrossRef]
  73. Chaudhary NS, Grandner MA, Perlis ML, Kampman KM, Chakravorty S. Psychosocial problems are greater among alcoholics who complain of insomnia. SLEEP. 2014;37(Abstract Supplement):A207–A8.
  74. Sateia MJ, Buysse DJ, Krystal AD, Neubauer DN, Heald JL. Clinical practice guideline for the pharmacologic treatment of chronic insomnia in adults: an American Academy of Sleep Medicine Clinical Practice Guideline. J Clin Sleep Med. 2017;13(2):307–349. doi:10.5664/jcsm.6470 [CrossRef]
  75. Qaseem A, Kansagara D, Forciea MA, Cooke M, Denberg TD. Clinical Guidelines Committee of the American College of Practive Management of Chronic Insomnia Disorder in Adults: A Clinical Practice Guideline From the American College of Physicians. Ann Intern Med. 2016;165(2):125. doi:10.7326/M15-2175 [CrossRef]
  76. George CF, Kab V. Sleep-disordered breathing in the National Football League is not a trivial matter. Sleep (Basel). 2011;34(3):245. doi:10.1093/sleep/34.3.245 [CrossRef]
  77. George CF, Kab V, Kab P, Villa JJ, Levy AM. Sleep and breathing in professional football players. Sleep Med. 2003;4(4):317–325. doi:10.1016/S1389-9457(03)00113-8 [CrossRef]
  78. Chung F, Subramanyam R, Liao P, Sasaki E, Shapiro C, Sun Y. High STOP-Bang score indicates a high probability of obstructive sleep apnoea. Br J Anaesth. 2012;108(5):768–775. doi:10.1093/bja/aes022 [CrossRef]
  79. Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep. 1991;14(6):540–545. doi:10.1093/sleep/14.6.540 [CrossRef]
  80. National Collegiate Athletics Association. Mental Health Best Practices: An Inter-Association Consensus Document: Best Practices for Understanding and Supporting Student-Athlete Mental Wellness. NCAA Sport Sciences Institute; 2016.
  81. Leung RS, Comondore VR, Ryan CM, Stevens D. Mechanisms of sleep-disordered breathing: causes and consequences. Pflugers Arch. 2012;463(1):213–230. doi:10.1007/s00424-011-1055-x [CrossRef]
  82. Brown GT. Mind, Body, and Sport. NCAA Sport Sciences Institute; 2016.
  83. Grandner MA. Healthy sleep for student-athletes: a guide for athletics departments and coaches. NCAA Sport Sciences Institute Newsletter. 2016;42(2).

Characteristics of the Sample

CharacteristicCategory / UnitsValues
AgeYears19.353 ± 4.949
SexMen54.21%
Women45.79%
Year in schoolFirst5.26%
Second33.16%
Third31.05%
Fourth23.68%
Fifth5.26%
Part-time1.58%
StressPSS score23.342 ± 7.116
DepressionCESD score10.763 ± 7.470
AnxietyGAD score5.137 ± 4.459
Mental well-beingGood mental health days5.365 ± 7.764
Social supportMSPSS Family score23.453 ± 5.309
MSPSS Friends score22.221 ± 5.290
MSPSS Significant Other score22.237 ± 5.931
Team score15.537 ± 4.829
Sleep durationHours6.963 ± 1.171
Sleep qualityPSQI score8.147 ± 3.051
InsomniaISI score7.684 ± 5.150
FatigueFSS score29.468 ± 10.981
Loud snoringYes17.37%
Snorting/gaspingYes17.90%

Relationships Between Sleep Variables and PSS Stress Score, Adjusted for Age, Sex, and Year in School

Sleep VariableB95% CIP
PSQI Sleep Duration−1.001(−1.901 to −0.101).0295
PSQI Sleep Quality1.036(0.725 to 1.347)< .0001
ISI Insomnia0.779(0.607 to 0.952)< .0001
FSS Fatigue0.246(0.156 to 0.337)< .0001
MAP Snoring2.26(−0.621 to 5.141).1233
MAP Snorting/Gasping3.601(0.829 to 6.373).0111

Relationships Between Sleep Variables and Depression (CESD Score), Anxiety (GAD Score), and Mental Well-being (Healthy Days), Adjusted for Age, Sex, and Year in School

