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PURPOSE: The effect of various sleep traits on the risk of lung cancer differs among pre-existing studies. This study aims to systematically review and synthesise the association between sleep duration and insomnia with the incidence of lung cancer. METHODS: PubMed, Embase and The Cochrane Library were searched from inception to 23 April 2023 for observational studies examining the effect of sleep quantity or insomnia on lung cancer incidence. We pooled maximally-adjusted hazard ratios and odds ratios separately using random effects inverse variance weighted models. The risk of bias of observational studies was assessed using the Newcastle-Ottawa Scale. RESULTS: We included 11 observational studies with a pooled cohort of 5,049,141 patients. The mean age of the patients was 49.5 ± 17.7 years, and 51.4% were males. The risk of bias ranged from low-moderate. Individuals who slept for a shorter or longer duration than the reference range of sleep per night showed an increased risk of lung cancer by 11% (HR:1.11; 95%CI:1.00-1.23) and 16% (HR:1.16; 95%CI:1.06-1.27) respectively. Furthermore, individuals with insomnia symptoms had a 9% greater risk of lung cancer than those without symptoms (HR:1.09; 95%CI:1.05-1.13). CONCLUSION: This study suggests that insufficient sleep, excessive sleep and insomnia may be associated with an increased risk of lung cancer. Physicians should be mindful of this association and encourage healthy sleep practises among patients. Given the observed heterogeneity among some pre-existing studies, future research with longer periods of follow-up, greater control for covariates and objective testing of sleep parameters may add value to this topic.

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OBJECTIVES: Corporate executive job demands may lead to poor sleep habits, increasing their risk for cardiometabolic disease. This study aimed to describe and explore associations between objectively measured habitual sleep characteristics and cardiometabolic disease risk of corporate executives, while accounting for occupational, psychological, and lifestyle factors. METHODS: Habitual sleep was measured using wrist-worn actigraphy and a sleep diary over seven consecutive days in 61 (68.3% men) corporate executives aged 46.4 ± 8.7years. A composite cardiometabolic disease risk score was determined using body mass index, waist circumference, blood pressure and fasting glucose and lipid concentrations. Prediction models were built using a backward stepwise selection approach to explore associations between sleep characteristics and cardiometabolic disease risk factors adjusting for occupational, psychological, and lifestyle covariates. RESULTS: Average total sleep time was 6.60 ± 0.75 hours, with 51.7% of participants reporting poor sleep quality and 26.2% extending their weekend sleep. Adjusted models showed that lower sleep efficiency (ß = -0.25, 95%CI: -0.43; -0.08, P = .006), shorter weekday total sleep time (ß = -1.37, 95% CI: -2.41, -0.32; P = .011) and catch-up sleep (ß = 0.84, 95%CI: 0.08, 1.60, P = .002) were associated with higher cardiometabolic disease risk scores. Adjusted models also found that shorter average time-in-bed (ß=-2.00, 95%CI: -3.76; -0.18, P = .031), average total sleep time (ß=1.98, 95%CI: -3.70; -0.25, P = .025) and weekday total sleep time (ß = -2.13, 95%CI: -3.56; -0.69, P = .025) as well as catch-up sleep (ß = 1.67, 95% CI: 0.52; 2.83; P = .012) were all associated with a higher body mass index. CONCLUSION: Corporate executives who compromise sleep duration during the working week may increase their risk for obesity and future cardiometabolic disease.

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Consuming coffee, a widely enjoyed beverage with caffeine, can impact the central nervous system and disturb sleep if taken too close to bedtime. Caffeine impacts sleep by slowing the onset, blocking adenosine receptors, lowering deep sleep levels, disrupting sleep patterns, and lessening rapid eye movement sleep. Although coffee can help with alertness in the morning, it may disturb sleep in the evening, particularly for individuals who are sensitive to caffeine. To enhance the quality of sleep, reduce the consumption of caffeine in the afternoon and evening, refrain from drinking caffeine before going to bed, and choose decaffeinated drinks instead. Variables such as personal reactions, ability to handle caffeine, and engagement with other compounds also influence the impact of coffee on sleep. Keeping track of how much caffeine you consume and your sleeping habits can assist in recognizing any disturbances and making needed changes. Furthermore, taking into account variables such as metabolism, age, and the timing of coffee consumption can assist in lessening the effects of coffee on sleep. In general, paying attention to the amount of caffeine consumed from different sources and consuming it at the right times can assist in preserving healthy sleep patterns even while enjoying coffee.

