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.
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Sleep & Impact on Student-Athletes