www.centreforsleep.comCopyright © 2006-2012 Samuels C.H.

Sleep, Recovery and Human Performance in Elite

Athletes

Division 1A Faculty Athletics RepresentativesAnnual Meeting

Dallas, Tx September 22, 2014

Dr. Charles Samuels, MD, CCFP, DABSMMedical Director, Centre for Sleep and Human

PerformanceClinical Assistant Professor, Faculty of Medicine,

University of CalgaryAdjunct Professor, Faculty of Kinesiology, University of

Calgary

Disclosures Research Funding:

City of Calgary, Calgary Police Service CPS Health and Human Performance Research Initiative

Canadian Olympic Committee “Own the Podium” Research Fund Sleep and Human Performance Research Program

Valeant Pharmaceutical Nabilone Neuropathic Pain and Sleep Research

Pfizer Pharmaceuticals Pregabalin Effects on Sleep in Fibromyalgia

CME Funding 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©

ObjectivesThe 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

GENETICSPHYSIOLOGY

TIME

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 Determine True Sleep Need Reduce Accumulated Sleep Debt

2) Timing Sleep Phase Environmental Factors

3) Quality Environmental Factors Sleep Disorders

Amount of Sleep1) 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) Need help with adjusting the sleep phase to

match the training schedule.

2) Larks (sleep time 10-11PM) Easier to manage with respect to early

training schedules

3) Circadian preference needs to be taken into account for competition times and countermeasures can be implemented to prepare the athlete appropriately.

Quality of Sleep1) Non-Restorative Sleep

Defined as the perception of sleep but waking un-rested and suffering daytime fatigue that cannot be explained by training volume/intensity.

2) 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

Adapted from Vila B & Samuels C 2009 (in press)

ATHLETIC PERFORMANCEHEALTH /

WELLNESSRESILIENCENUTRITION/HYDRATION SLEEP

FACTORS

TRAINING FACTORS

CIRCADIAN FACTORS

LIFE FACTORS

-Psychology

-Social

-Environmental

SLEEPCOPING

THRESHOLD

Recovery/Regeneration

Copyright © 2006-2012 Samuels C.H.

Training/Recovery Balance

Adapted from Kentta G. & Hassmen P. Sports Med 1998; 26(1):1-16.

Fig 5. Nimmo M.A. & Ekblom B. Journal of Sports Sciences 2007; 25(S1): S93-S102

Training Cycle

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

Sleep in Collegiate AthletesSayaka ARITAKE, MT, PhD, RPSGT

Sunao UCHIDA, MD, PhD

Waseda University, Faculty of Sport Sciences

Sport Psychiatry and Neuroscience laboratory

Symposium 11 June 3, 2014, 8:00 – 10:00

The Epidemiology of Sleep Behavior in Collegiate Athletes:

An Observational Survey Based Study Using the Pittsburgh Sleep Quality Index

MethodsParticipants2,200 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 questionnaireParticipants provided informed consent via the questionnaire.

Study 2

1) Sociodemographic information (age, gender, weight, height, etc.)

2) Sport names, training regime, practicing hours per week3) Sleep habits (nocturnal sleep time, bedtime, wake-up

time, napping habit) in the past month4) Sleep difficulty via a PSQI*: cut off score =5.55) Excessive daytime sleepiness (EDS) via a ESS*:

cut-off score=116) Mood status via a POMS*: T-score for 6 components

　7) Morning type or Evening type: MEQ*

Questionnaire

*PSQI: Pittsburg sleep quality index, ESS: Epworth sleepiness scale, POMS: Profile of mood status, MEQ: morning and evening questionnaire

Study 2

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

Napping habit （ % ） 78.5 79.1 76.9 0.151

Nocturnal sleep time was under 7 hours.Females had significantly shorter sleep time, higher PSQI score, ESS score, and MEQ score.

Nocturnal sleep time was under 7 hours.Females had significantly shorter sleep time, higher PSQI score, ESS score, and MEQ score.

Demographic variables and sleep related scores (n=1,111)

(in preparation)

（ h ）

Most sports slept under 7 hoursMost sports slept under 7 hours

Nocturnal sleep time in each sport

7.4hours7.4hours

(n=1,111)

(in preparation)

Sport Nocturnal Sleep time (hours)

Practice start time

Skating 4.1 4:15 amLacrosse 5.2 7:00 am

Equestrian 5.4 7:00 amRowing 5.6 6:30 am

Golf 5.7 6:30 am Sumo 7.4 6:00 pm

American football 7.2 5:30 pm

The sports that started practice early in the morning tended to have shorter sleep time. The sports that started practice early in the morning tended to have shorter sleep time.

Nocturnal sleep duration and practice start time

(in preparation)

LongLong shortshort

5.5 pt.

With sleep

difficulty

Without sleep

difficulty

PSQI score in each sportSame order as Nocturnal sleep time

(pt.)

