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Abstract

Background There is growing understanding of mental health needs in elite athletes, but less is known about the mental health of coaches and support staff who work within elite sport settings. This study examined the prevalence and correlates of mental health symptoms in elite-level coaches and high-performance support staff (HPSS) and compared rates against published elite athlete samples. A cross-sectional, anonymous, online survey was administered to coaches and HPSS working in Australia’s high-performance sports system. Main outcomes were scores on validated measures of psychological distress, probable ‘caseness’ for a diagnosable psychological condition, alcohol consumption and sleep disturbance. Results Data were provided by 78 coaches (mean age = 46.4 years, 23.8% female) and 174 HPSS (mean age = 40.0 years, 56.7% female). Overall, 41.2% of the sample met probable caseness criteria, 13.9% reported high to very high psychological distress, 41.8% reported potential risky alcohol consumption and 17.7% reported moderate to severe sleep disturbance, with no statistically significant differences between coaches and HPSS. The most robust correlates of psychological distress and probable caseness were dissatisfaction with social support and dissatisfaction with life balance, while poor life balance was also associated with increased alcohol consumption and poor social support with sleep disturbance. Coaches and HPSS reported similar prevalence of mental health outcomes compared to rates previously observed in elite athletes, with the exception of higher reporting of alcohol consumption among coaches and HPSS. Conclusions Elite-level coaches and HPSS reported levels of psychological distress and probable caseness similar to those previously reported among elite-level athletes, suggesting that these groups are also susceptible to the pressures of high-performance sporting environments. Screening for mental health symptoms in elite sport should be extended from athletes to all key stakeholders in the daily training environment, as should access to programs to support mental health and well-being.
Pilkingtonetal. Sports Medicine - Open (2022) 8:89
https://doi.org/10.1186/s40798-022-00479-y
ORIGINAL RESEARCH ARTICLE
Prevalence andCorrelates ofMental Health
Symptoms andWell-Being Among Elite Sport
Coaches andHigh-Performance Support Sta
Vita Pilkington1,2* , Simon M. Rice1,2, Courtney C. Walton1,2, Kate Gwyther1,2, Lisa Olive1,2,3, Matt Butterworth4,
Matti Clements4, Gemma Cross4 and Rosemary Purcell1,2
Abstract
Background: There is growing understanding of mental health needs in elite athletes, but less is known about the
mental health of coaches and support staff who work within elite sport settings. This study examined the prevalence
and correlates of mental health symptoms in elite-level coaches and high-performance support staff (HPSS) and com-
pared rates against published elite athlete samples. A cross-sectional, anonymous, online survey was administered to
coaches and HPSS working in Australia’s high-performance sports system. Main outcomes were scores on validated
measures of psychological distress, probable ‘caseness’ for a diagnosable psychological condition, alcohol consump-
tion and sleep disturbance.
Results: Data were provided by 78 coaches (mean age = 46.4 years, 23.8% female) and 174 HPSS (mean
age = 40.0 years, 56.7% female). Overall, 41.2% of the sample met probable caseness criteria, 13.9% reported high to
very high psychological distress, 41.8% reported potential risky alcohol consumption and 17.7% reported moderate
to severe sleep disturbance, with no statistically significant differences between coaches and HPSS. The most robust
correlates of psychological distress and probable caseness were dissatisfaction with social support and dissatisfaction
with life balance, while poor life balance was also associated with increased alcohol consumption and poor social
support with sleep disturbance. Coaches and HPSS reported similar prevalence of mental health outcomes compared
to rates previously observed in elite athletes, with the exception of higher reporting of alcohol consumption among
coaches and HPSS.
Conclusions: Elite-level coaches and HPSS reported levels of psychological distress and probable caseness similar
to those previously reported among elite-level athletes, suggesting that these groups are also susceptible to the
pressures of high-performance sporting environments. Screening for mental health symptoms in elite sport should
be extended from athletes to all key stakeholders in the daily training environment, as should access to programs to
support mental health and well-being.
Keywords: Mental health, Well-being, Coach, Support staff, Sport, High performance
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Key Points
Coaches and HPSS reported similar rates of mental
health symptoms as previous elite athlete samples,
suggesting that these groups are also susceptible to
mental health concerns and pressures within high-
performance sports settings.
Open Access
*Correspondence: vita.pilkington@unimelb.edu.au
1 The Centre for Youth Mental Health, The University of Melbourne,
Melbourne, VIC, Australia
Full list of author information is available at the end of the article
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Pilkingtonetal. Sports Medicine - Open (2022) 8:89
Satisfaction with life balance and satisfaction with
social support appear to act as key protective factors
for mental health. Efforts aiming to enhance these
psychosocial factors have the potential to directly
enhance coach and HPSS well-being.
Unlike previous research with elite athlete samples,
no significant gender differences in mental health
symptomatology were observed, suggesting a differ-
ential role of gender between athletes and members
of the daily training environment in terms of mental
health and well-being outcomes.
Background
ere is increasing awareness of the rates and nature of
mental health symptoms experienced among elite ath-
letes [1], with approximately 1 in 3 currently competing
athletes reporting symptoms of common mental health
concerns, such as anxiety, depression and psychological
distress [2, 3]. ese rates are consistent with or higher
than those observed in general community samples [2,
3]. A number of sport-specific risk factors for elite ath-
lete mental ill health have been identified to date, includ-
ing performance pressures, serious (including chronic)
injury, maladaptive perfectionism, maladaptive coping
strategies and inadequate social support [1, 3, 4]. ere
is comparatively limited understanding, however, of
the mental health and well-being of coaches and high-
performance support staff (HPSS) who work alongside
athletes within elite sport settings [5]. e latter group
includes a wide network of professionals who support
athlete health, functioning and performance, such as ath-
letic trainers, physiotherapists, nutritionists, strength and
conditioning coaches, sports psychologists, and athlete
well-being and engagement managers.
Coaches and HPSS operate within a broader ‘ecology’
of elite sporting environments [6]. As argued in recent
sports mental health position papers and frameworks,
in addition to key responsibilities related to athlete per-
formance, athlete health, team cohesion and organiza-
tional functioning, coaches and HPSS also have critical
roles in promoting and protecting the well-being of
athletes [1, 7, 8], including promoting the importance
of mental health, recognizing experiences of mental ill
health as legitimate, identifying emerging symptoms
of mental ill health and encouraging appropriate help-
seeking. Coaches and HPSS may share characteristics
already established as risk factors for mental ill health
in elite athletes (e.g., pressure to perform, maladap-
tive perfectionism) and may experience specific role-
related stressors that place them at risk for mental ill
health, such as insecure employment, unclear roles,
feeling undervalued and doubting their coaching (or
role) competencies [9]. Understanding coach and HPSS
mental health and well-being is therefore pivotal for
understanding the mental health needs and resourc-
ing requirements within elite sports settings holisti-
cally and has additional potential benefits that may flow
from promoting athlete well-being and creating a flour-
ishing elite sports environment. However, it is currently
unclear whether elite-level coaches and HPSS experi-
ence mental health symptoms at a similar rate to elite
athletes, or whether known risk factors for mental ill
health in athletes (such as female gender [10] and indi-
vidual as opposed to team sport participation [11]) also
confer risks to coach and HPSS mental health.
