Content uploaded by Alexa Jenny Chandler
Author content
All content in this area was uploaded by Alexa Jenny Chandler on Oct 07, 2021
Content may be subject to copyright.
Downloaded from http://journals.lww.com/acsm-tj by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywCX1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC1y0abggQZXdtwnfKZBYtws= on 09/22/2021
Downloadedfromhttp://journals.lww.com/acsm-tj by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywCX1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC1y0abggQZXdtwnfKZBYtws= on 09/22/2021
The Impacts of COVID-19 on Collegiate
Student-Athlete Training, Health, and Well-Being
Alexa J. Chandler,
1
Michelle A. Arent,
2
Harry P. Cintineo,
1
Toni M. Torres-McGehee,
1
Zachary K. Winkelmann,
1
and Shawn M. Arent
1
The coronavirus 2019 (COVID-19) pandemic caused by the
severe acute respiratory syndrome coronavirus 2 virus
(SARS-CoV-2) incited a national emergency (1) that forced
colleges and universities in the United
States to close their doors in March 2020
(2). These sudden university closures left
minimal time for sport coaches, strength
and conditioning (S&C) coaches, and other
support staff to create and disseminate
feasible at-home training programs for
student-athletes. Nationwide shutdowns
further complicated athletes’training at
home by limiting access to adequate exercise
equipment and space required for training.
As this is the first time all sports have come
to a halt since the 1940s, no data exist
regarding student-athlete sport training
regimens, nutritional habits, and mental
health status during times of limited or
no access to adequate training equipment
and/or resources (3). Therefore, research is
warranted to investigate the effect extended
time away from typical training routines
has on collegiate student-athlete sport
training habits and overall well-being.
Collegiate student-athletes’sport train-
ing and competition seasons typically fol-
low a set schedule with routine access to
school-based support including sport coaches
responsible for on-field sport-specific training,
S&C coaches responsible for general per-
formance development, athletic trainers
in charge of injury and rehabilitation man-
agement, nutritional support for dietary
needs, and access to adequate exercise training equipment.
Brief periods away from these resources generally occur in 2-
to 6-wk blocks over semester breaks. Lack of training during
these times can result in detraining evidenced by decreased aer-
obic capacity, speed, and muscular power (4). Large increases
in acute workloads in general or after periods of detraining
increase the risk of both overuse and traumatic injuries (5,6).
For example, higher injury rates are often seen among
collegiate athletes during preseason when training volume
markedly increases (7). Return to sport after COVID-19
lockdowns may exaggerate this effect, similar to the increased
tendon injury occurrence seen in 2011 after the National
Football League’s 19-week lockout (8). More recently, a case
study following a professional soccer team through the fall
1
Department of Exercise Science, University of South Carolina, Columbia, SC;
and
2
Department of Health Promotion, Education, and Behavior, University of
South Carolina, Columbia, SC
Address for correspondence: Shawn M. Arent, Ph.D., C.S.C.S.*D., F.I.S.S.N.,
F.A.C.S.M., F.N.A.K., University of South Carolina, 921 Assembly St., Columbia,
SC 29208 (E-mail: sarent@mailbox.sc.edu).
2379-286 8/0604/e000173
Translational Journal of the ACSM
Copyright © 2021 by the American College of Sports Medicine
ABSTRACT
Introduction: The purpose of this study was to determine the impact of COVID-19
and stay-at-home (SAH) orders on collegiate student-athletes’training, nutrition,
sleep habits, and mental health and to identify disparities between sexes and com-
petitive divisions. Methods: Collegiate student-athletes (n= 401; age, 20 ± 2 yr)
completed an 84-question anonymous survey regarding demographics, sport/
exercise training, nutrition, sleep habits, and mental health. Response frequencies
were calculated for each question, and χ
2
analyses were used to determine statis-
tical significance (α=0.05).Results: Although 80.7% of respondents indicated
training for their sport, only 38.7% could fully perform their training programs. More
D1 versus D3 athletes reported they could perform their training plan as written
(D1: 44.4% [n= 83] vs D3: 27.3% [n=50];P< 0.01), but there were no differences
between sexes. Cardiovascular exercise was the most common mode (87.5%)
followed by resistance exercise (78.4%). Although there were no differences for
cardiovascular exercise, moremales (87.5%) than females (74.8%) indicated resis-
tance training (P< 0.01). Average number of meals consumed per day remained
similar before and during SAH, but females reported consuming less food and per-
ceived increased healthfulness of their diets. Although most athletes did not use
nutritional supplements, rates were higher among D3 and females. Respondents
reported longer sleep durations but increased sleep disturbances, negative psy-
chological states, and overall concerns during SAH. Maintaining fitness and
sport-specific skills (~70.0%) were the most common concerns. In addition,
~60.6% of females and 41.9% of males indicated increased mental health con-
cerns. Conclusions: Our findings suggest that while attempting to be diligent with
training during SAH, many student-athletes reported difficulties regarding limited
equipment, motivation, and mental health concerns such as heightened anxiety.
Many of these difficulties were division- and sex-specific. Discussions between
coaches and student-athletes regarding SAH training and mental stressors may
aid in determining student-athletes’readiness to return to sport.
http://www.acsm-tj.org Translational Journal of the ACSM 1
Original Investigation
Copyright © 2021 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
2020 season found athletes were 3.12more likely to sustain
an injury after lockdown (9). Furthermore, 17.3% of these
injuries occurred before or during their initial match of the
season (9). Although collegiate coaches likely attempted to
provide home-based exercise programs aimed at maintaining
fitness and physical skills during the school closures, adherence
to these programs may be varied because of limited equipment
and decreased motivation (4,10).
In addition to exercise and sport performance, forced lock-
down and university closures present challenges regarding nu-
trition, sleep, and mental health. For instance, without on-campus
dining services, many student-athletes no longer have a reliable
source of food (2) as roughly 30% of student-athletes report
facing food insecurity (11). Suspended team activities and
associated social gatherings led to forced isolation from
support systems (i.e., teammates, coaches) creating growing
concern surrounding mental health, specifically anxiety and
depressive symptoms (12). In general, student-athletes are
less likely to suffer from depressive and anxiety symptoms
than nonathletes (13) because, in part, of positive social
relationships and increased self-esteem fostered through
sport participation (13,14). Despite this, 14%–33% of
student-athletes report depressive symptoms while in college
(15,16). These rates may be increased after forced isolation
from teammates and sport cessation due to stay-at-home (SAH)
orders. A recent survey among college students, including
nonathletes, found 60% reported increased stress levels, and
84% reported dramatic changes to sleep patterns during
SAH (17). Assessing the student-athletes’psychological distress
levels before and upon return to campus may further aid coaches
and S&C staff in successfully reintegrating student-athletes
back to team training and competition.
Knowledge surrounding student-athletes’training/nutrition
habits and mental health during SAH may be useful for coaches
when developing at-home training programs and return-to-play
guidelines for future extended training breaks. Therefore, the pur-
pose of this study was to determine the impact of COVID-19 and
SAH orders on collegiate student-athletes’training, nutrition,
sleep habits, and mental health and to identify disparities between
sexes and competitive divisions. It was hypothesized that
student-athletes would report training discontinuation due to
factors including equipment access, training support, and mo-
tivation during SAH. This research may help to determine
student-athlete health and wellness practices during the cur-
rent COVID-19 pandemic and offer recommendations for
safely transitioning student-athletes back to school-based
sport training and competitions following extended breaks
from supervised training.
