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Background: Physical inactivity is a key contributor to the global burden of disease and disproportionately impacts the wellbeing of people experiencing mental illness. Increases in physical activity are associated with improvements in symptoms of mental illness and reduction in cardiometabolic risk. Reliable and valid clinical tools that assess physical activity would improve evaluation of intervention studies that aim to increase physical activity and reduce sedentary behaviour in people living with mental illness. Methods: The five-item Simple Physical Activity Questionnaire (SIMPAQ) was developed by a multidisciplinary, international working group as a clinical tool to assess physical activity and sedentary behaviour in people living with mental illness. Patients with a DSM or ICD mental illness diagnoses were recruited and completed the SIMPAQ on two occasions, one week apart. Participants wore an Actigraph accelerometer and completed brief cognitive and clinical assessments. Results: Evidence of SIMPAQ validity was assessed against accelerometer-derived measures of physical activity. Data were obtained from 1,010 participants. The SIMPAQ had good test-retest reliability. Correlations for moderate-vigorous physical activity was comparable to studies conducted in general population samples. Evidence of validity for the sedentary behaviour item was poor. An alternative method to calculate sedentary behaviour had stronger evidence of validity. This alternative method is recommended for use in future studies employing the SIMPAQ. Conclusions: The SIMPAQ is a brief measure of physical activity and sedentary behaviour that can be reliably and validly administered by health professionals.
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R E S E A R C H A R T I C L E Open Access
Assessing physical activity in people with
mental illness: 23-country reliability and
validity of the simple physical activity
questionnaire (SIMPAQ)
S. Rosenbaum
, R. Morell
, A. Abdel-Baki
, M. Ahmadpanah
, T. V. Anilkumar
, L. Baie
, A. Bauman
, S. Bender
J. Boyan Han
, S. Brand
, S. Bratland-Sanda
, J. Bueno-Antequera
, A. Camaz Deslandes
, L. Carneiro
A. Carraro
, C. P. Castañeda
, F. Castro Monteiro
, J. Chapman
, J. Y. Chau
, L. J. Chen
, B. Chvatalova
L. Chwastiak
, G. Corretti
, M. Dillon
, C. Douglas
, S. T. Egger
, F. Gaughran
, M. Gerber
, E. Gobbi
K. Gould
, M. Hatzinger
, E. Holsboer-Trachsler
, Z. Hoodbhoy
, C. Imboden
, P. S. Indu
, R. Iqbal
F. R. Jesus-Moraleida
, S. Kondo
, O. Lederman
, E. H. M. Lee
, B. Malchow
, E. Matthews
P. Mazur
, A. Meneghelli
, A. Mian
, B. Morseth
, D. Munguia-Izquierdo
, L. Nyboe
A. Perram
, J. Richards
, A. J. Romain
, M. Romaniuk
, D. Sadeghi Bahmani
, M. Sarno
, F. Schuch
N. Schweinfurth
, B. Stubbs
, R. Uwakwe
, T. Van Damme
, E. Van Der Stouwe
, D. Vancampfort
, S. Vetter
A. Waterreus
and P. B. Ward
Background: Physical inactivity is a key contributor to the global burden of disease and disproportionately impacts
the wellbeing of people experiencing mental illness. Increases in physical activity are associated with improvements
in symptoms of mental illness and reduction in cardiometabolic risk. Reliable and valid clinical tools that assess
physical activity would improve evaluation of intervention studies that aim to increase physical activity and reduce
sedentary behaviour in people living with mental illness.
Methods: The five-item Simple Physical Activity Questionnaire (SIMPAQ) was developed by a multidisciplinary,
international working group as a clinical tool to assess physical activity and sedentary behaviour in people living
with mental illness. Patients with a DSM or ICD mental illness diagnoses were recruited and completed the SIMPAQ
on two occasions, one week apart. Participants wore an Actigraph accelerometer and completed brief cognitive
and clinical assessments.
Results: Evidence of SIMPAQ validity was assessed against accelerometer-derived measures of physical activity. Data
were obtained from 1010 participants. The SIMPAQ had good test-retest reliability. Correlations for moderate-
vigorous physical activity was comparable to studies conducted in general population samples. Evidence of validity
for the sedentary behaviour item was poor. An alternative method to calculate sedentary behaviour had stronger
evidence of validity. This alternative method is recommended for use in future studies employing the SIMPAQ.
Conclusions: The SIMPAQ is a brief measure of physical activity and sedentary behaviour that can be reliably and
validly administered by health professionals.
Keywords: Physical activity, Measurement, Mental illness, Exercise, Assessment, Sedentary behaviour
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* Correspondence:
School of Psychiatry, UNSW Sydney, Sydney, Australia
Full list of author information is available at the end of the article
Rosenbaum et al. BMC Psychiatry (2020) 20:108
People with mental disorders experience high rates of co-
morbid chronic physical diseases including diabetes, obes-
ity, and cardiovascular disease, contributing to an increased
mortality risk, regardless of psychiatric diagnosis [1,2]. Al-
though genetic factors contribute to overall cardio-
metabolic risk, the role of modifiable lifestyle behaviours,
such as physical inactivity and low physical fitness are be-
coming better recognised [3,4]. Increasing physical activity
remains a cornerstone of metabolic and cardiovascular dis-
ease treatment and prevention in the general population
[5], with growing recognition that cardiorespiratory fitness
is inversely associated with all-cause mortality [6]. A 2019
Lancet Psychiatry Commission on protecting the physical
health of people with mental illness recommended that
physical activity be incorporated as part of routine psychi-
atric care regardless of diagnosis and across all treatment
settings [7]. In addition to the established physical health
benefits, physical activity can have both preventive and
treatment effects on psychiatric symptomatology for people
experiencing a range of mental disorders, including depres-
sion [810], anxiety disorders [11]andpsychosis[12].
People with mental disorders have been shown to be sig-
nificantly less physically active or less likely to meet inter-
national physical activity recommendations [4,1315].
Despite numerous calls for physical activity to be recog-
nised as an integral component of routine psychiatric care
[16], including recognition in the recent WHO guidelines
[17], access to programs and integration within mental
health services remains ad-hocinmanyjurisdictions,with
limited funding or resources available for implementation
in routine clinical care [18].
One barrier to the implementation of physical activity
programs within mental health settings is the lack of a
clinical tool to assess physical activity that enables risk
stratification based on activity levels. Similarly, without a
clinically feasible tool that can be used as part of routine
care, evaluating the effectiveness of interventions de-
signed to increase physical activity is problematic. Cur-
rently methods used to assess physical activity vary in
cost, accuracy and feasibility [19].
Furthermore, no self-reported physical activity measures
have been developed specifically for people with mental ill-
ness and there is little consensus regarding the utility of
existing self-report questionnaires. A 2014 review of the
psychometric properties of physical activity assessment
tools identified 10 unique self-report questionnaires that
had been used in psychiatric populations with limited evi-
dence for robust psychometric properties [20]. Arguably,
themostcommonlyusedquestionnaire for research pur-
poses is the International Physical Activity Questionnaire
(IPAQ). The IPAQ was developed in 2003 specifically for
assessing population levels of total physical activity and
allowing for cross-country comparison [21,22]. In 2006,
the measurement properties of the IPAQ (short-form) in
35 people with schizophrenia who were living in the com-
munity, were found to be comparable to those in the gen-
eral population [23]. The IPAQ has been used extensively
to measure physical activity in people diagnosed with men-
tal health conditions [24] including as a measure of change
in clinical intervention studies. The validity of the IPAQ to
assess total sedentary behaviour has also been questioned,
with recent data suggesting that the IPAQ is unsuitable for
population level assessment of sitting time among individ-
uals with schizophrenia [25]. Furthermore, a recent study
using data from the UK Biobank found that, although
people with schizophrenia self-reported the same physical
activity levels as the general population assessed using the
IPAQ, objective measures revealed that they were overall
less active than 80% of the general population, providing
evidence that existing self-report measures used in epi-
demiological studies of physical activity may fail to capture
lower physical activity levels in schizophrenia [26].
Use of the IPAQ in clinical settings may also be prob-
lematic for a number of reasons and differs from the
intended purpose of the tool which was to conduct popu-
lation surveillance [22]. For example, physical activity last-
ing less than 10min is not assessed using self-report
questionnaires such as the IPAQ, despite the potential
mental health benefits of such activity. The Second Edi-
tion of the Physical Activity Guidelines for Americans
published in 2018, note that any amount of physical activ-
ity has some health benefits, and removed the recommen-
dation that only 10-min bouts of physical activity counted
towards meeting the guidelines [27]. Finally, while the
IPAQ assesses total levels of physical activity, it does not
differentiate between activities performed for the purposes
of structured exercise and physical activities performed as
part of daily life, which may also have important implica-
tions for mental health outcomes [28].
The measurement of physical activity in people with
mental illness presents unique challenges given diagnos-
tic heterogeneity and differing symptom profiles among
psychiatric patients. For example, clinical variability in
mood may influence the ability to accurately respond to
self-report questionnaires, especially among people who
experience symptom fluctuations such as those with
rapid-cycling bipolar disorder. Psychotic symptoms,
grandiosity, and severe symptoms of depression and anx-
iety are also likely to influence the utility of self-report
measures. In addition, people with mental illness may
have unique barriers to accessing exercise facilities such
that hospitalization may result in restricted opportunities
to engage in physical activity. Alternatively, inpatient ad-
mission may allow access to customised physical activity
interventions in some settings. Given that physical activ-
ity is a key strategy to prevent cardio-metabolic disease
[17], a leading cause of premature mortality in people
Rosenbaum et al. BMC Psychiatry (2020) 20:108 Page 2 of 12
with mental illness, a measure appropriate for routine
clinical use in this population is required.