　　　　　　　　　

　　　　　　　　　

Skating Lacrosse Equestrian Row

ing G

olf Shorinji Kem

po W

restling Judo Cheerleading Tennis Baseball G

ymnastics

Junko Baseball Volleyball H

ockey Kyudo Track &

Field Archery Cycling Sw

imm

ing W

andervogel Basketball Table Tennis Skiing H

andball Soft

Tennis Aviation Rugby Soft

ball N

ippon Kempo

Kendo W

eightlifting

Soccer Am

erican Football Shooting Sum

o

PSQI score tended to be higher in the sports that had shorter nocturnal sleep durationPSQI score tended to be higher in the sports that had shorter nocturnal sleep duration

(n=1,111)

(in preparation)

Napping habit in each sport

Most athletes tended to nap frequentlyMost athletes tended to nap frequently

longlong shortshortSame order as Nocturnal sleep time(pt.)

(in preparation)

Exercise Intensity 　We classified METs of each sport in the 4 categoriesdue to the intensity of athletic sports

METs groupⅠMETs groupⅠ METs groupⅡMETs groupⅡ METs groupⅢMETs groupⅢ METs ⅣgroupMETs Ⅳgroup

*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

(Ainsworth et al., Med Sci Sports Exerc., 2011)

p=0.329

Sleep parameters among METs categoriesp<0.001F=12.391

(pt.)

Prevalence of Napping habit（ %）

p=0.032Χ2=8.840

ESS scorep=0.710

(pt.)

*

*

(in preparation)

POMS score among 4 METs categories

p<0.01

＊

＊

＊ ＊

（ pt. ）

*p<0.001

T-A D A-H V F C

Higher POMS score in the METs category than Ⅳthe other 3 categoriesHigher POMS score in the METs category than Ⅳthe other 3 categories

T-A: Tension-Anxiety, D: Depression , A: Anger, V: Vigor, F: Fatigue, C: Confusion

(in preparation)

Subjective Sleep Quality Differences between Elite Athletes and Controls

May 31 – June 4, 2014

Minneapolis Convention Center

Amy M. Bender, MS, RPSGTWashington State University

• 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

1Fietze I, et al. (2009). Chronobiol. Int. 26(6):1249-1262.2Leeder J, et al. (2012). J. Sports Sci. 30(6):541-545.

C C

C

C

C

C

C

C

CA AA

A A

A A

A

A

05

101520253035404550

1 2 3 4 5 6 7 8 9

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.

C C

C C

A

A

A

A0

102030405060708090

100

1 2 3 4

Amy M. Bender1, Hans P.A. Van Dongen1, Winne H. Meeuwisse2,3, Charles H. Samuels4,5 1Sleep and Performance Research Center, Spokane, WA, USA; 2University of Calgary Sport Medicine Centre, Calgary, AB, Canada;

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

Subjective Sleep Quality in Elite Athletes Compared to Normal Controls on the Pittsburgh Sleep Quality Index

Introduction• Previous research examining sleep in

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).

Methods• 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.

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.

% o

f S

ub

ject

s

Very Good Fairly Good Fairly Bad Very Bad

“During the past month, how would you rate your sleep quality overall?”

CC

CC

C CC

C C

AA

A

A

A

A

A

A

A

0102030405060708090

100

1 2 3 4 5 6 7 8 9

% o

f S

ub

ject

s

Wak

e up

in m

iddl

e of

ni

ght/e

arly

mor

ning

Can

not b

reat

he

com

fort

ably

Fee

l too

col

d

Hav

e to

get

up

to

use

bath

room

Cou

gh o

r sn

ore

loud

ly

Hav

e pa

in

Fee

l too

hot

Oth

er

Had

bad

dre

ams

• 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.

Discussion• 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.

% o

f S

ub

ject

s

←Eveningness Morningness→

Figure 2: Self-reported sleep disturbance responses in controls (C) and elite athletes (A).

Figure 3: Distribution of binned morningness scores in controls (C) and elite athletes (A).

0

10

20

30

40

50

1 2 3 4 5 6 7 8

Subjective Sleep Quality in Elite Athletes

0-1 2-3 4-5 6-7 8-9 14-2112-1310-11

Combined datasets of the National Sport School and Bobsleigh Canada Skeleton team adapted from Samuels C., Neurol Clin 26 (2008)

% o

f A

thle

tes

PSQI Global Scores

N=68

• 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 (Questionnaires)

• 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

Methods (Subjects)

0

10

20

30

40

50

60

0-1 2-3 4-5 6-7 8-9 10-11 12-13 14-15 16-21

% o

f S

ubje

cts

Controls

Athletes

Results – PSQI Global Scores

Controls (2.6 ± 1.3) vs. Athletes (5.0 ± 2.6)

p<0.01

0

20

40

60

80

100

Very Good Fairly Good

Fairly Bad Very Bad

% o

f Sub

ject

s

Controls

Athletes

0

20

40

60

80

100

Not in past month

<1 time per week

1-2 times per week

3+ times per week

Results – Sleep Quality and Sleep Latency

p=0.01

How would you rate your sleep quality overall?

