ORIGINAL INVESTIGATION
Clinical guidelines for the use of lifestyle-based mental health care in major
depressive disorder: World Federation of Societies for Biological Psychiatry
(WFSBP) and Australasian Society of Lifestyle Medicine (ASLM) taskforce
Wolfgang Marx
a
, Sam H. Manger
b,c
, Mark Blencowe
c
, Greg Murray
d
, Fiona Yan-Yee Ho
e
,
Sharon Lawn
f,g
, James A. Blumenthal
h
C3
, Felipe Schuch
i
, Brendon Stubbs
j
, Anu Ruusunen
a,k,l
,
Hanna Demelash Desyibelew
m
, Timothy G. Dinan
n
, Felice Jacka
a
, Arun Ravindran
o
, Michael Berk
a
and Adrienne O’Neil
a
C3
a
Institute for Mental and Physical Health and Clinical Translation (IMPACT), Food & Mood Centre, School of Medicine, Barwon Health,
Deakin University, Geelong, Australia;
b
College of Medicine and Dentistry, James Cook University, Queensland, Australia;
c
Australasian
Society of Lifestyle Medicine, Melbourne, Australia;
d
Centre for Mental Health, Swinburne University of Technology, Melbourne,
Australia;
e
Department of Psychology, The Chinese University of Hong Kong, Hong Kong SAR;
f
Lived Experience Australia Ltd,
Adelaide, Australia;
g
College of Medicine and Public Health, Flinders University, Adelaide, Australia;
h
Department of Psychiatry and
Behavioral Sciences, Duke University Medical Center, Durham, NC, USA;
i
Department of Sports Methods and Techniques, Federal
University of Santa Maria, Santa Maria, Brazil;
j
Department of Psychological Medicine, Institute of Psychiatry, Psychology and
Neuroscience (IoPPN), King’s College London, London, UK;
k
Institute of Public Health and Clinical Nutrition, University of Eastern
Finland, Kuopio, Finland;
l
Department of Psychiatry, Kuopio University Hospital, Kuopio, Finland;
m
Department of Nutrition and
Dietetics, School of Public Health, College of Medicine and Health Sciences, Bahir Dar University, Bahir Dar, Ethiopia;
n
APC
Microbiome Ireland, University College Cork, Cork, Ireland;
o
Department of Psychiatry & Institute of Medical Sciences, Centre for
Addiction and Mental Health, University of Toronto, Toronto, Canada
ABSTRACT
Objectives: The primary objectives of these international guidelines were to provide a global
audience of clinicians with (a) a series of evidence-based recommendations for the provision of
lifestyle-based mental health care in clinical practice for adults with Major Depressive Disorder
(MDD) and (b) a series of implementation considerations that may be applicable across a range
of settings.
Methods: Recommendations and associated evidence-based gradings were based on a series
of systematic literature searches of published research as well as the clinical expertise of task-
force members. The focus of the guidelines was eight lifestyle domains: physical activity and
exercise, smoking cessation, work-directed interventions, mindfulness-based and stress manage-
ment therapies, diet, sleep, loneliness and social support, and green space interaction. The fol-
lowing electronic bibliographic databases were searched for articles published prior to June
2020: PubMed, EMBASE, The Cochrane Library (Cochrane Database of Systematic Reviews,
Cochrane Central Register of Controlled Trials (CENTRAL), Cochrane Methodology Register),
CINAHL, PsycINFO. Evidence grading was based on the level of evidence specific to MDD and
risk of bias, in accordance with the World Federation of Societies for Biological
Psychiatry criteria.
Results: Nine recommendations were formed. The recommendations with the highest ratings
to improve MDD were the use of physical activity and exercise, relaxation techniques, work-
directed interventions, sleep, and mindfulness-based therapies (Grade 2). Interventions related
to diet and green space were recommended, but with a lower strength of evidence (Grade 3).
Recommendations regarding smoking cessation and loneliness and social support were based
on expert opinion. Key implementation considerations included the need for input from allied
health professionals and support networks to implement this type of approach, the importance
of partnering such recommendations with behaviour change support, and the need to deliver
interventions using a biopsychosocial-cultural framework.
Conclusions: Lifestyle-based interventions are recommended as a foundational component of
mental health care in clinical practice for adults with Major Depressive Disorder, where other
evidence-based therapies can be added or used in combination. The findings and recommenda-
tions of these guidelines support the need for further research to address existing gaps in
ARTICLE HISTORY
Received 18 May 2022
Revised 24 July 2022
Accepted 7 August 2022
KEYWORDS
Major depressive disorder;
lifestyle; mental health;
treatment; guidelines
CONTACT Adrienne O’Neil adrienne.oneil@deakin.edu.au; Wolfgang Marx wolf.marx@deakin.edu.au Institute for Mental and Physical Health
and Clinical Translation (IMPACT), Food & Mood Centre, School of Medicine, Barwon Health, Deakin University, Geelong, Australia
C3
Taskforce co-chair.
Supplemental data for this article can be accessed at https://doi.org//10.1080/15622975.2022.2112074.
C223 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-
nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed,
or built upon in any way.
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY
https://doi.org/10.1080/15622975.2022.2112074
efficacy and implementation research, especially for emerging lifestyle-based approaches (e.g.
green space, loneliness and social support interventions) where data are limited. Further work is
also needed to develop innovative approaches for delivery and models of care, and to support
the training of health professionals regarding lifestyle-based mental health care.
1. Executive summary of recommendations
Lifestyle-based mental health care includes the assess-
ment and intervention of the lifestyle determinants of
health in the prevention, recovery and treatment of
mental disorders. Both Royal Australian & New
Zealand Royal College of Psychiatrists (RANZCP) (Malhi
et al. 2021) and draft National Institutes of Health and
Care Excellence (NICE) (National Institute for Health
and Care Excellence 2022) guidelines endorse lifestyle-
based approaches as important aspects of depression
management. These recommendations are presented
as a foundational component of care that can be used
in combination with other evidence-based therapies.
Focussing on the management of Major Depressive
Disorder (MDD) in adults, the current guidelines
endorse this position and build on it by: (1) systemat-
ically reviewing evidence for the clinical application of
specific lifestyle-based approaches in this clinical
population; (2) expanding upon the four aforemen-
tioned lifestyle factors to include emerging lifestyle
targets of loneliness and social support, mindfulness-
based therapies and stress management, green space
interaction, work-directed interventions, and; (3) pro-
viding a series of implementation considerations that
may be applied across a range of settings that are
applicable to a global audience. Based on available
scientific evidence and supplemented with expert con-
sensus, nine recommendations are proposed in
Table 1.
For all the target lifestyle behaviours recommended
by the guidelines, effectiveness will be maximised
when delivered in conjunction with behaviour change
techniques that are appropriate for the person and
their circumstances.
Informed by the evidence-base that supports these
recommendations, a series of additional recommenda-
tions are provided for future research into lifestyle-
based approaches to strengthen the current evidence
and to inform translation and implementation into
clinical settings. These include the need for utilising
lessons from the field of implementation science,
novel effectiveness and non-inferiority study designs,
cost-effectiveness considerations, greater understand-
ing of the optimal delivery methods, and identifying
mechanisms of action.
Finally, a series of considerations are provided to
assist clinicians with implementation of these recom-
mendations, regardless of clinical setting. These
include highlighting our position that lifestyle-based
approaches should be considered a core component
of mental health care; recognising the benefits of
input from allied health professionals; engaging sup-
port networks into the delivery of the interventions;
recognising the need for formal assessment of social
needs; screening for substance and alcohol use; and
incorporating culturally sensitive approaches and self-
management strategies into the delivery of the life-
style interventions. Figure 1 provides a visual summary
of how these implementation considerations and rec-
ommendations sit within a continuum of care.
The evidence on which these guidelines are based
supports the application of lifestyle-based mental
health care as part of broader biopsychosocial-cultural
management of MDD. Lifestyle-based mental health
care is generally considered safe for most individuals
(with generally low incidence of side-effects and major
adverse events) when delivered alone or in conjunc-
tion with established therapies and has the potential
to be provided at relatively low cost across a range of
settings to adults with diverse clinical and demo-
graphic characteristics. Benefits of lifestyle-based
approaches for MDD may extend to physical health
outcomes (particularly cardiovascular, metabolic, and
respiratory disease risk). The findings and recommen-
dations of these guidelines encourage further research
in this area, especially for those emerging lifestyle-
based approaches where data are currently limited
(e.g. green space, loneliness and social support inter-
ventions); greater education of health professionals
regarding lifestyle-based approaches; and support for
innovative approaches for the delivery of new integra-
tive models of care for people with MDD.