In order to ensure the accurate assessment of physical
activity across people with mental illness, we developed
a self-report, physical activity measurement tool, de-
signed to be administered via interview. The Simple
Physical Activity Questionnaire (SIMPAQ) is a tool suit-
able for routine clinical use, and the current study was
conducted to determine the reliability and validity of the
SIMPAQ for assessing physical activity among inpatients
and outpatients experiencing mental illness.
Approval was obtained from the Human Research Ethics
Committee (HREC) of UNSW Sydney, Australia (HC15586)
as the lead site. In addition, local ethics approval was sought
from each participating site as per local requirements. Details
of approving committees are provided under the Declaration
section below.
SIMPAQ development
The SIMPAQ was iteratively developed between April 2014
and May 2016 by a multidisciplinary, international working
group with both clinical and research expertise (including
psychiatrists, psychologists, physiotherapists, exercise physi-
ologists, and epidemiologists) regarding physical health care
interventions for people living with mental illness. The first
meeting was held in Padua, Italy, in April, 2014, to identify
the common challenges experienced when assessing phys-
ical activity among people with mental illness. At a subse-
quent meeting in July, 2015, held at the Institute of
Psychiatry, Psychology and Neuroscience in London (UK),
consensus agreement on the wording of the questions that
constitute the SIMPAQ was obtained.
Participating Research sites
In addition to disseminating information about the pro-
ject via the international workgroup, an editorial was
published in 2016 describing the proposed validation
process that helped to identify additional study sites
[29]. All study material and administration protocols
were available from the project website (www.simpaq.
org) when recruitment commenced in May 2016. All
sites were required to nominate a site coordinator and
sign an authorship agreement document. Along with
study material, site coordinators received a briefing from
investigators SR and PBW and were also in regular con-
tact with the study coordinator RM. Eligibility criteria
for potential sites included willingness to recruit patients
meeting the inclusion criteria outlined below and avail-
ability of a site coordinator with expertise in either men-
tal health or physical activity research.
Translation process
Translation was conducted according to the Principles of
Good Practice for the Translation and Cultural Adaptation
Process for Patient-Reported Outcomes (PRO) Measures,
as proposed by the International Society of Pharmacoeco-
nomics and Outcomes (ISPOR) [30]. This process involved
ten steps including 1) preparation, 2) forward translation, 3)
reconciliation, 4) back translation, 5) back translation re-
view, 6) harmonization, 7) cognitive debriefing, 8) review of
cognitive debriefing results and finalization, 9) proof read-
ing, 10) publication on SIMPAQ website.
All participants were required to provide written informed
consent and be willing to wear an accelerometer for seven
days. Eligibility criteria also included: i) aged between 18
and 65 years, ii) a current inpatient or outpatient of one of
the treatment facilities identified as a SIMPAQ validation
study site and iii) met DSM-5 or ICD-10 criteria for any
mental disorder, excluding eating disorders.
Study procedures
Participants were approached by a researcher nominated
by the site coordinator who was not involved in the dir-
ect care of the patient. The researcher obtained written
informed consent. Data was collected from each partici-
pant during two face-to-face sessions, at least seven days
apart. Researchers involved in data collection included
either mental health or exercise professionals.
Session 1
Demographic and descriptive information was collected
including assessment of symptoms and cognitive ability.
Participants completed the SIMPAQ (Time 1) and were
given a tri-axial accelerometer (Actigraph GT3x or
GT3x + (both models contain the same accelerometer
and processing method)) along with standardised in-
structions for wearing the device.
Session 2
Participants completed the SIMPAQ (Time 2) covering
the period of accelerometer wear time.
Data collection
Participant demographics and descriptive information
A standardised form was used to obtain demographic and
descriptive information including: age, sex, treatment set-
ting (inpatient or other), years of completed education,
previous 7-day employment status (yes or no), previous 7-
day tobacco smoking status (yes or no), body mass index
(derived from measures of height [m] and weight [kg]).
Each country in which a site acquired SIMPAQ data
was assigned an income status (either high income or
Rosenbaum et al. BMC Psychiatry (2020) 20:108 Page 3 of 12
other) based on World Bank classification (
Psychiatric diagnoses
Psychiatric diagnoses that applied to individual participants
based on medical records were recorded. It was recognized
that participants may meet criteria for more than one psychi-
atric diagnosis, and all diagnoses that applied to each partici-
pant were recorded. The standardised form asked
researchers to tick yes or no for the following diagnostic cat-
egories based on clinical diagnoses; schizophrenia spectrum
disorders, bipolar disorder, depressive disorders, anxiety dis-
orders, obsessive-compulsive disorders, substance-related &
addictive disorders, neurocognitive disorders and other disor-
ders. We identified individuals who were assigned a single
diagnostic category, and those with psychiatric co-morbidity.
Physical health conditions
The presence or absence (yes or no) of the following
physical health conditions at the time of assessment
were also recorded by the researcher; diabetes, high
cholesterol, high blood pressure, stroke and chronic pain
based on self-report and medical records.
Medication status
Researchers were asked to indicate whether participants
were currently prescribed the following classes of psy-
chotropic medication (yes or no): antidepressant, anti-
psychotic, or mood stabilising medications.
Symptom severity DSM-5 self rated level 1 cross cutting
symptom measure
The 23-item DSM-5 Self-rated Level 1 Cross-cutting
Symptom Measure [31] was used to assess symptom se-
verity. This measure consists of 23 questions that assess
13 psychiatric domains, including depression, anger,
mania, anxiety, somatic symptoms, suicidal ideation,
psychosis, sleep problems, memory, repetitive thoughts
and behaviours, dissociation, personality functioning,
and substance use [31]. Each question asks about how
much (or how often) the individual has been bothered
by the specific symptom during the past two weeks and
is rated on a 5-point scale (0 = none or not at all; 1 =
slight or rare, less than a day or two; 2 = mild or several
days; 3 = moderate or more than half the days; and 4 =
severe or nearly every day). We summed the total scores
across these domains and dichotomized the scores
around the median (20); lower symptom severity was de-
fined as scores < 21; higher symptom severity was de-
fined as scores > = 21.
Cognitive functioning Montreal cognitive assessment
The Montreal Cognitive Assessment (MoCA) is a brief
screening tool used to assess cognitive functioning [32].
The MoCA assesses multiple cognitive domains includ-
ing attention and concentration, executive functioning,
memory, language, visuo-constructional skills, concep-
tual thinking, calculation and orientation. Scores ranged
from 0 to 30 with scores of 26 or higher considered
within normal range. Given that many psychiatric syn-
dromes are associated with cognitive impairment (e.g.
schizophrenia), we did not exclude participants scoring
less than 26. Results are reported for those with scores
above and below this threshold.
Simple physical activity questionnaire
The 5-item SIMPAQ required people being interviewed
to account for time spent in bed overnight (box 1), time
sedentary, including napping (box 2), time spent walking
(box 3), time spent exercising (box 4) and time engaged in
incidental activity (box 5), averaged over the past seven-
day period (see Fig. 1). The sum of the hours recorded in
the five SIMPAQ boxes should add to approximately 24-
h, providing interviewers with an opportunity to clarify
with participants if significant under or over-reporting has
occurred (e.g. < 18 h or > 30 h of estimated time). For an
estimate of total self-reported moderate-vigorous physical
activity (MVPA) time, time spent walking (box 3) and ex-
ercising (box 4) were combined to provide total MVPA
(hours per week).
Percentage of 24-h period accounted for by SIMPAQ items
The SIMPAQ was designed to capture activity over a
representative 24-h period from the previous 7-days. By
summing Boxes 1 through 5, the total hours accounted
for should equal approximately 24. To evaluate how well
this was achieved in the current study, we calculated the
fraction of time accounted for by using the following
sedentary time (box 2) + walking time (box 3) +
exercise time (box 4) + incidental activity time (box 5)
24 time in bed (box 1)
Accelerometer Actigraph GT3/x
Participants were asked to wear a tri-axial accelerometer
(Actigraph GT3x or GT3x+; ActiGraph LLC, Fort Walton
Beach, FL) on the right hip during waking hours for a period
of seven consecutive days to objectively assess physical activ-
ity. Accelerometers record raw acceleration data (at a sam-
pling interval of 60 s epochs) that is converted into objective
activity measures such as step counts. Participants were
shown how to wear the device on the right hip using either a
belt clip or elastic waist band. After the seven-day period
Rosenbaum et al. BMC Psychiatry (2020) 20:108 Page 4 of 12
participants returned the device and again completed the
SIMPAQ for comparison with Session 1 data. Prior to Acti-
graph devices being issued to participants they were initia-
lised using the online portal. Each participant was setup in
CentrePoint and sex, age and weight were entered and the
device allocated to the subject. Accelerometry data were re-
trieved from the device using CentrePoint, a secure online
portal designed and distributed by Actigraph specifically for
multi-site study co-ordination. ActiLife v6.13.3 software was
used to extract data from CentrePoint and derive variables
to be used in the calculation of validity between accelerome-
try data and SIMPAQ items. Participant data were included
for analysis if at least eight hours of valid wear time were
available for at least four days. Non wear time was defined as
at least 60 min of consecutive zeroes, allowing for spike level
of 100 counts per minute [33]. We followed Freedson et al.