A study by Smith and colleagues [12] highlighted rel-
atively high mental health need among coaches, with
55% reporting that they had experienced mental illness.
However, this sample comprised coaches from a range
of professional backgrounds and performance levels
(including n = 35 elite coaches) and most study findings
were not reported separately for the elite coach group. To
date, only three studies have examined the rates of com-
mon mental health symptoms among elite coaches, with
estimates ranging from 14% for depressive symptoms in
a sample of 69 New Zealand coaches [13], to 39.5% for
mixed depression/anxiety symptoms among 119 Dutch
and Flemish coaches [14]. A recent study by Åkesdotter
and colleagues [15] investigated a small sample of high-
performance coaches (n = 34) seeking treatment from
a psychiatric outpatient service (in addition to 221 elite
athletes seeking support from the same service). Nearly
all the coaches presenting to the outpatient service (93%)
presented with anxiety disorders, while 28% presented
with major depressive disorder. e authors also reported
high prevalence (72%) of stress-related disorders among
coaches (compared to 25% among the athlete sample).
Coaches that are contemplating or recently experi-
encing retirement report even higher rates of mental
health symptomatology [13, 16], which is consistent
with a pattern observed in retired or former elite ath-
letes [2]. Known risk factors for mental ill health among
coaches include lack of life balance, burnout, perfor-
mance-based stressors (e.g., lack of athlete commitment,
poor performance and poor performance preparation),
organizational stressors (e.g., poor organizational com-
munication, unclear roles, conflict) and personal chal-
lenges (e.g., missing children’s education, long periods
away from home) [13, 14, 17]. Of note, organizational but
not performance stressors have been found to be predic-
tive of increased depression/anxiety symptoms [14]. In
the limited available evidence, coaches have identified job
security, professional and personal growth opportunities,
high autonomy support and life balance as protective
mental health factors [18, 19].
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Pilkingtonetal. Sports Medicine - Open (2022) 8:89
To date, no research has systematically examined
rates of mental health concerns among HPSS, although
Hill and colleague’s [5] qualitative study of members
of the daily training environment (inclusive of coaches
and HPSS) reported key perceived protective factors
for mental health to include social support, leadership
and organizational culture. Key perceived risk factors
included high workload, competitive performance and
isolation [1]. However, risk and protective factors for
mental ill health in HPSS are yet to be studied using
quantitative methods.
is study examined the rates and correlates of men-
tal health symptoms in a large cohort of elite-level
coaches and HPSS. Associated aims were to (a) com-
pare rates of symptoms to published elite athlete sam-
ples to determine whether mental health profiles differ
between these groups; (b) explore similarities and dif-
ferences between coach vs HPSS profiles (in relation to
symptoms of mental ill health, adverse events, social
support, life balance and strategies for managing stress
and mental well-being); and (c) explore correlates of
mental health in this group (such as satisfaction with
life balance and social support). It was hypothesized
that [H1] symptom rates of common mental health
concerns in coaches and HPSS would be similar to
those reported by elite athletes; [H2] coaches and HPSS
would have similar profiles in terms of mental health
symptoms; and [H3] putative risk factors would be
associated with symptoms of common mental health
concerns, including sport-related factors (e.g., fre-
quency of sport-related travel, missing significant life
events due to sport-related travel) and general risk
factors (e.g., number of lifetime and past year adverse
events, previous mental health treatment, female gen-
der), while known protective factors (e.g., life balance
and social support) would be negatively associated with
symptoms of common mental health concerns.
Methods
Participants
All coaches and HPSS employed by national sporting
organizations (NSOs) and national institute networks
(NINs) in Australia’s high-performance sport system
(the Australian Institute of Sport: AIS) were invited to
participate in an anonymous online survey regarding
their mental health and well-being. HPSS included high-
performance directors, physiotherapists, nutritionists,
medical doctors, sports psychologists, strength and con-
ditioning coaches, athlete well-being and engagement
advisors, and others involved in the daily training envi-
ronment. No exclusion criteria were applied for survey
participation other than the ability to read English.
Procedure
A link to the online survey was provided to potential par-
ticipants via text message or email (depending on each
participant’s preferred AIS registered contact details).
e survey was built by Orygen’s research database man-
agement team and hosted on a secure research manage-
ment platform. e survey was open between March 16
and May 31, 2020. Participants completed the survey
at a place and time of their choosing. e survey took
approximately 20min to complete and was enabled for
completion on any electronic device (i.e., smartphone,
computer or tablet).
All participants were provided with information about
the purpose and nature of the survey prior to commenc-
ing, and informed consent was implied by participants
choosing to click to ‘enter’ the survey. e survey con-
cluded with participants being directed to a debrief-
ing statement that included contact details for relevant
mental health support services and the project investiga-
tors, should the participant wish to discuss their expe-
rience with the survey or any concerns regarding their
responses. e research was approved by, and conducted
in accordance with, the ethical standards of the Univer-
sity of Melbourne Human Ethics Research Committee
(#13718) and the 1964 Helsinki Declaration.
Survey Content
e survey was developed in consultation with AIS staff
and Paralympics Australia based on a previous project
[3]. Wherever possible, validated scales that were devel-
oped for, or used with, elite athletes and shown to be reli-
able in prior research were used in the survey, in order to
enable comparisons.
Background Information/Demographics
Basic demographic details were collected, including
participant age, gender, relationship status, sexual ori-
entation and highest level of education. Participants
were also asked about employment-related characteris-
tics, including the number of years they had worked in
high-performance sport, and their current employment
status with a national sporting organization or institute
and whether they had engaged in any voluntary or paid
employment in the past month in addition to their sport-
ing role. Sport-related characteristics included the type
of sport(s) they coached or supported (e.g., individual
or team-based), whether they were currently preparing
athletes for upcoming competition, frequency of sport-
related travel over the past 12 months, whether they had
missed significant life events due to sport-related travel
and concerns for safety while traveling for their sport in
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Pilkingtonetal. Sports Medicine - Open (2022) 8:89
the 12months prior to the survey. Participants were also
asked if they had previously accessed treatment for a psy-
chological issue or mental health problem.
Symptom Outcome Measures
Mental Health Symptoms and Probable Caseness e
28-item General Health Questionnaire (GHQ-28; [20])
was used to assess mental health symptoms in the past
4weeks. e GHQ-28 includes a total score and four sub-
scale scores, which assess somatic complaints (e.g., ‘been
feeling run down and out of sorts’), anxiety and insom-
nia (e.g., ‘lost much sleep over worry’), social dysfunction
(e.g., ‘felt on the whole you were doing things well’) and
severe depression (e.g., ‘felt that life is entirely hopeless’).