METHODS
Subjects
Student-athletes enrolled in a college/university competing
in the National Collegiate Athletic Association (NCAA) in
the United States at the Division I (D1), II (D2), or III (D3)
levels were invited to take part in an anonymous electronicsur-
vey. Student-athletes were eligible to participate in the survey if
they were at least 18 years old and planning to participate in an
NCAA collegiate sport in the 2020–2021 academic year. A to-
tal of 494 student-athletes initially responded to the survey, of
which 447 gave informed consent to participate. From this
sample, 11 of the respondents were excluded because of
ineligibility based on lack of participation in an NCAA sport.
An additional 35 respondents did not complete any questions
after giving informed consent and were subsequently excluded.
The final sample size was 401 student-athletes (males:n=136;
females: n= 260; did not specify: n= 5) with a mean ± SD age
of 20 ± 2 yr. Of these 401 respondents, 275 completed the
questionnaire in its entirety, whereas 126 did not.
Survey Development
The Sport Science Lab at the University of South Carolina
developed the survey in conjunction with certified athletic
trainers and registered dietitians from the university. The
survey (Qualtrics, Inc., Provo, UT) began with items assessing
participation eligibility followed by an informed consent
statement. There were 84 questions targeted at demographic
information (n= 4), living conditions (n=2),COVID-19
diagnosis or COVID-19–like symptoms (n= 2), sport training
(n= 34), nutrition and supplement habits (n= 12), sleep
habits (n=6),andmentalhealth(n= 24).
Question structure included Likert scales, open-ended, mul-
tiple choice, and fill-in-the-blank. Training-focused questions
asked about frequency, intensity, and duration of cardiovascu-
lar exercise, resistance exercise, sport-specific drills, and flexi-
bility training during the SAH period. Questions regarding
nutrition, sleep, and mental health were adapted from previ-
ously validated questionnaires including the State Anxiety In-
ventory (18), Multicomponent Training Distress Scale (19),
and the Pittsburg Sleep Quality Index (20) to determine how
these relevant factors changed during the SAH period relative
to the pre-SAH period. Questions that best targeted the aims
of this project were selected at the researcher’s discretion, as
opposed to entire questionnaires, in an attempt to minimize
time required by participants to complete the survey. The
survey was approved by the University of South Carolina
Institutional Review Board and was pilot tested by former
collegiate student-athletes for relevance, readability, and time
commitment to establish content validity before dissemination.
Procedures
Survey promotion and distribution to eligible student-athletes
occurred via snowball sampling through word-of-mouth, e-mail,
and social media. Colleagues and athletic staff at universities were
asked to share the anonymous electronic survey link with their
student-athletes at their institution. All athletic departments and
coaches who were contacted to aid in survey dissemination were
informed student-athlete responses would remain anonymous.
The survey took approximately 15 min to complete and was
open from May 27, 2020, to July 25, 2020.
Data Analysis
Individual respondents were screened and excluded based
on inclusion criteria. Response frequencies were assessed for
each question, and sample sizes used to determine frequencies
were calculated from completed answers on a question-by-
question basis. χ
2
analyses with Yates’continuity correction
were performed to determine differences in frequencies be-
tween sexes and between competitive divisions with α
level = 0.05 to determine statistical significance. Analyses by
sex included response frequencies of males (n= 136) and fe-
males (n= 260); those who responded, “prefer not to say”
(n= 5) were excluded from analyses as a function of sex.
2Volume 6 •Number 4 •Fall 2021 Effects of COVID-19 on Student-Athletes
Copyright © 2021 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
Analyses by division included response frequencies from D1
(n=187)orD3(n= 183) respondents only; D2 respondents
were excluded from by-division analyses because of a small
sample size (n= 12) but were included in all other analyses.
All statistical analyses were performed using the package
“funModeling”(version 1.9.4) in R (version 4.0.2). For indi-
vidual questions, data are presented as frequency percentages
and as mean frequency percentage when questions regarding
the same topics were assessed together.
RESULTS
Demographics
Respondents represented male (n= 136) and female (n= 260)
NCAA student-athletes from 18 different sports at the D1, D2,
and D3 levels. Half of respondents (50%; n= 187) indicated
their sport was in-season at the time of the lockdown, whereas
the other half indicated they were in the off-season. Most re-
spondents indicated they were living at home with their parents
(61.9%; n= 237) or in an apartment/house with roommates
(20.6%; n= 79) for the duration of SAH. Less than 10% of re-
spondents reported being diagnosed with or experiencing symp-
toms of COVID-19 (9.0%; n= 28). Respondent demographics
are displayed in Table 1.
Exercise and Sport Training
TRAINING PROGRAMS
Most respondents indicated they were currently training for
their sport (80.7%; n= 301), and of these, 64.6% (n=239)re-
sponded they were following a specific training program.
When asked where they obtained the training program, the
most common response was “my S&C coach at school”
followed by “Imadeitonmyown”and “sport coach”
(Table 2). When asked if they had the appropriate training
equipment to perform their program, 38.7% (n=137)ofall
respondents stated they could perform their plan as written
without any modifications and 15.0% (n= 53) stated they
could not perform the training plan they were given, even with
modifications.
Females were more likely than males to receive their train-
ing plan from their sport coach as opposed to S&C coach.
However, there were no differences between males and females
in regard to ability to perform the given training program, as
44.6% of males (n= 50) and 36.1% of females (n= 86) re-
ported they could fully perform their training programs
(χ
2
= 1.98, P= 0.16), and 13.4% of males (n= 15) and
16.0% of females (n= 38) reported being unable to perform
their program at all (χ
2
=0.22,P= 0.64). Along with females,
D3 athletes were more likely to receive training programs from
sport coaches or make a plan for themselves, whereas D1
TABLE 1.
Respondent Demographics.
All
a
Male Female
Race
b
(n=401) (n=136) (n= 260)
White 87.0% 83.1% 90.0%
Black/African
American
8.0% 11.0% 6.2%
Native American/
Alaska Native
0.7% 0.7% 0.8%
Asian 3.7% 4.4% 3.1%
Native Hawaiian/
Pacific Islander
1.0% 1.5% 0.8%
Other 5.5% 6.6% 5.0%
School year
2020–2021
(n=397) (n=133) (n= 260)
Freshman 7.6% 7.5% 7.7%
Sophomore 25.9% 24.1% 27.3%
Junior 32.5% 35.3% 30.8%
Senior 32.2% 29.3% 33.5%
Graduate 1.8% 3.8% 0.8%
Competitive division (n=378) (n=125) (n= 247)
Division I 49.0% 55.6% 46.0%
Division II 3.1% 3.2% 3.2%
Division III 47.9% 41.3% 50.8%
Sport
b
(n=391) (n=130) (n= 257)
Soccer 22.3% 18.5% 24.5%
XCountry/track
and field
13.3% 10.0% 14.8%
Swimming
and diving
12.5% 10.0% 13.6%
Football 7.2% 20.8% 0.0%
Baseball 6.6% 20.0% 0.0%
Basketball 5.6% 4.6% 6.2%
Softball 5.4% 0.0% 8.2%
Vo l l ey b a l l / b e ac h
volleyba ll
6.9% 1.5% 9.7%
Field hockey 4.6% 0.0% 7.0%
Lacrosse 4.6% 3.1% 5.1%
Rowing 3.6% 0.8% 5.1%
Equestrian 2.6% 0.0% 3.9%
Wrestling 2.6% 6.9% 0.4%
TABLE 1.