[34] to classify activity intensity using cutpoints for time
spent in sedentary (< 100 cpm), light (1002019 cpm), mod-
erate (20205998 counts/ min), and vigorous intensity (>
5999 cpm) activity [34].
Data analysis and cleaning
Non-parametric Spearman correlation coefficients were cal-
culated as the primary measure of agreement between as-
sessment time points (Session 1 and Session 2) (test-retest
reliability), and between the SIMPAQ data and accelerom-
eter counts (evidence of validity). Agreement between the
SIMPAQ and accelerometer data was also assessed through
Bland-Altman mean-difference plots with 95% limits of
agreement. Intraclass correlation coefficients (ICC) along
with 95% confidence intervals were also calculated. Analyses
were conducted both with all valid data, and excluding out-
liers defined as those with SIMPAQ values that were greater
or less than 2.5 SD from the mean for that item. Results are
reported for the entire sample with available data and strati-
fied by cognitive function as assessed by the MoCA and
psychiatric symptom severity derived from the DSM
Cross-cutting tool. The sample were also stratified according
to specific diagnoses, and those with psychiatric comorbidity.
Income status, treatment setting, sex, age, body mass index
(BMI) and smoking status data were analysed separately.
Data were analysed using SPSS v24.
Test re-test reliability was determined using Spearman
Rho correlation coefficients between SIMPAQ items at
Session 1 and Session 2. Given that the SIMPAQ asks
responders to report activity from the previous seven-
day period, and the potential for hospital admission to
impact physical activity levels, only data from outpa-
tients were utilised for reliability calculations.
tionnaire, Spearman correlation coefficients were calculated
for MVPA as assessed by the SIMPAQ (box 3 + box 4) and
Fig. 1 Flow diagram of participants and analyses
Rosenbaum et al. BMC Psychiatry (2020) 20:108 Page 5 of 12
MVPA as recorded by the accelerometer, and for sedentary
time (SIMPAQ box 2) against the accelerometer.
In total, data were collected from 1010 participants re-
cruited from 23 countries. More than half of the sample of
participants were male (56%), from a high income country
(77%), between 25 and 54 years old (71%), current
smokers (60%), overweight or obese (60%; mean BMI =
27.1 SD 5.8), did not complete any paid employment in
the previous seven-day period (70%) and were recruited
from an inpatient facility (53%) (See Table 1). Overall,
there was significant psychiatric comorbidity (34%). Of
those with a single diagnosis, the most prevalent condition
was schizophrenia (23%) followed by depression (16%)
and bipolar disorder (14%). In total, 65% of the sample
(n= 648) scored greater than or equal to 26 on the MoCA
indicative of normal cognitive functioning. Regarding
medication usage, 56% of the sample were reported as
Table 1 Demographic characteristics
Total sample 1010
Sex Male 561 56
Female 449 44
Age group 1824 years 156 15
2534 years 243 24
3544 years 231 23
4554 years 238 24
5565 years 142 14
Diagnosis Psychiatric Comorbidity 343 33
Schizophrenia only 233 23
Bipolar disorder only 145 14
Depressive disorder only 159 16
Other 130 14
Psychotropic Medication Antipsychotic 562 56
Antidepressant 477 47
Mood-stabiliser 290 29
Cognitive ability Normal (> = 26) 648 65
impaired (< 26) 354 35
Treatment setting Inpatient 537 53
Outpatient 469 47
Smoking status Smoker 611 60
Non-smoker 399 40
Body mass index (BMI)(kg/m
) Underweight (< 18.5) 32 4
Desired (18.524.99) 305 36
Overweight (2529.99) 267 31
Obese I (3034.99) 171 20
Obese II (3539.99) 50 6
Obese III (4044.99) 27 3
Region Europe 507 50
Asia 249 25
Oceania 144 14
Americas 100 10
Africa 10 1
High income 777 77
Country income status Other (lower-upper middle income) 233 23
Rosenbaum et al. BMC Psychiatry (2020) 20:108 Page 6 of 12
receiving antipsychotic medication, 47% antidepressant
medication and 29% were prescribed mood-stabilisers.
Physical comorbidities were also recorded on the standar-
dised assessment form with hypercholesterolemia (14%)
the most commonly reported, followed by chronic pain
(13%), hypertension (13%) and diabetes (6%).
Percentage of 24-h period accounted for by SIMPAQ
In the overall sample, 70% of a standard 24-h period was
accounted for by the SIMPAQ. This did not vary within
any subgroups, with 7080% of a 24-h time period consist-
ently accounted for across region, country income status,
diagnostic group, cognitive ability, smoking status and age.
Test-retest repeatability was assessed in outpatients (see
Table 2). For these participants (n= 452), Spearman correl-
ation coefficients were 0.75, p< 0.001 (box 1 time spent in
bed), 0.69, p < 0.001 (box 2 time spent sedentary), 0.76,
p < 0.001 (box 3 time spent walking), 0.76, p < 0.001 (box 4
time spent exercising) and 0.63, p < 0.001 (box 5 time
spent in incidental activity), indicating acceptable to good
Evidence of validity
To assess validity, only participants with a minimum of
four valid days of accelerometer data were included. In
addition, for each individual SIMPAQ item, participants
who scored ±2.5SD from the mean were excluded (Fig. 1;
ns for individual items range from n=581to n=653).
Moderate-to-vigorous physical activity
The Spearman rho correlation coefficient between the two
measures for moderate-to-vigorous physical activity was
0.25 for the entire sample with available data (n=617, p<
0.001; ICC = 0.23, 95% CI 0.01 to 0.34) (Table 3). For those
with higher MoCA scores, the Spearman rho correlation
coefficient was 0.32 (n= 401, p < 0.001) and for those with
lower MoCA scores, 0.10 (n= 210, p= 0.17). Validity was
lower in high-income countries, and this was most evident
in data from European sites (Table 3). High-income coun-
tries in Oceania had larger correlations than the full sample.
Larger correlations were observed in current smokers than
those who were non-smokers. Evidence of validity was
lower in those aged 5565. Correlations were higher for
those who were obese compared to those who were normal
weight or overweight. Participants who were inpatients at
the time of assessment had lower correlations than those
who were outpatients. Those with psychiatric comorbidity
showed comparable correlations, while a higher correlation
was found in those with a diagnosis of depression in com-
parison with those with a diagnosis of schizophrenia. There
was no difference in correlations as a consequence of psy-
chiatric symptom severity.
The Bland-Altman plot for MVPA (Fig. 2) indicates
less agreement between the two measures with higher
values of MVPA.
Sedentary time
The Spearman rho correlation coefficient was not statis-
tically significant for the entire sample with available
data (rho = 0.02, n= 653; p= 0.6, ICC = 0.01, 95% CI
0.15 to 0.15) (Table 4). For those with a higher MoCA
score, the Spearman rho correlation coefficient was 0.06
(n= 431) and for those with lower MoCA scores, 0.06
(n= 215). Psychiatric comorbidity did not impact the
magnitude of the correlation and there was no difference
in correlations as a consequence of psychiatric symptom
severity. There was considerable variability in the ob-
served correlation coefficients between SIMPAQ box 2
and sedentary time as assessed by the accelerometer.
The correlation was lower in high income countries, and
highest in Oceania and Asia. Correlations were similar
for smokers and non-smokers, and higher in those who
were older, overweight or obese and outpatients. The
Bland-Altman plot for sedentary time (Fig. 3) showed no
evidence of bias with higher or lower values of sedentary
time as assessed by the two measures.
Alternative method for calculating sedentary time
Given that self-report questionnaires are likely to lead to
underestimates of sedentary behaviour, and given that
the average percentage of time accounted for by the
SIMPAQ as a percentage of 24-h (7080%), we derived
an alternative method of scoring sedentary time from
the SIMPAQ. We summed the scores of time spent in
bed (box 1), time spent walking (box 3), time exercising
(box 4) and time incidental activity (box 5), which we
Table 2 Test-retest reliability of SIMPAQ items (Spearman Rho correlation coefficients) in outpatients
N Box 1: Time in Bed Box 2: Sedentary
Box 3: Walking
Box 4: Exercise
Box 5: Incidental
activity time
Total outpatients 452 0.75 0.69 0.76 0.76 0.63
Outpatients by country income status
high income 323 0.8 0.68 0.59 0.69 0.58
other (lower-upper middle income) 131 0.7 0.49 0.74 0.84 0.81
All ps < 0.001
*Ns for treatment setting and country income status do not equal total sample due to missing demographic data
Rosenbaum et al. BMC Psychiatry (2020) 20:108 Page 7 of 12
defined as non-sedentary time. We subtracted this figure
from 24-h to provide an alternative estimate of sedentary
behaviour. Evidence of validity for this alternative
method was statistically significant for the overall sample
(rho = 0.19, n= 581, p< 0.001; ICC = 0.29, 95% CI 0.17 to
4.0 (Table 5).