Items are scored 0 = not at all, 1 = no more than usual,
2 = more than usual and 3 = much more than usual, with
GHQ-28 total scores ranging from 0 to 84.
e GHQ-28 can also be scored as a categorical meas-
ure, which can be used to indicate the proportion of par-
ticipants meeting the threshold for ‘probable caseness’
(the reporting of psychological symptoms at a level that
would usually warrant treatment from a health profes-
sional). To calculate caseness, binary coding is applied to
the four response items (0 = not at all or no more than
usual, 1 = more than usual or much more than usual)
and the total score with this binary coding is calculated
(range = 0–28). e cutoff score used was 5 or more indi-
cating probable caseness, as per [21] and to allow com-
parisons with a comparable athlete sample [3].
Psychological Distress e Kessler-10 (K-10; [22])
was used to measure psychological distress. e K-10
requires respondents to rate the frequency at which
they have experienced symptoms of psychological dis-
tress over the previous 4weeks (e.g., ‘about how often did
you feel that everything was an effort’). Items are scored
1 = none of the time, 2 = a little of the time, 3 = some of the
time, 4 = most of the time, 5 = all of the time, where K-10
total scores range 10–50.
Risky Alcohol Consumption e Alcohol Use Disorder
Identification Tool-Concise (AUDIT-C; [23]) was used as
a brief 3-item measure of alcohol consumption that iden-
tified individuals at risk of risky alcohol consumption.
Items enquire about frequency and quantity of alcohol
consumption, where each item is scored 0–4 and total
scores range from 0 to 12. To allow for comparisons with
the previously published literature (e.g., [15]), we used a
cutoff score equal to or above 4 for women and 5 for men
to determine potentially risky alcohol consumption (also
see footnote in Table2 for the rate meeting risky alco-
hol consumption using the more stringent IOC recom-
mended cutoffs [24]).
Sleep e Athlete Sleep Screening Question-
naire (ASSQ; [25]) was used to assess possible sleep
disturbance. is measure includes five items that
enquire about satisfaction with recent sleep quality, sleep
duration, sleep onset latency, sleep maintenance and use
of sleep medication. ASSQ total scores (range = 0–17)
can be categorized into levels of sleep disturbance
(5–7 = mild disturbance, 8–10 = moderate disturbance,
11–17 = severe disturbance) [26].
Comparison Data
For each of the main mental health outcome measures,
comparisons were made between coaches and HPSS ver-
sus published elite athlete data. Where possible, athlete
data were obtained from a study with a comparable ath-
lete sample, comprising athletes aged 17years and older
contracted with the AIS [3]. Where comparison data with
this sample were unavailable (i.e., for the AUDIT-C and
ASSQ), data from studies with elite athlete samples that
used the same cutoff scores as described above were used
[15, 27, 28].
Psychosocial Correlates
Quality of Life Past 4-week quality of life was assessed
using a single item from the World Health Organisation
[29] (‘inking about your life in the last 4weeks, how
would you rate your quality of life?’), rated on a five-point
scale (1 = very poor, 2 = poor, 3 = neither good nor poor,
4 = good, 5 = very good).
Satisfaction with Life Satisfaction with life was assessed
using the Satisfaction with Life Scale [30], which includes
5 items (e.g., ‘So far, I have gotten the important things I
want in life’) rated on a 7-point scale (1 = strongly disa-
gree, 2 = disagree, 3 = slightly disagree, 4 = neither agree
or disagree, 5 = slightly agree, 6 = agree, 7 = strongly
agree). Total scores range from 5–35.
Life balance was assessed using a single Y/N item (‘Are
you satisfied with your life balance, e.g., managing your
sport, work, social life, family, sleep, etc.?’).
Social support was assessed using six questions, which
enquired about presence (Y/N) of support, main source
of support, level of satisfaction with support (rated
1 = totally dissatisfied to 7 = completely satisfied), and
experiences of social isolation (feeling of lacking com-
panionship, feeling left out, feeling isolated; rated in
terms of frequency 1 = hardly ever, 2 = some of the time,
3 = often). e social support items were assessed indi-
vidually, rather than summed.
Adverse life events were assessed over the past year and
lifetime. irteen items were included (see Additional
file 1: Table S1), which included experiences of gen-
eral adverse events (e.g., ‘A person close to me died’) and
sport-specific events (e.g., ‘I felt under-valued or under-
paid’; ‘I was harassed or abused on social media’), each
rated 0 = no, never, 1 = yes, 2 = yes, past year.
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Pilkingtonetal. Sports Medicine - Open (2022) 8:89
Strategies for managing mental well-being was assessed
by providing participants with a list of strategies com-
monly used to manage stress or mental well-being (e.g.,
using relaxation techniques’; ‘talking with a friend/part-
ner’), with participants indicating which of the strategies
they used in their daily life with binary Y/N responses
(see Additional file1: TableS2).
Concern about COVID-19 At the time of the planned
survey implementation, the COVID-19 pandemic was
emerging, with attendant restrictions. A question was
included in the survey to assess COVID-19 concern
(Y/N), with affirmative responses asked to specify their
level of concern about the pandemic (1 = a little con-
cerned, 2 = somewhat concerned, 3 = greatly concerned)
and specific concerns related to the pandemic via provid-
ing a list of potential concerns, as well as an open-ended
response option for other concerns.
Data Analyses
Categorical variables were summarized using frequen-
cies and percentages, and continuous variables were
summarized using mean and standard deviation. Group
comparisons were made to examine possible differences
according to demographic characteristics (e.g., gender,
role) and for comparing coach and HPSS data to pub-
lished data with elite athlete samples. Group comparisons
for continuous outcome measures were made using inde-
pendent samples t tests (measure of effect size = Cohen’s
d), while comparisons for categorical outcome meas-
ures were made using chi-square (measure of effect
size = Cramer’s V). All outcomes have been evaluated as
statistically significant at the p 0.01 level, to reduce the
risk of Type I error.
Separate regression models were developed for each
major outcome: caseness (according to GHQ-28),
psychological distress (K-10), alcohol consumption
(AUDIT-C) and sleep (ASSQ). For caseness, which had
a dichotomous outcome (i.e., meets caseness criteria vs
does not meet criteria), logistic regression analysis was
used. Continuous outcomes (K-10, AUDIT-C and ASSQ)
were assessed for significant departures from normality
using the Shapiro–Wilk test, and quantile median regres-
sion was used (where median scores were used instead of
mean scores to account for departures from normality).
