www.centreforsleep.com Copyright © 2006-2012 Samuels C.H. Sleep, Recovery and Human Performance in Elite Athletes Division 1A Faculty Athletics Representatives Annual Meeting Dallas, Tx September 22, 2014 Dr. Charles Samuels, MD, CCFP, DABSM Medical Director, Centre for Sleep and Human Performance Clinical Assistant Professor, Faculty of Medicine, University of Calgary Adjunct Professor, Faculty of Kinesiology, University of Calgary Disclosures Research Funding: City of Calgary, Calgary Police Service Canadian Olympic Committee “Own the Podium” Research Fund Pregabalin Effects on Sleep in Fibromyalgia CME Funding Nabilone Neuropathic Pain and Sleep Research Pfizer Pharmaceuticals Sleep and Human Performance Research Program Valeant Pharmaceutical CPS Health and Human Performance Research Initiative Servier National Working Group: Insomnia Primary Care Clinical Practice Guidelines Shire Pharmaceutical: National working group: Occupational Medicine and Shift Work Sanofi-Aventis Pharmaceutical: Insomnia Advisory Board Valeant Pharmaceuticals: Primary Care Insomnia Program Chairman Advisory Boards Shire Pharmaceuticals Sanofi-Aventis Pharmaceuticals Valeant Pharmaceuticals Palladin Pharmaceuticals www.centreforsleep.com Copyright © 2014 Samuels C.H. Conflicts of Interest None to Declare www.centreforsleep.com Copyright © 2014 Samuels C.H. Part of the series; Sleep, Recovery and Human Performance in Elite Athletes© Objectives The Participant Will: 1) be able to apply the basic science of sleep and circadian physiology to the practice of sport medicine and administration of sport teams. 2) be able to implement sleep screening strategies into the annual medical assessments of student athletes. 3) Be able to develop interventions to manage student athletes who have sleep issues. The Problem ENVIRONMENT TIME PHYSIOLOGY GENETICS SIMPLE MATH 24 Hours in a Day 7 Days a Week 50 – 60 Hours of Sleep a Week! The Barrier: Wired for Distraction Basic Sleep Science The Basic Science of Sleep 1) Amount 2) Timing 3) Determine True Sleep Need Reduce Accumulated Sleep Debt Sleep Phase Environmental Factors Quality Environmental Factors Sleep Disorders Amount of Sleep 1) Individual Sleep Requirement: Determine the amount of time in sleep that leaves you feeling fully refreshed and rested in the morning. Sleep onset should be 20-30 minutes. Sleep offset (awakening) should be spontaneous (without an alarm). General requirement 7 – 9 hours in most training athletes. Circadian Timing of Sleep 1) Individual Sleep Phase: What is the preferred and optimal time for bed that allows the individual to fall asleep within 30 minutes. This is not in response to environmental demands ie; training, school etc. Ask the questions: Do you like the night? Do you do your best work at night? Do you get a second wind in the evening? Do you have trouble falling asleep before midnight – 1AM. Do you struggle to wake up in the morning? Do you finally wake up or get going by 10-11AM. Circadian Timing of Sleep 1) Nightowls ( sleep time 1-2AM or later) 2) Larks (sleep time 10-11PM) 3) Need help with adjusting the sleep phase to match the training schedule. Easier to manage with respect to early training schedules Circadian preference needs to be taken into account for competition times and countermeasures can be implemented to prepare the athlete appropriately. Quality of Sleep 1) Non-Restorative Sleep 2) Defined as the perception of sleep but waking unrested and suffering daytime fatigue that cannot be explained by training volume/intensity. Disturbed Sleep Described as restless, light sleep, easily woken from sleep resulting in waking unrested and suffering fatigue that cannot be explained by training volume/intensity. Sleep, Recovery and Regeneration Sleep as a Foundation for Recovery ATHLETIC PERFORMANCE HEALTH / WELLNESS RESILIENCE NUTRITION/HYDRATION SLEEP FACTORS