2. Introduction
2.1. Rationale
Major Depressive Disorder (MDD) is a leading cause of
global disability and is one of the leading causes of
disease burden worldwide (GBD Mental Disorders
Collaborators 2022). MDD is common, with
2 W. MARX ET AL.
approximately 4.7% of the world’s population experi-
encing depression in any 12-month period (Ferrari
et al. 2013). The prevalence of MDD is also consistent
across high, middle, and low income countries,
emphasising the global burden of this disease (World
Health Organization 2017). Pharmacological and psy-
chological approaches are effective for MDD manage-
ment (Leichsenring et al. 2022). However, meta-
analyses suggest that both of these forms of therapy
may have only modest benefits and are not effective
for everyone for reducing depressive symptoms
(Leichsenring et al. 2022). Moreover, antidepressant
medications may be accompanied by undesirable
side-effects including sexual dysfunction, sedation, car-
diac dysfunction, osteoporosis, and weight gain, which
may reduce treatment efficacy and diminish long-term
adherence (Carvalho et al. 2016). Furthermore, finan-
cial and resourcing barriers to accessing mental health
services are notable especially in low- and middle-
income countries where there is a high prevalence of
stigma to mental health care (Herrman et al. 2022).
Consequently, there has been considerable research
and clinical interest in the role of lifestyle-based
approaches for the management of mental illness.
Lifestyle-based approaches can be defined as ‘the
application of environmental, behavioural and motiv-
ational principles, including self-care and self-manage-
ment, to the management of lifestyle-related health
problems in a clinical setting’ (Sagner et al. 2017). This
approach may present several key benefits to other
Table 1. Summary of recommendations.
Strength of supporting evidence/evidence statement phrasing
Grade B/could
Grade C1/may
Grade C3/may
Domain Recommendation statement Level of evidence Recommendation Grade
5.1 Physical activity and exercise
interventions
Physical activity and exercise interventions
could be used to reduce depressive
symptoms in people with Major
Depressive Disorder
Limited; Grade B 2
5.2 Smoking cessation interventions Smoking cessation interventions that involve
counselling and/or pharmacotherapy (e.g.
nicotine replacement) may be used to
reduce depressive symptoms in current
smokers with Major Depressive Disorder
Low; Grade C3 3
5.3 Work-directed interventions A combination of work focussed counselling
and work-directed interventions could be
used to reduce depressive symptoms in
people with Major Depressive Disorder
Limited; Grade B 2
5.4 Mindfulness-based and
stress management interventions
Mindfulness-based therapies (e.g.
Mindfulness Based Cognitive Therapy
[MBCT] and Mindfulness Based Stress
Reduction [MBSR]) could be used to
reduce depressive symptoms in people
with Major Depressive Disorder
Limited; Grade B 2
Stress management and relaxation
techniques (e.g. breathing techniques,
progressive muscle relaxation) could be
used to reduce depressive symptoms in
people with Major Depressive Disorder
Limited; Grade B 2
5.5 Dietary interventions Dietary counselling to improve nutritional
habits that is in line with healthy dietary
guidelines and/or nutrient-dense dietary
patterns may be used to reduce
depressive symptoms in people with
Major Depressive Disorder
Low; Grade C1 3
5.6 Sleep-related interventions Cognitive behavioural therapy for insomnia
(CBT-I) could be used to reduce
depressive symptoms in people with
Major Depressive Disorder
Limited; Grade B 2
5.7 Loneliness and Social support-
related interventions
Improving social support and reducing
loneliness may be used to reduce
depressive symptoms in people with
Major Depressive Disorder
Low; Grade C3 3
5.8 Green space interventions Support regarding individualised interaction
with green spaces or participation in a
green space-focussed program may be
used to reduce depressive symptoms in
people with Major Depressive Disorder
Low; Grade C1 3
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 3
Figure 1. Conceptual framework for lifestyle-based mental health care. A proposed clinical flowchart for lifestyle-based mental
health care using a 4 A’s (Assess, Advise, Assist, Arrange) structure. For the online/colour version of this figure, each lifestyle inter-
vention is colour coded for grade of evidence (dark green ? grade B, light green ? grade C, yellow ? expert opinion).
4 W. MARX ET AL.
approaches as they are generally considered low risk
with respect to causing adverse events. Furthermore,
due to the high morbidity and mortality risk associ-
ated with MDD and other mental disorders (Machado
et al. 2018), this approach may offer a dual benefit,
addressing clinical symptoms of MDD while potentially
mitigating physical comorbidities – a recognised chal-
lenge for those with mental illness (Firth et al. 2019b).
Despite the promise and relatively low risk of using
lifestyle-based mental health care, to our knowledge,
there are no available clinical practice guidelines that
grade the evidence for established and emerging life-
style interventions by which to assist clinicians in pro-
viding this type of care. These guidelines are intended
to address this key gap in our knowledge and to serve
as an aid to clinicians. This document is intended to
serve a global audience and it is acknowledged that
implementation will vary across service delivery, disci-
plines, jurisdictional, country and regional contexts.
Ultimately, lifestyle-based mental health care looks dif-
ferent across settings with varying resources.
2.2. Guideline objectives
A primary objective for writing these guidelines was
to evaluate lifestyle-based mental health care using
the best available evidence (section 4). In this docu-
ment, we present the evidence and gradings before
providing further discussion on clinically useful appli-
cation strategies within the identified lifestyle inter-
ventions. Further, we provide an overview of the key
gaps in the current evidence (section 5) and dedicate
a section on implementation considerations related to
contextual and practical elements of using lifestyle-
based interventions for optimal mental health care
(section 6).
2.3. Scope of guidelines
Using the PICO format (Population, Intervention,
Comparator, Outcome), the guidelines were designed
to cover the following scope.
2.3.1. Population
We acknowledge that language matters in the provi-
sion of care and in creating person-centered care for
those with lived experience of mental illness.
Moreover, that this language can change in its mean-
ing or appropriateness across setting, culture, discip-
line and context (e.g. consumer, patient, client, service
user, person). These guidelines pertain to people with
current experience with a major depressive disorder,
henceforth referred to as people with MDD. We recog-
nise a move away from conventional and formal psy-
chiatric diagnoses in mental health care, especially in
clinical application for which a more transdiagnostic
approach can be better suited. However, while the
clinical considerations may be relevant to those with
sub-clinical depression, other related mood disorders
(e.g. bipolar disorder, cyclothymic disorder, or peri-par-
tum onset depression), or depression co-occurring
with anxiety, the target population was specifically
people with MDD as distinct from subthreshold
depressive illness or variations of mood disorders as
specified in DSM-5.
2.3.2. Interventions
Although there is a wide range of interventions that
may be considered as lifestyle-based mental health
care, (Egger 2019) to ensure a feasible scope of work,
these guidelines were restricted to the follow-
ing approaches:
C15 Physical activity and exercise
C15 Smoking cessation
C15 Work-directed interventions
C15 Mindfulness-based therapies and stress manage-
ment (including relaxation techniques and coping
skills training)
C15 Diet
C15 Sleep
C15 Loneliness and social support
C15 Green space interaction
For clarity, we reviewed the eight selected lifestyle
domains separately, while acknowledging that in
many cases, behavioural changes recommended for
people with MDD in any one domain (e.g. strategies
to increase physical activity) may also have demon-
strable effects in another (e.g. sleep or social connect-
edness). Furthermore, there are challenges in trying to
artificially categorise certain lifestyle behaviours that
span multiple domains under just one domain. For
example, yoga is a diverse group of practices that can
include exercise, stress management, relaxation, con-
templative practices and breathing techniques. It is
also the case that there is overlap in what constitutes
some lifestyle-based approaches and those that may
be used as part of psychological-based practices (e.g.
mindfulness). For this activity, we consider the content
as being lifestyle-based in nature, thus eligible for
inclusion in these guidelines. It was considered
beyond the scope of this document to include other
evidence-based techniques used as part of
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 5
psychological practices. We specifically excluded cessa-
tion interventions related to alcohol and illicit drugs
given there are existing substance use disorder man-
agement guidelines that can be consulted for those
with co-occurring mental illness (see Marel et al.
2016); however, this area is discussed in Section 6.We
also focussed the scope of the recommendations on
interventions that targeted the lifestyle factor rather
than the effect of environmental and/or lifestyle fac-
tors (e.g. environmental pollution, social media use).
Finally, we focussed on clinical, rather than population
level interventions.
2.3.3. Comparator
Studies were not excluded based on the compara-
tor used.
2.3.4. Outcome
The key outcome of interest was reductions in depres-
sive symptoms of people with MDD. Other important
targets of MDD treatment in this population (e.g.
relapse/recurrence, length of inpatient stay, quality of
life or lifestyle behaviours) were beyond the pre-
sent scope.
2.4. Target audience
The document is intended for any health professional
who may diagnose and/or who is part of a team pro-
viding care for adults with MDD, including allied or
generalist health professionals, as well as community
rehabilitation and psychosocial or peer support work-
ers working directly with people with MDD. All recom-
mendations should be considered with the interests,
preferences and circumstances of the individual in
mind and within the available clinical context with
consideration of current training, expertise, and inter-
est, of the clinician as well as the availability of related
health professionals and relevant resources (Malhi
et al. 2021).