A two-stage analysis was performed for each model,
where unadjusted associations were examined between
the outcome measure and possible correlates, which
included demographic variables (e.g., gender, age), sport-
related characteristics (e.g., individual/team sport, fre-
quency of sport-related travel), employment-related
variables (e.g., number of years working in high-perfor-
mance sport), number of adverse life events (past year
and lifetime) and other possible psychosocial correlates
(e.g., previous or current mental health treatment, satis-
faction with life balance, satisfaction with social support).
Additionally, the presence of concern about the COVID-
19 pandemic (Y/N) and date of survey completion
(pre- or post-announcement about the postponement
of the Tokyo Olympics and Paralympics) were included
as possible correlates in each regression model. In the
second stage (following the identification of significant
correlates), only significant correlates were entered into
the adjusted model, therefore controlling for the effects
of each salient variable from the unadjusted model. All
analyses were conducted using IBM SPSS Statistics 25
and R Version 4.0.0.
Results
Descriptive Statistics
A total of 78 coaches and 174 HPSS completed some or
all of the survey (i.e., at least two mental health outcome
measures), representing a valid response rate of 31.5%.
Participants reported working across 32 sports,
with the majority involved in individual sports (55.0%
of coaches; 66.7% of HPSS), rather than team-based
sports. e majority of participants were born in Aus-
tralia (77.8% of coaches; 83.9% of HPSS), married (72.5%
of coaches; 56.4% of HPSS), identified as heterosexual
(95.1% of coaches; 96.1% of HPSS), and had completed
a university degree (67.5% of coaches; 87.8% of HPSS).
e mean age was 46.4 years ( = 8.78) for coaches and
40.0years (SD = 9.65) for HPSS. Among coaches, more
individuals were male-identifying (76.3%) than female-
identifying (23.8%), whereas there was a more even gen-
der distribution among HPSS (56.7% female-identifying
and 41.1% male-identifying). A small number (n < 5) pre-
ferred not to disclose their gender. Approximately two-
thirds were employed by a NSO (66.2% of coaches; 64.2%
of HPSS), while approximately one-third were employed
by a NIN (33.8% of coaches; 35.8% of HPSS). e major-
ity reported they had worked in high-performance sport
for 10 or more years (60.5% of coaches; 51.1% of HPSS).
Participant demographic and sport-related characteris-
tics are summarized in Table1.
Psychosocial Variables: Help‑Seeking, Adverse Events,
Social Support, Quality ofLife andLife Balance
Approximately 1 in 3 participants reported they had
sought treatment for a psychological issue or mental
health problem at some stage (34.6% of coaches, 34.4%
of HPSS). e reporting of adverse life events was simi-
lar between coaches and HPSS (see Additional file 1:
TableS1). e most commonly reported lifetime adverse
events were the death of a close person (54.3% of coaches;
49.2% of HPSS), a relative or close friend suffering from
serious illness, injury or assault (reported by 51.9% of
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Pilkingtonetal. Sports Medicine - Open (2022) 8:89
coaches and 49.7% of HPSS), and feeling undervalued
or underpaid (54.3% of coaches; 48.6% of HPSS). is is
consistent with adverse events reported by elite athletes
[10].
Almost all participants reported having social sup-
port (92.1% of coaches; 92.8% of HPSS), and the majority
reported satisfaction with their social support (75.7% of
coaches; 85.3% of HPSS). e majority of coaches (85.5%)
and HPSS (87.9%) reported that their main source of sup-
port was someone outside their sport, most commonly a
spouse/partner, followed by a friend, then a parent. Only
5.3% of coaches and 1.2% of HPSS reported their main
source of support was someone within their sport (such
as a member of HPSS or sport psychologist), while few
reported mainly receiving support from a mental health
professional (no coaches, 1.7% of HPSS).
Satisfaction with life balance was endorsed by less
than half of the coach sample (43.6%) and just over half
of the HPSS sample (54.9%). e majority of partici-
pants rated their quality of life as ‘good’ or ‘very good’
Table 1 Demographics and sport-related characteristics
Dash (–) indicates n < 5
Demographic and sport‑related characteristics Coaches % (n) HPSS % (n)
Mean age (SD) 46.4 (8.78) 40.0 (9.65)
Gender (% female) 23.8 (19) 56.7 (102)
Australian-born 77.8 (63) 83.9 (151)
Employer
National Sporting Organization 66.2 (49) 64.2 (111)
National Institute Network 33.8 (25) 35.8 (62)
Employment modality
Full time 83.8 (67) 67.2 (121)
Part time (> 0.5 FTE) 6.3 (5) 14.4 (26)
Part time (< 0.5 FTE) 3.8 (–) 7.8 (14)
Casual 6.3 (5) 10.6 (19)
Other work in previous month
Voluntary 18.5 (15) 8.9 (16)
Paid casual 11.1 (9) 12.8 (23)
Paid part time 11.1 (9) 15.0 (27)
Paid full time 4.9 (–) 7.8 (14)
Duration working in high-performance sport
Less than 12 months 0.0 (–) 2.2 (–)
1 year 2.5 (–) 3.9 (7)
2–3 years 6.2 (5) 14.4 (26)
4–5 years 11.1 (9) 11.1 (20)
6–9 years 19.8 (16) 17.2 (31)
10 years or more 60.5 (49) 51.1 (92)
Sport type
Individual sport 55.0 (44) 66.7 (112)
Team sport 45.0 (36) 33.3 (56)
Preparing athletes for upcoming competition 66.3 (53) 76.0 (136)
Time travelling for sport (past 12 months)
Less than 1 month 14.8 (12) 46.4 (83)
1–2 months 39.5 (32) 29.6 (53)
3–4 months 29.6 (24) 19.6 (35)
5–6 months 7.4 (6) 2.2 (–)
6 months or more 8.6 (7) 2.2 (–)
Missed significant life events due to sport-related travel 71.6 (58) 49.7 (89)
Concerned for safety while travelling
Personal concern 16.0 (13) 6.1 (11)
Family/friends expressed concern 28.4 (23) 21.2 (38)
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Pilkingtonetal. Sports Medicine - Open (2022) 8:89
(64.9% of coaches; 73.8% of HPSS), while a small number
rated their quality of life as ‘poor’ or ‘very poor’ (9.1% of
coaches; 8.7% of HPSS).
Strategies forManaging Stress andMental Well‑Being
Participants endorsed using a range of strategies to man-
age their stress and mental well-being, with few differ-
ences observed between coaches and HPSS. e most
commonly utilized strategies included talking with a
friend/partner (reported by 71.4% of coaches and 83.8%
of HPSS), exercising for pleasure (67.5% coaches; 80.2%
HPSS), engaging in routine enjoyable activities such as
walking the dog or listening to music (59.7% coaches;
74.3% HPSS) and sleeping (61.0% coaches; 71.9% HPSS).
A small number reported doing nothing to manage their
stress or mental well-being (6.5% coaches; 3.6% HPSS),
and even fewer reported they did not know how to man-
age their stress or mental well-being (3.9% coaches; 1.8%
HPSS).