Recovery/Regeneration SLEEP COPING THRESHOLD LIFE FACTORS TRAINING FACTORS -Psychology CIRCADIAN FACTORS -Social -Environmental Adapted from Vila B & Samuels C 2009 (in press) Copyright © 2006-2012 Samuels C.H. Training/Recovery Balance Adapted from Kentta G. & Hassmen P. Sports Med 1998; 26(1):1-16. Training Cycle Fig 5. Nimmo M.A. & Ekblom B. Journal of Sports Sciences 2007; 25(S1): S93-S102 Overtraining vs Under-recovery Fig 2. Kentta G. & Hassmen P. Sports Med 1998; 26(1):1-16. Impaired Sleep Factors Focus on Sleep! Normal Sleep Move On! The Research Symposium 11 June 3, 2014, 8:00 – 10:00 Sleep in Collegiate Athletes Sayaka ARITAKE, MT, PhD, RPSGT Sunao UCHIDA, MD, PhD Waseda University, Faculty of Sport Sciences Sport Psychiatry and Neuroscience laboratory The Epidemiology of Sleep Behavior in Collegiate Athletes: An Observational Survey Based Study Using the Pittsburgh Sleep Quality Index Study 2 Methods Participants 2,200 collegiate athletes in Waseda University （1492 male and 708 female） 36 sports The survey was conducted from 9/2013 to 10/2013 Sampling type Unsigned self-reporting questionnaire Participants provided informed consent via the questionnaire. Study 2 Questionnaire 1) Sociodemographic information (age, gender, weight, height, etc.) 2) Sport names, training regime, practicing hours per week 3) Sleep habits (nocturnal sleep time, bedtime, wake-up time, napping habit) in the past month 4) Sleep difficulty via a PSQI*: cut off score =5.5 5) Excessive daytime sleepiness (EDS) via a ESS*: cut-off score=11 6) Mood status via a POMS*: T-score for 6 components 7) Morning type or Evening type: MEQ* *PSQI: Pittsburg sleep quality index, ESS: Epworth sleepiness scale, POMS: Profile of mood status, MEQ: morning and evening questionnaire Demographic variables and sleep related scores (n=1,111) Item Total Male Female p-value Age（years） 20.1±1.4 20.1±1.6 19.7±1.9 0.719 Height（cm） 169.8±8. 0 173.3±5.6 160.8±6.2 0.033 Weight （kg） 67.0±13. 4 72.0±12.2 54.1±7.2 <0.001 BMI 23.1±2.1 23.9±3.6 18.9±6.4 <0.001 Nocturnal sleep time (hours) 6.5±1.3 6.5±1.3 6.3±1.3 0.004 Bedtime(h) 23.9±1.8 23.9±1.9 24.0±1.5 0.345 Wake-up time（h） 6.8±1.6 6.9±1.6 6.7±1.5 0.097 PSQI score 4.9±2.5 4.7±2.5 5.3±2.6 <0.001 ESS score 9.1±4.1 8.8±4.2 9.8±3.8 <0.001 MEQ score 51.7±7.5 50.8±7.2 53.9±7.8 <0.001 (in preparation) 0.151 79.1 76.9 time was78.5 under 7 hours. Females had significantly shorter sleep time, higher PSQI score, ESS score, and MEQ score. Napping habit（%） Nocturnal sleep （h） Nocturnal sleep time in each sport (n=1,111) 7.4hours (in preparation) Most sports slept under 7 hours Nocturnal sleep duration and practice start time Sport Nocturnal Sleep time (hours) 4.1 Skating 5.2 Lacrosse 5.4 Equestrian 5.6 Rowing 5.7 Golf 7.4 Sumo 7.2 American football Practice start time 4:15 am 7:00 am 7:00 am 6:30 am 6:30 am 6:00 pm 5:30 pm (in preparation) The sports that started practice early in the morning tended to have shorter sleep time. short Same order as Nocturnal sleep time Long Without sleep difficulty Skating Lacrosse Equestrian Rowing Golf Shorinji Kempo Wrestling Judo Cheerleading Tennis Baseball Gymnastics Junko Baseball Volleyball Hockey Kyudo Track & Field Archery Cycling Swimming Wandervogel Basketball Table Tennis Skiing Handball Soft Tennis Aviation Rugby Softball Nippon Kempo Kendo Weightlifting Soccer (in preparation) American Football Shooting Sumo PSQI score tended to be higher in the sports that had shorter nocturnal sleep duration With sleep difficulty PSQI score in each sport (pt.) 5.5 pt. (n=1,111) Napping habit in each sport (pt.) long Same order as Nocturnal sleep time short (in preparation) Most athletes tended to nap frequently Exercise Intensity We classified METs of each sport in the 4 categories due to the intensity of athletic sports *METs (Metabolic Equivalents): One MET is defined as the energy it takes to sit