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Daily rest period (DRP) refers to the interval between the end of one workday and the start of the next. This study examined the joint association of DRP and sleep duration with subsequent sick leave among Japanese daytime employees. Participants (n=5,593) were measured for DRP and sleep duration at baseline and for sick leave at 1-year follow-up. They were categorized into 10 groups based on their DRP and daily sleep duration. Logistic regression analyses for individuals experiencing sick leave for longer than a month showed that the combination of short DRP (<11 h) and sleep duration (<6 h) had a higher odds ratio (4.981, 95% confidence interval [CI] = 1.126-22.046) than the reference group. Furthermore, the combination of short DRP and normal sleep duration had a higher odds ratio (8.152, 95% CI = 1.801-36.902) than the reference group. Short DRP was associated with subsequent long sick leave.

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INTRODUCTION: Psoriasis, a chronic inflammatory skin condition, affects approximately 3.0% of the US population, with patients often experiencing significant sleep disturbances. These disturbances include a higher prevalence of conditions such as obstructive sleep apnea, restless leg syndrome, and insomnia. Given the additional risks for cardiovascular disease, metabolic disorders, and depression linked to both poor sleep and psoriasis, addressing sleep issues in this patient group is critical. METHODS: The study utilized National Health and Nutrition Examination Survey (NHANES) data, focusing on individuals aged ≥ 20 years who provided information on psoriasis status and sleep. Multistage stratified survey methodology was applied, with multivariable logistic regression models used to examine the association between psoriasis and sleep issues, adjusting for factors such as age, gender, and health history. RESULTS: Psoriasis diagnosis was significantly associated with trouble sleeping (adjusted odds ratio [aOR] 1.88; 95% confidence interval [CI] 1.44-2.45). There was no significant association between psoriasis and sleep quantity. Older age, female gender, and a history of sleep disorders were predictors of trouble sleeping among psoriasis patients. CONCLUSIONS: Psoriasis is significantly associated with sleep disturbances, independent of sleep duration. This underscores the need for clinical screening focusing on sleep quality rather than quantity in psoriasis patients to effectively identify and treat sleep-related comorbidities. Further research using objective sleep measures is warranted to guide clinical management and improve patient quality of life.

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BACKGROUND: Indigenous Australians score worse on both sleep and oral health. This study aimed to evaluate sleep quality and quantity associated with oral health-related quality of life (OHRQoL) among Indigenous Australian adults. METHODS: A cross-sectional study involving 728 Indigenous Australian adults aged 18+ years was conducted. Exposure variables were sleep quality and quantity. The primary outcome variable was Oral Health Impact Profile-14 (OHIP14), which has been used to assess OHRQoL. Multivariable log-Poisson regression models were applied to estimate the mean ratios (MRs) for mean OHIP14 scores. RESULTS: The average OHIP14 score was 14.9, and the average amount of sleep was 6.8 h/night. After adjusting for all covariates, self-rated very bad sleep quality was associated with 2.2 times (MR = 2.17, 95% CI: 1.97-2.37) higher OHIP14 scores than those who rated their sleep quality as very good. Participants who self-reported sleeping 7-8 h/night had 0.9 times (MR = 0.89, 95%CI: 0.83-0.95) lower OHIP14 scores than those sleeping more than 8 h. CONCLUSIONS: The average number of sleep hours for Indigenous participants were lower than recommended (7-8 h/night). Our findings indicate that poor sleep quality and quantity, and oral health-related behaviours associated with sleep deprivation were positively associated with poor oral health related quality of life among Indigenous Australian adults.