Possible Impacts ofCOVID‑19
Given that data collection occurred during the onset of
the COVID-19 pandemic (March–May 2020), we exam-
ined possible impacts of concern about COVID-19 on
the major outcome measures (GHQ-28, K-10, ASSQ and
AUDIT-C). Independent samples t tests were used to
examine concern about the presence of COVID-19 (Y/N)
and outcome measures, with results demonstrating no
significant differences between participants who reported
feeling concerned about the pandemic compared to those
who did not (in all instances, p > 0.01 for all).
Comparisons According toRole, Gender andSport Type
e rates of mental health symptoms for coaches and
HPSS are presented in Table2. While a significant pro-
portion met the threshold for caseness (~ 40%) and risky
alcohol consumption (41.8%), the reported rates of high
to very high psychological distress (13.9%) were com-
paratively lower. For all major outcome measures (i.e., the
K-10, GHQ-28, AUDIT-C and ASSQ), group compari-
sons were made according to role (coach vs HPSS), gen-
der (male vs female) and sport type (individual vs team
sport). No significant differences were observed accord-
ing to role (p > 0.01 for all). Within the coach sample,
no significant group differences according to gender or
sport type were observed (all p > 0.01). In contrast, male
HPSS reported significantly higher alcohol consump-
tion than females on the basis of AUDIT-C total scores
Table 2 Reported mental health symptoms among coaches and HPSS compared to published elite athlete samples
No statistically signicant dierences were found between coaches and HPSS. Comparisons were made between the coach sample and published athlete samples
and between the HPSS sample and published athlete samples, *p < .01, **p < .001. For GHQ-28 caseness, the cuto score 5 or more has been used. For risky alcohol
consumption, the cuto score 4 or more has been used for females and 5 or more has been used for males. Using cutos recommended by the IOC [24] of 3 or more
for women and 4 or more for men, 56.6% of participants met risky drinking criteria (59.7% of coaches, 55.2% of HPSS). K-10 scores between 22 and 50 were suggestive
of ‘high to very high’ distress
Measure Coaches HPSS Published athlete samples
GHQ-28
Total score M (SD) 20.62 (9.87) 20.70 (9.95) 19.66 (10.81) [3]
Somatic complaints M (SD) 5.56 (3.42) 5.68 (3.76) 5.53 (3.58) [3]
Anxiety/insomnia M (SD) 6.27 (4.53) 6.38 (4.46)* 5.47 (4.51) [3]*
Social dysfunction M (SD) 7.58 (2.39) 7.82 (2.71)* 7.17 (2.64) [3]*
Severe depression M (SD) 1.27 (2.58) 0.77 (1.53)** 1.50 (2.77) [3]**
Caseness % 43.6 40.1 35 [3]
K-10
Total score M (SD) 15.58 (4.95) 15.75 (5.25) 16.40 (5.89) [3]
High to very high distress % 10.3 15.5 17.7 [3]
ASSQ
Total score M (SD) 5.73 (2.48) 5.09 (2.35) 5.3 (–) [41]
No sleep disturbance % 32.5 40.7 43 [27]
Mild sleep disturbance % 44.2 44.2 41 [27]
Moderate sleep disturbance % 18.2 12.8 16 [27]
Severe sleep disturbance % 5.2 2.3 0 [27]
AUDIT-C
Total score M (SD) 3.88 (2.55) 3.18 (2.12) 4.28 (2.61) [28]
Risky alcohol consumption % 48.1** 39.0** 25.8 [15]**
Satisfaction with life total score M (SD) 25.22 (5.75) 25.91 (5.40) 26.6 (5.95) [3]
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Pilkingtonetal. Sports Medicine - Open (2022) 8:89
(mean = 3.77 vs 2.77, p = 0.004; medium effect: Cohen’s
d = 0.47). Additionally, a larger proportion of female
HPSS reported that they had sought mental health treat-
ment at some stage relative to their male counterparts
(43.1% vs 23.0%, p = 0.006), although this reflected a
small effect (Cramer’s V = 0.21).
Comparisons Between Coach andHPSS Outcomes
andPublished Elite Athlete Data
Separate comparisons were made between the coach
and HPSS samples and published elite athlete data (see
Table2; also see community comparisons in Additional
file 1: Table S3). e only statistically significant dif-
ference observed in relation to coaches was a higher
reporting of risky/hazardous alcohol consumption (X2
(1, N = 450) = 13.60, p < 0.001; small effect: Cramer’s
V = 0.17). Overall, 48.1% of coaches met hazardous/risky
drinking criteria.
In comparison with published athlete data, HPSS
scored significantly higher (i.e., worse) on two of the
GHQ-28 subscales: the anxiety/insomnia subscale
(p = 0.008; Cohen’s d = 0.20) and the social dysfunction
subscale (p = 0.002; Cohen’s d = 0.24). However, HPSS
reported significantly lower (i.e., better) scores on the
severe depression subscale than the comparable ath-
lete sample (p < 0.001; Cohen’s d = 0.33). Finally, HPSS
reported significantly lower scores than athletes on
the ASSQ (p < 0.001; Cohen’s d = 0.28), suggesting less
sleep disturbance among HPSS compared to the athlete
sample.
As per coaches, HPSS were more likely than athletes to
report risky alcohol consumption, X2 (1, N = 545) = 7.61,
p < 0.01 (weak effect: Cramer’s V = 0.12). Overall, 39.0%
of HPSS met risky drinking criteria. No differences were
observed between HPSS and a comparable athlete sam-
ple on the K-10 total score or the proportion reporting
‘high to very high’ distress (p > 0.01 for both).
Correlates ofMental Health andAlcohol Consumption
Given the overall lack of differences between coach
and HPSS mental health outcome measures, data were
pooled to examine correlates of mental health and well-
being symptoms, using coaches and HPSS as a combined
group. Relationships were assessed between each out-
come and a range of possible correlates. Tables3, 4 and 5
display the correlates that were significant in the univari-
able and/or multivariable modeling stage.
Correlates ofPsychiatric Caseness/Morbidity (GHQ‑28)
As Table3 indicates, a range of factors were associated
with meeting the threshold for caseness on the GHQ-
28 in the unadjusted model. e variables that remained
significant in the adjusted model were satisfaction with
social support and satisfaction with life balance, both of
which predicted lower odds of meeting caseness criteria.
Correlates ofPsychological Distress (K‑10)
Unadjusted and adjusted models for the odds of report-
ing higher median K-10 total scores are shown in Table4.
After controlling for the effects of salient predictors from
the unadjusted model, the adjusted model indicated that
satisfaction with life balance, satisfaction with social sup-
port and (older) age were associated with lower (i.e., bet-
ter) psychological distress scores.