This study examined the test-retest reliability and evi-
dence of validity of a novel, brief, interview-based, self-
reported physical activity measure, designed for routine
clinical use within psychiatric settings. In a large diverse
sample of psychiatric patients, ascertained across a var-
iety of treatment settings and including a range of psy-
chiatric diagnoses, with substantial representation from
low- and middle- income countries, we found that the
SIMPAQ was a reliable tool for assessing physical activ-
ity and sedentary behaviour. Evidence of validity for
MVPA was higher for outpatients than inpatients and
was comparable to that reported in general population
samples [35,36] and in smaller cohorts of people with
mental illness [23].
In physical activity research, correlation coefficients be-
tween self-report and objective measures of physical activ-
ity of 0.3 are often reported as acceptable evidence of
validity [3539]. This limited shared variance reflects the
challenges associated with both self-report questionnaires
and accelerometers when assessing physical activity in the
general population. Given that the correlations found for
the SIMPAQ were not substantially lower than those
deemed acceptable in general population samples, attests
to the utility of the SIMPAQ in people with mental illness
who can experience a range of additional challenges e.g.
psychiatric symptoms and cognitive impairment.
Correlations were lower for those with MoCA scores
below the usual cut-off indicative of cognitive impair-
ment. We explicitly did not use the MoCA score as an
exclusion criterion considering that a number of psychi-
atric syndromes are characterised by cognitive impair-
ment, e.g. schizophrenia. While the reliability of the
Table 3 Correlations between MVPA assessed via the SIMPAQ
and accelerometry
N Spearman rho p
Total sample 617 0.25 < 0.001
male 340 0.25 < 0.001
female 274 0.23 < 0.001
Treatment setting
inpatient 346 0.09 0.11
outpatient 264 0.43 < 0.001
Country income status
high income 480 0.12 0.01
other (lower-upper middle income) 134 0.26 0.002
Cognitive ability
normal (> = 26) 401 0.32 < 0.001
impaired (< 26) 210 0.10 0.17
psychiatric comorbidity 212 0.25 < 0.001
schizophrenia only 130 0.13 0.14
bipolar disorder only 78 0.23 0.04
depressive disorder only 112 0.33 < 0.001
*All participants with available data were included in each analysis
Fig. 2 Bland-Altman plot of absolute difference between MVPA assessed via SIMPAQ and accelerometery derived MVPA estimate
Rosenbaum et al. BMC Psychiatry (2020) 20:108 Page 8 of 12
SIMPAQ was largely unaffected by cognitive capacity, it
is evident that those with lower MoCA scores had a
lower correlation with objectively measured MVPA.
Therefore, self-reported MVPA in those with higher
levels of cognitive impairment may be less accurately
For the overall sample, self-reported and objectively
assessed sedentary time were not significantly correlated.
Significant correlations were found for outpatients,
which may reflect the statistically significant lower
symptom severity (p< 0.001) and greater cognitive (p <
0.001) capacity of our outpatient sample. People living
with more severe mental illness may engage in high
levels of sedentary behaviour, and combined with some
degree of cognitive impairment, are likely to experience
particular difficulty in accurately estimating sedentary
time [40]. Additionally, the poor correlations between
the SIMPAQ and objective measure of sedentary behav-
iour can be in part explained by the fact that the Acti-
graph was waist-mounted and therefore is not a true
assessment of postural allocation (i.e. sitting or stand-
ing). Therefore low intensity activities performed while
sitting or standing may have been misclassified [41].
Given the known limitations of self-reported estimates
of sedentary behaviour in both the general population [41]
and in people living with mental illness [25,26], we gener-
ated an alternative method for calculating sedentary time
using the SIMPAQ data (see Section 3.5). This involved
summing the scores of non-sedentary time estimates
(boxes 1, 3, 4 and 5) and subtracting this from 24h. This
method therefore takes into account the tendency for
underreporting of sedentary behaviour and based on the
correlation analysis, appears to be a more valid estimate of
sedentary behaviour in the target population. Based on
these results, we recommend users of SIMPAQ adopt this
alternative scoring method to obtain more valid estimate
of sedentary behaviour, especially among inpatients and
those with high levels of cognitive impairment. Future
Fig. 3 Bland-Altman plot of absolute difference between sedentary time assessed via SIMPAQ and accelerometery derived estimate
Table 4 Correlations between sedentary behaviour assessed via
the SIMPAQ and accelerometry
N Spearman rho p
Total sample 653 0.02 0.57
Male 360 0.08 0.12
Female 274 0.08 0.19
Treatment setting
inpatient 377 0.08 0.14
outpatient 269 0.14 0.02
Country income status
high income 518 0.04 0.38
other (lower-upper middle income) 132 0.11 0.23
Cognitive ability
normal (> = 26) 431 0.06 0.22
impaired (< 26) 215 0.06 0.41
psychiatric comorbidity 220 0.03 0.71
schizophrenia only 140 0.04 0.66
bipolar disorder only 84 0.08 0.47
depressive disorder only 123 0.03 0.72
*All participants with available data were included in each analysis
Rosenbaum et al. BMC Psychiatry (2020) 20:108 Page 9 of 12
research should also aim to investigate the validity of the
SIMPAQ sedentary behaviour item using inclinometers.
The evidence of validity of the SIMPAQ as a tool to as-
sess MVPA was comparable to other self-report measures
in the general population (e.g. [36]), and results were rela-
tively consistent across diagnoses, sex and age. Unsurpris-
ingly, we found different levels of correlations in different
settings and among different sub-groups within the sam-
ple. It should be noted that SIMPAQ was designed to be
used as a clinical tool administered by health professionals
regardless of training or expertise in exercise prescription
or assessment. In some of the participating centres, SIM-
PAQ was administered by exercise specialists (e.g. physical
therapists or exercise physiologists), whereas in other sites
SIMPAQ was administered by staff with primary mental
health qualifications (e.g. psychiatrists or psychiatric
nurses). There was no evidence of greater validity in set-
tings where exercise professionals administrated the SIM-
PAQ versus mental health professionals. Given the diverse
backgrounds of people likely to administer the SIMPAQ,
the table in Item 4 of the tool deliberately allows for either
a brief summary, or a more comprehensive assessment of
exercise time (e.g. by completing the entire Table) if clin-
ically indicated or the assessor has available time.
Limitations of this study include the opportunistic sam-
pling method that does not reflect the global diagnostic
prevalence of different psychiatric disorders. While effort
was made to recruit a diverse sample of participants from
a range of settings including high and low income coun-
tries, there was an overrepresentation from high income,
English speaking countries. Regarding the development of
the SIMPAQ, in order to maximise clinical utility, we
aimed to ensure that administration time was minimised
and therefore comprehensive assessment of detailed as-
pects of physical activity such as the domain are not spe-
cifically evaluated. Another limitation is the use of
accelerometers as the objective measure of physical activ-
ity. While accelerometers are cheaper and more accessible
than other forms of objective measurement, they are not
without limitations including the inability to assess move-
ment associated with non-ambulatory activity (e.g. cycling
and resistance training) [42].
In conclusion, we demonstrated that the SIMPAQ is a
reliable and valid tool to assess physical activity in
people living with mental illness. SIMPAQ does not re-
quire detailed training, identifies even small amounts of
activity which is useful in providing positive feedback to
patients participating in physical activity interventions, is
quick to administer and did not prove difficult for
people with mental health problems to complete. These
initial results are promising and suggest that the instru-
ment is an appropriate tool for routine use in clinical
mental health services. Assessing and promoting phys-
ical activity as a component of care within mental health
services is a key means by which the physical and mental
health of this population can be improved.
BMI: Body mass index; MoCA: The Montreal Cognitive Assessment (MoCA);
MVPA: Moderate-vigorous physical activity; SIMPAQ: Simple Physical Activity
SR is funded by an NHMRC Early Career Fellowship (APP1123336). BS is
supported by Health Education England and the National Institute for Health
Research HEE/ NIHR ICA Programme Clinical Lectureship (ICA-CL-2017-03-
001). FG and BS are part supported by the Maudsley Charity and the
National Institute for Health Research (NIHR) Collaboration for Leadership in
Applied Health Research and Care South London (NIHR CLAHRC South
London) at Kings College Hospital NHS Foundation Trust with support from
the National Institute for Health Research (NIHR) Biomedical Research Centre
at South London and Maudsley NHS Foundation Trust. The views expressed
in this publication are those of the authors and not necessarily those of the
NHS, the National Institute for Health Research or the Department of Health
and Social Care. JBA was supported by the Spanish Ministry of Education
(FPU13/05130). AW recived funding from the Raine Medical Research
SR & PBW conceived the study concept and design. RM was the study
coordinator. AB, AC, FG, MG, JR, FS, BS, AW, DV made up the executive
committee and led the development of the tool with input from other
authors. FS coordinated the translation process. ZH, TVA, EG, STE, CI, AW,
JBH, RI, PSI, SV, MH, MA, DMI, PWC, AMe, SB, NS, AAB, PM and AMi were site
Table 5 Correlations between sedentary behaviour assessed via
the SIMPAQ and accelerometry, using the alternative SIMPAQ
scoring method
N Spearman rho p
Total sample 581 0.19 < 0.001
Male 319 0.20 < 0.001
Female 259 0.18 < 0.01
Treatment setting
inpatient 331 0.22 < 0.001
outpatient 243 0.18 < 0.01
Country income status
high income 474 0.24 < 0.001
other (lower-upper middle income) 104 0.14 0.16
Cognitive ability
normal (> = 26) 384 0.15 < 0.01
impaired (< 26) 191 0.25 < 0.001
psychiatric comorbidity 199 0.27 < 0.001
schizophrenia only 126 0.26 < 0.01
bipolar disorder only 74 0.04 0.76
depressive disorder only 112 0.09 0.32
*All participants with available data were included in each analysis
Rosenbaum et al. BMC Psychiatry (2020) 20:108 Page 10 of 12
co-ordinators and facilitated recruitment and data collection. JYC, JR, AB, SR
and PBW led the data analyses. SR and PBW were responsible for drafting
the manuscript. All other authors were responsible for critical revision of the
manuscript and have accepted the final version. All authors read and
approved the final manuscript.