(Continued)
All
a
Male Female
Other
c
4.9% 3.8% 5.4%
Numbers of total, males, and females are listed for each question.
a
Five respondents did not specify sex and are only included in “All.”
b
Question for which respondents could select more than one response.
c
Other sports (<2% reported participation) include golf, tennis, gym-
nastics, and cycling.
http://www.acsm-tj.org Translational Journal of the ACSM 3
Copyright © 2021 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
athletes were more likely to receive training programs from
S&C coaches (Table 2). However, almost twice as many D1
versus D3 athletes could perform their training plan as written
(D1: 44.4% [n= 83] vs D3: 27.3% [n= 50]; χ
2
= 12.88;
P= 0.0003), but the amount of athletes who could not perform
their program was similar between divisions (D1: 11.8%
[n= 22] vs D3: 16.9% [n= 31]; χ
2
=1.37,P= 0.24).
TRAINING HABITS
Respondents were asked to provide the type, average fre-
quency, duration, and rating of perceived exertion of their ex-
ercise sessions. Cardiovascular exercise was the most reported
exercise type, with 87.4% (n= 299) of respondents selecting
this option. Of those performing cardiovascular exercise,
61.8% (n= 194) reported performing 3–5 sessions per week,
with most (69.7%; n= 223) reporting <45-min session dura-
tion. Only 10.7% (n= 35) of respondents reported sessions
>60 min. Running was the most common modality (83.1%;
n= 289) followed by biking (38.2%; n=133)and
high-intensity interval training (37.9%; n= 132). Other mo-
dalities reported included jump rope, hiking, circuit training,
and sprint workouts. Resistance exercise was the second most
common exercise type (78.4%; n= 210), with most respon-
dents (72.7%; n= 210) performing between 2 and 4 d·wk
−1
for 30–45 min (28.0%; n= 167) or >45 min (39.1%;
n= 127). Resistance bands and dumbbells were the most com-
mon resistance exercise equipment used, with 60.5% (resis-
tance bands: n= 210; dumbbells: n= 210) of respondents
using these modalities. Other exercise types being performed
included sport-specific drills (57.0%; n= 195) and yoga/
stretching routines (48.8%; n= 167). Only 1.2% (n=4)ofre-
spondents indicated they were currently performing physical
therapy exercises. Yoga/stretching and sport-specific drill ses-
sions were mostly ≤30 min (78.4% [n= 189] and 37.0%
[n= 87], respectively). However, 22.6% (n= 53) of respon-
dents reported engaging in sport-specific drill practice sessions
>60 min. Cardiovascular and resistance exercise session inten-
sities were “somewhat hard”or “hard”(69.3% [n=210]and
74.4% [n= 206], respectively), whereas yoga/stretching ses-
sion was “easy”or “very easy”(60.2%; n= 137). There was
more variation in the sport-specific drill activity intensity, with
22.4% (n= 48) of respondents rating their intensity as “easy,”
36.4% (n=78)as“somewhat hard,”and 22.9% (n=49)as
“hard.”Despite this, most respondents (64.7%; n=209)indi-
cated feeling their training was “less effective”as opposed to
“more effective”or “the same”during SAH compared with
at school.
Cardiovascular exercise participation was similar between
sexes (males: 81.7% [n= 85]; females: 89.7% [n= 210];
χ
2
=3.47;P= 0.062), but more males (87.5%; n= 91) than fe-
males (74.8%; n= 175) were performing resistance exercise
(χ
2
= 17.10; P= 0.0001). The majority of females (64.1%;
n= 127) reported resistance exercise sessions <45 min,
whereas the majority of males (58.5%; n= 55) reported ses-
sions >45 min. A larger percentage of males than females re-
ported using dumbbells (males: 79.4% [n= 85]; females:
58.5% [n=138];χ
2
= 13.32, P= 0.0003) and barbells (males:
54.2% [n= 58]; females: 26.3% [n= 62]; χ
2
= 24.04,
P< 0.00001), but there were no differences in kettlebell (males:
31.8% [n= 34]; females: 24.6% [n= 58]) or resistance band
usage (males: 57.9% [n= 62]; female: 61.9% [n= 146]) be-
tween sexes. The only divisional differences in training habits
were in resistance exercise equipment, as more D1 athletes
used dumbbells (D1: 66.8% [n= 125] vs D3: 53.0%
[n=97];χ
2
=13.20,P= 0.0003), kettlebells (D1: 32.1%
[n= 60] vs D3: 16.4% [n= 30]; χ
2
=14.45,P= 0.0001),
and barbells (D1: 42.3% [n= 79] vs D3: 20.2% [n= 37];
χ
2
= 24.78, P< 0.0001).
Nutrition/Supplements
Respondents reported subjective feelings about the health-
fulness of their diet compared with before SAH, as well as
changes in dietary patterns. Reported meal patterns were sim-
ilar from before to during SAH, with most athletes reporting
consuming 2–3 meals per day (pre: 75.2% [n= 236]; during:
79.6% [n= 249]). When analyzing meal frequency by sex,
~5% of females and ~3% of males reported consuming fewer
meals during SAH compared with at school. However, when
asked about food quantity consumed during SAH compared
with at school, more females reported decreased food intake
(female: 43.8% vs male: χ
2
= 10.24, P= 0.001) but also per-
ceived their dietary habits as healthier during SAH (females:
38.7% vs males: χ
2
=7.01;P=0.008).
TABLE 2.
Training Plan Source.
All
(n=354)
Male
(n= 112)
Female
(n= 238) χ
2
(P-Value) D1 (n=172) D3(n=170) χ
2
(P-Value)
S&C coach
at school
52.0% 46.4% 53.8% 2.14 (0.14) 61.0%** 44.7% 8.52 (0.004)
I made iton my own 41.0% 46.4% 37.8% 2.00 (0.16) 32.6%** 48.8% 9.36 (0.002)
Sport coach 30.2% 18.8% 35.7%** 9.59 (0.002) 19.8%*** 38.8% 14.10 (<0.001)
Coach at home 12.7% 12.5% 13.0% <1.00 (1.00) 18.0%* 8.2% 6.34 (0.01)
Percentage of student-athletes who recieved their training plan from each source during SAH. Respondents selected all responses that applied. Significant
differences between sexes/divisions are denoted by asterisks.
*P<0.05.
**P<0.01.
***P< 0.001.
4Volume 6 •Number 4 •Fall 2021 Effects of COVID-19 on Student-Athletes
Copyright © 2021 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
Overall supplement usage and changes in supplement usage
are shown in Table 3. Most athletes reported “do not use”for
each supplement, and of those who did use supplements, most
reported using the supplement before and continuing during
SAH. More females than males reported never using supple-
ments (~61.6% vs 42.4%, respectively), apart from multivita-
mins (females: 47.7% vs males: 39.7%; P= 0.16). However,
there were no significant differences between respondents
who started versus stopped supplement usage during SAH by
sex. Similar patterns were seen for divisional analyses, as more
D3 (~62.2%) than D1 (~42.5%) athletes reported never using
supplements, except for creatine, but a similar percentage of
athletes in both divisions reported either stopping or starting
most supplements during SAH.