2.5. Financial disclosure and conflicts of interest
Individual funding for each study author is included at
the end of the manuscript. No funding body had any
input into the design or conduct of the guidelines.
Potential conflicts of interest for all taskforce members
were compiled at the initiation of the guideline task-
force and declared in the relevant section of
this manuscript.
3. Methods
3.1. General methods and literature search
In 2019, an internationally representative taskforce of
researchers, clinicians and lived experience experts
was formed and endorsed by the World Federation of
Societies of Biological Psychiatry (WFSBP) and the
Australasian Society of Lifestyle Medicine (ASLM). This
taskforce was composed of members from nine differ-
ent countries (across the Asia-Pacific, North and South
America, Europe, and Africa), with representation from
high-, mid-, and low-income countries. The develop-
ment of these guidelines is in line with the recom-
mendations of the WFSBP guidelines development
document (see Figure 2) (Hasan et al. 2019).
3.2. Supporting evidence
Guideline recommendations were generated based on
a series of systematic literature searches of published
peer-reviewed research for each lifestyle domain as
well the clinical and research expertise of the taskforce
members.
3.2.1. Literature search
We searched the following electronic bibliographic
databases: Pubmed, EMBASE, The Cochrane Library
(Cochrane Database of Systematic Reviews, Cochrane
Central Register of Controlled Trials (CENTRAL),
Cochrane Methodology Register), CINAHL, PsycINFO.
Search terms are included in Supplementary material.
Only studies published in English were eligible for
inclusion. Studies published since journal inception to
June 2020 were sought. Additional eligible literature
that was published after this date and that was identi-
fied by members of the taskforce was also included.
3.2.2. Eligibility criteria
Eligibility criteria were in line with the details provided
in section 2.3. Although there were additional studies
that evaluated the use of lifestyle-based approaches in
Figure 2. Guideline recommendations development process.
6 W. MARX ET AL.
people with sub-syndromal depression and healthy
populations, and/or measured related outcomes such
as stress and quality of life, these were considered
beyond the scope of this work.
3.2.2.1. Types of studies included. Due to the varied
level of available evidence for the included interven-
tions, a stepwise approach was used to synthesise
relevant data using the Australian National Health &
Medical Research Council Evidence Hierarchy (National
Health and Medical Research Council 2009): Initially,
the search results were screened for systematic
reviews and meta-analyses; if available, these data
formed the basis of the guideline recommendations
for that intervention. In cases where no systematic
reviews and meta-analyses available, the search was
expanded to randomised clinical trials (RCTs) and then
non-randomised trials.
3.2.2.2. Data extraction. Titles and/or abstracts of
studies retrieved using the search strategy and those
from additional sources were screened independently
by two reviewers to identify studies potentially meet-
ing the inclusion criteria outlined above.
Full texts of these potentially eligible studies were
retrieved and independently assessed for eligibility by
two team members. Any disagreement between them
over the eligibility of studies was resolved through dis-
cussion with a third author.
The reported effect sizes were extracted from the
included meta-analyses or individual studies that
formed the basis of each recommendation. Each effect
size was categorised as Small, Moderate or Large,
using standard effect size (e.g. Cohen’s d) cut offs,
(Cohen 2013) and reported within each clinical recom-
mendations section. Although these effect sizes pro-
vide context for the magnitude of each intervention
effect, they should be viewed with caution due to lim-
ited data on treatments (e.g. stand-alone versus
adjunctive to other approaches) and small sample
sizes and should not be used in isolation to guide
preferential treatment selection.
3.3. Risk of bias assessment
Where risk of bias assessments had already been con-
ducted (e.g. as part of the published systematic
reviews), these assessments were extracted for use in
these guidelines. Where risk of bias assessment was
not previously conducted, risk of bias was assessed
independently by two taskforce authors, with conflict-
ing scores resolved first through discussion; if
disagreements persisted, a third author provided final
judgement. Risk of bias tools were used as below:
C15 Systematic reviews and meta-analyses were
assessed using the AMSTAR-2 checklist (Shea
et al. 2017)
C15 RCTs were assessed using the Cochrane Risk of Bias
2 tool (Sterne et al. 2019)
C15 Non-randomised and quasi-experimental studies
were assessed using the Joanna Briggs Institute
(JBI) Critical Appraisal Checklist for Quasi-
Experimental Studies (Tufanaru et al. 2017)
3.4. Grading of evidence and synthesis of
Evidence-Based statements
The level of evidence and strength of recommenda-
tions were graded in accordance with the WFSBP
guidelines (Hasan et al. 2019). In summary, supporting
evidence was first graded to determine the level of
evidence using the matrix detailed in Table 2. For
these guidelines, we amended the grading criteria for
meta-analyses to consider the risk of bias of the
included individual studies as well as the risk of bias
of the overall meta-analysis. Acceptability of an inter-
vention was also assessed using the following factors:
C15 Risk–benefit ratio (e.g. adverse effects, interactions)
C15 Cost–benefit ratio
C15 Applicability in the target population
C15 Ethical and legal aspects
C15 Preferences of service users
C15 Practicability
As described elsewhere (Hasan et al. 2019), the
grade of recommendations was based upon the
amount and quality of evidence (Table 2) in conjunc-
tion with the acceptability of the intervention, result-
ing in strong (Grade 1), limited (Grade 2), low (Grade 3),
or no evidence (Grade 4) recommendation levels. To
help aid translation of these recommendations into
clinical practice, recommendations were phrased as
action statements where ‘should’ indicates a strong
strength of evidence, ‘could’ indicates a limited
strength of evidence, and ‘may’ indicates a low
strength of evidence.
3.5. Taskforce consensus process
A two-stage Delphi process was used to achieve con-
sensus from the taskforce members about each guide-
line recommendation. In doing so, a set of draft
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 7
recommendations were developed and provided to
each taskforce member via an anonymous survey for
review and endorsement. This feedback was then
incorporated into a revised set of recommendations,
which was again disseminated for review and endorse-
ment by the taskforce. A recommendation was final-
ised when >80% consensus was achieved.
3.6. Future research needs, implementation and
clinical considerations
To provide further context to the recommendations
and to guide their implementation, we (1) provided a
‘Clinical Advice and Tips’ Box for each guideline, (2)
identified key evidence gaps and future research
needs (section 5), and (3) included a series of
implementation considerations for lifestyle-based
approaches (section 6). These sections, along with the
background and Clinical Considerations section for
each domain, do not follow the previously mentioned
systematic review procedure and are based on the
broader current literature regarding depression (e.g.
studies in subthreshold depressive symptoms as well
as those in MDD).
3.7. Guideline lifecycle
Subject to availability of funding and resourcing, the
taskforce intends to update these guidelines every
5years or when developments in the research litera-
ture or clinical management warrant an update, in line
with the criteria by Rosenfeld et al. (2013).
Table 2. Evidence Grading System as recommended by the WFSBP (Hasan et al. 2019).
Evidence that the intervention
is effective
Evidence
statement
phrasing
Level of
evidence Explanation
Strong Should A At least two independent RCTs with a low risk of bias showing efficacy
(superiority to placebo or, in the case of psychotherapy studies, superiority
to an ‘active psychological placebo’ in a study with adequate blinding),
OR
Superiority to/equivalent efficacy compared with an established comparator
treatment in a three-arm study with placebo control or in a well-powered
non-inferiority trial (only applicable if such a standard treatment exists) with
a low risk of bias,
AND
No negative RCTs with a low risk of bias exist.
If there are contradicting results from RCTs, the majority of RCTs AND/OR a
meta-analysis with low risk of bias, and that included studies that were
generally at low risk of bias, showing efficacy.
If there are more than one ‘A’ treatment options, the decision should be based
on head-to-head comparisons or meta-analyses showing superiority of one
of the treatments
Limited Could B One RCT with a moderate risk of bias showing superiority to placebo (or in the
case of psychotherapy studies, superiority to an ‘active psychological
placebo’)
OR
A randomised controlled comparison with a standard treatment without
placebo control with a sample size sufficient for a non-inferiority trial with a
moderate risk of bias,
AND
No negative studies exist
OR
Meta-analyses with a moderate risk of bias that show efficacy or Meta-analyses
with low risk of bias that included studies that were generally at a high risk
of bias
Low May C1 One or more prospective open studies (with a minimum of 10 evaluable
participants per group) using a control group, but no randomisation, or
using no control group, show efficacy
OR
One or more well-conducted case control or cohort studies (with a minimum
of 10 evaluable patients) with a moderate probability that the relationship is
causal show efficacy
OR
RCTs AND/OR meta-analyses with a high risk of bias showing efficacy
C2 Non-analytic studies, e.g. case reports or case series with fewer than 10
evaluable participants show efficacy in the majority of cases
C3 Expert opinions not based on any published data reporting efficacy
No evidence D
RCT: randomised controlled trial.
8 W. MARX ET AL.
3.8. External review procedure
An extensive external review process was imple-
mented to ensure that input and feedback from rele-
vant stakeholders was incorporated into the
development of the guideline recommendations.