Correlates ofAlcohol Consumption (AUDITC)
In the unadjusted model, the only significant correlate for
alcohol consumption (AUDIT-C) scores was satisfaction
with life balance (p = 0.001), where satisfaction was asso-
ciated with lower reported alcohol consumption. Given
that satisfaction with life balance was the only significant
correlate in the unadjusted model, no multivariate mod-
eling was performed for this outcome variable.
Correlates ofSleep Disturbance (ASSQ)
Unadjusted and adjusted models of sleep disturbance
are shown in Table5. In the adjusted model, the odds
of reporting higher ASSQ scores (indicative of elevated
sleep disturbance) was only significantly associated with
satisfaction with social support.
Discussion
To our knowledge, this is the first study to examine the
rates of common mental health concerns in HPSS, and to
compare coach and HPSS mental health and well-being
outcomes to published elite athlete data. e results
show that coaches and HPSS report similar mental health
symptom profiles and that the prevalence of mental
health and well-being concerns is largely consistent with
those previously observed in elite athletes [3, 15, 27, 28].
Satisfaction with social support and satisfaction with life
balance were found to be key correlates of mental health
and well-being outcomes. ese results suggest that
coaches and HPSS are susceptible to the pressures asso-
ciated with high-performance sports settings and may
benefit from access to appropriate mental health sup-
ports and strengthening the known protective factors for
mental health that are increasingly being advocated for
elite athletes (e.g., [31]).
Comparing Estimated Rates ofMental Health Concerns
withPublished Athlete Data
e proportion of coaches and HPSS reporting men-
tal health symptoms at a level that would warrant pro-
fessional treatment (i.e., caseness) was approximately
40%. is rate is similar to that previously observed in
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Page 9 of 14
Pilkingtonetal. Sports Medicine - Open (2022) 8:89
a comparable elite athlete sample (35%) [3], but nota-
bly higher than community norms (see Additional file1:
TableS3). e proportion of coaches meeting caseness
criteria (43.6%) was consistent with the rate of 39.5%,
which was reported in a recent study of coaches by Keg-
elaers and colleagues [14], as was the proportion of HPSS
meeting caseness criteria (40.1%). Notably, 34.5% of par-
ticipants also reported accessing psychological treatment
Table 3 Unadjusted and adjusted odds ratios for GHQ-28 caseness; multi-predictor logistic regression for GHQ-28 caseness
Bold indicates the factor is signicant at p < .01 or .001 level. Dash (–) indicates there were insucient numbers in the group
Factor Level Unadjusted OR (95% CI) p value Adjusted OR (95% CI) p value
Age (years) 0.96 (0.93, 0.99) 0.004 0.96 (0.92, 0.99) 0.041
Relationship status Single/never married Reference Reference
Partnered 0.44 (0.13, 1.47) 0.182 0.77 (0.17, 3.52) 0.738
De facto/living together 0.46 (0.17, 1.23) 0.122 0.46 (0.13, 1.56) 0.211
Married 0.66 (0.31, 1.42) 0.286 1.59 (0.55, 4.59) 0.388
Separated 1.00 (0.00, 0.00) < .001
Divorced 0.22 (0.04, 1.20) 0.081 0.22 (0.03, 1.70) 0.146
Widowed N/A
Not reported 0.88 (0.05, 15.37) 0.932
Sexual orientation Heterosexual Reference Reference
Same sex attracted 1.00 (0.00, 0.00) < .001
Bisexual 1.00 (0.00, 0.00) < .001
Don’t know 2.09 (0.34, 12.71) 0.426 2.81 (0.21, 37.32) 0.434
Other N/A
Not reported 1.00 (0.00, 0.00) < .001
Gender Binary female 1.22 (0.73, 2.02) 0.452 1.24 (0.63, 2.44) 0.530
Binary male Reference Reference
Non-binary N/A
Not sure 1.00 (0.00, 0.00) < .001
Not reported 1.00 (0.00, 0.00) 0.000
Aboriginal or Torres Strait Islander No Reference Reference
Yes 1.00 (0.00, 0.00) < .001
Not reported 0.57 (0.30, 1.10) 0.095
Highest educational level completed No formal schooling 1.00 (0.00, 0.00) < .001
Primary school N/A
Year 10–11 0.50 (0.05, 4.87) 0.549
Year 12 1.24 (0.51, 3.02) 0.628 1.68 (0.59, 4.79) 0.331
University degree Reference Reference
Trade/Apprenticeship/TAFE 1.49 (0.59, 3.75) 0.393 2.51 (0.78, 8.05) 0.122
Not reported 1.00 (0.00, 0.00) < .001
Accommodation Living at family home Reference Reference
Living with host family N/A
Living in college/university N/A
Renting 1.75 (0.52, 5.94) 0.366 2.08 (0.49, 8.88) 0.324
Own home (mortgage) 1.04 (0.32, 3.33) 0.954 0.83 (0.21, 3.20) 0.788
Own home (outright) 0.61 (0.15, 2.43) 0.483 0.98 (0.18, 5.37) 0.980
Other 1.00 (0.00, 0.00) < .001
Not reported 1.60 (0.08, 31.77) 0.758
Satisfaction with life balance Yes 0.25 (0.15, 0.43) < .001 0.40 (0.21, 0.77) 0.006
No Reference Reference
Not reported 0.74 (0.05, 12.15) 0.835
Satisfaction with social support Yes 0.62 (0.49, 0.79) < .001 0.65 (0.49, 0.87) 0.004
No Reference Reference
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Pilkingtonetal. Sports Medicine - Open (2022) 8:89
Table 4 Unadjusted and adjusted odds ratios (beta-coefficients) for median total K-10 scores; multi-predictor median regression for
psychological distress
Bold indicates the factor is signicant at p < .01 or .001 level. Dash (–) indicates there were insucient numbers in the group
Factor Level Unadjusted β‑coecient
(95% CI) p value Adjusted β‑coecient (95% CI) p value
Age (years) 0.16 ( 0.23, 0.09) < .001 0.09 ( 0.14, 0.03) 0.003
Sexual orientation Heterosexual Reference Reference
Same sex attracted 2.00 ( 3.26, 7.26) 0.455 0.33 ( 3.82, 4.47) 0.877
Bisexual 2.00 ( 8.46, 12.46) 0.707 2.85 ( 5.50, 11.19) 0.502
Don’t know 14.00 (9.68, 18.32) < .001 1.46 ( 2.26, 5.17) 0.440
Other
Not reported 3.00 ( 13.46, 7.46) 0.573
Any psychological or mental health treatment Yes 2.00 (0.73, 3.27) 0.002 0.72 ( 0.54, 1.97) 0.261
No Reference Reference
Not reported
Current psychological or mental health treatment Yes 5.00 (2.34, 7.66) < .001 1.15 ( 1.34, 3.65) 0.364
No Reference Reference
Not reported
Satisfaction with life balance Yes 3.00 ( 4.20, 1.80) < .001 1.93 ( 3.25, 0.61) 0.004
No Reference Reference
Not reported 2.00 ( 7.52, 11.52) 0.679
Satisfaction with social support Yes 1.75 ( 2.23, 1.27) < .001 1.38 ( 1.91, 0.86) < 0.001
No Reference Reference
Felt undervalued or underpaid (ever) Yes 2.00 (0.48, 3.52) .010 0.556 ( 0.57, 1.68) .332
No Reference Reference
Table 5 Unadjusted and adjusted odds ratios (beta-coefficients) for median total ASSQ scores; multi-predictor median regression for
sleep disturbance
Bold indicates the factor is signicant at p < .01 or .001 level. Dash (–) indicates there were insucient numbers in the group
Factor Level Unadjusted β‑coecient (95%
CI) p value Adjusted β‑coecient (95% CI) p value