Sleep Habits and Mental Health
Respondents increased sleep duration during SAH, as 9.1%
(n= 28) of respondents reported sleeping <7 h during SAH
compared with 29.6% (n= 91) who reported <7 h before
SAH (χ
2
= 33.35, P< 0.001). In addition, the number of re-
spondents who reported >9 h of sleep per night during SAH
was higher than those who reported this duration before
SAH (pre: 2.9% [n= 9]; during: 11.7% [n= 36]; χ
2
= 16.2,
P< 0.001). There were no changes in respondents reporting
TABLE 3.
Supplement Usage Patterns.
Male Female χ
2
(P-Value) D1 D3 χ
2
(P-Value)
Protein powder
Never 23.50% 45.8%*** 22.32 (<0.001) 28.30% 53.0%*** 17.79 (<0.001)
Stopped 16.20% 6.5%** 0.89 (0.34) 12.30% 8.70% 8.29 (0.004)
Started 5.90% 11.20% 1.35 (0.25) 11.80% 7.70% 2.34 (0.13)
Omega-3/fish oil
Never 56.60% 70.4%** 13.4 (<0.001) 59.40% 77.6%*** 6.91 (0.009)
Stopped 4.40% 1.20% 3.97 (0.046) 4.30% 0.55%* 2.93 (0.09)
Started 3.70% 3.80% 1.02 (0.31) 5.30% 2.70% <0.001 (1.00)
Multivitamin
Never 39.70% 47.70% 14.76 (<0.001) 36.90% 57.4%*** 1.99 (0.16)
Stopped 10.30% 4.60% 2.56 (0.11) 9.10% 4.40% 3.81 (0.051)
Started 5.10% 6.90% 4.06 (0.044) 9.60% 3.8%* 1.49 (0.64)
Vitam in C
Never 41.90% 53.1%* 9.13 (0.003) 43.3%** 59.60% 4.02 (0.045)
Stopped 7.40% 4.60% 0.37 (0.54) 7.00% 4.90% 0.81 (0.37)
Started 2.20% 5.20% 1.35 (0.25) 6.40% 3.30% 1.49 (0.22)
Vitam in D
Never 39.70% 58.5%*** 12.68 (<0.001) 44.40% 63.4%*** 11.85 (<0.001)
Stopped 6.60% 4.20% 0.72 (0.40) 7.00% 4.40% 0.62 (0.43)
Started 3.70% 4.60% 0.20 (0.65) 5.30% 3.80% 0.03 (0.88)
Creatine
Never 50.00% 80.4%*** 2.31 (0.13) 69.50% 77.10% 37.79 (<0.001)
Stopped 6.60% 0.78%** 0.082 (0.77) 3.20% 2.20% 9.24 (0.002)
Started 3.68% 0.78% 2.24 (0.13) 3.20% 1.20% 2.83 (0.092)
Significant differences between sexes/divisions are denoted by asterisks.
*P<0.05.
**P<0.01.
***P< 0.001.
http://www.acsm-tj.org Translational Journal of the ACSM 5
Copyright © 2021 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
sleeping 7–9 h per night (pre: 67.4% [n= 207]; during: 79.2%
[n=244];χ
2
=3.04,P= 0.081). Despite increased sleep dura-
tion, ~24.6% of respondents experienced sleep disturbances
during, compared with ~5.7% before, SAH (Fig. 1). Although
a similar percentage of respondents from each sex indicated
experiencing these disruptions before SAH (females: ~7.4%
vs males: ~9.0%), a greater percentage of females experienced
lack of sleep onset within 30 min of going to bed (females:
36.7% [n= 77] vs males: 24.2%, [n= 23]; χ
2
=4.06,
P= 0.045), and difficulty sleeping due to racing thoughts/
anxiety (females: 30.5% [n= 64]; males: 15.8% [n= 15];
χ
2
=6.61;P= 0.01) during SAH. There were no differences
in sleep aid/medication usage (females: 11.0% [n= 23]; males:
12.6% [n=12];χ
2
=0.053;P= 0.82) or those who indicated
“waking up in the middle of the night/really early in the morn-
ing”(females: 27.0% [n= 61]; males: 21.6% [n= 24];
χ
2
= 0.30; P= 0.59) between sexes during SAH. Overall,
~20.8% of D3 and ~17.5 of D1 student-athletes reported onset
of sleep disruptions during SAH, but there were no significant dif-
ferences between divisions for any sleep disturbances (P> 0.10).
The percentage of respondents who reported receiving sup-
port from a mental healthprovider before SAH was not signif-
icantly higher than those who reported receiving support
during SAH (pre: 15.6% [n= 49] vs during: 11.4% [n= 36];
χ
2
=2.37;P=0.12).However,morethanhalfofrespondents
reported feeling “alotless”or “less”motivated to train (53.2%;
n= 166) and reported increased feelings of stress (71.3%;
n= 223), general concern (69.2%; n= 216), lack of focus
(62.5%; n= 195), and tension (50.6%; n= 158) during
SAH. More females indicated increased feelings of general
concern, indecisiveness, stress, tension, lack of focus, and un-
happiness than did males (Fig. 2A). In addition, significantly
more females reported decreased motivation to train during
SAH (females: 58.7% [n= 125] vs males: 40.2% [n= 39];
χ
2
=8.16;P= 0.004). When asked about the psychological impact
of continuing to train during SAH, 43.9% (n= 109) of females in-
dicated their training increased their stress levels in contrast to
26.2% (n= 26) of males. Despite the reported increased stress
levels, 69.1% (n= 150) of females and 67.7% (n= 67) of males re-
ported that continuing to train increased their feelings of well-
being. Although the majority of males indicated they enjoyed their
training during the SAH period (62.3%; n= 61), only 49.1%
(n= 107) of females indicated the same. In fact, 41.8% (n=91)
of females stated they did “not really”or did “notatall”enjoy
training during SAH compared with 27.6% (n= 27) of males. In
terms of division, significantly more D3 respondents reported de-
creased motivation to train (D1: 46.4% [n= 71] vs D3: 59.6%
[n=90];χ
2
=4.80;P= 0.03) along with increased feelings
of general concern, indecisiveness, stress, tension, lack of fo-
cus, and unhappiness (Fig. 2B). In addition, significantly more
D1 respondents reported increased feelings of calmness, relax-
ation, and happiness compared with D3 during SAH.
Figure 1: Visual depiction of reported sleep disturbances for all respondents (n= 307). Graph displays percent respondents who indicated “only before
SAH”and “only during SAH.”Respondents who answered “never”and “both before and during SAH”are not displayed.
6Volume 6 •Number 4 •Fall 2021 Effects of COVID-19 on Student-Athletes
Copyright © 2021 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
Lastly, when asked about their overall concerns regarding
this interruption to training, student-athletes indicated be-
ing most concerned about overall fitness levels (71.0%;
n= 215), sport-specific skills (69.0%; n=209),andstaying
healthy while training at home (68.6%; n= 208). Overall,
56.4% (n= 171) of respondents stated they were concerned
about social isolation and 53.8% (n= 163) were concerned
about mental health. Significantly more females reported
concerns regarding fitness (male: 57.0% [n=53]vsfemale:
77.4% [n= 161]; χ
2
=8.88;P= 0.003), sport-specific
training (male: 54.8% [n= 51] vs female: 75.0%
[n= 156]; χ
2
= 14.43; P= 0.0001), staying healthy overall
(male: 67.5% [n= 54] vs female: 84.4% [n=152];
χ
2
= 8.66; P= 0.003), and mental health (male: 35.5%
[n= 33] vs female: 61.5% [n= 128]; χ
2
= 13.70,
P= 0.0002) compared with males. There were no differences
in concerns between divisions (P> 0.05) except in regard to
scholarships, for which significantly more D1 (35.3%;
n= 53) than D3 (20.8%; n= 30) respondents indicated feeling
concerned (χ
2
=10.3;P=0.001.