Stakeholders included researchers who have published
in relevant fields, people with lived experience of
MDD, cultural experts, and mental health clinicians.
The draft guidelines were disseminated for external
review from November to December 2021.
Submissions were reviewed by the taskforce and,
where appropriate, incorporated into the final guide-
line document.
4. Evidence-based guideline statements
In summary, nine recommendations were developed
covering the eight specific lifestyle domains. The
details of the evidence on which recommendations
were made are presented by lifestyle domain in this
section. Table 1 provides an overview of the nine rec-
ommendations, of which five received Grade B
strength of evidence, two received Grade C1, and two
were based on expert opinion (Grade C3). To provide
support for the use of these recommendations, the
sections below also include domain-specific clinical
considerations, tips and advice, and further resources.
For general clinical advice that applies across all
domains, see Box 1. For further context and discussion
of the limitations of the recommendation process,
please see section 5.
4.1. Physical activity and exercise interventions
4.1.1. Background literature
Physical activity, defined as any bodily movement that
requires energetic expenditure, and exercise, defined
as structured physical activity that aims to maintain or
improve physical fitness (Caspersen et al. 1985), have a
bidirectional relationship with MDD (Blumenthal et al.
1999; Schuch et al. 2017; Vancampfort et al. 2017;
Ashdown-Franks et al. 2020). Meta-analytic evidence
demonstrates that, compared to the general popula-
tion, people with MDD have reduced levels of physical
activity and are less likely to achieve the public health
recommendations of 150min of moderate and vigor-
ous physical activity per week. Similarly, inactive indi-
viduals are more likely to become depressed (Schuch
et al. 2017; Vancampfort et al. 2017). Although MDD is
likely to be associated with reduced physical activity,
there is a growing body of evidence that supports
exercise and physical activity as an intervention for
reducing depressive symptoms and preventing the
development of MDD or the worsening of depressive
symptomatology (Blumenthal et al. 1999; Ashdown-
Franks et al. 2020). A recent large scale Mendelian ran-
domisation study found that higher levels of acceler-
ometer-based activity were causally protective against
MDD (Choi et al. 2019). This is consistent with meta-
analyses of cohort studies (Schuch et al. 2018). Further,
Mendelian randomisation research has demonstrated
that people who are more active and are genetically
predisposed to MDD are less likely to develop MDD
than people of equal genetic risk for MDD and low
physical activity levels (Choi KW et al. 2020). The mech-
anisms underlying the potential anti-depressant effect
of exercise are complex and are not fully understood.
The beneficial effects may include a combination of
neurobiological mechanisms (e.g. stimulation of brain-
derived neurotrophic factor (Kerling et al. 2017),
reduced inflammation, stimulation of pre-frontal cortex
and hippocampus (Lin K et al. 2020), including volu-
metric changes) and psychosocial factors (e.g.
increased self-efficacy, social support, improved self-
esteem) (Kandola et al. 2019).
In a series of randomised controlled trials, aerobic
exercise has been shown to be as effective as
antidepressant medication (e.g. Serotonin Reuptake
Inhibitors [SSRIs] such as sertraline) in reducing depres-
sive symptoms in adults with MDD (Blumenthal et al.
1999; Blumenthal et al. 2007) and in individuals with
coronary disease and MDD or elevated depressive
symptoms (Blumenthal et al. 2012). However, the pres-
ence of depression and co-morbid anxiety may
Box 1. Clinical advice and tips for lifestyle-based mental health care.
C15 Delivery of lifestyle lifestyle-based mental health care is sug-
gested to be in line with our proposed conceptual framework
(Figure 1)
C15 Explore individual factors (e.g. financial, geographical, medical,
and social considerations) when initiating behaviour change to
promote uptake and sustainability
C15 Explore the individual’s capability, opportunity, and motivation
for initiating and maintaining behaviour change
C15 Encourage the individual to seek out formal programs relevant
to lifestyle interventions that provide supervision and struc-
tured activity.
C15 Encourage the individual to incorporate social components (e.g.
clubs, community groups, friends and/or family) to interventions.
C15 Clinicians are encouraged to engage with relevant allied health
professionals and specialists, where warranted
C15 Consider the integration of digital and online tools to lifestyle
interventions to assist with adherence and self-management
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 9
attenuate the beneficial effects of exercise on depressive
symptoms (Rebar et al. 2015; Blumenthal et al. 2021).
Studies have generally been successful in recruiting
people with MDD to RCTs with dropout rates being, in
some cases, less than 20% (Schuch, Vancampfort,
Rosenbaum, et al. 2016; Stubbs et al. 2016;Kroghetal.
2017). This is comparable to dropout rates found in trials
of exercise in non-depressed individuals and in those
receiving antidepressant medications (Schuch,
Vancampfort, Rosenbaum, et al. 2016; Stubbs et al. 2016;
Krogh et al. 2017), and lower compared to usual care
controls (Stubbs et al. 2016). In addition, the rate of
adverse events appears to be low and no worse than
antidepressant medications or to control conditions
(Stubbs et al. 2018). Furthermore, meta-analyses of RCTs
have found that multiple modes of exercise improves
depressive symptoms in people with MDD, including
aerobic exercise (e.g. running, rowing) (Schuch,
Vancampfort, Richards, et al. 2016), resistance training
(e.g. weight lifting), (Gordon et al. 2018)aswel asa
smaller evidence base that supports yoga (Brinsley et al.
2021) and pilates (Fleming and Herring 2018)(forformal
definitions of different exercise modalities, see reference
(Howley 2001)). Meta-analyses of RCTs also have demon-
strated that exercise can have significant improvements
on other psychological and behavioural functions includ-
ing self-esteem, various aspects of quality of life, and
sleep (Schuch et al. 2017; Lederman et al. 2019).
4.1.2. Clinical recommendations
4.1.3. Clinical considerations
4.1.3.1. Type and context of intervention.
Contemporary clinical trials have largely focussed on
aerobic exercise; however, there is growing evidence
to suggest strength-based exercise or resistance train-
ing (e.g. weight lifting) may also improve depressive
symptoms (Schuch, Vancampfort, Richards, et al. 2016;
Gordon et al. 2018). Given the potential complemen-
tary benefits of each mode of exercise on physical
health, a regimen that combines both modes of exer-
cise could be advantageous.
Yoga, tai chi, and qi gong are practices that incorp-
orate physical activity as well as mindfulness, breath
work, and spiritual components (Vancampfort et al.
2021). These practices have shown antidepressant
benefits in a small number of randomised controlled
trials amongst people with MDD and is supported by
other international guidelines (Ravindran et al. 2016;
Prathikanti et al. 2017; Sharma et al. 2017). There is
also a wider body of evidence that suggest these
interventions may benefit depressive symptoms, stress,
and quality of life in non-clinical populations
(Breedvelt et al. 2019; Sivaramakrishnan et al. 2019).
Furthermore, due to the generally low impact on
joints and, depending on the type of practice, physical
intensity of mind-body interventions, they may be
well-suited to individuals with physical comorbidities
that prevent them from engaging in more intense
forms of physical activity.
Other factors that should be considered include a
person’s preference, age and physical condition – the
latter is especially true in the context of a past or cur-
rent COVID-19 infection and the short- and long-term
implications on exercise capacity. Another consider-
ation is the context of exercise (e.g. leisure-based phys-
ical activity vs work-related physical activity)
(Teychenne et al. 2020). Previous observational
research suggests that the context is an important fac-
tor, with leisure or transport-related physical activity
showing the greatest benefits to mental health,
whereas domestic and work-related activity being
least beneficial (Schuch et al. 2021).
Some evidence suggests that exercise programs
where the individual has a clear sense of autonomy
may be more beneficial than prescriptive regimens
(Teychenne et al. 2020). Hence, individualising physical
activity programs to those that the individual enjoys
and finds meaningful should be encouraged. The
introduction of a level of accountability – whether
from oneself, a clinician, peers or community – is
another factor that may improve sustained adherence.
This may be one reason why integration of social sup-
port into physical activity programs such as exercising
with friends/family or via classes and team sports may
improve efficacy and long-term adherence of the
intervention. Improvements in dropout rates and
effectiveness have been demonstrated when exercise
is supervised (Schuch, Vancampfort, Richards, et al.
2016; Stubbs et al. 2016). In the contemporary setting,
where many individuals with MDD may be recovering
from COVID-19 or have ‘long COVID-19
0
, the import-
ance of supervision by a recognised exercise
Statement: Physical activity and exercise interventions could be used to
reduce depressive symptoms in people with Major Depressive Disorder
Recommendation Grade: 2
Strength of evidence: Limited; Grade B
Acceptability: Good
Clinical recommendation was based on: 2C2 Meta-analysis (k?25–35
studies, N?1487–2498 participants) (Schuch, Vancampfort,
Rosenbaum, et al. 2016; Krogh et al. 2017)
Reported effect size: Medium to large effect size (standardized mean
difference ? 0.66–1.11) (Schuch, Vancampfort, Rosenbaum, et al. 2016;
Krogh et al. 2017)
Risk of bias assessment: Low ROB meta-analyses of high ROB
individual trials.