quietly. Physiological measure expressing the energy cost of physical activities and is defined as the ratio of metabolic rate during a specific physical activity to a reference metabolic rate 2 3 4 5 Shooting Table tennis Equestrian Track & Field *4 Archery Golf Softball Baseball Kyudo METsⅠgroup 6 Rugby 7 8 Hockey Lacrosse Wrestling Tennis Sumo Basketball Volleyball Weightlifting Track & Field *3 METsⅡ group 9 10 Skating Judo American Skiing Football Soccer Handball Kendo Swimming 11 12 13 14 Nippon Track & Field *1 Kempo Cycling Track & Field *2 Rowing Shorinji Kempo METsⅢ group METsⅣ group (Ainsworth et al., Med Sci Sports Exerc., 2011) Sleep parameters among METs categories (pt.) p=0.329 (pt.) （%） ESS score p=0.710 p<0.001 F=12.391 * Prevalence of Napping habit * p=0.032 Χ2=8.840 (in preparation) POMS score among 4 METs categories （pt.） 58.0 ＊ 56.0 54.0 ＊ ＊ ＊ 52.0 METsⅠ 50.0 METsⅡ 48.0 METsⅢ 46.0 44.0 *p<0.001 p<0.01 T-A D A-H V CC T-A D A-H V FF （緊張） （抑うつ） （怒り） （活気） （疲れ） （混乱） METsⅣ T-A: Tension-Anxiety, D: Depression , A: Anger, V: Vigor, F: Fatigue, C: Confusion Higher POMS score in the METs Ⅳ category than the other 3 categories (in preparation) May 31 – June 4, 2014 Minneapolis Convention Center Subjective Sleep Quality Differences between Elite Athletes and Controls Amy M. Bender, MS, RPSGT Washington State University Subjective Sleep Quality in Elite Athletes • 50% (12/24) professional ballet dancers had Pittsburgh Sleep Quality Index global (PSQI) scores >5 (Fietze et al., 2009) • 37% (95/258) Swiss Olympic adolescent athletes reported poor sleep on a modified PSQI (Gerber et al., 2011) • 56% (25/45) of adolescents from the Canadian National Sport School reported PSQI global scores >5 (Samuels, 2008) • 57% (13/23) of Bobsleigh Canada Skeleton team reported PSQI global scores >5 (Samuels,2008) Subjective Sleep Quality in Elite Athletes Compared to Normal Controls on the Pittsburgh Sleep Quality Index 1 1 2,3 Amy M. Bender , Hans P.A. Van Dongen , Winne H. Meeuwisse , Charles H. Samuels4,5 and Performance Research Center, Spokane, WA, USA; 2University of Calgary Sport Medicine Centre, Calgary, AB, Canada; Introduction 3Faculty of Kinesiology, University of Calgary, Calgary, AB, Canada; 4Faculty of Medicine, University of Calgary, Calgary, AB, Canada; 5Centre for Sleep and Human Performance, Calgary, AB, Canada • Previous research examining sleep in 1Sleep • Results • • PSQI global scores were distributed differently (D=2.83, p<0.01) in the athletes (5.0±2.6) compared to the controls (2.6±1.3). For the PSQI component scores, sleep quality (D=1.63, p=0.01; See Figure 1), sleep latency (D=1.85, p<0.01), sleep disturbances (D=2.02, p<0.01; See Figure 2) and daytime dysfunction (D=2.92, p<0.01) were distributed differently, with the athletes reporting greater sleep disturbance and more daytime dysfunction. • 100 90 80 70 60 50 40 30 20 10 0 C C A A Very Good 1 Fairly Good 2 C C A Fairly Bad 3 Very Bad 4 Figure 1: Self-reported sleep quality responses in controls (C) and elite athletes (A). Research supported by Own the Podium, CDMRP award W81XWH-05-1-009, and NIH grants R01HL105768, R21CA167691. A A A C A A C C A 4 5 6 7 Other 3 Have pain 2 C C C C 1 9 8 Figure 2: Self-reported sleep disturbance responses in controls (C) and elite athletes (A). “During the past month, how would you rate your sleep quality overall?” A C Had bad dreams • C Feel too hot • Elite athletes reported poorer sleep quality, as evidenced by higher PSQI global scores, and higher PSQI component scores of sleep quality, sleep latency, sleep disturbances, and daytime dysfunction, relative to a control group of healthy, normal sleepers. This was found in the absence of significant group differences in TIB, TST, SE, and timing of the sleep period. However, the athletes’ distribution of morningness scores showed greater skew towards morningness. Further research should elucidate whether circadian factors reduce sleep quality in elite athletes and how this impacts recovery. Feel too cold • Cough or snore loudly • Discussion A A Cannot breathe comfortably • 63 National and Olympic winter team athletes (aged 26.0±4.0; 32% females) from the Canadian Sport Centre Calgary completed the PSQI and the Athlete Morningness Eveningness Scale. 