Figure 2: A–B, Increases in psychological states during SAH compared with before SAH for (A) males (n=97)vsfemales(n= 214), and (B) D1 (n= 153)
vs D3 (n= 151). Significant differences between divisions and sexes are denoted by *P<0.05,**P< 0.01, and ***P< 0.001.
http://www.acsm-tj.org Translational Journal of the ACSM 7
Copyright © 2021 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
DISCUSSION
This study sought to investigate the impact SAH orders,
resulting from the COVID-19 pandemic, had on training, nu-
trition, sleep habits, and mental health of NCAA collegiate
student-athletes. Although restrictions varied across the
United States, most student-athletes performed unsupervised
at-home training for at least 11–16 weeks before facilities, in-
cluding universities and public gyms, reopened. Surprisingly,
the majority of survey respondents reported training for their
sport during SAH, and over half were following specific train-
ing programs. When analyzed by competitive division, ~15%
more D1 student-athletes received a training plan from an
S&C coach at school compared with D3 student-athletes,
who were twice as likely to receive a program from their sport
coach. In addition, D3 student-athletes had the highest likeli-
hood of designing their own training program. These differ-
ences likely reflect the available resources and priorities at
D1 compared with D3 schools. Data from the NCAA show
that, although the numbers of student-athletes competing in
D1 and D3 are similar (182,658 vs. 194,487), there are far
more D1 S&C coaches compared with those at the D3 level
(D1: 1755; D3: 457) resulting in D3 S&C coaches being re-
sponsible for four times more student-athletes than D1 S&C
coaches (D1: 104 student-athletes per S&C coach; D3: 426
student-athletes per S&C coach) (21). In addition, D1
student-athletes were most likely to report working with an
S&C coach/trainer while at home, which may be a result of
the emphasis placed on athletics between divisions in terms
of scholarships (22).
Ensuring student-athletes can physically perform their pre-
scribed at-home training program is essential for fitness main-
tenance and injury risk mitigation upon return to sport (23).
Although most participants in the current survey indicated
they could perform their prescribed program with little or no
modifications, there were large discrepancies between
divisions with almost twice as many D1 student-athletes
reporting being able to complete their training program
without modifications. Although the differences were smaller
when comparing sexes (males: 44.6%; females: 36.1%), this
finding supports those from an NCAA survey in which 72%
of student-athletes cited “access to appropriate equipment”as
a barrier to training at home (10). One idea that may serve as
“best-practice”going forward would be for the strength coach
to survey each athlete to obtain a better understanding of the
equipment each person has access to and then modify
individual training programs based on these results.
At-home exercise training recommendations during SAH
include both cardiovascular and resistance exercise, as well
as flexibility and plyometrics (24), to help minimize the
detraining that may occur during this extended break.
Although the majority of respondents indicated performing
resistance training along with cardiovascular exercise, the
greater amount of D1 compared with D3 student-athletes
who reported using resistance exercise equipment (barbells,
dumbbells, kettlebells) may be related to greater access to
S&C coaches. With twice as many females not performing
any resistance exercise during SAH compared with males,
our findings are consistent with research indicating males
may place more value on strength training than females (25).
However, it is also possible females and D3 student-athletes
reported a lower participation rate in resistance exercise
solely because of lack of resistance exercise equipment while
at home. Despite lack of formal equipment, some athletes
were resourceful and reported using implements such as a
heavy speaker, soup cans, bags filled with textbooks/bricks/
cement blocks, cat litter containers, and laundry detergent
bottles filled with sand as weights, whereas others reported
doing car pushing and pulling in lieu of formal weight training.
The inability to complete training sessions because of lack
of proper equipment and guidance from S&C staff during
training sessions may have contributed to the increased per-
ceived stress and decreased perceived effectiveness of at-home
training reported by females in this survey. These stressors
may be further augmented by the lack of social support during
SAH training, as females tend to be more extrinsically moti-
vated than males to exercise (26). A recent study among
team-sport athletes during SAH found higher physical
activity levels in males compared with females (27), further
suggesting female athletes may rely on social support and
motivation during training.
Despite increased feelings of stress surrounding training
among females, most respondents reported that training dur-
ing SAH increased their feelings of overall well-being. This is
consistent with findings of negative correlations between physical
activity levels and stress, depression, and anxiety among athletes
during SAH (27). Furthermore, this emphasizes the necessity of
training continuity during breaks from team-based activities for
both physical readiness and improved psychological states. In
fact, research suggests reframing the student-athletes’mindset to
use SAH to recover from physical injuries and psychological
burnout and focus SAH training programs on maintaining
fitness and preventing detraining rather than improving
fitness (28). It is imperative for coaches to emphasize that,
although SAH training may feel less effective, it is necessary to
prevent detraining and reduce injury risk upon return to play.
Nutrition/Supplements
In addition to training regimens, nutrition patterns and habits
during SAH impact performance upon return to school-based
training. This is an important consideration as ~39% of college
students come from homes facing food insecurity (29) and 24%
of male and 18% of female student-athletes reported minimal
access to healthy food choices during SAH (10). Although
average number of meals consumed per day remained similar,
more females indicated eating less, yet perceived their diets to be
healthier, during SAH. This pattern may represent beliefs that
reduced energy intake constitutes a healthy diet. Because female
athletes are at an increased risk for reduced energy availability
(30), this reported energy intake restriction should be further
investigated, especially as athletes return to heavy training
and energy requirements increase.
Although not significant, a greater proportion of females in-
dicated starting new supplements during SAH, whereas more
males stopped taking supplements they used before SAH.
The slight increases in vitamin C and vitamin D usage among
females may be directly related to the COVID-19 pandemic,
as vitamin C is known for immune system benefits and a pos-
sible connection has been made between vitamin D deficiency
and severity of COVID-19 symptoms (31,32). Changes in
supplement usage between males versus females and D1 versus
D3 were minimal, but the overall discrepancies between usage
among males compared with females and D1 compared with
8Volume 6 •Number 4 •Fall 2021 Effects of COVID-19 on Student-Athletes
Copyright © 2021 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
D3 should be noted. The largest difference was seen with protein
powder as almost twice as many D1 compared with D3
respondents indicated using protein powder both before and
during SAH. However, if total energy intake decreases while
away from school, protein intake after exercise may be
beneficial for recovery and training adaptations (33). Although
student-athletes may seek supplement and nutrition-related
information from coaches (34), an estimated 35% of coaches
demonstrated adequate sports nutrition knowledge compared
with 83% of S&C coaches (35), leaving athletes without
access to S&C, such as D3, at a disadvantage. Education
regarding health, performance, and recovery optimization
through nutrition and supplementation protocols are especially
important upon return to campus, as student-athletes reported
negative dietary changes during SAH.
Sleep Habits and Mental Health
In addition to the role of nutrition on recovery, adequate
sleep quantity and quality are important for improving perfor-
mance as well as maintaining a healthy immune system. Sleep
issues are not unique to student-athletes, as the current pan-
demic has been associated with decreased sleep quality among
college students (10,17,36–38), with females at higher risk. In
general, females are more likely to experience sleep
dysfunction (39,40). The increased sleep disturbances, yet
increased sleep duration, found in this study are consistent
with prior research conducted during SAH (37,38). Poor
sleep quality is a concern because of the link between sleep
patterns and self-esteem, anxiety, and depression (36). In the
current study, both males and females experienced decreases
in positive emotions (i.e., motivation to train, happiness)
with increases in negative feelings (i.e., tension, concern,
stress), which is consistent with findings from other studies
among athletes (27,38,41,42). Coupled with the large
proportion of student-athletes who cited sleep disruptions,
these changes may indicate the need for stress and anxiety
management upon return to school-based training.