No funding was obtained for this study.
Availability of data and materials
The dataset used during the current study is available from the
corresponding author on reasonable request.
Ethics approval and consent to participate
Approval was obtained from the Human Research Ethics Committee (HREC)
of UNSW Sydney, Australia (HC15586) as the lead site. In addition, local ethics
approval was sought from each participating site as per local requirements
and are listed below. Written informed consent was obtained from all
participants. South East Sydney Local Health Distrcit (16/082 (LNR/16/POWH/
142)); Waterford Institute of Technology (15/NUR/04); UPC Z.ORG KU Leuven
(EC2016307); Comité déthique de la recharche du CHUM (16.184); REK
Regionale Komiteer for Medisinsk og Helsefaglig Forskningsetikk (2016/696/
REK nord); NSD Institutt for idrettsfag Finnmarksfakultetet UiT Norges arktiske
universitet (48719); Melbourne Health (HREC/16/MH/415); The Aga Khan
University (4576-Obs-ERC-16); QIMR Berghofer Medical Research Institute
(P2280); St John of God Health Care (1093); Tsaotun Psychiatric Center,
Ministry of Health and Welfare (105024); UCLA Medical IRB 3 (13001078);
University of Washington IRB Committee J (STUDY00001841); The University
of Western Australia (RA/4/1/8018); University of Wollongong (2017/006); HSE
North East Area Research Ethics Committee; Independent Ethics Committe of
the Biomedical Sciences Department for the approval of human
experimentation (HEC-DSB 05/16); Grupo de pesquisa e pós-graduação
(CAAE 51453115.7.1001.5327); Hospital Universitario Walter Cantidio (943.677);
Ethical Committee of Central Region Denmark (11072-106-16); Nnamdi
Azikiwe University Teaching Hospital Ethics Committee (NAUTH/CS/66/VOL
11//115/055); Ethikkommission Nordwest- und Zentralschweiz EKNZ (Ethical
commission of Northwest and Central Switzerland) (201601547); Northern
Metropolitan Health Service Research and Ethics Committee (000143);
Human Ethics Committee Trivandrum (06/01/2016/MCT); Ludwig-Maximilians
University Munich (60916); Greenslopes Research and Ethics Committee
(16/40); Hospital das Clinicas of Federal University of Rio Grande do Sul
(51453115.7.1001.5327); Ethik-Kommission der Medizinischen Fakultät der
Universität Duisburg-Essen (177327-BO); Independent Ethics Committe of
the Biomedical Sciences Department for the approval of human experimen-
tation (HEC-DSB 05/16).
Consent for publication
Not Applicable.
Competing interests
The authors declare that they have no competing interests .
Author details
School of Psychiatry, UNSW Sydney, Sydney, Australia.
Centre de Recherche
du Centre Hospitalier de lUniversité de Montréal (CRCHUM), Montreal,
Behavioral Disorders and Substances Abuse Research Center,
Hamadan University of Medical Sciences, Hamadan, Iran.
Department of
Psychiatry, Government Medical College, Trivandrum, India.
Department of
Psychosomatics and Psychotherapy, University Hospital Münster, Münster,
School of Public Health, University of Sydney, Sydney, Australia.
LWL-Klinik Marsberg, Hospital for Psychiatry, Psychotherapy and
Psychosomatics, Marsberg, Germany.
California State University, Los Angeles,
University of Basel, Psychiatric Clinics, Center for Affective, Stress and
Sleep Disorders, Basel, Switzerland.
Department of Biomolecular Sciences,
University of Urbino, Urbino, Italy.
The Sutherland Hospital, South Eastern
Sydney Local Health District, Sydney, Australia.
Department of Sport,
Physical Education and Outdoor Studies, University of South-Eastern Norway,
Bø, Notodden, Norway.
Physical Performance & Sports Research Center,
Department of Sports and Computer Science, Section of Physical Education
and Sports, Faculty of Sports Sciences, Universidad Pablo de Olavide, Seville,
Psychiatry Institute, Universidade Federal do Rio de Janeiro, Rio de
Janeiro, Brazil.
Research Centre in Sports Sciences, Health Sciences and
Human Development, CIDESD, GERON Research Community, Vila Real,
Faculty of Education, Free University of Bolzano, Bolzano, Italy.
Early Intervention Program, JHorwitz Psychiatric Institute, Santiago, Chile.
Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande
do Sul, Porto Alegre, Brazil.
QIMR Berghofer Medical Research Institute,
Brisbane, Australia.
Department of Health Systems and Populations,
Macquarie University, Sydney, Australia.
Department of Exercise Health
Science, National Taiwan University of Sport, Taichung, Taiwan.
Institute of Mental Health, Klecany, Czech Republic.
Department of
Psychiatry and Behavioral Sciences, University of Washington, Seattle, USA.
Department of Mental Health, North-West Tuscany, Italy.
HSE Louth
Meath Mental Health Services, Louth, Ireland.
South Coast Private Hospital,
Wollongong, Australia.
Department of Psychiatry, Faculty of Medicine,
University of Oviedo, Oviedo, Spain.
Department of Psychiatry,
Psychotherapy and Psychosomatics, University Hospital of Psychiatry Zurich,
University of Zurich, Zurich, Switzerland.
South London and Maudesley
NHS Foundation Trust, London, UK.
Department of Sport, Exercise and
Health, Division of Sport and Psychosocial Health, University of Basel, Basel,
St John of God Hospital, North Richmond, Australia.
Psychiatric Services Solothurn, Solothurn, Switzerland.
Adult Psychiatric
Clinics (UPKE), University of Basel, Basel, Switzerland.
Department of
Paediatrics and Child Health, The Aga Khan University, Karachi, Pakistan.
Private Clinic Wyss, Muenchenbuchsee, Switzerland.
Department of
Community Medicine, Government Medical College, Trivandrum, India.
Department of Community Health Sciences, Aga Khan University, Karachi,
Department of Physical Therapy, Universidade Federal do Ceará,
Fortaleza, Brazil.
Department of Neuropsychiatry, The University of Tokyo
Hospital, Tokyo, Japan.
Graduate Institute of Sports and Health, National
Changhua University of Education, Changhua, Taiwan.
Keeping the Body In
Mind, South Eastern Sydney Local Health District, Sydney, Australia.
Department of Psychiatry, University of Hong Kong, Hong Kong, China.
Department of Psychiatry and Psychotherapy, University Medical Center
Göttingen, Göttingen, Germany.
School of Health Sciences, Waterford
Institute of Technology, Waterford, Ireland.
Association of early intervention
in mental disorders-Cambiare la Rotta-Onlus, Milano, Italy.
Department of
Psychiatry, Aga Khan University, Karachi, Pakistan.
School of Sport Sciences,
UiT The Arctic University of Norway, Tromsø, Norway.
Department of
Affective Disorders, Aarhus University Hospital, Aarhus, Denmark.
the National Centre of Excellence in Youth Mental Health, Melbourne,
Faculty of Health, Victoria University Wellington, Wellington, New
Gallipoli Medical Research Institute, Brisbane, Australia.
Kermanshah University of Medical Sciences, Sleep Disorders and Substance
Abuse Prevention Research Center, Kermanshah, Iran.
Department of Sports
Methods and Techniques, Federal University of Santa Maria, Santa Maria,
Department of Psychological Medicine, Kings College London,
London, England.
Faculty of Medicine, Nnamdi Azikiwe University, Awka,
Department of Rehabilitation Sciences, KU Leuven, Leuven,
University of Groningen, University Medical Center Groningen,
University Center of Psychiatry, Groningen, Netherlands.
Epidemiology Research Unit, School of Population and Global Health,
University of Western Australia, Perth, Australia.
Schizophrenia Research
Unit, Ingham Institute of Applied Medical Research, Liverpool, Australia.
Received: 15 July 2019 Accepted: 30 January 2020
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Rosenbaum et al. BMC Psychiatry (2020) 20:108 Page 12 of 12
... A recently introduced questionnaire for assessing PA and SB among patients with mental disorders, the Simple Physical Activity Questionnaire (SIMPAQ) [47], considers time spent in PA and SB and the context for these related questions. The SIMPAQ seeks information about time spent in bed overnight, sedentary time, including napping, time spent awake, time spent exercising, and time engaged in incidental activity, averaged over the previous seven-day period [47]. ...
... A recently introduced questionnaire for assessing PA and SB among patients with mental disorders, the Simple Physical Activity Questionnaire (SIMPAQ) [47], considers time spent in PA and SB and the context for these related questions. The SIMPAQ seeks information about time spent in bed overnight, sedentary time, including napping, time spent awake, time spent exercising, and time engaged in incidental activity, averaged over the previous seven-day period [47]. Furthermore, attempts to validate the SIMPAQ by comparing it to the accelerometer to measure PA showed good test-retest reliability [47]. ...