83 healthy, normal sleepers (aged 27.3±4.7; 51% females) from studies at Washington State University’s Sleep and Performance Research Center completed the PSQI and the Composite Scale of Morningness. For comparability, morningness scores were classified in 9 equal intervals for both morningness questionnaires. Using Kolmogorov-Smirnov tests, the two groups were compared for age, gender, PSQI global scores, PSQI component scores (sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction), morningness, and self-reported time in bed (TIB), sleep latency (SL), total sleep time (TST), bedtimes and wake times. % of Subjects • A Have to get up to use bathroom Methods 100 90 80 70 60 50 40 30 20 10 0 Wake up in middle of night/early morning • Morningness scores were also distributed differently (D=1.45, p=0.03), with greater skew towards morningness in the athletes. See Figure 3. There were no significant distribution differences between the groups for age, gender, TIB, SL, TST, bedtimes and wake times. % of Subjects • % of Subjects • athletes has suggested that elite athletes have reduced objective sleep quality compared to controls.1,2 Here we compared the subjective sleep of elite athletes and normal controls using the Pittsburgh Sleep Quality Index (PSQI). 50 45 40 35 30 25 20 15 10 5 0 A C C C A A C A C A CA A C CA 1 ←Eveningness 2 3 CA 4 5 6 Morningness→ 7 8 9 Figure 3: Distribution of binned morningness scores in controls (C) and elite athletes (A). 1Fietze I, et al. (2009). Chronobiol. Int. 26(6):1249-1262. J, et al. (2012). J. Sports Sci. 30(6):541-545. 2Leeder % of Athletes Subjective Sleep Quality in Elite Athletes 50 40 30 20 10 0 N=68 0-1 1 2-3 2 4-5 3 6-7 4 8-9 5 10-11 12-13 14-21 6 7 8 PSQI Global Scores Combined datasets of the National Sport School and Bobsleigh Canada Skeleton team adapted from Samuels C., Neurol Clin 26 (2008) Methods (Questionnaires) • Pittsburgh Sleep Quality Index (PSQI) (Buysse et al., 1989): • 19 item validated questionnaire to assess sleep quality and sleep disturbance over the last month • 7 component scores (sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction) • Global score - determines severity of sleep problems • 5 cutoff score (≤5 normal healthy sleepers, >5 identifies cases with sleep problems) • Morningness and Eveningness: • Athletes - Athlete Morningness Eveningness Scale • Controls - Composite Scale of Morningness (Smith et al., 1989) • Morningness scores were classified into 9 equal intervals for both questionnaires Methods (Subjects) • N=63 National and Olympic winter team athletes (mean age 26.0 ± 4.0; 32% females) who trained at Canadian Sport Center Calgary • N=83 healthy normal sleepers as defined by medical history, physical, and various questionnaires including PSQI score ≤5 (mean age 27.3 ± 4.7; 51% females) taken from studies at WSU’s Sleep and Performance Research Center • Groups were compared using Kolmogorov-Smirnov tests for: • PSQI global scores • PSQI component scores (sleep quality, sleep latency, sleep efficiency, sleep duration, sleep disturbance, use of sleeping medication, daytime dysfunction) • Morningness and eveningness preference • Time spent in bed, and habitual bedtimes and wake times Results – PSQI Global Scores 60 Controls Athletes % of Subjects 50 p<0.01 40 30 20 10 0 0-1 2-3 4-5 6-7 8-9 10-11 12-13 14-15 16-21 Controls (2.6 ± 1.3) vs. Athletes (5.0 ± 2.6) Results – Sleep Quality and Sleep Latency How often have you had trouble sleeping because you cannot get to sleep