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OBJECTIVE: This study aimed to determine the longitudinal associations between self-reported sleep duration and cardiometabolic disease (CMD) risk in corporate executives. METHODS: Self-reported sleep duration and lifestyle, occupational, psychological, and anthropometrical, blood pressure and blood marker variables were obtained from 1512 employees at annual health risk assessments in South Africa between 2016 and 2019. Gender-stratified linear mixed models, adjusting for age, lifestyle, occupational and psychological covariates were used to explore these longitudinal associations. RESULTS: Among women, shorter sleep duration was associated with higher body mass index (BMI) covarying for age only (ß with 95% confidence intervals: -0.19 [-0.36, -0.03]), age and occupational factors (-0.20 [-0.36, -0.03]) and age and psychological factors (-0.20 [-0.37, -0.03]). Among men, shorter sleep was associated with both BMI and waist circumference (WC) covarying for age only (BMI: -0.15 [-0.22; -0.08]; WC: -0.62 [-0.88; -0.37]); age and lifestyle factors (BMI: -0.12 [-0.21; -0.04]); WC: -0.016 [-0.92; -0.29], age and occupational factors (BMI: -0.20 [-0.22; 0.08]; WC: -0.62 [-0.88; -0.36]), and age and psychological factors (BMI: -0.15 [-0.22; -0.07]; WC: -0.59 [-0.86; -0.33]). Among men, shorter sleep was also longitudinally associated with higher CMD risk scores in models adjusted for age and lifestyle factors (CMD: -0.12 [-0.20; -0.04]) and age and psychological factors (CMD: -0.08 [-0.15; -0.01]). CONCLUSION: Corporate executives who report shorter sleep durations may present with poorer CMD risk profiles, independent of age, lifestyle, occupational and psychological factors. Addressing sleep health in workplace health programmes may help mitigate the development of CMD in such employees.

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The effect of strenuous exercise on sleep patterns in swimmers is equivocal. Therefore, the purpose of the study was to describe possible changes in sleep parameters among elite swimmers subjected to different training loads (TL). Methods: Eighteen elite swimmers (8 females) were monitored across two high-volume preparatory 1-wk periods (P1, P2) and a lower-volume tapering 1-wk period (P3) before a major competition. Internal (the session rating of perceived exertion [sRPE]) and external TL (training duration and volume) were measured, along with several sleep indices (e.g., bedtime, get-up time, sleep time, wake after sleep onset [WASO]). Serum measurements of urea, creatine kinase (CK), testosterone and cortisol were taken before and after training sessions at the beginning (Mondays) and end (Fridays) of each micro cycle. Athlete TL decreased significantly in a stepwise manner from P1 to P2 and from P2 to P3. Of all sleep parameters, only significant differences in bedtime and get-up time emerged (P3 > P1 and/or P2). Sleep duration (~6.3 h) or quality (WASO: 41-45 min) were also unaffected by TL. CK levels declined from P1 to P3 (d = -0.8), and from P2 to P3 (d = -0.6). Positive exercise-induced changes in CK were also seen in each training period. The other biomarkers did not show the same temporal or acute patterns. Irrespective of the TL, the monitored swimmers experienced insufficient and fragmented sleep across this study. Neither sleep quality nor quantity were affected by different magnitudes of TL. Among the biochemical markers of fatigue, baseline plasma CK activity best reflected the physiological response to TL.

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STUDY OBJECTIVES: Sleep duration has been shown to associate with cognitive function, but little is known about the short-term effect of sleep duration on the previous night. This study examines how usual sleep duration and previous night's sleep duration are associated with cognitive function in older adults. METHODS: The study population consisted of 2949 adults aged 59-92 years (mean 72.6, SD 5.7) derived from three Finnish cohorts. Participants' self-reported usual sleep duration was categorized into short (< 7 h, 19%), mid-range (7- < 9 h, 64%), and long (≥ 9 h, 17%). Self-reported sleep duration on the night prior to cognitive testing was categorized into shorter (59%), same (35%), and longer (5.9%) than usual sleep duration. Computerized Cambridge Neuropsychological Test Automated Battery (CANTAB®) was used to assess: (1) learning and memory, (2) working memory, (3) information processing, and (4) reaction time. RESULTS: Participants with self-reported long, but not short, usual sleep duration had poorer learning and memory (p = .004), information processing (p = .003), and reaction time (p = .006) when compared to those with mid-range sleep duration. Those who slept more than usually the night prior to cognitive testing had poorer information processing (p = .019) than those sleeping the same as usually, while sleeping less than usually was not associated with cognitive function. CONCLUSIONS: This study suggests that while long sleep duration was associated with worse cognitive function, sleeping more than usually the night prior to cognitive testing was only associated with information processing, and sleeping less than usually is not associated with cognitive function.