10 W. MARX ET AL.
professional (e.g. physiotherapist, exercise physiologist)
is underscored (see Box 2 for further considerations).
4.1.3.2. Dose, frequency, intensity. Prescription
should be based on feasibility of adherence and indi-
vidualised to the person’s motivation and current lev-
els of physical activity and fitness. A target of
150–300min/week of moderate-intensity physical
activity or 75–150min/week of vigorous-intensity
physical activity has been proposed as this aligns with
the World Health Organisation 2020 guidelines on phys-
ical activity and sedentary behaviour (Bull et al. 2020;
Teychenne et al. 2020). Both WHO and mental illness
specific guidelines stress that these are aspirational
targets for many with MDD, and the best exercise pre-
scription is one that can be maintained. Initiating exer-
cise of any level of duration, intensity and frequency is
important and can be built up over time as an individ-
ual achieves success and an increasing sense of auton-
omy and internal motivation to sustain long term
behaviour change (Vancampfort et al. 2015; Stubbs
et al. 2018).
4.1.3.3. Assessment considerations. Caution should
be taken when prescribing physical activity, especially
intensive forms, to those with certain medical conditions,
such as heart disease, diabetes, asthma, vertigo, osteo-
porosis, or joint disease (notwithstanding that exercise is
recommended for many of these conditions) and the
aforementioned COVID-19 related conditions. This may
require consultation with physicians, possibly involving
formal exercise testing, prior to initiating an exercise pro-
gram. Pre-exercise screening tools and guidelines are
available to support professionals, as needed (Norton
and Norton 2011;Riebeetal.2018).
4.1.3.4. Sedentary behaviour. Related to the role of
increased physical activity on MDD is the association of
MDD and sedentary behaviour, defined as behaviours
with an energy expenditure C201.5 metabolic equivalents,
such as sitting and reclining (Tremblay et al. 2017).
While the evidence is based primarily on observational
data (Teychenne et al. 2020), prospective meta-analyses
suggest that higher levels of sedentary behaviour are
associated with a greater risk of MDD (Zhai et al. 2015).
Evidence from a recent prospective cohort using an
objective assessment of sedentary and physical activity
data with 60,235 participants found that sedentary time
is a risk factor for MDD (Kandola et al. 2021).
Importantly, the study found replacing 60min of seden-
tary behaviour with light or moderate-to-vigorous activ-
ity, was associated with lower MDD symptom scores at
follow-up by OR 0.75 (95% CI, 0.74–0.76) and OR 0.90
(95% CI, 0.90–0.91) respectively (Kandola et al. 2021).
There is emerging evidence that the type of sedentary
behaviour may have a differential effect, with mentally
passive sedentary behaviour (e.g. watching TV) being
associated with increased risk of future MDD, whereas
mentally active sedentary behaviour (e.g. playing com-
puter games, reading) is not (Hallgren et al. 2020;
Werneck et al. 2021). This finding has been confirmed
by a number of modestly powered randomised con-
trolled trials, where the intervention increased sedentary
behaviour in healthy populations, leading to worsening
of mental health (Edwards and Loprinzi 2016), possibly
due to increased inflammation/stress (Endrighi et al.
2016). Discussing strategies to reduce sedentary behav-
iour (e.g. using standing desks to disrupt long periods of
sitting) may be incorporated into physical activ-
ity education.
4.1.4. Resources
1. EPA guidance on physical activity as a strategy for
severe mental illness: a meta-review of the evidence
and Position Statement from the European
Box 2. Clinical advice and tips for increasing physical activity
and exercise
C15 Inquire about and encourage individuals to engage in modes of
physical activity that they enjoy and at a frequency and intensity
that they can sustain
C15 Discuss the use of supervised physical activity options such as
group classes, use of personal trainers, and team sports as these
may improve adherence in some individuals
C15 Engaging with an accredited exercise physiologist may be war-
ranted especially where physical comorbidities exist for individu-
als with MDD (e.g heart conditions, COVID-19) to overcome
barriers to participating in physical activity
C15 Pairing exercise with enjoyable activities can increase motivation
e.g. listening to music, socialising, or exercising with a partner,
watching television, or exercising in a pleasant environment
C15 Positive mental, physical, and social experiences acknowledged
during physical activity (in real-time as opposed to retrospect-
ively) can guide attention and increase motivation
C15 Encourage exercise routines that are feasible to implement most
days rather than sporadically and that are effortful but not too
difficult, exhausting, or painful. Examples may include commenc-
ing with initially low-moderate intensity exercise (e.g. walking/
cycling short distances) rather than commencing with high inten-
sity exercise routines (e.g. sprints, long distance running)
C15 Where feasible and appropriate, work with individuals to grad-
ually incorporate bouts of higher intensity exercise to gain max-
imal antidepressant benefits
C15 Provide examples of ways to reduce sedentary behaviour as well
as improving physical activity (e.g. digital apps and push notifica-
tions, reminders, standing/walking meetings, environmental modi-
fications such as standing desks)
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 11
Psychiatric Association (EPA), supported by the
International Organisation of Physical Therapists in
Mental Health (IOPTMH) (Stubbs et al. 2018).
Further guidelines on the use of physical activity
in MDD as well as other forms of severe men-
tal illnesses
2. Physical Activity factsheet (World Health
Organization 2021). A World Health Organisation
fact sheet on physical Activity guidelines across
age groups
3. Exercise Right (Exercise Right 2022). A public
awareness campaign run by Exercise & Sports
Science Australia that provides resources and
information regarding exercise
4.2. Smoking cessation interventions
4.2.1. Background literature
Smoking is a critical risk factor for several chronic dis-
eases such as chronic obstructive pulmonary disease,
lung cancer, coronary heart disease, and type II dia-
betes, and premature death (US Department of Health
and Human Services 2004). People with MDD are
more likely to be smokers compared to the general
population, exacerbating their already elevated comor-
bidity and mortality risk (Weinberger et al. 2017). The
relationship between smoking and depressive symp-
toms has historically been considered a form of cop-
ing or self-medication. This has resulted in a hesitancy
to engage people with MDD in smoking cessation pro-
grams due to concerns that this may exacerbate
depressive symptoms (Prochaska 2011). However,
there is growing evidence to suggest that the relation-
ship between smoking and mental illness may be
bidirectional (Bj?rngaard et al. 2013; Taylor AE et al.
2014; Wootton et al. 2020). Prospective observational
studies demonstrate that smokers have increased
odds of subsequent MDD later in life (Luger et al.
2014; Fluharty et al. 2017). More recently, the use of
Mendelian randomisation methods have tended to
corroborate this bidirectional relationship (although
not consistently) (Bj?rngaard et al. 2013; Taylor AE
et al. 2014; Wootton et al. 2020). A recent Cochrane
review of 34 studies concluded that there was signifi-
cant, albeit very low-certainty evidence that smoking
cessation is associated with reduced depressive symp-
toms (Taylor GM et al. 2021). However, there is cur-
rently limited evidence from randomised controlled
trial that support smoking cessation interventions for
managing depressive symptoms in people with MDD
(Secades-Villa, Gonzalez-Roz, et al. 2017).
4.2.2. Clinical recommendations
4.2.3. Clinical considerations
4.2.3.1. Type and context of intervention. There are
a wide range of pharmacological and behavioural
approaches that may be beneficial to smoking cessa-
tion for people with MDD. The range of interventions
is largely in line with those that can be offered to the
general population. In the general population, abstin-
ence rates for >6months range from 3% to 5% for
those unassisted through to 25–30% with combined
psychological and pharmacotherapy support (Zwar
et al. 2011). Nicotine replacement therapy is widely
used both within the general population and for peo-
ple with MDD. Previous meta-analyses reported that
nicotine replacement therapy can provide a small but
significant improvement in smoking cessation rates in
those with MDD (Gierisch et al. 2012; Secades-Villa,
GonzC19alez-Roz, et al. 2017). A recent Cochrane review
of antidepressant medications for smoking cessation,
in both populations with MDD and without, reported
that there was high-certainty evidence that bupropion
increased long-term smoking cessation rates. However,
there was a greater risk of adverse events compared
to placebo (Howes et al. 2020). The same review
reported that varenicline has a larger effect size than
bupropion, and that nortriptyline may be effective in a
smaller number of studies (Howes et al. 2020).
Commonly used psychological approaches include
motivational interviewing, cognitive behavioural
approaches, behavioural activation, and mindfulness-
based approaches (Taylor GM et al. 2021). Recent
meta-analytic data suggests that the use of cessation
medications and greater use of behaviour change
techniques was predictive of improved cessation rates
(Black et al. 2020).