Aboriginal or Torres Strait Islander No Reference Reference
Yes 1.00 ( 5.54, 3.54) 0.665
Not reported 1.00 ( 1.70, 0.30) 0.005
Highest educational level completed No formal schooling
Primary school
Year 10–11 1.00 ( 2.04, 4.04) 0.518 1.00 ( 1.94, 3.94) 0.503
Year 12 1.00 ( 0.35, 2.35) 0.146 0.50 (-0.63, 1.63) 0.386
University degree Reference Reference
Trade/Apprenticeship/TAFE 2.00 (0.59, 3.41) 0.006 1.50 (0.26, 2.74) 0.018
Not reported 1.00 ( 7.03, 5.03) 0.744 N/A
Satisfied with life balance Yes 1.00 ( 1.60, 0.40) 0.001 1.50 ( 2.20, 0.80) 0.018
No Reference Reference
Not reported N/A N/A
Satisfaction with social support Yes 0.75 ( 1.05, 0.45) < .001 0.50 ( 0.79, 0.21) 0.001
No Reference Reference
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Page 11 of 14
Pilkingtonetal. Sports Medicine - Open (2022) 8:89
at some stage, suggesting responsiveness to mental health
symptoms and openness to treatment among this group.
e relatively high proportion of coaches and HPSS in
this sample meeting caseness criteria (and reporting past
help-seeking) suggests that it is not just competing (as
an athlete) in elite sports that confers a risk for mental
ill health, but operating within the broader social ecology
of high-performance sport and the attendant pressures
associated with these systems that may be relevant.
In further support of hypotheses 1 and 2, no difference
was observed between psychological distress reported by
coaches or HPSS compared to athletes. Coach and HPSS
psychological distress was also similar to community
norms (Additional file1: TableS3) [32, 33]. While these
findings do not align with Kim and colleagues’ study [13],
which found the prevalence of reported depressive symp-
toms among coaches to be similar to the general com-
munity, but lower than elite athletes, they are consistent
with Kegelaers and colleagues’ results, which found
similar reporting of mental health symptoms between
elite-level coaches and athletes [14]. ese mixed find-
ings likely reflect the early stage of empirical research
into elite coach mental health and indicate the need for
further attention. Possible differences across studies are
also important to consider in relation to sport-specific
factors, such as period of the competitive season, per-
formance outcomes or sport type. e lack of differences
in mental health symptoms observed between HPSS and
elite athletes in this study is a unique contribution to the
literature and supports the need for investment in mental
health support services that are offered to all key stake-
holders in elite sports settings rather than only athletes
(such as the AIS Mental Health Referral Network [34],
which has been expanded to support coaches and HPSS,
in addition to current and former athletes).
Risky alcohol consumption was reported by a signifi-
cantly higher proportion of coaches and HPSS than elite
athletes [15], with 48.1% of coaches and 39.0% of HPSS
reporting potentially risky levels of alcohol consump-
tion (with no significant difference between coaches and
HPSS). e reporting of elevated alcohol consumption
in the coach and HPSS groups relative to athletes may
relate to coaches and HPSS not being subject to the same
physical fitness and performance demands as elite ath-
letes (including physical metrics such as skin fold tests
and weigh-ins), who consistently report low rates of alco-
hol and other substance use [35, 36]. However, coaches
and HPSS reported significantly lower levels of alcohol
consumption than community norms (Additional file1:
TableS3) [37]. To our knowledge, no other studies have
examined alcohol consumption in HPSS and only two
other studies [14], 15 have examined alcohol consump-
tion in elite coaches, reporting lower levels than those
observed here. Future studies could consider coach and
HPSS alcohol consumption in response to performance
outcomes (e.g., poor performance) and work-related
stress in order to ascertain optimal methods to sup-
port such staff in high-pressure and high-performance
(including ‘win at all costs’) settings.
e responses of the HPSS group on the GHQ-28 indi-
cated higher reporting of anxiety/insomnia and social
dysfunction symptoms, and lower severe depression
symptoms, than the comparable elite athlete sample. It is
unclear why these differences were found for HPSS and
not coaches. One possible reason regarding the anxiety
symptoms is that the HPSS sample represented a more
even gender distribution than the coach sample (which
had a higher proportion of male participants). Given that
previous research has shown elevated anxiety in females
relative to males among elite athlete samples [10] and in
the general population [38], the elevated scores on the
anxiety/insomnia and social dysfunction subscales in
the HPSS but not coach group are perhaps unsurpris-
ing (given this difference in gender breakdown between
groups).
Similarities andDierences Between Coaches andHPSS
Coaches and HPSS reported similar mental health and
well-being scores on all major outcome measures. is is
consistent with the finding that an almost identical rate
of coaches and HPSS reported seeking treatment for a
mental health problem (approximately 1 in 3 for both).
In further support of H2, coaches and HPSS also
reported similar adverse life events and similar strate-
gies for managing stress and mental well-being. Of note,
approximately half of the coaches and HPSS reported
feeling undervalued or underpaid (across the lifetime).
Sporting organizations are encouraged to consider strat-
egies for highlighting the value of members of the daily
training environment, whether through financial com-
pensation, public recognition, enhancing the organi-
zational culture or other strategies. Research using
qualitative methods would be particularly valuable for
exploring ways that coaches and HPSS can be supported
to feel better valued.
Additionally, approximately half of the coaches and
HPSS reported satisfaction with life balance and satisfac-
tion with their available social support. is is consistent
with previous work, where elite coaches also reported
having a lack of life balance (e.g., lack of time to spend
with family, competing responsibilities) [13]. Given that
both satisfaction with life balance and satisfaction with
social support were key protective factors for mental ill
health among elite coaches and HPSS, there should be
dedicated efforts to strengthen these factors, particularly
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Page 12 of 14
Pilkingtonetal. Sports Medicine - Open (2022) 8:89
during periods of higher workload and pressure (e.g., in
the lead-up to major competition).