within 30 minutes? How would you rate your sleep quality overall? How would you rate your Controls sleep quality overall? % of Subjects 100 Athletes 80 p=0.01 100 80 p<0.01 60 60 40 40 20 20 0 0 Very Good Fairly Good Not in past <1 time per 1-2 times month week per week Fairly Bad Very Bad Controls Athletes 3+ times per week Results – Sleep Disturbance Reasons % Subjects ofSubjects %of 0 20 40 60 80 100 Wake up in middle of night or early morning Have to get up to use bathroom Cannot breathe comfortably Cough or snore loudly p<0.01 Feel too cold Feel too hot Had bad dreams Have pain Controls Athletes Other % of Sub Controls Jec Athletes ts Results – Sleep Disturbance Frequency % of Subjects 100 80 Controls Athletes p<0.01 60 40 20 0 Not in past <1 time 1-2 times 3+ times month per week per week per week Results – Daytime Dysfunction How much of a problem has it been for you to keep up enough enthusiasm to get things done? % of Subjects How often have you had trouble staying awake while driving, eating meals, or engaging in social activity? 100 100 80 80 60 60 40 40 20 20 0 0 No problem Not in past <1 time 1-2 times 3+ times month per week per week per week Controls Athletes p<0.01 A slight problem Somewhat A very big of a problem problem Results for Other Sleep Parameters • No significant differences for self-reported time in bed, sleep duration, sleep efficiency, sleep latency, use of sleep medication, habitual bedtimes and wake times Self-Reported Sleep Parameters TIB TST Sleep Latency Bedtime Wake Time Controls 8.78±59 8.03±44 15.2±10 22:45±50 07:32±55 Athletes 8.80±60 8.06±60 21.5±18 22:55±57 07:44±1:07 Results – Morningness/Eveningness % of Subjects 50 Controls Athletes 40 p<0.01 30 20 10 0 1 2 3 4 5 6 M/E Scores ←Eveningness 7 8 Morningness→ 9 PSQI Global Scores Results – Correlation between Morningness/Eveningness with PSQI scores r =-0.35 20 p<0.01 15 10 5 0 10 15 20 25 30 Athlete Morningness Eveningness Scores ←Eveningness Morningness→ Conclusions • Elite athletes subjectively reported poorer sleep quality than controls • Greater PSQI global scores (32% >5) • 10% reported sleep quality as “fairly bad” • ~40% had issues getting to sleep within 30min (1 or more times/week) • More sleep disturbances and greater frequency of these occurrences • Elite athletes reported more preference for morningness The Psychometric Development of an Athlete Sleep Screening Questionnaire: Process & Methods Samuels C.H.1,2, Alexander B.N.1, Lawson D.1, Lun V.3,4, Meeuwisse W.H.3,4 Centre for Sleep and Human Performance, Calgary, AB, Canada 1; Faculty of Medicine, University of Calgary, Calgary, AB, Canada 2, University of Calgary, Sport Medicine centre, Calgary, AB, Canada 3; Faculty of Kinesiology, University of Calgary, Calgary, AB, Canada 4 Background/Rationale Methods Continued There is great interest in the effect of sleep and circadian rhythms on athletic performance, recovery, and regeneration.1 Sleep extension and circadian rhythm research have provided objective evidence in well designed studies in support of this focus.2 The amount and quality of sleep, as well as chronotype, are considered to be important factors that affect an athlete’s ability to train, maximize the training response, and recover.3 Phase III: A review of sleep-related items from the Patient Reported Outcomes Measurement Information System (PROMIS)4, in addition to a review of the SRSSR questions that indicated good concordance with the SCI (clinical outcomes) and best theoretical grounding (as determined by a subject-matter expert) were used to further guide the development process for the ASSQ. The 51 questions from the SRSSR were reduced to 15 and structured around the three clinical domains used to assess sleep: total sleep time, sleep quality, insomnia. An aggregate Sleep Difficulty Score (SDS) based on responses from each domain will be used to guide