How often have you had trouble sleeping because you cannot get to

sleep within 30 minutes?

p<0.01

ControlsAthletes

How would you rate your

sleep quality overall?

0 20 40 60 80 100% of Subjects

Controls

Athletes

Results – Sleep Disturbance Reasons

p<0.01

Wake up in middle of night or early morning

Cannot breathe comfortably

Had bad dreams

Feel too cold

Have to get up to use bathroom

Cough or snore loudly

Have pain

Feel too hot

Other

% of Subjects

% of SubJects

ControlsAthletes

0

20

40

60

80

100

Not in past month

<1 time per week

1-2 times per week

3+ times per week

% o

f S

ubje

cts

Controls

Athletes

Results – Sleep Disturbance Frequency

p<0.01

Results – Daytime Dysfunction

p<0.01

How often have you had trouble staying awake while driving, eating meals, or engaging in

social activity?

How much of a problem has it been for you to keep up enough enthusiasm to get things done?

0

20

40

60

80

100

Not in past month

<1 time per week

1-2 times per week

3+ times per week

% o

f Sub

ject

s

0

20

40

60

80

100

No problem A slight problem

Somewhat of a

problem

A very big problem

ControlsAthletes

• No significant differences for self-reported time in bed, sleep duration, sleep efficiency, sleep latency, use of sleep medication, habitual bedtimes and wake times

Results for Other Sleep Parameters

TIB TST SleepLatency

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

Self-Reported Sleep Parameters

0

10

20

30

40

50

1 2 3 4 5 6 7 8 9

% o

f S

ubje

cts

M/E Scores

Controls

Athletes

Results – Morningness/Eveningness

←Eveningness Morningness→

p<0.01

0

5

10

15

20

10 15 20 25 30

PS

QI

Glo

ba

l S

co

res

Athlete Morningness Eveningness Scores

←Eveningness Morningness→

p<0.01

r =-0.35

Results – Correlation between Morningness/Eveningness with PSQI scores

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, Canada1; Faculty of Medicine, University of Calgary, Calgary, AB, Canada2,

University of Calgary, Sport Medicine centre, Calgary, AB, Canada3; Faculty of Kinesiology, University of Calgary, Calgary, AB, Canada4Methods Continued

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.

Results ContinuedPhase 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.

Figure 2. ASSQ: Proposed scoring system, clinical outcomes and referral decision algorithm.

ObjectiveCurrent 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).MethodsA 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.

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.

Background/RationaleThere 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

Figure 1. ASSQ Development phases, methods , process and outcomes algorithm.

ResultsPhase 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.

Future DirectionsThe 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.References1.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.

Sport Total Sleep TimeMean 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)

ASSQ by Sport: Mean (SD) Total Sleep Time, Sleep Difficulty Score

Copyright © 2006-2012 Samuels C.H.

Sport Total Sleep TimeMean 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)

ASSQ by Sport: Mean (SD) Total Sleep Time, Sleep Difficulty Score (Continued…)

Copyright © 2006-2012 Samuels C.H.

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).

Data Collected from the ASSQ

Copyright © 2006-2012 Samuels C.H.

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.

Data Collected from the ASSQ

Copyright © 2006-2012 Samuels C.H.

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).

Data Collected from the ASSQ

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.

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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?

Discussion

Athlete Sleep Screening

Remote Sleep Screening

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Canadian Sport Centre Network

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ASSQ ScreeningResults

Follow-up

Managing Sleep, Circadian Factors,

Training and Performance

Sleep Management Sleep Debt

How much sleep do you need? Sleep Quality

Is your sleep restorative? Sleep Phase

When do you fall asleep easily and wake up spontaneously?

Sleep Hygiene

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Training and Sleep

1) Make a plan and stick to it!1) Determine your total sleep need2) Determine your optimum sleep phase3) Adjust your training around the

foundation of sleep, rest and recovery.4) Use strategic napping to minimize

sleep debt.5) Stick to a routine.

Recovery

1) Rest: Planned rest to reduce arousal. Eyes Closed and Slow, Deep Breathing

2) Napping: Strategic napping reduces the accumulation of sleep debt. 20-30 minutes at the circadian lows (2-4 PM)

3) 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

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Recovery1. 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!

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Athlete’s Bottom Line1. 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 Recovery4. If you get what you need, THAT IS

AS GOOD AS IT GETS!

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Coaches Bottom LineIf 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!!

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Light Therapy

Recommended Reading

Jacobs GD. Say Good Night to Insomnia: the 6 week solution.

Mednick SC. Take a Nap! Change your life.

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Conclusions1) 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!

Cara Thibault

Dr. Victor LunCo-

Investigator

Dr. Istvan Balyi

Dr. Jon KolbScientific Director

Own The Podium

University of Calgary Sport Medicine Centre

Sport Canada Sport For Life Long Term Athlete Development

Acknowledgments

Dr. Willem Meeuwisse

Co-Investigator

CSHPResearch

Coordinator

Lois James Phd

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

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