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PURPOSE: To investigate sleep quantity as a moderator of vaping and self-reported suicidality among adolescents. DESIGN: Cross-sectional. Setting: United States high schools. SAMPLE: 10,520 high-school students with complete data on the primary outcome of suicide attempt in the past year (76.9% response rate). MEASURES: 2019 Youth Risk Behaviors Survey. ANALYSIS: Logistic regression to examine main effects and potential moderation. RESULTS: Students with under seven sleep hours on school nights (OR = 2.6; 95% CI = 2.1-3.3) and who vaped in the past month (OR = 3.0; 95% CI = 2.1-3.9) had higher odds of attempting suicide in the last year. Sleep quantity moderated the relationship between vaping and suicidal thoughts in the past year (P = .01) but did not moderate the relationship between vaping and a suicide plan (P = .15) or suicide attempts (P = .06). Specifically, vaping had a smaller effect on suicidal thoughts among students who slept under seven hours on school nights (OR = 1.8) compared to the descriptively larger effect among participants with more sleep (OR = 2.5). CONCLUSIONS: Students who vape or report low sleep quantity would be ideal participants in suicide prevention interventions as they may be at higher risk for suicidality. Organizations implementing sleep or vaping interventions should incorporate information regarding the higher odds of suicide among students with low sleep quantity or vaping habits.

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Based on the assumptions that moral judgement activities require cognitive control, a capacity impaired by low sleep quality or a lack of sleep, several studies have explored the association between sleep and moral judgements. However, even if some studies support the association between sleep and both moral awareness and unethical behaviours, others failed to find a robust association between sleep and moral utilitarianism. In the present well-powered preregistered cross-sectional study, we explored the role of sleep in another class of moral judgement, namely third-party punishment (in which people have to assess the morality of an agent who transgressed a moral rule). Specifically, we targeted the association of sleep with judgements of accidental harm transgressions, which are assumed to be especially cognitively costly. Our main analysis showed no association of overall sleep quality during the past month with moral severity in these transgressions. This result was confirmed for other sleep indexes (sleep quantity in the past month, and sleep quantity and quality in the past night). Lastly, we exhaustively explored the associations of all sleep indexes with all classes of moral judgement (accidental, intentional, attempted transgressions and control scenarios). These additional results revealed associations between sleep and moral severity, but none survived correction for multiple testing. Equivalence tests confirmed that the effect sizes of all these associations were relatively low (|r < 0.25|). We ensured that the lack of robust association between natural sleep and third-party punishment could not be explained by a low quality of the data collected.

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The prevalence of sleep problems is high in primary care patients and in anxious individuals. This study assessed whether total sleep time and bedtime procrastination mediated the association between anxiety and sleep problems. We predicted higher anxiety would be negatively associated with total sleep time and positively associated with bedtime procrastination and sleep problems, and these variables would statistically mediate the association between anxiety and sleep problems. Participants were 308 adult primary care patients, predominantly female (non-Hispanic White = 158, Latinx = 111, mean age = 33.30), who initiated behavioral health services at an integrated primary care clinic. Patients completed a questionnaire regarding psychological health and sleep behaviors. Using structural equation modeling, we found higher anxiety related to higher sleep problems, partially mediated by bedtime procrastination but not total sleep time. This study highlights related factors like anxiety and prebedtime behaviors that may be effective treatment targets for sleep challenges.

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BACKGROUND: Abnormal sleep is commonly observed in the ICU and is associated with delirium and increased mortality. If sedation is necessary, it is often performed with gamma-aminobutyric acid agonists such as propofol or midazolam leading to an absence of restorative sleep. We aim to evaluate the effect of dexmedetomidine on sleep quality and quantity. METHODS: Thirty consecutive patients were included. The study was conducted as a double-blinded, randomized, placebo-controlled trial with two parallel groups: 20 patients were treated with dexmedetomidine, and 10 with placebo. Two 16 h of polysomnography recordings were done for each patient on two consecutive nights. Patients were randomized to dexmedetomidine or placebo after the first recording, thus providing a control recording for all patients. Dexmedetomidine was administered during the second recording (6 p.m.-6 a.m.). OBJECTIVE: To compare the effect of dexmedetomidine versus. placebo on sleep - quality and quantity. PRIMARY OUTCOME: Sleep quality, total sleep time (TST), Sleep efficiency (SE), and Rapid Eye Movement (REM) sleep determined by Polysomnography (PSG). SECONDARY OUTCOME: Delirium and daytime function determined by Confusion Assessment Method of the Intensive Care Unit and physical activity. Alertness and wakefulness were determined by RASS (Richmond Agitation and Sedation Scale). RESULTS: SE were increased in the dexmedetomidine group by; 37.6% (29.7;45.6 95% CI) versus 3.7% (-11.4;18.8 95% CI) (p < .001) and TST were prolonged by 271 min. (210;324 95% CI) versus 27 min. (-82;135 95% CI), (p < .001). No significant difference in REM sleep, delirium physical activity, or RASS score was found except for RASS night two. CONCLUSION: Total sleep time and sleep efficiency were significantly increased, without elimination of REM sleep, in mechanically ventilated ICU patients randomized to dexmedetomidine, when compared to a control PSG recording performed during non-sedation/standard care.