... The SIMPAQ seeks information about time spent in bed overnight, sedentary time, including napping, time spent awake, time spent exercising, and time engaged in incidental activity, averaged over the previous seven-day period [47]. Furthermore, attempts to validate the SIMPAQ by comparing it to the accelerometer to measure PA showed good test-retest reliability [47]. These data support the idea that more detailed questionnaires are needed for self-report PA assessment, perhaps even more so for patients with mental disorders. ...
Full-text available
The purpose of this research was to investigate the degree of agreement between data from the International Physical Activity Questionnaire—Short Form (IPAQ) and accelerometer (ActiGraph®) readings for physical activity (PA), classified as moderate, vigorous, and moderate–vigorous PA, and sedentary behavior (SB) in participants with major depressive or bipolar disorder. Following a cross-sectional observational design (n = 30), participants used an accelerometer for 4 to 7 days (minimum of 10 h per day) and answered the IPAQ (for the same period as accelerometer use). Our results suggest significant differences (p < 0.05) when comparing the ActiGraph® and IPAQ data: for moderate PA, 155 min vs. 25 min per week; for moderate–vigorous PA, 157 min vs. 50 min per week; and for SB, 8 h vs. 3 h per day. Spearman’s correlation coefficients (ActiGraph® and IPAQ) were low for moderate PA, vigorous PA, and moderate–vigorous PA (rho = 0.03 to 0.13). The Bland–Altman plot showed a bias of −75 min for moderate PA, 9 min for vigorous PA, −66 min for moderate–vigorous PA, and −5 h for SB. Considering the differences observed and the objectivity of the ActiGraph® measurements, whenever possible, we recommend ActiGraph® measurements of PA and SB for these clinical groups.
... Based on the scattering of meal and snack times, a score for the regularity of mealtimes can be established [37,56,57]. Physical activity will be measured by the SIMPAQ [58] which was validated for the mentally ill [59]. ...
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Background A subgroup of patients with Major Depressive Disorder shows signs of low-grade inflammation and metabolic abberances, while antidepressants can induce weight gain and subsequent metabolic disorders, and lacking antidepressant response is associated with inflammation. Objectives A comprehensive investigation of patient phenotypes and their predictive capability for weight gain and treatment response after psychotropic treatment will be performed. The following factors will be analyzed: inflammatory and metabolic markers, gut microbiome composition, lifestyle indicators (eating behavior, physical activity, chronotype, patient characteristics (childhood adversity among others), and polygenic risk scores. Methods Psychiatric inpatients with at least moderate Major Depressive Disorder will be enrolled in a prospective, observational, naturalistic, monocentric study using stratified sampling. Ethical approval was obtained. Primary outcomes at 4 weeks will be percent weight change and symptom score change on the Montgomery Asberg Depression Rating Scale. Both outcomes will also be binarized into clinically relevant outcomes at 5% weight gain and 50% symptom score reduction. Predictors for weight gain and treatment response will be tested using multiple hierachical regression for continuous outcomes, and multiple binary logistic regression for binarized outcomes. Psychotropic premedication, current medication, eating behavior, baseline BMI, age, and sex will be included as covariates. Further, a comprehensive analysis will be carried out using machine learning. Polygenic risk scores will be added in a second step to estimate the additional variance explained by genetic markers. Sample size calculation yielded a total amount of N = 171 subjects. Discussion Patient and physician expectancies regarding the primary outcomes and non-random sampling may affect internal validity and external validity, respectively. Through the prospective and naturalistic design, results will gain relevance to clinical practice. Examining the predictive value of patient profiles for weight gain and treatment response during pharmacotherapy will allow for targeted adjustments before and concomitantly to the start of treatment.
Purpose: The aim of this study is to evaluate the validity and reliability of the Turkish version of the Simple Physical Activity Questionnaire (SIMPAQ) in patients with common mental disorders. Methods: A total of eighty-one patients (mean age: 40.14 ± 13.05 years) were included in this study. The Turkish version of the SIMPAQ was used to evaluate the physical activity levels and sedentary behaviors of the participants. To be used as descriptive data, DSM-5 Level 1 Cross-Cutting Symptom Measure-Adult was used to evaluate mental health symptomatology. International Physical Activity Questionnaire-Short Form (UFAA-SF) and Brief Psychiatric Rating Scale (BPRS) were used to test validity of the questionnaire. Results: The items of Turkish version of the SIMPAQ exhibited excellent intercorrelation coefficient (ICC) values (time spent in bed (0.93 (95% CI: 0.90-0.96)), sedentary time 0.87 (95% CI: 0.80-0.92), walking time 0.98 (95% CI: 0.98-0.99), exercise time 0.99 (95% CI: 0.99-0.99), and incidental activity time 0.95 (95% CI: 0.92-0.97)). However, the BPRS had a significant correlation with only the sedentary time of the SIMPAQ (rho=0.25, p=0.02), indicating convergent validity was poor. Conclusion: The Turkish version of the SIMPAQ is semantically and linguistically adequate to quickly assess physical activity level and sedentary behavior in patients with common mental disorders.
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Background: Factors that contribute to the early mortality observed in psychotic disorders, specifically obesity, smoking and sedentary behaviour, occur early in the disorder. Aims: We aimed to determine whether the integration of a physical health nurse in the care of young people with first-episode psychosis could prevent clinically significant weight gain (≥7% body weight). Secondary outcomes included rates of smoking, metabolic syndrome and sedentary behaviour. Method: In this single-blind, randomised controlled trial, participants who had received under 4 weeks of antipsychotic medication were randomly allocated to either the intervention (addition of a physical health nurse to their care) or treatment as usual (TAU) for 12 weeks. Results: Of the 77 participants, there were follow-up data for 86.8% (n = 33) of the intervention group and 82.1% (n = 32) of the TAU group. After 12 weeks, 27.3% of the intervention group experienced clinically significant weight gain compared with 34.4% of the TAU group (odds ratio 0.72, 95% CI 0.25-2.06, P = 0.54). After 6 months, 40.7% of the intervention group gained clinically significant weight compared with 44.1% of the TAU group (P = 0.79). There was no difference in mean change in weight between groups after 12 weeks (2.6 kg v. 2.9 kg, P = 0.87) or 6 months (3.6 kg v. 4.3 kg, P = 0.64). There were no differences in the rates of tobacco smoking cessation, prevalence of metabolic syndrome or physical activity levels. Conclusions: This intervention failed to prevent the metabolic complications that are highly prevalent in psychotic disorders in the short to medium term, indicating that more intensive interventions are required.
Purpose This cross-sectional study aimed (a) to explore levels of compassion satisfaction, secondary traumatic stress, and symptoms of burnout among Ugandan mental health nurses working in regional referral hospitals in Uganda during the Covid-19 pandemic, and (b) to investigate associations between compassion satisfaction, secondary traumatic stress, and symptoms of burnout and sedentary levels, physical activity (PA) levels, sleep quality, and harmful drinking. Material and methods In total 108 mental health nurses from 8 regional referral hospitals across Uganda (age = 34.8 ± 10.0 years; 55.6 % female) completed the Professional Quality of Life Scale-5, (PQoLS-5), the Simple Physical Activity Questionnaire (SIMPAQ), Physical Activity Vital Sign (PAVS), Pittsburgh Sleep Quality Index (PSQI), and Alcohol Use Disorder Identification Test – Concise (AUDIT-C). Spearman Rho correlations and Mann-Whitney U tests were applied. Results ProQOL-5 compassion satisfaction correlated significantly with SIMPAQ walking, PSQI and AUDIT-C, ProQOL-5 burnout with SIMPAQ exercise and PSQI and ProQOL-5 traumatic with SIMPAQ walking and PSQI. Mental health nurses meeting PA guidelines reported higher ProQOL-5 compassion satisfaction and lower ProQOL-5 burnout and traumatic stress than those who did not. Those who reported a poor sleep quality reported significantly less ProQOL-5 compassion satisfaction and higher ProQOL-5 burnout than those who did not. Those who reported harmful drinking patterns reported a significantly lower compassion satisfaction versus those who did not. Discussion In mental health nurses, a lower professional quality of life is associated with an unhealthy lifestyle. The effectiveness and efficacy of resilience and self-care programs for mental health nurses focusing on unhealthy lifestyle patterns should be explored.
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In some regions, such as North America, sports psychiatry strongly focuses on competitive sports and treating psychiatric disorders in elite athletes. In other regions, such as German-speaking countries, sports psychiatry has developed in two ways: competitive sports on the one hand, and physical activity, exercise and sport in the case of mental illnesses on the other. Both topics are also addressed by the Sport and Exercise Psychiatry Special Interest Group (SEPSIG) of the Royal College of Psychiatrists and in the World Psychiatric Association (WBA), Section Sport and Exercise. As shown in this issue by Claussen and colleagues, sports psychiatry professionals today identify several other fields of activities that they consider relevant for this young discipline. Over the past two decades, there has been a steady increase in awareness that physical activity, exercise and sport can play an essential role in preventing and treating mental illness. The number of methodically sound studies has increased significantly. In recent years, knowledge has also been pooled in the form of systematic reviews and meta-analyses. In the meantime, a solid basis of scientific evidence exists, from which conclusions for practice can be derived. As a result, several international professional societies now recommend physical activity, exercise and sport in treating mental disorders as standard therapy. It can also be seen that many psychiatric institutions have moved to follow these recommendations. This is a positive development, as physical activity, exercise and sport in psychiatric care not only positively affect symptom severity but can also counteract increased morbidity and mortality in psychiatric patients.