referral decisions. Individuals scoring below the cutoff do not suffer from a clinically significant sleep problem and are directed to general sleep education or monitoring by their Integrated Support Team. Individuals scoring higher than the cutoff value are referred to either a sports medicine physician for moderate clinical problems, or a sleep physician for severe clinical problems. Additionally, certain combinations of responses to questions corresponding to sleep disordered breathing, chronotype, or travel disturbance can either act as modifiers to the SDS, or in some cases result in a recommendation for referral on their own. Objective Current sleep screening tools/questionnaires are inadequate for screening an athlete population because this cohort is younger, healthier, and fitter than the general population. The present study was designed to develop, validate and test the reliability of a subjective sleep screening questionnaire for elite athletes – the Athlete Sleep Screening Questionnaire (ASSQ). Methods A convenience sample of 80 athletes was selected from 300 eligible athletes who train out of the Canadian Sport Centre – Calgary. Sixty athletes were consented and randomized into the study; 30 were assigned to Phase I, and another 30 were assigned to Phase II. Results Continued Phase I: The athletes completed a self-report sleep screen (SRSS) composed of current standard self-report psychometric tools from the field (Pittsburgh Sleep Quality Index (PSQI), Adjusted Neck Circumference (ANC), Athlete Morningness/Eveningness Scale (AMES)) that were selected on the basis of publication, clinical use, and subject matter-expert preference. Each athlete subsequently had a clinical interview by an expert sleep specialist based on the PSQI. The goal of Phase I was to identify weaknesses in the current self-report methods in an athlete population. The information gathered was then meant to inform and guide the development the ASSQ. Phase II: Following the assessment of data from Phase I, the second group of athletes completed a revised SRSS (SRSSR) which included the Insomnia Severity Index (ISI), the AMES and ANC were replaced with the Composite Scale of Morningness (CSM) and the Maislin Apnea Risk Index (MAP), respectively. The athletes repeated the SRSSR 24 hours later to provide retest correlation. Each athlete had a structured clinical interview (SCI; a clinical comparator) by the expert sleep specialist. Clinical outcomes (none, mild, moderate, or severe clinical problem) were generated from the results of the SRSS and SCI. The SCI sessions were video recorded to facilitate rescoring by the expert sleep specialist for intra-rater reliability; and to be viewed and scored by two other sleep physicians (one general sleep clinician, and one sleep clinician practiced in assessing athletes) for inter-rater reliability testing. Figure 2. ASSQ: Proposed scoring system, clinical outcomes and referral decision algorithm. Phase II: Analysis of Phase II data to-date supports the findings that common tools from sleep medicine do not associate well with clinical outcomes as determined by an expert sleep specialist – in this sample of athletes. Although athlete test-retest correlations were high (0.94 on average) for the PSQI, ISI, MAP, and the CSM, there was poor association with the clinical judgment of the sleep expert (Sleep disturbance, 10.3%; Sleep quality, 31.0%; sleep apnea, 72.4%; chronotype, 24.1%; insomnia, 6.9%). Additional results of intra and inter-rater reliability are yet to be established. Current Phase II data continue to support the need for selection and refinement of the questions (items) for inclusion into the sleep screening questionnaire that would associate more strongly with clinical interview and provide a valid and reliable ASSQ. Future Directions Figure 1. ASSQ Development phases, methods , process and