Correlates ofMental Health andWell‑Being
e most robust correlates in this sample were satisfac-
tion with social support and satisfaction with life bal-
ance, which both showed negative associations with
symptoms of common mental health concerns and psy-
chological distress. Satisfaction with social support was
also negatively associated with sleep disturbance, while
satisfaction with life balance was negatively associated
with alcohol consumption. Social support and life bal-
ance are well-known modifiable protective factors for
mental health [39, 40]. Enhancing these protective fac-
tors in coaches and HPSS not only has the potential to
directly enhance coach and HPSS well-being, but also
has the potential to improve these factors among athletes
through the role modeling of a healthy life balance and
the importance of maintaining supportive relationships.
Few sport-related or demographic variables were sig-
nificantly associated with the outcome measures in the
adjusted analyses, with the exception that younger age
was associated with elevated psychological distress. No
significant gender differences or differences according to
sport type were found in the current sample, which sup-
ports findings from prior studies, which also report a lack
of gender differences in mental health symptoms among
elite coaches [13, 14]. However, this is in contrast to pre-
vious research with elite athlete samples, which show
elevated reporting of mental health symptoms in females
[10] and athletes from individual sports [11]. Taken
together, these findings tentatively suggest the potential
for a differential effect of gender between athletes ver-
sus non-athlete members of the daily training environ-
ment in terms of mental health and well-being outcomes.
Future studies would benefit from including a greater
number of female participants to further examine pos-
sible gender differences in mental health and well-being
outcomes in coach and HPSS samples.
Limitations
is study has several limitations, chief among them
being the response rate of 31.5%. It is possible (though
unable to be determined) that coaches and HPSS with
experience of mental health symptoms were more
inclined to participate in the survey, leading to a non-
representative and potentially biased sample. Further-
more, the use of cross-sectional data does not allow for
consideration of changes in mental health and well-being
outcomes across key time points. In particular, it would
be valuable to investigate possible changes in reported
life balance, mental health symptoms, alcohol consump-
tion and sleep disturbance across the competitive season
and following various performance outcomes. Investigat-
ing the relationship between performance and mental
health outcomes is paramount, particularly in the con-
text of findings by Kegelaers et al. [14], who reported
that performance-based stressors had the highest self-
reported impact on Dutch and Flemish coach mental
health (followed by organizational stressors, then per-
sonal stressors). It is also recommended that future stud-
ies consider the examination of the broader spectrum of
mental health experiences, rather than merely presence
of mental health symptomatology. Finally, the survey
was launched in March 2020 and closed in May 2020 (by
which time the postponement of the Tokyo Olympics and
Paralympics had been confirmed). e significant disrup-
tion to participants in light of the pandemic and atten-
dant lockdowns may have influenced the survey response
rate, although no major differences in the main outcomes
according to reported concern about the pandemic were
found.
Conclusions
is paper describes the mental health and well-being of
252 elite coaches and HPSS from a range of sports within
Australia’s high-performance sport system. Results
showed similar profiles between coaches and HPSS on
the included measures. Despite relatively high rates of
probable caseness, coaches and HPSS scored favorably
on the measure of alcohol consumption (in comparison
with community data) and a relatively high proportion
reported previous help-seeking for mental health prob-
lems. Coaches and HPSS also reported similar mental
health and well-being profiles as elite athlete samples,
with the exception of higher alcohol consumption in
coaches and HPSS relative to athletes. Some mixed find-
ings were observed with the HPSS group, where they
reported elevated symptoms of anxiety/insomnia and
social dysfunction, but lower scores on the measure of
severe depression, relative to athletes. Although only
approximately half of the coaches and HPSS reported
satisfaction with their life balance and their social sup-
port, these were the most robust correlates of the mental
health and well-being outcomes included in this paper,
where both acted as key protective factors for mental ill
health. Based on these findings, sporting organizations
should be aware that members of the daily training envi-
ronment are relatively likely to experience mental health
difficulties and should aim to strengthen key protective
factors in members of the daily training environment,
including optimal life balance and social supports.
Abbreviations
HPSS: High-performance support staff; AIS: Australian Institute of Sport; GHQ-
28: General Health Questionnaire-28 items; K-10: Kessler Psychological Distress
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Page 13 of 14
Pilkingtonetal. Sports Medicine - Open (2022) 8:89
Scale-10 items; ASSQ: Athlete Sleep Screening Questionnaire; AUDIT-C:
Alcohol Use Disorders Identification Test-Consumption.
Supplementary Information
The online version contains supplementary material available at https:// doi.
org/ 10. 1186/ s40798- 022- 00479-y.
Additional le1. Supplementary Table1. Adverse events reported by
coaches and HPSS. Supplementary Table2. Coach and HPSS reported
strategies for managing stress and mental wellbeing. Supplementary
Table3. Reported mental health symptoms among coaches and HPSS
compared to published community samples.
Acknowledgements
We thank Larry Hendricks for developing the online survey, Tim Spelman for
assisting with the statistical analyses and Pamela Dyson for assisting with
project coordination and providing relevant details from the AIS.
Author Contributions
VP made comparisons between participant data and published data and
was a major contributor in writing and preparing the manuscript. RP was the
project lead. Authors SR, CW, LO, KG and RP contributed to the manuscript
based on their expertise surrounding the mental health and well-being of
elite sportspeople. Authors MB, MC and GC contributed to the manuscript
based on their knowledge of the AIS and relevant stakeholders and were
also responsible for compiling updated contact information for all eligible
participants and coordinating the distribution of survey links to potential
participants. All authors have read and approved the final manuscript.
Funding
Australian Sports Commission.
Availability of Data and Materials
The data that support the findings of this study are available on request from
the corresponding author [VP] and with the permission of the Australian
Institute of Sport. The data are not publicly available due to them containing
information that could compromise research participant privacy.
Declarations
Ethics Approval and Consent to Participate
The research was approved by, and conducted in accordance with, the ethical
standards of the University of Melbourne Human Ethics Research Committee
(#13718) and the 1964 Helsinki Declaration.
Consent for Publication
All participants were made aware that data provided would be used for
publication.
Competing interests
Authors MB, MC and GC are employed by the Australian Institute of Sport,
which is funded by the Australian Sports Commission. Their involvement in
the study included the survey design and contributions to the final manu-
script, but not to the survey implementation or data analysis. The remaining
authors have no conflicts of interest to declare.
Author details
1 The Centre for Youth Mental Health, The University of Melbourne, Melbourne,
VIC, Australia. 2 Elite Sports and Mental Health, Or ygen, 35 Poplar Road,
Parkville, VIC 3052, Australia. 3 School of Psychology, Faculty of Health, Deakin
University, Geelong, VIC 3220, Australia. 4 Australian Institute of Sport, People
Wellbeing and Engagement, Bruce, Australia.
Received: 5 April 2022 Accepted: 14 June 2022
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