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PURPOSE: To investigate the quantity and quality of sleep hours in young athletes in a professional football club, to study if there is a significant relationship with mood state and subjective well-being, and to identify the relationship between sleep and quarterly academic performance. We also explored the relationship between sleep and quarterly academic performance. METHOD: the study included 261 players of the various age group categories from football at Barcelona Football Club (average age:13.04 ± 3.16). Participants maintained a sleep diary and completed questionnaires on their mood state and the quantity and quality of their sleep. RESULTS: 70% of the athletes slept less hours than recommended by the American National Sleep Foundation. Athletes with worse quantity and quality of sleep showed negative effects on academic results. CONCLUSIONS: The results show that the majority of young players sleep less than recommended and show that those who sleep more hours obtain better academic results.

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Sleep is a significant biological requirement for all living mammals due to its restorative properties and its cognitive role in memory consolidation. Sleep is ubiquitous amongst all mammals but sleep profiles differ between species dependent upon a range of biological and environmental factors. Given the functional importance of sleep, it is important to understand these differences in order to ensure good physical and psychological wellbeing for domesticated animals. This review focuses specifically on the domestic horse and aims to consolidate current information on equine sleep, in relation to other species, in order to (a) identify both quantitatively and qualitatively what constitutes normal sleep in the horse, (b) identify optimal methods to measure equine sleep (logistically and in terms of accuracy), (c) determine whether changes in equine sleep quantity and quality reflect changes in the animal's welfare, and (d) recognize the primary factors that affect the quantity and quality of equine sleep. The review then discusses gaps in current knowledge and uses this information to identify and set the direction of future equine sleep research with the ultimate aim of improving equine performance and welfare. The conclusions from this review are also contextualized within the current discussions around the "social license" of horse use from a welfare perspective.

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The primary aim of this study was to examine the validity of six commonly used wearable devices, i.e., Apple Watch S6, Garmin Forerunner 245 Music, Polar Vantage V, Oura Ring Generation 2, WHOOP 3.0 and Somfit, for assessing sleep. The secondary aim was to examine the validity of the six devices for assessing heart rate and heart rate variability during, or just prior to, night-time sleep. Fifty-three adults (26 F, 27 M, aged 25.4 ± 5.9 years) spent a single night in a sleep laboratory with 9 h in bed (23:00-08:00 h). Participants were fitted with all six wearable devices-and with polysomnography and electrocardiography for gold-standard assessment of sleep and heart rate, respectively. Compared with polysomnography, agreement (and Cohen's kappa) for two-state categorisation of sleep periods (as sleep or wake) was 88% (κ = 0.30) for Apple Watch; 89% (κ = 0.35) for Garmin; 87% (κ = 0.44) for Polar; 89% (κ = 0.51) for Oura; 86% (κ = 0.44) for WHOOP and 87% (κ = 0.48) for Somfit. Compared with polysomnography, agreement (and Cohen's kappa) for multi-state categorisation of sleep periods (as a specific sleep stage or wake) was 53% (κ = 0.20) for Apple Watch; 50% (κ = 0.25) for Garmin; 51% (κ = 0.28) for Polar; 61% (κ = 0.43) for Oura; 60% (κ = 0.44) for WHOOP and 65% (κ = 0.52) for Somfit. Analyses regarding the two-state categorisation of sleep indicate that all six devices are valid for the field-based assessment of the timing and duration of sleep. However, analyses regarding the multi-state categorisation of sleep indicate that all six devices require improvement for the assessment of specific sleep stages. As the use of wearable devices that are valid for the assessment of sleep increases in the general community, so too does the potential to answer research questions that were previously impractical or impossible to address-in some way, we could consider that the whole world is becoming a sleep laboratory.