outcomes algorithm. Results Phase I: Findings from Phase I supported a concordance rate of 57% and 53% between the SRSS and the PSQI retested by the sleep specialist for the AMES and PSQI, respectively; close to chance. The results identified the weaknesses in the current self-report tools that were selected for use to assess total sleep time, sleep quality, insomnia, and chronotype when compared to a sleep expert. This confirmed the need for further investigation into the weaknesses of these tools, and the future development of a clinically reliable psychometric questionnaire for sleep screening. The current version of the ASSQ will be deployed through the Canadian Athlete Monitoring Program (CAMP) electronic database to all the National Sport Organization national team athletes. Data from this large scale screen and monitoring of outcomes (referral vs no referral) will inform further validity and reliability testing and determination of the SDS. The goal will be to determine the validity of each item, the strength of each domain and the SDS that accurately predicts the clinical outcome in an athlete population. References 1. Postolache TT, et al. Sports chronobiology consultation: from the lab to the arena. Clin Sports Med 2005; 24(2):415-456. 2. Reilly T, Edwards B. Altered sleep-wake cycles and physical performance in athletes. Physiol Behav 2007; 90(2-3):274-284. 3. Samuels C. Sleep, recovery, and performance: the new frontier in high-performance. Neurol Clin 2008; 26(1):169-180. 4. Buysse DJ. Development and Validation of Patient-Reported Outcome Measures for Sleep Disturbance and Sleep-Related Impairments. SLEEP 2010; 33(6): 781-792. Athlete Sleep Screening Questionnaire Data Data: collected from 2011 to 2013 Subjects: Summer and Winter National Team and Olympic Athletes N: 307 athletes consented and participated 132 males 168 females Copyright © 2006-2012 Samuels C.H. ASSQ by Sport: Mean (SD) Total Sleep Time, Sleep Difficulty Score Sport Total Sleep Time Mean Hours/Night (SD) Sleep Difficulty Score Mean (SD) BMX (n=11) 8.11 (0.94) 8.83 (4.21) Curling (n=27) 8.12 (1.07) 7.93 (3.06) Rugby (n=50) 7.71 (1.16) 9.30 (2.86) Alpine Skiing (n=30) 7.80 (1.14) 8.83 (4.21) Biathlon (n=6) 8.38 (0.86) 8.83 (2.23) Bobsleigh (n=12) 7.85 (0.90) 8.50 (2.97) Cycling (n=21) 8.20 (1.10) 8.33 (3.01) Copyright © 2006-2012 Samuels C.H. ASSQ by Sport: Mean (SD) Total Sleep Time, Sleep Difficulty Score (Continued…) Sport Total Sleep Time Mean Hours/Night (SD) Sleep Difficulty Score Mean (SD) Para-Olympics (n=13) 7.94 (1.26) 8.15 (2.44) Skeleton (n=10) 7.70 (0.86) 9.30 (4.16) Speed-skating (n=34) 8.00 (1.09) 8.74 (3.29) Swimming (n=11) 7.86 (1.18) 9.91 (4.11) Volleyball (n=6) 8.62 (0.68) 8.83 (4.36) Water-polo (n=11) 7.82 (1.02) 8.64 (4.03) Wrestling (n=6) 7.71 (1.27) 8.83 (3.82) Copyright © 2006-2012 Samuels C.H. Data Collected from the ASSQ Approximately 13% of athletes had a difficulty score > 12, and required further screening. Female athletes had higher sleep difficulty scores than males, but not significantly (p=0.75). There was a significant inverse correlation between sleep difficulty score and total sleep time (rho= -0.52). Copyright © 2006-2012 Samuels C.H. Data Collected from the ASSQ Athletes who reported satisfaction with their sleep had total sleep times averaging over 8 hours per night. Athletes who reported dissatisfaction with their sleep had total sleep times averaging less than 7 hours per night. As dissatisfaction with sleep increases, average sleep difficulty scores also increase. Copyright © 2006-2012 Samuels C.H. Data Collected from the ASSQ Athletes’ increasing age and reduced sleep were significantly associated (p=0.01). Athletes’ increasing age and increased sleep difficulty were also significantly associated (p=0.03). Copyright © 2006-2012 Samuels C.H. Early Conclusions The ASSQ is demonstrating clinical significance