Student-athletes may need additional mental health support
upon return to campus and sport, yet Cox et al. (15) reported
25.7% of college student-athletes said they did not know how
or where to access mental health support at their university.
Furthermore, 44% of student-athletes reported they did
not receive any mental health education from their athletic
departments. Although regularly screening athletes for depressive
symptoms has been suggested for many years (43), this may
be an even more important practice upon return to campus
after SAH, as the current pandemic and associated uncertainty
are additional stressors for student-athletes. Prior research
suggests student-athletes are more likely to discuss these mental
health concerns with a coach or athletic trainer as opposed to
seeking out a mental health professional, further emphasizing the
importance of awareness and monitoring by athletic staff to
identify student-athletes in need (43,44).
Perhaps an equally concerning issue is the relationship be-
tween depressive symptoms and injury among collegiate
student-athletes (45,46). Earlier research suggested various
psychosocial factors, such as high trait anxiety or increased
life stressors, are related to injury incidence among athletes
because of decreased concentration levels and possible
physiological disruptions (45–47). This may be particularly
important as student-athletes return to team activities, as
those who report anxiety and depressive symptoms during
preseason are at greater risk for injury (45). Increased injury
risk may be further compounded by the poor sleep habits
(37), and additional stressors student-athletes are facing
upon return to sports after SAH (38,41,48,49). The majority
of survey respondents indicated being most concerned with
maintaining fitness and sport-specific technical skills while
away from their normal training, with more females reporting
concerns compared with males. Females were more concerned
with mental health and social isolation, as well as injury
recovery, despite only 1.3% of females currently participating
in physical therapy or rehab exercises.
When looking at competitive divisions, D3 reported higher
concern levels relative to D1, with the exception of “scholar-
ship concerns.”Specifically, D3 student-athletes reported
greater concerns regarding mental health and social isolation,
which may be related to the fact that some D3 programs had
already suspended fall sports and even the in-person fall semes-
ter at the time this survey was conducted. Future research is
needed to assess the mental health status of student-athletes,
especially for those competing in fall sport whose seasons were
canceled or postponed. Athletics staff should be adequately
prepared to assist student-athletes with mental health con-
cerns, as the NCAA found only slightly more than half of
student-athletes (51%–62%) knew how to access mental health
support while at home. Awareness regarding student-athlete’sac-
cumulated mental and physical stress upon return to play is critical
for coaches/training staff when reconditioning student-athletes
after prolonged time away from organized training.
Limitations
While bringing to light obstacles and opportunities sur-
rounding program design and implementation for both athletes
and coaches during unprecedented times, this investigation does
have limitations. Although all attempts were made to emphasize
the anonymity and confidentiality of respondents, social desir-
ability bias may have impacted responses. Also, the survey was
completed online making it inaccessible to any student-athletes
without reliable internet access, which could lead to potential
biases in the responding sample. In addition, the number of
survey requests that individuals were receiving may have led
to survey fatigue and decreased sample size for the current
study. Survey distribution by an individual with whom the
student-athletes had sufficient rapport may have increased re-
sponse rates, as athletes may be less likely to respond to an un-
familiar e-mail address or social media (e.g., Twitter and
Facebook) advertisements. Reading comprehension and lan-
guage barriers are also a potential limitation, as there was no
option to have the questions read aloud to respondents or clar-
ifications made, which may also lead to biases in the sample
surveyed. Future investigations should utilize combinations
of online and in-person survey distribution with to athletes via
pen and paper with an anonymous return/drop-off location,
an easily accessible Internet location for completion, options
for verbal dissemination, or incentives for survey completion.
Although the results of the current study are generalizable
to collegiate student-athletes competing within the NCAA in
the UnitedStates, the sample demographics are not representa-
tive of the overall NCAA student-athlete body (21). Despite
this, demographic response patterns of the current study are
similar to those of the survey regarding COVID-19 conducted
http://www.acsm-tj.org Translational Journal of the ACSM 9
Copyright © 2021 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
by the NCAA in May 2020 (10,50) and follow typical survey
response patterns of more female than male and White than
non-White respondents (50) leading to nonresponse biases.
Because of small sample sizes of respondents self-identified as
Black or African American, Native American or Alaskan
Native, Asian, Native Hawaiian or Pacific Islander, or other,
authors were not able to reliably determine potential racial
disparities in guidance from S&C coaches, access to resources
required to execute training programs, or any other variable
measured. Future investigations should seek to determine the
existence of any such racial disparity.
CONCLUSIONS
Overall, this study suggests that, although student-athletes
attempted to be diligent with training during SAH, many re-
ported difficulties regarding limited equipment. Although a ma-
jority of respondents were living at home with their family
during SAH, many still reported suboptimal nutritional habits,
sleep quality, and other mental health concerns such as height-
ened anxiety and decreased motivation. With short notice of
university closures and suspension of team sport activities, uni-
versity athletic department coaches and staff may not have had
sufficient time to prepare athletes for completing SAH training.
The additional stressors related to maintaining fitness, sport
performance, and health affected many student-athletes, al-
though this disproportionately affected females. Reducing anx-
iety and stress is imperative to help student-athletes refocus on
training and healthy behaviors to ensure they return to campus
adequately prepared for upcoming competitions.
Ideally, upon return to typical supervised training regimens,
conversations between individual student-athletes and a multi-
disciplinary team of sport coaches, and S&C, nutrition, ath-
letic training, and sport psychology professionals are
recommended to determine the student-athlete’s overall readi-
ness to return to typical training regimens. Communication
should center on student-athlete health and wellness to ensure
steps are taken to support long-term on-field viability rather
than punishments for failure to complete adequate SAH train-
ing. The circumstances also highlight the importance of
instilling proper exercise technique and programmatic under-
standing early in an athlete’s career in order to instill auton-
omy and self-efficacy to perform unsupervised training.
In an attempt to decrease injury risk upon return to sport,
reduced training volumes may be necessary, especially for
student-athletes who indicate decreased training frequency
and/or intensity while at home, along with those who report
increased tension, stress, and unhappiness (45). Before the
return to school-based and team-based activities, university
athletic staff should have psychological and physical screening
procedures, such as mental health evaluations and physiological
performance testing, to better understand how to progress
athletes to reduce risk of injury due to overtraining.
The authors thank Dr. Bridget A. McFadden and Dr. Brittany N.
Bozzini for their help with revising and editing the manuscript in dur-
ing the initial writing stages.
The authors declare no conflict of interest. The authors have
nothing to disclose. The results of the present study do not consti-
tute endorsement by the American College of Sports Medicine. The
results of this study are presented clearly, honestly, and without
fabrication, falsification, or inappropriate data manipulation.
REFERENCES
1. Hartnett KP, Kite-Powell A, DeViesJ, et al. Impact of the COVID-19 pandemic
on emergency department vists—United States, January 1, 2019–May 30,
2020. MMWR. 2020;69(23).
2. Smalley A. Higher education responses to coronavirus (COVID-19): National
Conference of State Legislatures; 2020 2020 [cited 15 Sept 2020]. Available
from: https://www.ncsl.org/research/education/higher-education-responses-
to-coronavirus-covid-19.aspx.