4.2.3.2. Smoking-medication interactions. Tobacco
smoking can affect the metabolism of some anti-
depressant and antipsychotic medications (e.g. cloza-
pine, olanzapine, fluvoxamine, duloxetine, mirtazapine,
and trazodone) (Oliveira et al. 2017). Hence, smoking
cessation may also affect metabolism and absorption
of currently prescribed medications and will require
Statement: Smoking cessation interventions that involve counselling and/
or pharmacotherapy (e.g. nicotine replacement) may be used to
reduce depressive symptoms in current smokers with Major
Depressive Disorder
Recommendation Grade: 3
Strength of evidence: Low; Grade C3
Acceptability: Good
Clinical recommendation was based on: Expert opinion
12 W. MARX ET AL.
appropriate monitoring. This may also affect metabol-
ism of caffeine consumed via diet (e.g. coffee, tea,
energy drinks) and therefore may potentiate stimula-
tory effects, resulting in restlessness and sleep distur-
bances (Marel et al. 2016). Thus, smoking status
should be considered in the context of dietary- and
sleep-based mental health approaches.
4.2.3.3. Ongoing support required. Smoking cessa-
tion and MDD appear to have a bidirectional relation-
ship whereby smoking cessation can reduce
depressive symptoms, but the presence of MDD can
also reduce efficacy of smoking cessation efforts
(Stepankova et al. 2017). Past diagnosis of MDD is
associated with decreased abstinence rates and
increased relapse rates (Stepankova et al. 2017).
Furthermore, relevant cognitions (e.g. low self-efficacy)
and behaviours (e.g. smoking as a maladaptive coping
behaviour) that may reduce adherence to smoking
cessation may be more prevalent amongst people
with MDD. These data suggest that, to enhance the
effectiveness of sustained smoking cessation interven-
tions, people with MDD may require further support
and additional long-term monitoring. There are also
some concerns that the intensity of nicotine with-
drawal may lead to heightened fatigue, thus smoking
cessation needs to be initiated under clinical
supervision.
4.2.3.4. Adjunctive lifestyle-based approaches.
Physical activity has been suggested as a potential
adjunctive intervention to standard smoking cessation
programs. However, a Cochrane review of 24 interven-
tions in non-clinical samples reported that there was
no evidence to suggest adjunctive physical activity
enhances the benefits of smoking cessation programs
(Ussher et al. 2019). Despite the lack of evidence that
physical activity facilitates smoking cessation, in add-
ition to its antidepressant effects, physical activity may
reduce symptoms of smoking withdrawal such as irrit-
ability and restlessness, be used as a coping strategy
in response to cravings, and also may help minimise
weight gain associated with smoking cessation (Marel
et al. 2016). Furthermore, incorporation of exercise
and other lifestyle-based approaches may improve car-
dio-metabolic risk factors associated with smoking
(see Box 3).
Sleep disturbances are a recognised consequence
of nicotine withdrawal, occurring in up to 42% of peo-
ple who have quit smoking (Patterson et al. 2019).
These symptoms can arise both from nicotine with-
drawal as well as medications used for smoking
cessation (e.g. varenicline). These symptoms generally
subside after 3–12months post-cessation (Patterson
et al. 2019). Prior studies suggest that both pre-cessa-
tion and post-cessation sleep disturbances are associ-
ated with greater relapse rates, suggesting that
addressing these sleep disturbances may facilitate
long-term cessation (Patterson et al. 2019).
Similarly, weight gain is common after smoking ces-
sation and is a predictor of smoking relapse (Tian
et al. 2015). Lifestyle-based approaches may provide
benefit in managing weight gain. A Cochrane review
found limited clinical trial evidence that has evaluated
such interventions but concluded that physical activity
and personalised dietary interventions may be effect-
ive interventions for post-cessation weight gain (Farley
et al. 2012). Importantly, general weight management
advice only was not effective, suggesting that person-
alised approaches are likely to offer greater benefit.
Finally, smoking cessation and relapse appear to be
highly linked to an individual’s social environment
whereby the perceived reason for ongoing smoking
may be linked to feelings of marginalisation or social
isolation, and where smoking relapse is much higher
in social networks where there are many other smok-
ers (Blok et al. 2017). Within such contexts, smoking
Box 3. Clinical advice and tips for smoking cessation
C15 Provide individualised education on the physical, mental, social,
and financial benefits of smoking cessation
C15 Encourage social support from family and friends and local smok-
ing cessation support groups, including ‘social quitting’ when
multiple people quit at the same time
C15 If required, refer to a smoking cessation specialist
C15 Discuss alternative coping strategies for stressors
C15 Assess and develop strategies with individuals for managing
urges, noting that the strategy intensity should often match the
urge intensity to be effective
C15 Acronyms like ‘DEaDS’ may be helpful in managing urges: Delay
(by 10minutes), Escape/avoid (change environment), Distract (e.g.
call someone, physical activity), Substitute (e.g. nicotine replace-
ment therapy, water)
C15 Discuss management strategies for triggers, such as environmen-
tal cues, linked to smoking
C15 Formal smoking cessation interventions should be discussed with
an appropriate medical practitioner including:
a. Nicotine replacement therapy
b. Specific smoking cessation medications e.g. varenicline
c. Antidepressant medications e.g. bupropion
d. Talking therapies including cognitive behavioural therapy
C15 Provide education related to withdrawal symptoms and
relapse management
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 13
behaviour is likely to have developed and be maintained
as a core vehicle for social connection with others and
may be paired with other substance use behaviours (e.g.
drinking) from which it is challenging to disassociate.
This dynamic can include an individual’s spouse, family,
friends, peers and work environment where smoking is
seen as a normative behaviour (Christakis and Fowler
2008). It can also include mental health settings where
smoking behaviours may have developed and been rein-
forced as part of the social milieu and to alleviate bore-
dom (Lawn SJ et al. 2002). This suggests that strategies
for managing ‘high risk’ social situations, and sub-cultural
and peer contexts where there are many smokers, may
be necessary.
4.2.4. Resources
C15 Co-occurring alcohol and other drug and mental
health conditions in alcohol and other drug treat-
ment settings (Marel et al. 2016). Further guidance
on management of smoking, alcohol, and other
drug use in the mental health setting
C15 Smoking and Mental Health (Mental Health
Foundation 2021b). Resource on the connection
between smoking and mental health that is suit-
able for general public
C15 Supporting smoking cessation: A guide for health
professionals. Second edition (Zwar et al. 2011).
Guidelines for smoking cessation developed by The
Royal Australian College of General Practitioners
4.3. Work-directed interventions
4.3.1. Background literature
In addition to providing financial benefits, employment
also provides considerable social, cognitive and psycho-
logical benefits (Modini et al. 2016). Employment is a
source of routine and structure for an individual and an
avenue for social interaction. Furthermore, an individual’s
employed position can be a significant source of confi-
dence, identity, status, vocational purpose, and self-
esteem. Previous prospective cohort studies suggest that
employment has a protective effect on MDD and psycho-
logical distress (van der Noordt et al. 2014). MDD can
also have a detrimental effect on work performance with
studies showing increased errors and safety issues in peo-
ple with MDD (Nieuwenhuijsen et al. 2020). A further
consequenceofMDDistheincreasedriskofabsenteeism
and unemployment, which may further exacerbate symp-
toms due to the increased isolation, financial stress, and
lack of routine (Wanberg 2012). There is also suggestive
evidence that the adverse mental health effects of
unemployment may be further compounded by
extended unemployment and periods outside of the
workforce (Finnes et al. 2019). Hence, interventions that
address contributing workplace-related factors and that
aim to address barriers to returning to work are likely to
be helpful in clinical management of depression in
unemployed or underemployed individuals. Workplace
culture both generally and pertaining to mental health
and wellbeing, including associated stigma, are also fac-
tors that can influence the mental health of an employee
and minimising mental health injury. Organisational or
occupational factors may need to be considered in the
context of work-directed interventions for those
with MDD.
In a Cochrane review of 45 intervention studies in peo-
ple with MDD, work-focussed interventions as well as clin-
ical interventions such as psychological, pharmacological,
and exercise-based interventions were investigated for
their effect on a range of work-related outcomes
(Nieuwenhuijsen et al. 2020). Interventions that used a
combination of workplace changes and a clinical program
had the strongest evidence and were reported to poten-
tially reduce number of days on sick leave, reduce symp-
toms of depression, and improve ability to cope with
work. There are certain organisational factors that have
been linked to poorer mental health of employees
including job strain (high demand and low control), job
insecurity and precarious employment, bullying and dis-
crimination. It has been estimated that among working
men and women, 13.2%, and 17.2% of depression is
attributable to job strain, respectively (LaMontagne et al.
2008). Protective factors include social support from col-
leagues and supervisors and there is meta-analytic level
evidence indicating that training managers in workplace
mental health may improve their mental health know-
ledge, attitudes towards mental health, and self-reported
behaviour related to supporting employees, though the
data remain in its infancy (Gayed et al. 2018).