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The Mediterranean diet is a plant-based, antioxidant-rich, unsaturated fat dietary pattern that has been consistently associated with lower rates of noncommunicable diseases and total mortality, so that it is considered one of the healthiest dietary patterns. Clinical trials and mechanistic studies have demonstrated that the Mediterranean diet and its peculiar foods and nutrients exert beneficial effects against inflammation, oxidative stress, dysmetabolism, vascular dysfunction, adiposity, senescence, cognitive decline, neurodegeneration, and tumorigenesis, thus preventing age-associated chronic diseases and improving wellbeing and health. Nocturnal sleep is an essential physiological function, whose alteration is associated with health outcomes and chronic diseases. Scientific evidence suggests that diet and sleep are related in a bidirectional relationship, and the understanding of this association is important given their role in disease prevention. In this review, we surveyed the literature concerning the current state of evidence from epidemiological studies on the impact of the Mediterranean diet on nighttime sleep quantity and quality. The available studies indicate that greater adherence to the Mediterranean diet is associated with adequate sleep duration and with several indicators of better sleep quality. Potential mechanisms mediating the effect of the Mediterranean diet and its foods and nutrients on sleep are described, and gap-in-knowledge and new research agenda to corroborate findings are discussed.

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Objective: Sleep has been impacted by the COVID-19 pandemic around the world. Furthermore, screen time has been reported to influence sleep and has increased during pandemic quarantines. This systematic review searched databases to determine if screen time affected sleep during the COVID-19 pandemic. Methods: PubMed, Nursing and Allied Health Proquest, and Science Direct Health and Lifescience college edition were searched for articles that fit the inclusion criteria. There were 2750 articles initially screened. Then, 119 articles were further assessed to determine eligibility, creating a final sample of 18 articles that explored whether screen time affected sleep. Results: After reviewing the included articles (n = 18), the main theme revealed that screen time negatively affected sleep during the COVID-19 pandemic, specifically aspects such as sleep duration, sleep quality, sleep onset latency, and wake time. However, several articles countered this implication. Therefore, it is important to consider other factors that may influence the relationship between screen time and sleep. Conclusions: Although the number of articles included is limited, the overall synthesis suggests that COVID-19-related lifestyle changes, such as increased screen time, may negatively affect sleep health. However, other unidentified factors may have contributed to these findings and warrant further research. Nonetheless, community leaders must consider the long-term consequences of the pandemic and implement initiatives to address sleep challenges due to the intricate connection between sleep and well-being.

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Job strain has been associated with poor sleep quality and could lead to changes in duration and timing of sleep as well. This study examined the association of job strain with sleep duration, bedtimes and awakening times among public sector employees close to their retirement age. Differences in these sleep parameters between workdays and free days across job strain groups were examined. Duration and timing of sleep were measured repeatedly with accelerometers among 466 public sector employees in Finland (mean age 63 years, 86% women), who contributed to 759 measurements in total. Job demands (low/high) and control (low/high) measured by self-reports and job exposure matrix were used to identify low strain (low demand, high control), passive (low, low), active (high, high) and high strain (high, low) jobs. No differences in sleep duration were observed on workdays, whereas on free days those in the high strain group had longer sleep duration than those in the low strain and passive job groups. The high strain group also extended their sleep from workdays to free days more, the extension being on average 59 min (95% CI 42 min-75 min) when adjusted for several sociodemographic, work and health factors. This extension of sleep duration resulted mostly from a greater delay of awakening times from workdays to free days. Psychosocial work factors, such as job strain, need to be considered when promoting sufficient sleep duration among older employees, as those with job strain may have a greater need for recovery and sleep.

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Purpose: The purpose of this study was to extend research on napping and sleep behaviors in collegiate athletes, and to compare nappers and non-nappers on sleep quality and duration. Methods: Current varsity, club, and intramural athletes between 18-29 years completed the Short Napping Behavior Scale, Pittsburgh Quality Sleep Index, Generalized Anxiety Disorder-7, and the Patient Health Questionnaire-9. Results: Approximately 72% (129/179) reported napping. There were no significant differences in outcomes between nap frequency groups on sleep quality (Χ2(3)=4.97, p=.17) or duration (Χ2(3)=1.20, p=.75). Moreover, there was no significant differences for nap length groups on sleep quality (Χ2(3)=7.03, p=.07) or duration (Χ2(3)=1.32, p=.72). Furthermore, there were no significant differences for nap timing groups on sleep quality (Χ2(3)=1.54, p=.67) or duration (Χ2(3)=2.43, p=.49). Conclusion: In a sample of collegiate athletes, nap frequency, length, and timing were not associated with worse sleep quality or duration.

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