3. Sarto F, Impellizzeri FM, Sporri J, et al. Impact of potential physiological
changes due to COVID-19 home confinement on athlete health protection in
elite sports: a call for awareness in sports programming. Sports Med.2020;
50(8, 9): 1417. Epub May 30, 2020. doi:10.1007/s40279-020 -01297-6 .
PubMed PMID: 32468329; PubMed Central PMCID: PMCPMC7254973.
4. Kovacs MS, Pritchett R, Wickwire PJ, Green JM, Bishop P. Physical perfor-
mance changes after unsupervised training during the autumn/spring semes-
ter break in competitive tennis players. Br J Sports Med. 2007;41(11):705–10;
discussion10. Epub June 15, 2007. doi:10.1136/bjsm.2007.035436. PubMed
PMID: 17562748; PubMed Central PMCID: PMCPMC2465299.
5. Blanch P, Gabbett TJ. Has the athlete trained enough to return to playsafely?
The acute:chronic workload ratio permits clinicians to quantify a player's risk
of subsequent injury. Br J Sports Med. 2016;50(8 ):471–5. Epub December
25, 2015. doi:10.1136/bjsports-2015-095445. PubMed PMID: 26701923.
6. Drew MK, Finch CF. The relationship between training load and injury, illness
and soreness: a systematic and literature review. Sports Med. 2016;46(6):
861–83. Epub January 30, 2016. doi:10.1007/s40279-015-0459-8. PubMed
PMID: 268 22969.
7. Hootman JM, Dick R, Agel J. Epidemiology of collegiate injuries for 15 sports:
summary and recommendations for injury prevention initiatives. JAthlTrain.
2007;42(2):311–9.Epub August 22, 2007.PubMed PMID: 17710181; PubMed
Central PMCID: PMCPMC1941297.
8. Myer GD, Faigenbaum AD, Cherny CE, Heidt RSJr., Hewett TE. Did the NFL
lockout expose the Achilles heel of competitivesports? JOrthopSportsPhys
Ther. 2011;41(10):702–5. Epub September 24, 2011. doi:10.2519/
jospt.2011.0107. PubMed PMID: 21941038.
9. Seshadri DR, Thom ML, Harlow ER, Drummond CK, VoosJE. Case report: re-
turn to sportfollowing the COVID-19 lockdown and tts impact on injuryrates in
the German Soccer League. Front Sports Act Living. 202 1;3:60 4226. Epu b
March 9, 2021. doi:10.3389/fspor.2021.604226. PubMed PMID: 33681759;
PubMed Central PMCID: PMCPMC7931153.
10. NCAA. NCAA Student-Athlete COVID-19 Well-Being Study.Indianapolis(IN):
National Collegiate Athletic Association; 2020.
11. Hagedorn RL, McArthur LH, Hood LB, et al. Expenditure, coping, and aca-
demic behaviors among food-insecure college students at 10 higher educa-
tion institutes in the appalachian and southeastern regions. Curr Dev Nutr.
2019;3(6). doi:UNSP nzz05810.1093/cdn/nzz058. PubMed PMID: WOS:
000493058200009.
12. Graupensperger S, Benson AJ, Kilmer JR, Evans MB. Social (un)distancing:
teammate interactions, athletic identity, and mental health of student-athletes
during the COVID-19 pandemic. J Adolesc Health. 2020. Epub September
19, 2020. doi:10.1016/j.jadohealth.2020.08.001. PubMed PMID: 32943294;
PubMed Central PMCID: PMCPMC7489994.
13. Armstrong SN, Oomen-Early J. Social connectedness, self-esteem, and de-
pression symptomatology among collegiate athletes versus nonathletes.
JAmCollHealth. 2009;57(5):521–6.
14. Armstrong SN, Burcin MM, Bjerke WS, Early J. Depression in student-
athletes: a particularly at-riskgroup? A systematic review of the literature. Ath-
letic Insight. 2015;7(2):177–93.
15. Cox CE, Ross-Stewart L, Foltz BD. Investigating the prevalence and risk fac-
tors of depression symptoms among NCAA division I collegiate athletes.
JSportsSci.2017;5(1):14
–28. doi:10.17265/2332-7839/2017.01.002.
16. Proctor SL, Boan-Lenzo C. Prevalence of depressive symptoms in male inter-
collegiate student-athletes and nonathletes. J Clin Sports Psychol.2010;4(3):
204–20. doi:10.1123/jcsp.4.3.204.
17. Jelaca M, Anastasovski I, Velickovska LLA. A report on the impacts of the co-
ronavirus SARS-COV-2 “shelter-in-place order”on fitness and well-being.
Res Phys Educ Sport Health. 2020;9(1):13–8.
18. Spielberger CD, GorsuchRL, Lushene R, Vagg PR, JacobsGA. Manual f or the
State-Trait Anxiety Inventory. Palo Alto (CA): Consulting Psychologists Press; 1983.
19. Raglin JS, Morgan WP. Development of a scale for use in monitoring
training-induced distress in athletes. Int J Sports Med.1994;15(2):84–8. doi:
10.1055/s-2007-1021025.
20. Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh
Sleep Quality Index: a new instrument for psychiatric practice and research.
Psychiatry Res.1989;28(2):193–213. Epub May 1, 1989. doi:10.1016/0165-
1781(89)90047-4. PubMed PMID: 2748771.
10 Volume 6 •Number 4 •Fall 2021 Effects of COVID-19 on Student-Athletes
Copyright © 2021 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
21. NCAA. NCAA Demographics Database: National Collegiate Athletics Associ-
ation; 2020 2020. Available from: http://www.ncaa.org/about/resources/
research/ncaa-demographics-database.
22. NCAA. 2020–21 Guide for the college-bound student-athlete. 2020. Available
from: http://fs.ncaa.org/Docs/eligibility_center/Student_Resources/CBSA.pdf.
Accessed December 12, 2020.
23. Brumitt J, Heiderscheit BC, ManskeRC. Preaseasonfunctional test scores are
associated with future sports injury in female collegiate athletes. JStrength
Cond Res. 2018;32(6):1692–701.
24. Andreato LV, Coimbra DR, Andrade A. Challenges to athletesduring the home
confinement caused by the COVID-19 pandemic. Strength Cond J. 2020;
42(3):1–5. doi:10.1519/Ssc.0000000000000563. PubMed PMID: WOS:
000538877200001.
25. Eisner MT, Elder C, Sinclair-Elder A, Kelly C. Collegiate athletes’perceptions
on the importance of strengthand conditioning coaches and their contribution
to increased athletic performance. JAthlEnhance. 2014;03(04). d oi:
10.4172/2324-9 080.1000159.
26. Portela-Pino I, Lopez-Castedo A, Martinez-Patino MJ, Valverde-Esteve T,
Dominguez-Alonso J. Gender differences in motivation and barriers for the
practice of physical exercise in adolescence. Int J Environ Res Public Health.
2019;17(1). Epub December 29, 2019. doi:10.3390/ijerph17010168. PubMed
PMID: 31881707; PubMed Central PMC ID: PMCPMC6981955.
27. Senisik S, Denerel N, Koyagasioglu O, Tunc S. The effect of isolation on ath-
letes' mental health during the COVID-19 pandemic. Phys Sportsmed.2020;
49:1–7.Epub August 9, 2020. doi:10.1080/00913847.2020.1807297.PubMed
PMID: 327 62510,.