4.3.2. Clinical recommendations
Statement: A combination of work focussed counselling and work-
directed interventions could be used to reduce depressive symptoms in
people with Major Depressive Disorder
Recommendation Grade: 2
Strength of evidence: Limited; Grade B
Acceptability: Good
Clinical recommendation was based on: 1C2 Cochrane review (N?8
trials, 1091 participants) (Nieuwenhuijsen et al. 2020)
Reported effect size: Small (Standard mean difference ? 0.25)
(Nieuwenhuijsen et al. 2020)
Risk of Bias assessment: Low ROB meta-analysis of high ROB
individual trials.
14 W. MARX ET AL.
4.3.3. Clinical considerations
4.3.3.1. Determine role of work-related and other
factors in MDD. Determining the role of an individual’s
employment in contributing or causing depressive
symptoms is an important initial step in clinical manage-
ment. This assessment will inform work-related manage-
ment strategies such as if graded work-directed
interventions are available and appropriate. This deter-
mination can be made by clinical judgement based on
a comprehensive clinical assessment and may be appar-
ent in instances where clinical care has been sought
due to mental or psychological injury being reported or
where work compensation claims are sought. While
there is a lack of appropriately validated tools to assess
this,theuseoftoolssuchastheWorkplaceStressors
Assessment Questionnaire and the Work Environment
Scale may help guide clinical assessment (see Table 3 in
the Implementation Consideration section for further
details on assessment tools) (Mazza et al. 2019).
Conditions that are commonly comorbid with work-
related MDD include musculoskeletal pain, trauma, and
substance use (IsHak et al. 2018). Interventions should
assess for, and where appropriate, manage these condi-
tions as they may exacerbate and/or prolong depressive
symptoms. Please see section 6.2 for further information
regarding assessment of lifestyle factors in clinical care.
4.3.3.2. Consider partial return to work where pos-
sible. Extended unemployment increases the risk of
and may exacerbate existing adverse conditions of
unemployment including increased MDD, alcohol
abuse, isolation, hopelessness, decreased self-esteem,
suicide, financial debt, and diminished social status
(Bond et al. 2017; Audhoe et al. 2018). To compound
this further, research demonstrates that the probability
of returning to work decreases as the length of time
since employment increases (Audhoe et al. 2018).
Therefore, partial return to work and related strategies
such as temporarily reducing work hours, graded
exposure to returning to full work capacity, or seeking
deployment to achievable duties, should be consid-
ered to avoid extended absenteeism (Australasian
Faculty of Occupational Environmental Medicine 2010;
Mazza et al. 2019).
4.3.3.3. Need for work directed interventions com-
bined with psychotherapy. A recent Cochrane review
found that a combination of psychotherapy and work-
targeted interventions may be more effective for the
management of MDD than work-targeted interven-
tions alone (Nieuwenhuijsen et al. 2020). Work-directed
interventions may include modifying expected duties of
the role, work routines and work environment, mentor
support programs, and education regarding coping skills
and compensatory work strategies (e.g. stress manage-
ment strategies, memory aids) (Lerner et al. 2020;
Nieuwenhuijsen et al. 2020). People with higher self-effi-
cacy are more likely to return to work and incorporating
interventions that improve self-efficacy may aid in work-
directed interventions (Mazza et al. 2019). Additional
considerations include addressing perceived work quality
(Butterworth et al. 2013), as jobs with a high number of
adverse factors (e.g. job insecurity, psychological
demands) have a comparable risk of MDD relating to
unemployment (Australasian Faculty of Occupational
Environmental Medicine 2010). There are now Mental
Health First Aid programs that are available in many
countries around the world that are designed to assist
managers, peers, friends, family and colleagues in
responding to mental health concerns. They are increas-
ingly being adapted and delivered in the workplace set-
ting (e.g. (Mental Health First Aid International 2022)).
4.3.3.4. Engagement with workplace and occupa-
tional therapists. Where possible and with consent
from the individual, communication with the employer
can assist with treatment through management of work
environment-related factors that may be exacerbating
symptoms (Pomaki et al. 2010). Relaying concerns of the
individual regarding returning to work, perceived bar-
riers, and suggested alternative arrangements to the
employer may facilitate work-directed interventions.
Furthermore, collaboration with the employer may allow
for additional intervention strategies that are difficult to
implement without engagement from the workplace.
Examples of such work-targeted interventions include
partial return, temporary reduction of job demands, and
delegating tasks (Finnes et al. 2019). Working with work-
place rehabilitation providers, when available, can pro-
vide further clinical support, help coordinate, and aid in
delivering individualised work-directed strategies and
education (Schene et al. 2007; Hees et al. 2013). Further
considerations can be seen in Box 4.
4.3.3.5. Volunteering. Volunteering may be a related
avenue where paid employment may not be attain-
able, feasible, or necessary (e.g. post-retirement). A
systematic review of health benefits of volunteering
found mixed evidence of positive impacts on MDD,
though a greater number of the cohort studies
reported reduced levels of MDD than those reporting
no benefits (Jenkinson et al. 2013). Heterogeneity
across studies makes it difficult to synthesise clear
advice, though type of volunteering did not appear to
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 15
influence outcomes, nor did intensity, though sus-
tained volunteering rather than intermittent volunteer-
ing did appear to accrue benefits for addressing MDD,
particularly in older volunteers (Jenkinson et al. 2013).
A more recent systematic review also found benefits
to depressive symptoms from volunteering for older
adults (Filges et al. 2020).
4.3.4. Resources
C15 Realising the health benefits of work – An evidence
update (Australasian Faculty of Occupational and
Environmental Medicine 2015). Guidance document
on return-to-work practices developed by The
Australasian Faculty of Occupational &
Environmental Medicine and The Royal Australasian
College of Physicians
C15 Best Practices for Return-to-work/Stay-at-work:
Interventions for Workers with Mental Health
Conditions (Pomaki et al. 2010). Further guidelines
on return-to-work interventions for people with
mental illness, developed by the Canadian
Occupational Health and Safety Agency
for Healthcare
C15 Clinical guideline for the diagnosis and management
of work-related mental health conditions in general
practice (Mazza et al. 2019). Further guidelines for
general practitioners for the diagnosis and manage-
ment of work-related MDD as well as anxiety,
post-traumatic stress disorder, acute stress disorder,
adjustment disorder and substance use disorder
C15 Returning to work after mental health issues
(National Health Service 2021). Resource developed
by the UK National Health Service on returning to
work for people with mental health issues
4.4. Mindfulness-based and stress management
interventions
4.4.1. Background literature
Stress and MDD have a bidirectional relationship; for
example, life stressors can increase the risk of MDD,
while MDD can increase susceptibility to a height-
ened stress response (Liu and Alloy 2010). Several
biological systems have been implicated in the path-
ology of stress in MDD including hypothalamic pitu-
itary adrenal axis, the sympathetic nervous system,
genetic susceptibility, and changes in brain structure
and function (Hammen 2015). An important aspect
of addressing stressors in MDD is to improve resili-
ency and coping responses that help to attenuate
stress responses. Stress management and mindful-
ness-based approaches in people with MDD can
take various forms. Mindfulness-based stress reduc-
tion (MBSR) has been widely used for the purpose
of targeting stress and to address MDD. Mindfulness
Based Cognitive Therapy (MBCT) is a manualized,
evidence-based psychological treatment for MDD,
and may be preferred for prevention of relapse
(Kuyken et al. 2016). As stated previously, mindful-
ness overlaps with a wide range of psychological
therapies (e.g. Acceptance and commitment therapy,
DBT, and positive psychology) that address similar
domains and concepts but are outside the scope of
these guidelines (Chakhssi et al. 2018; Carr et al.
2021). Relaxation therapies such as progressive relax-
ation training or autogenic training may also be
beneficial for depressive symptoms (Jorm et al.
2008; Klainin-Yobas et al. 2015; Jia et al. 2020). A
Cochrane Review and recent updated meta-analysis
report that relaxation techniques can be beneficial
for depressive symptoms when compared to wait-list
or minimal intervention, but not compared to psy-
chotherapy (Jorm et al. 2008; Jia et al. 2020).
Overall, evidence supports the use of stress man-
agement approaches and specifically mindfulness for
MDD management (Goldberg et al. 2018). Mechanisms
of action remain undetermined but potential cognitive
mechanisms could include an improvement in mind-
fulness, decreases in rumination and worry, and
increasing self-compassion and psychological flexibility
Box 4. Clinical advice and tips related to employment and work-
directed interventions
C15 Where available, an interdisciplinary approach, including the use
of a trained workplace rehabilitation provider, may facilitate
work-directed interventions
C15 Consideration should be given to whether the individual can
engage in work, either at full or reduced capacity. Consideration
needs to incorporate individual related factors (e.g. symptom
severity, personal motivation, comorbidities) and work-related fac-
tors (e.g. work environment, support from management,
ongoing stressors)
C15 Ongoing management should identify and address personal fac-
tors (e.g. personal relationships, finances, housing arrangements),
health behaviours and attitudes, employment factors, and medical
factors that may impair or delay recovery
C15 Work-directed interventions should incorporate the individual’s
functional capacity rather than considering only improvement in
depressive symptoms
C15 Individualised volunteer activities can be encouraged where
employment is not feasible or appropriate
Further information provided by Mazza et al. (2019).