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Background Physical exercise is an evidence-based treatment to reduce symptoms and negative affect in several psychiatric disorders, including depressive, anxiety, and psychotic disorders. However, the effect of physical exercise on negative affect in patients with borderline personality disorder (BPD) has not yet been investigated. In this pilot study, we tested the safety, acceptability, and potential acute effects on negative affect of a single session of aerobic physical exercise in adults with BPD. Method After completing a negative mood induction procedure, 28 adults with BPD were randomly assigned to a 20-minute single session of stationary bicycle or a control condition (emotionally neutral video). Results No adverse effects attributed to the physical exercise were reported and it was considered acceptable to patients. Following the negative mood induction, both conditions decreased the level of negative affect with a medium effect size but there was no significant difference between them. Conclusion The results suggest that a single 20-minute session of physical exercise does not produce a reduction of negative affect in BPD. Future research should consider the duration and intensities of physical exercise with the greatest potential to reduce negative affect both acutely and in a more prolonged manner in this patient group.
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Background Despite elevated risk of cardiometabolic disease among those with serious mental illness, and widespread recognition that physical activity interventions are required, there are multiple barriers to implementing typically recommended physical activity programmes in secure inpatient settings. Due to low mood, negative symptoms and poor socio-occupational functioning, psychiatric inpatients often lack motivation to engage in physical activity programmes. Moreover, regular access to outdoor spaces and exercise equipment is limited. As such, there is a need for novel physical activity interventions that are suitable for secure settings. This study aims to investigate the feasibility, acceptability and potential effectiveness of an intervention (exergaming) to promote physical activity among patients in a secure mental health setting. Methods This non-randomised, two-arm pilot study will employ a pre-test/post-test parallel group design, comparing the exergaming intervention with a “routine treatment” control. Two high-secure, sub-acute wards in the Long Bay Hospital Mental Health Unit will be non-randomly allocated to either the exergaming intervention or the “routine treatment” control group. The intervention group will receive a 12-week programme comprising three 30-min exergaming sessions per week using various Xbox KinectTM activity-based games designed to simulate moderate intensity exercise. The “routine treatment” group will continue to receive the standard model of care delivered by the Justice Health and Forensic Mental Health Network. Accelerometers will be distributed to all participants to collect daily energy expenditure, number of steps taken, intensity of physical activity and heart rate data throughout the study. The primary outcomes are (1) intervention feasibility and acceptability, and (2) baseline to post-intervention changes in physical health outcomes (levels of physical activity; cardiovascular fitness; clinical measures of cardiometabolic risk). Secondary outcomes are baseline to post-intervention changes in mental health outcomes (depression, anxiety, stress, positive psychiatric symptoms). Outcomes will be assessed at baseline, mid-intervention, and post-intervention. Discussion This research will contribute to evidence-based practice in the care of patients with serious mental illness: a vulnerable population with complex physical and mental health needs and a markedly elevated risk of cardiovascular disease. The findings will inform cardiovascular health promotion strategies and the implementation of physical activity interventions in secure inpatient settings. Trial registration ANZCTR, ACTRN12619000202167. Registered on 12 February 2019, ANZCTR mandatory data items comply with the minimum dataset requirements of the World Health Organisation (WHO). The ANZCTR contributes trial registration data to the WHO International Clinical Trials Registry Platform (WHO ICTRP).
Purpose of review: The aim of this study was to provide psychiatrists with the knowledge, tools and guidance to support physical activity promotion in clinical practice. The review also aims to provide an up-to-date summary of the evidence regarding physical activity in the prevention and treatment of mental disorders in adults. Recent findings: There is emerging evidence demonstrating that physical activity can protect against incident anxiety and depression. There is robust evidence showing that physical activity is an effective adjunct treatment strategy for depressive disorders and anxiety and stress-related disorders, with emerging evidence for schizophrenia and bipolar disorders. Translation of this evidence into practice is in general ad hoc, and large physical health disparities for people with mental disorders persist. The reasons for this are multifactorial, and include the intersection of social, economic and personal barriers to physical activity. Evidence-based approaches include regular screening of physical activity levels, staff culture change within mental health services and established referral pathways. Summary: Translation of evidence regarding physical activity for mental health into routine programmes is critical. Efforts to move beyond solely targeting individual-level barriers to physical activity and address systemic barriers include lack of access to appropriate exercise services. This requires consideration of training needs, service structure and culture change.
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Background This study aimed to investigate the validity of the Active Australia Survey across different subgroups and its responsiveness to change, as few previous studies have examined this. Methods The Active Australia Survey was validated against the ActiGraph as an objective measure of physical activity. Participants (n = 465) wore the ActiGraph for 7 days and subsequently completed the Active Australia Survey. Moderate activity, vigorous activity and total moderate and vigorous physical activity were compared using Spearman rank-order correlations. Changes in physical activity between baseline and 3-month assessments were correlated to examine responsiveness to change. The data were stratified to assess outcomes according to different subgroups (e.g., gender, age, weight, activity levels). Results With regards to the validity, a significant correlation of ρ = 0.19 was found for moderate physical activity, ρ = 0.33 for vigorous physical activity and ρ = 0.23 for moderate and vigorous physical activity combined. For vigorous physical activity correlations were higher than 0.3 for most subgroups, whereas they were only higher than 0.3 in those with a healthy weight for the other activity outcomes. With regards to responsiveness to change, a correlation of ρ = 0.32 was found for moderate physical activity, ρ = 0.19 for vigorous physical activity and ρ = 0.35 for moderate and vigorous physical activity combined. For moderate and vigorous activity combined correlations were higher than 0.4 for several subgroups, but never for vigorous physical activity. Conclusions Little evidence for the validity of Active Australia Survey was found, although the responsiveness to change was acceptable for several subgroups. Findings from studies using the Active Australia Survey should be interpreted with caution. Trial registration World Health Organisation Universal Trial Number: U111–1119-1755. Australian New Zealand Clinical Trials Registry, ACTRN12611000157976. Registration date: 8 March 2011.
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Importance Adverse cardiovascular findings associated with habitual vigorous exercise have raised new questions regarding the benefits of exercise and fitness. Objective To assess the association of all-cause mortality and cardiorespiratory fitness in patients undergoing exercise treadmill testing. Design, Setting, and Participants This retrospective cohort study enrolled patients at a tertiary care academic medical center from January 1, 1991, to December 31, 2014, with a median follow-up of 8.4 years. Data analysis was performed from April 19 to July 17, 2018. Consecutive adult patients referred for symptom-limited exercise treadmill testing were stratified by age- and sex-matched cardiorespiratory fitness into performance groups: low (<25th percentile), below average (25th-49th percentile), above average (50th-74th percentile), high (75th-97.6th percentile), and elite (≥97.7th percentile). Exposures Cardiorespiratory fitness, as quantified by peak estimated metabolic equivalents on treadmill testing. Main Outcomes and Measures All-cause mortality. Results The study population included 122 007 patients (mean [SD] age, 53.4 [12.6] years; 72 173 [59.2%] male). Death occurred in 13 637 patients during 1.1 million person-years of observation. Risk-adjusted all-cause mortality was inversely proportional to cardiorespiratory fitness and was lowest in elite performers (elite vs low: adjusted hazard ratio [HR], 0.20; 95% CI, 0.16-0.24; P < .001; elite vs high: adjusted HR, 0.77; 95% CI, 0.63-0.95; P = .02). The increase in all-cause mortality associated with reduced cardiorespiratory fitness (low vs elite: adjusted HR, 5.04; 95% CI, 4.10-6.20; P < .001; below average vs above average: adjusted HR, 1.41; 95% CI, 1.34-1.49; P < .001) was comparable to or greater than traditional clinical risk factors (coronary artery disease: adjusted HR, 1.29; 95% CI, 1.24-1.35; P < .001; smoking: adjusted HR, 1.41; 95% CI, 1.36-1.46; P < .001; diabetes: adjusted HR, 1.40; 95% CI, 1.34-1.46; P < .001). In subgroup analysis, the benefit of elite over high performance was present in patients 70 years or older (adjusted HR, 0.71; 95% CI, 0.52-0.98; P = .04) and patients with hypertension (adjusted HR, 0.70; 95% CI, 0.50-0.99; P = .05). Extreme cardiorespiratory fitness (≥2 SDs above the mean for age and sex) was associated with the lowest risk-adjusted all-cause mortality compared with all other performance groups. Conclusions and Relevance Cardiorespiratory fitness is inversely associated with long-term mortality with no observed upper limit of benefit. Extremely high aerobic fitness was associated with the greatest survival and was associated with benefit in older patients and those with hypertension. Cardiorespiratory fitness is a modifiable indicator of long-term mortality, and health care professionals should encourage patients to achieve and maintain high levels of fitness.