28. Jukic I, Calleja-Gonzalez J, Cos F, et al. Strategies and solutions for team
sports athletes in isolation due to COVID-19. Sports (Basel).2020;8(4).Epub
April 30, 2020. doi:10.3390/sports8040056. PubMed PMID; PubMed Central
PMCID: PM CPMC72 40607.
29. Bruening M, Argo K, Payne-Sturges D, Laska MN. The struggle is real: a sys-
tematic review of food insecurity on postsecondary education campuses.
JAcadNutrDiet. 2017;117(11):1767–91. doi:10.1016/j.jand.2017.05.022.
PubMed PMID: WOS:000417199800012.
30. Coelho GM, Gomes AI, Ribeiro BG, Soares Ede A. Prevention of eating disor-
ders in female athletes. Open Access J Sports Med. 2014;4(5):105–13. Epub
June 4, 2014. doi:10.2147/OAJSM.S36528. PubMed PMID: 24891817;
PubMed Central PMCID: PMCPMC4026548.
31. Yousfi N, Bragazzi NL, Briki W, Zmijewski P, Chamari K. The COVID-19 pan-
demic: how to maintain a healthy immune system during the lockdown—a
multidisciplinary approach with special focus on athletes. Biol Sport.2020;
37(3):211–6. doi:10.5114/biolsport.2020.95125.
32. Khoramipour K, Basereh A, Hekmatikar AA, Castell L, Ruhee RT, Suzuki K.
Physical activity and nutrition guidelines to help with the fight against
COVID-19. JSportsSci.2020;39:1–7. Epub August 28, 2020. doi:
10.108 0/02640414.202 0.1807089. PubMe d PMID: 328 42905.
33. Cintineo HP, Arent MA, Antonio J, Arent SM. Effects of protein supplementa-
tion on performance and recovery in resistance and endurance training. Front
Nutr. 2018;5:83. Epub September 27, 2018. doi:10.3389/fnut.2018.00083.
PubMed PMID: 30255023; PubMed Central PMCID: PMCPMC6142015.
34. Jovanov P, Dordic V, Obradovic B,et al. Prevalence, knowledge andattitudes
towards using sports supplements among young athletes. JIntSocSports
Nutr. 2019;16(1):27. Epub July 6, 2019. doi:10.1186/s12970-019-0294-7.
PubMed PMID: 31272457; PubMed Central PMCID: PMCPMC6611041.
35. Torres-McGehee TM, Pritchett KL, Zippel D, Minton DM, Cellamare A, Sibilia
M. Sports nutrition knowledge among collegiate athletes, coaches, athletic
trainers, and strength and conditioning specialists. JAthlTrain.2012;47(2):
205–11. PubMed PMID: WOS:000302386600012.
36. Zhou SJ, Wang LL, Yang R, etal. Sleep problems among Chineseadolescents
and young adults during the coronavirus-2019 pandemic. Sleep Med.2020;
74:39–47 Epub August 25, 2020. doi:10.1016/j.sleep.2020.06.001. PubMed
PMID: 3283618 5.
37. Facer-Childs ER, Hoffman D, Tran JN, Drummond SPA, Rajaratnam SMW.
Sleep and mental health in athletes during COVID-19 lockdown. Sleep.
2021. Epub February 4, 2021. doi:10.1093/sleep/zsaa261. PubMed PMID:
33535229; PubMed Central PMCID: PMCPMC7928674.
38. Mon-Lopez D, Garcia-Aliaga A, Gines Bartolome A, Muriarte Solana D. How
has COVID-19 modified training and mood in professional and
non-professional football players. Physiol Behav. 2020;227:113148. Epub
August 29, 2020. doi:10.1016/j.physbeh.2020.113148. PubMed PMID:
32858031; PubMed Central PMCID: PMCPMC7445487.
39. Zhang B, Wing YK. Sex differences ininsomnia: a meta-analysis. Sleep.2006;
29(1):85–93. Epub February 4, 2006. doi:10.1093/sleep/29.1.85. PubMed
PMID: 1645398 5.
40. Becker SP, Jarrett MA, Luebbe AM, Garner AA, BurnsGL, Kofler MJ. Sleep in
a large, multi-university sample of college students:sleep problem prevalence,
sex differences, and mental health correlates. Sleep Health. 2018;4(2):174–81.
Epub March 21, 2018. doi:10.1016/j.sleh.2018.01.001. PubMed PMID:
29555131; PubMed Central PMCID: PMCPMC5863586.
41. Pons J, Ramis Y, Alcaraz S, Jordana A, Borrueco M, Torregrossa M. Where
did all the sport go? Negative impact of COVID-19 lockdown on life-spheres
and mental health of S panish you ng athletes . Front Psychol.2020;11:
611872. Epub December 29, 2020. doi:10.3389/fpsyg.2020.611872. PubMed
PMID: 33365006; PubMed Central PMCID: PMCPMC7750436.
42. McGuine TA, Biese KM, Petrovska L, etal. Mental health, physical activity, and
quality of life of US adolescent athletes during COVID-19–related school clo-
sures and sport cancellations: a study of 13 000 athletes. J Athl Train.2020.
Epub December 9, 2020. doi:10.4085/1062-6050-0478.20. PubMed PMID:
33290516; PubMed Central PMCID: PMCPMC7863599.
43. Etzel EF, Watson JC, Visek AJ, Maniar SD. Understanding and promoting col-
lege student-athlete health: essential issues for student affairs professionals.
NASPA J. 2006;43(3):518–46.
44. Maniar SD, Curry LA, Sommers-Flanagan J, Walsh JA. Student-athletes pref-
erences in seeking help when confronted with sport performance problems.
Sport Psychologist. 2001;15(2):205–23. doi:10.1123/tsp.15.2.205. PubMed
PMID: WOS:000169059100006.
45. Li H, Moreland JJ, Peek-Asa C, Yang J. Preseason anxiety and depressive
symptoms and prospective injury risk in collegiate athletes. Am J Sports Med.
2017;45(9):2148–55. Epub April 26, 2017. doi:10.1177/0363546517702847.
PubMed PMID: 28441037.
46. Johnson U. Psychosocial antecedents of sport injury, prevention, and inter-
vention: an overview of theoretical approaches and empirical findings. Int J
Sport Exerc Psychol. 2007;5(4):352–69. Epub February 28, 2011. doi:
10.1080/1612197x.2007.9671841.
47. Fawkner HJ, McMurraryNE, Summers JJ. Athletic injury and minor lifeevents:
a prospective study. JSciMedSport. 1999;2(2):117–24 Epub September 7,
1999. doi:10.1016/s1440-2440(99)80191-1. PubMed PMID: 10476975.
48. Hagiwara G, editor Relationships among student-athlete’s identity and mental
health condition—survey in the COVID-19 pandemic. The 3rd International
Electronic Conference on Environmental Research and Public Health: Public
Health Issues in the Context of COVID-19 Pandemic; 2021; Online: MDPI.
49. Bullard JB. The impact of COVID-19 on the well-being of Division III student-
athletes. Sport J. 2020;41(2 ).
50. Porter SR, Whitcomb ME. Non-response in student surveys:the role of demo-
graphics, engagement and personality. Res Higher Educ. 2005;46(2):127–52.
doi:10.1007/s11162-004 -1597-2.
http://www.acsm-tj.org Translational Journal of the ACSM 11
Copyright © 2021 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