Sleep VariableMental Health OutcomeAdjustedAdjusted + Stress


B95% CIPB95% CIP
PSQI Sleep DurationCESD Depression Score−1.854(−2.750 to −0.957)< .0001−1.186(−1.862 to −0.509).0006
GAD Score−0.775(−1.322 to −0.228).0057−0.382(−0.806 to 0.042).0772
Healthy Mental Health Days−0.824(−1.797 to 0.150).0966−0.282(−1.139 to 0.575).5166
PSQI Sleep QualityCESD Depression Score1.143(0.830 to 1.457)< .00010.52(0.239 to 0.801).0003
GAD Anxiety Score0.788(0.610 to 0.966)< .00010.459(0.294 to 0.624)< .0001
Healthy Mental Health Days1.028(0.688 to 1.368)< .00010.572(0.224 to 0.919).0013
ISI InsomniaCESD Depression Score0.851(0.679 to 1.023)< .00010.442(0.266 to 0.618)< .0001
GAD Anxiety Score0.501(0.398 to 0.604)< .00010.27(0.162 to 0.377)< .0001
Healthy Mental Health Days0.598(0.393 to 0.802)< .00010.248(0.020 to 0.475).0329
FSS FatigueCESD Depression Score0.311(0.222 to 0.400)< .00010.162(0.086 to 0.237)< .0001
GAD Anxiety Score0.171(0.116 to 0.225)< .00010.083(0.036 to 0.130).0006
Healthy Mental Health Days0.192(0.091 to 0.293).00020.067(−0.030 to 0.163).1765
MAP SnoringCESD Depression Score3.102(0.158 to 6.046).0391.544(−0.650 to 3.739).1666
GAD Anxiety Score1.069(−0.701 to 2.838).23480.161(−1.190 to 1.512).8145
Healthy Mental Health Days−0.576(−3.730 to 2.577).7187−1.771(−4.497 to 0.955).2013
MAP Snorting/GaspingCESD Depression Score3.284(0.426 to 6.143).02450.799(−1.369 to 2.967).4681
GAD Anxiety Score1.34(−0.377 to 3.058).1253−0.114(−1.444 to 1.216).8656
Healthy Mental Health Days1.484(−1.544 to 4.511).3348−0.524(−3.190 to 2.143).6988

Relationships Between Sleep Variables and Social Support, Adjusted for Age, Sex, and Year in School

Sleep VariableSocial SupportAdjustedAdjusted + Stress


B95% CIPB95% CIP
PSQI Sleep DurationMSPSS Family0.939(0.291 to 1.586).00470.776(0.135 to 1.417).0179
MSPSS Friends0.301(−0.368 to 0.970).37590.034(−0.601 to 0.669).9156
MSPSS Significant Other0.513(−0.228 to 1.254).17350.382(−0.361 to 1.125).3119
Support from Teammates0.593(−0.016 to 1.201).05630.333(−0.238 to 0.904).2514
PSQI Sleep QualityMSPSS Family−0.31(−0.557 to −0.063).0141−0.15(−0.420 to 0.121).2765
MSPSS Friends−0.373(−0.622 to −0.124).0034−0.118(−0.382 to 0.146).3773
MSPSS Significant Other−0.325(−0.604 to −0.046).0224−0.222(−0.531 to 0.087).1587
Support from Teammates−0.39(−0.616 to −0.164).0008−0.139(−0.377 to 0.099).2509
ISI InsomniaMSPSS Family−0.304(−0.447 to −0.161)< .0001−0.233(−0.404 to −0.061).008
MSPSS Friends−0.279(−0.425 to −0.132).0002−0.101(−0.271 to 0.069).2414
MSPSS Significant Other−0.234(−0.400 to −0.069).0057−0.179(−0.378 to 0.019).0764
Support from Teammates−0.334(−0.465 to −0.204)< .0001−0.18(−0.332 to −0.029).02
FSS FatigueMSPSS Family−0.084(−0.154 to −0.014).0182−0.045(−0.119 to 0.028).2266
MSPSS Friends−0.06(−0.131 to 0.011).09620.007(−0.065 to 0.079).857
MSPSS Significant Other0.021(−0.058 to 0.101).60130.065(−0.019 to 0.149).1306
Support from Teammates−0.097(−0.161 to −0.033).0033−0.036(−0.100 to 0.029).2806
MAP SnoringMSPSS Family−0.056(−2.161 to 2.050).95830.362(−1.694 to 2.418).7285
MSPSS Friends−1.012(−3.139 to 1.115).3491−0.412(−2.416 to 1.591).6851
MSPSS Significant Other1.501(−0.857 to 3.859).21081.843(−0.496 to 4.182).1216
Support from Teammates−0.858(−2.808 to 1.093).3869−0.255(−2.065 to 1.555).7813
MAP Snorting/GaspingMSPSS Family−2.157(−4.181 to −0.133).0368−1.553(−3.564 to 0.458).1292
MSPSS Friends−3.889(−5.883 to −1.894).0001−3.031(−4.953 to −1.109).0021
MSPSS Significant Other−2.654(−4.925 to −0.382).0222−2.224(−4.518 to 0.070).0573
Support from Teammates−2.257(−4.130 to −0.383).0185−1.338(−3.109 to 0.433).1377
Authors

From the Sleep and Health Research Program (MAG, CH, AJ, PA-M, JG) and the SCAN Lab, Department of Psychiatry (WDSK), and the Department of Athletics (AA), University of Arizona, Tucson, Arizona.

Supported by a National Collegiate Athletic Association Innovations Grant (MAG) and National Institute on Minority Health and Health Disparities (US) Grant R01011600 (MAG).

Dr. Grandner has received grants from Jazz Pharmaceuticals, Kemin Foods, and Nexalin Technology and is a consultant for Merck, Fitbit, Casper, Curaegis, Natrol, Pharmavite, NightFood, SmartyPants Vitamins, and Thrive Global. The remaining authors have no financial or proprietary interest in the materials presented herein.

The authors thank the National Collegiate Athletic Association, the University of Arizona Department of Athletics, and the students for taking part in this project.

Correspondence: Michael A. Grandner, PhD, MTR, University of Arizona, 1501 North Campbell Avenue, P.O. Box 245002, Tucson, AZ 85724-5002. Email: grandner@email.arizona.edu

Received: May 20, 2017
Accepted: January 27, 2020
Posted Online: August 26, 2020

10.3928/19425864-20200521-01

Sign up to receive

Journal E-contents