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Background: Accurate assessment of physical activity is essential to determine the magnitude of the health-related benefits of regular physical activity. While physical activity questionnaires are easy to use, their accuracy in comparison to objective measures has been questioned. The purpose of the present study was to examine the utility of two interview-based questionnaires; a recently-developed instrument, the Simple Physical Activity Questionnaire (SIMPAQ), and the Seven Day-Physical Activity Recall (7DPAR). Methods: Accelerometer data was collected in 72 university students (50% females). Telephone interviews were conducted to complete the SIMPAQ and the 7DPAR. Results: Significant correlations (p<.001) were found between accelerometer-based moderate-to-vigorous physical activity (MVPA), the amount of self-reported moderate-to-vigorous exercise assessed via the SIMPAQ (rho=.49), and vigorous physical activity assessed via the 7DPAR (rho=.50). Exercise assessed via the SIMPAQ was significantly correlated with the vigorous physical activity score of the 7DPAR (rho=.56, p<.001). While participants needed three minutes less to complete the SIMPAQ (p<.001), participants tended to be more confident about the accuracy of the answers they provided on the 7DPAR (p<.01). Conclusions: These two questionnaire measures of physical activity performed similarly in a healthy young adult sample. The SIMPAQ can be completed in 15 minutes, which could be an advantage in settings where time for physical activity assessment is limited.
The aims of this commentary are to (1) examine the current global physical activity recommendations for adults and its relation to mental health, based on findings from meta-analyses primarily of prospective studies, and (2) determine whether there is a need to extend the scope/focus of existing guidelines to ensure they are mental health informed.
People with mental illness have an increased risk of physical disease, as well as reduced access to adequate health care. Physical-health disparities are observed across all mental illnesses in all countries. The high rate of physical comorbidity, which often has poor clinical management, reduces life expectancy for people with mental illness, and increases the personal, social, and economic cost of mental illness across the lifespan. This Commission summarises advances in understanding on the topic of physical health in people with mental illness, and presents clear directions for health promotion, clinical care, and future research. It aims to: (1) Establish highly pertinent aspects of physical health-related morbidity and mortality that have transdiagnostic applications; (2) Highlight the common modifiable factors that drive disparities in physical health; (3) Present actions and initiatives for health policy and clinical services to address these issues; and (4) Identify promising areas for future research that could identify novel solutions.
Importance Increasing evidence shows that physical activity is associated with reduced risk for depression, pointing to a potential modifiable target for prevention. However, the causality and direction of this association are not clear; physical activity may protect against depression, and/or depression may result in decreased physical activity. Objective To examine bidirectional relationships between physical activity and depression using a genetically informed method for assessing potential causal inference. Design, Setting, and Participants This 2-sample mendelian randomization (MR) used independent top genetic variants associated with 2 physical activity phenotypes—self-reported (n = 377 234) and objective accelerometer-based (n = 91 084)—and with major depressive disorder (MDD) (n = 143 265) as genetic instruments from the largest available, nonoverlapping genome-wide association studies (GWAS). GWAS were previously conducted in diverse observational cohorts, including the UK Biobank (for physical activity) and participating studies in the Psychiatric Genomics Consortium (for MDD) among adults of European ancestry. Mendelian randomization estimates from each genetic instrument were combined using inverse variance weighted meta-analysis, with alternate methods (eg, weighted median, MR Egger, MR–Pleiotropy Residual Sum and Outlier [PRESSO]) and multiple sensitivity analyses to assess horizontal pleiotropy and remove outliers. Data were analyzed from May 10 through July 31, 2018. Main Outcomes and Measures MDD and physical activity. Results GWAS summary data were available for a combined sample size of 611 583 adult participants. Mendelian randomization evidence suggested a protective relationship between accelerometer-based activity and MDD (odds ratio [OR], 0.74 for MDD per 1-SD increase in mean acceleration; 95% CI, 0.59-0.92; P = .006). In contrast, there was no statistically significant relationship between MDD and accelerometer-based activity (β = −0.08 in mean acceleration per MDD vs control status; 95% CI, −0.47 to 0.32; P = .70). Furthermore, there was no significant relationship between self-reported activity and MDD (OR, 1.28 for MDD per 1-SD increase in metabolic-equivalent minutes of reported moderate-to-vigorous activity; 95% CI, 0.57-3.37; P = .48), or between MDD and self-reported activity (β = 0.02 per MDD in standardized metabolic-equivalent minutes of reported moderate-to-vigorous activity per MDD vs control status; 95% CI, −0.008 to 0.05; P = .15). Conclusions and Relevance Using genetic instruments identified from large-scale GWAS, robust evidence supports a protective relationship between objectively assessed—but not self-reported—physical activity and the risk for MDD. Findings point to the importance of objective measurement of physical activity in epidemiologic studies of mental health and support the hypothesis that enhancing physical activity may be an effective prevention strategy for depression.
While moderate to vigorous physical activity may be one method of addressing common physical morbidities in schizophrenia, reducing sedentary time may be a low intensity adjunct. In order to determine whether sedentary behaviour is associated with health outcomes, valid and reliable tools for assessing sedentary time are necessary. In order to characterize the validity and reliability of the International Physical Activity Questionnaire (IPAQ) for assessing sitting (sedentary) time, participants completed the IPAQ at baseline and 4 weeks later and wore accelerometers for 7 days before the final assessment. Bland-Altman analyses and intraclass correlation coefficients (ICC) were used to compare agreement between measurements. One-hundred thirteen individuals completed the study. Mean difference between the IPAQ and accelerometer was 26.8 minutes (95% Limits of Agreement: -458.7 to 512.3) and ICCA,1 was 0.23 (95% CI: 0.06 to 0.39). Week 1 and Week 4 administrations of the IPAQ differed by an average of 26.6 minutes, (95% Limits of Agreement: -510.9 to 564.2) and ICCA,1 was 0.41 (95% CI: 0.21 to 0.59). The “minutes” of sitting reported by the IPAQ do not reflect objective sedentary behaviour measurements and this current measure may be unsuitable for the population level assessment of sitting time among individuals with schizophrenia.
Importance Approximately 80% of US adults and adolescents are insufficiently active. Physical activity fosters normal growth and development and can make people feel, function, and sleep better and reduce risk of many chronic diseases. Objective To summarize key guidelines in the Physical Activity Guidelines for Americans, 2nd edition (PAG). Process and Evidence Synthesis The 2018 Physical Activity Guidelines Advisory Committee conducted a systematic review of the science supporting physical activity and health. The committee addressed 38 questions and 104 subquestions and graded the evidence based on consistency and quality of the research. Evidence graded as strong or moderate was the basis of the key guidelines. The Department of Health and Human Services (HHS) based the PAG on the 2018 Physical Activity Guidelines Advisory Committee Scientific Report. Recommendations The PAG provides information and guidance on the types and amounts of physical activity to improve a variety of health outcomes for multiple population groups. Preschool-aged children (3 through 5 years) should be physically active throughout the day to enhance growth and development. Children and adolescents aged 6 through 17 years should do 60 minutes or more of moderate-to-vigorous physical activity daily. Adults should do at least 150 minutes to 300 minutes a week of moderate-intensity, or 75 minutes to 150 minutes a week of vigorous-intensity aerobic physical activity, or an equivalent combination of moderate- and vigorous-intensity aerobic activity. They should also do muscle-strengthening activities on 2 or more days a week. Older adults should do multicomponent physical activity that includes balance training as well as aerobic and muscle-strengthening activities. Pregnant and postpartum women should do at least 150 minutes of moderate-intensity aerobic activity a week. Adults with chronic conditions or disabilities, who are able, should follow the key guidelines for adults and do both aerobic and muscle-strengthening activities. Recommendations emphasize that moving more and sitting less will benefit nearly everyone. Individuals performing the least physical activity benefit most by even modest increases in moderate-to-vigorous physical activity. Additional benefits occur with more physical activity. Both aerobic and muscle-strengthening physical activity are beneficial. Conclusions and Relevance The Physical Activity Guidelines for Americans, 2nd edition, provides information and guidance on the types and amounts of physical activity that provide substantial health benefits. Health professionals and policy makers should facilitate awareness of the guidelines and promote the health benefits of physical activity and support efforts to implement programs, practices, and policies to facilitate increased physical activity and to improve the health of the US population.
Physical activity (PA) may be therapeutic for people with severe mental illness (SMI) who generally have low PA and experience numerous life style-related medical complications. We conducted a meta-review of PA interventions and their impact on health outcomes for people with SMI, including schizophrenia-spectrum disorders, major depressive disorder (MDD) and bipolar disorder. We searched major electronic databases until January 2018 for systematic reviews with/without meta-analysis that investigated PA for any SMI. We rated the quality of studies with the AMSTAR tool, grading the quality of evidence, and identifying gaps, future research needs and clinical practice recommendations. For MDD, consistent evidence indicated that PA can improve depressive symptoms versus control conditions, with effects comparable to those of antidepressants and psychotherapy. PA can also improve cardiorespiratory fitness and quality of life in people with MDD, although the impact on physical health outcomes was limited. There were no differences in adverse events versus control conditions. For MDD, larger effect sizes were seen when PA was delivered at moderate-vigorous intensity and supervised by an exercise specialist. For schizophrenia-spectrum disorders, evidence indicates that aerobic PA can reduce psychiatric symptoms, improves cognition and various subdomains, cardiorespiratory fitness, whilst evidence for the impact on anthropometric measures was inconsistent. There was a paucity of studies investigating PA in bipolar disorder, precluding any definitive recommendations. No cost effectiveness analyses in any SMI condition were identified. We make multiple recommendations to fill existing research gaps and increase the use of PA in routine clinical care aimed at improving psychiatric and medical outcomes.