and validity. The ASSQ is a useful screening tool that is easy to administer to a large population of athletes via the internet. Perceived Satisfaction, Total Sleep Time, Age correlate with the Sleep Disturbance Score. Copyright © 2006-2012 Samuels C.H. Discussion How do we accurately assess sleep factors objectively and subjectively in athletes? What is the relationship between training regimen and sleep requirement? What is the relationship between timing of training, endogenous circadian phase and training/performance outcome? What is the role of napping in the recovery process? How does sleep interact with mood and what is the effect on training, recovery and performance? Athlete Sleep Screening Remote Sleep Screening www.centreforsleep.com Copyright © 2014 Samuels C.H. Canadian Sport Centre Network Copyright © 2014 Samuels C.H. ASSQ Screening Results Follow-up Managing Sleep, Circadian Factors, Training and Performance Sleep Management Sleep Debt Sleep Quality Is your sleep restorative? Sleep Phase How much sleep do you need? When do you fall asleep easily and wake up spontaneously? Sleep Hygiene Copyright © 2006-2012 Samuels C.H. Training and Sleep 1) Make a plan and stick to it! 1) 2) 3) 4) 5) Determine your total sleep need Determine your optimum sleep phase Adjust your training around the foundation of sleep, rest and recovery. Use strategic napping to minimize sleep debt. Stick to a routine. Recovery 1) Rest: Planned rest to reduce arousal. 2) 3) Eyes Closed and Slow, Deep Breathing Napping: Strategic napping reduces the accumulation of sleep debt. 20-30 minutes at the circadian lows (2-4 PM) Sleep: 8 – 10 hours per night between 10 PM and 9AM. Be Consistent! Strategic Napping Naps should coincide with the circadian low. Naps should be limited to 20-30 minutes. The Athlete should wake spontaneously and refreshed Requiring longer naps indicates substantial sleep debt. Reassess the athletes’ sleep schedule Copyright © 2006-2012 Samuels C.H. Recovery 1. Rest: Planned rest to reduce arousal. Eyes Closed and Slow, Deep Breathing 2. Napping: Strategic napping (reduces sleep debt) 20-30 minutes (2-4 PM) 3. Sleep: 8–10 hours per night between 10 PM and 9AM. 4. Be Consistent! Copyright © 2006-2012 Samuels C.H. Athlete’s Bottom Line 1. Learn What You Need for Sleep And GET IT! 2. If Your Sleep is Poor, Get Help! 3. Rest and Sleep are Important for Adequate Recovery 4. If you get what you need, THAT IS AS GOOD AS IT GETS! Copyright © 2006-2012 Samuels C.H. Coaches Bottom Line If the Athlete: Goes to bed and falls asleep in 20-30 min. Sleeps through the night and fall back to sleep when he/she wakes up. Wakes up spontaneously in the morning and feels refreshed, and awake within 1 hour of waking. The Athlete is OK! He/She HAS NO SLEEP PROBLEM DON’T WORRY!! Copyright © 2006-2012 Samuels C.H. Light Therapy Recommended Reading Jacobs GD. Say Good Night to Insomnia: the 6 week solution. Mednick SC. Take a Nap! Change your life. Copyright © 2006-2012 Samuels C.H. Conclusions 1) Collegiate athletes would benefit from sleep education. 2) Collegiate athletes would benefit from structured sleep screening. 3) Both academic and sport performance is negatively affected by sleep disturbance. 4) This is a preventable problem! Acknowledgments Own The Podium Sport Canada Sport For Life Long Term Athlete Development University of Calgary Sport Medicine Centre Dr. Istvan Balyi Dr. Victor Lun Co-Investigator Cara Thibault CSHP Research Coordinator Dr. Jon Kolb Scientific Director Lois James Phd Dr. Willem Meeuwisse Co-Investigator Special Thanks Ms. Amy Bender, RPSGT, Phd Candidate Washington State University Sleep and Human Performance Program Dr. Sunao Uchida, MD, Phd Waseda University, Faculty of Sport Sciences Dr. Sayaka Aritake, Phd, RPSGT Waseda University, Faculty of Sport Sciences www.centreforsleep.com Copyright © 2006-2015 Samuels C.H.