16 W. MARX ET AL.
(Gu et al. 2015; Alsubaie et al. 2017). Mindfulness prac-
tices are also associated with biological pathways rele-
vant to MDD such as changes in hippocampal
structure, autonomic nervous system function, and
inflammatory pathways (Shen et al. 2020).
Mindfulness-based interventions (MBIs) perform com-
parably with cognitive behaviour therapy (CBT) for the
treatment of anxiety and MDD (Hofmann and GC19omez
2017). MBCT may also be more effective for maintain-
ing benefit compared to antidepressant medication
(Zhang Z et al. 2018). MBCT is more effective than
treatment as usual in the long-term prevention of
depressive relapse and time to relapse. However, there
was no statistically significant difference for the rate of
relapse or time to relapse of MDD between MBCT and
active treatments (e.g. CBT and antidepressants)
(McCartney et al. 2021). MBCT and other approaches
that incorporate mindfulness principles may also be
superior to inactive or treatment as usual controls, in
reducing symptoms of MDD, although more high-
quality studies are needed to confirm the efficacy of
these interventions (Seshadri et al. 2021).
4.4.2. Clinical recommendations
4.4.3. Clinical considerations
4.4.3.1. Considerations for delivery of mindfulness-
based interventions. MBIs may be delivered by appro-
priately trained professionals via face to face or digital
technology that includes evidence-based interventions.
Training courses are available to provide upskilling
opportunities and professional development for some
mindfulness methods such as MBCT, where there are
multiple training programs around the world. Side
effects of MBIs such as discomfort, irritability, and a
greater awareness of symptoms of stress or rumin-
ation, can be relatively common, especially initially
(Goldberg et al. 2022). One systematic review found
the overall prevalence of meditation-related adverse
events was 8.3%, which is similar to those reported for
psychotherapy practice in general (Farias et al. 2020).
Such side effects are not necessarily an indication to
terminate therapy but do require careful support and
guidance as the individual learns and assimilates the
skills. An individual’s religious and cultural background
and preferences should also be considered with
respect to the conduct of mindfulness to ensure align-
ment and/or integration.
4.4.3.2. Timing of mindfulness-based interventions.
Learning mindfulness may not be appropriate for
those experiencing acute or severe major depressive
episodes or psychosis. In such situations, it may be dif-
ficult for some to engage and practice, may accentu-
ate unpleasant symptoms, and may require close
supervision in such cases. Alternatively, intervention
may be delayed and safely applied when the individ-
ual is in a more stable condition. In contrast to inter-
ventions for people with elevated acuity, those
experiencing mild depressive symptoms may have a
lower risk of adverse events and requirement for close
clinical oversight may be reduced. Thus, introductory
and self-guided mindfulness training may be war-
ranted and can be facilitated with self-guided digital
health training programs and apps (e.g. Headspace,
InsightTimer, Calm). See Implementation consideration
#8 for further discussion on digital delivery methods.
4.4.3.3. Stress management and relaxation techni-
ques. In addition to mindfulness-based stress reduc-
tion, stress management strategies that are
individualised to the individual’s circumstance, as well
as the provision of psychoeducation regarding stress-
relief (e.g. addressing rest, exercise, and social support)
and relaxation techniques may form a beneficial com-
ponent of treatment and particularly as part of
ongoing management to prevent future depressive
episodes and comorbid disorders such as anxiety.
There are a variety of relaxation techniques that have
been investigated within clinical trials including auto-
genic training, guided relaxation imagery, and breath-
ing exercises with progressive muscle relaxation being
the most studied (Jorm et al. 2008; Jia et al. 2020). An
advantage of relaxation techniques is that they can be
relatively easily implemented without need for
Statement: Mindfulness-based therapies (e.g. Mindfulness Based Cognitive
Therapy [MBCT] and Mindfulness Based Stress Reduction [MBSR]) could
be used to reduce depressive symptoms in people with Major
Depressive Disorder (Grade 2).
Recommendation Grade: 2
Strength of evidence: Limited; Grade B
Acceptability: Good
Clinical recommendation was based on: 1C2 meta-analysis (k?9,
N?762) (Goldberg et al. 2018)
Reported effect size: Moderate (Standard mean difference ? 0.59)
(Goldberg et al. 2018)
Risk of Bias assessment: Low risk of bias meta-analysis of moderate risk of
bias trials
Statement: Stress management and relaxation techniques (e.g. breathing
techniques, progressive muscle relaxation) may be used to reduce
depressive symptoms in people with Major Depressive Disorder
Recommendation Grade: 2
Strength of evidence: Limited; Grade B
Acceptability: Good
Clinical recommendation was based on: 1C2 meta-analysis (k?8,
N?365) (Jia et al. 2020)
Risk of Bias assessment: Low risk of bias meta-analysis of high risk of
bias trials
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 17
specialised training, which suggests that it may be
particularly beneficial where health care access is lim-
ited. Further practical considerations can be seen in
Box 5.
4.4.4. Resources
C15 The Mindful Way Through Depression: Freeing
Yourself from Chronic Unhappiness (Williams et al.
2007). A book on mindfulness practices focussed
on MDD that is suitable for general public
C15 MBCT.com (MBCT.com). Online resource for training
and further information regarding MBCT
4.5. Dietary Interventions
4.5.1. Background literature:
Evidence to support the role of dietary interventions
in MDD and other mental disorders has grown over
the last decade (Marx et al. 2017). Meta-analyses of
both prospective and cross-sectional observational
data support an association between adherence to
nutrient-dense dietary patterns such as the
Mediterranean diet and a reduced risk of MDD (Firth
et al. 2020) These associations have been reported in
multiple international datasets, appear consistent
across the lifespan, and persist after accounting for
relevant potential confounders (O’neil, Quirk, et al.
2014; Lassale et al. 2019; Collins et al. 2022).
Furthermore, a recent harmonised meta-analysis
reported that this association persists when account-
ing for baseline MDD (Nicolaou et al. 2020). At the
same time, diets high in ultra-processed foods are
associated with an increased risk of depressive symp-
toms (Lane et al. 2021).
Meta-analyses of clinical trials that use whole of
diet interventions have provided preliminary evidence
that they significantly reduced depressive symptoms
albeit in small and largely non-clinical populations
(e.g. without current diagnosis of MDD) (Firth et al.
2019a). Several small RCTs have been conducted in
people with MDD and have reported moderate-to-
large improvements in depressive symptoms when
randomised to receive Mediterranean-style dietary
intervention compared to controls (Jacka et al. 2017;
Parletta et al. 2018; Francis et al. 2019; Bayes et al.
2022). Furthermore, cost-effectiveness analysis of these
dietary interventions suggests the possibility for sub-
stantial cost-savings to the individual and health sys-
tem (Chatterton et al. 2018; Segal et al. 2020).
Completion rates in these trials have been high (e.g.
SMILES 93.9% in the diet group and 73.5% in the
social support control group p?0.024) (Jacka et al.
2017). The samples in all studies are small and are
largely confined to Australian populations and this
needs to be taken into consideration. Biological mech-
anisms of action are, however, plausible and include
modulation of pathways involved in inflammation, oxi-
dative stress, mitochondrial dysfunction, the gut
microbiota, tryptophan–kynurenine metabolism, the
HPA axis, neurogenesis and BDNF, and epigenetics
(Marx et al. 2021).
4.5.2. Clinical recommendations
4.5.3. Clinical considerations
4.5.3.1. Type and context. While most randomised
controlled trials that have used dietary interventions
Box 5. Clinical advice and tips to address stress.
C15 Identify and address the underlying causes of stress if possible,
including administering a social needs screening tool (see
Implementation consideration #4). Examples include the provision
of education regarding problem solving skills and/or assertiveness
training and communication skills or linkages with community
and other support workers based on the specific stressor(s)
C15 Provide preventative and therapeutic interventions to enhance
resilience to stressors. Where feasible, these can include identify-
ing and addressing negative cognitions that may be exacerbating
and reinforcing external stressors, positive psychology practices,
loci of control, self-efficacy, social support, lifestyle measures, or
insecure environmental factors (e.g. housing, employment)
C15 Educate and reinforce that regular practice of mind-body techni-
ques (e.g. MBSR, relaxation techniques) improves the skill to
evoke these benefits when needed as well as increasing resilience
to stressors
C15 Mindfulness-based techniques that are delivered by well-trained
professionals are likely to be more effective and mitigate mindful-
ness-related adverse events
C15 Simple techniques include box breathing (breath for 4seconds in,
hold for 4seconds, exhale over 4seconds, hold for 4seconds),
progressive muscle relaxation, and basic mindfulness exercises
C15 Discuss ways to prioritise more time to activities that can reduce
stress, such as time with family, friends, and hobbies
Statement: Dietary counselling to improve nutritional habits that is in
line with healthy dietary guidelines and/or nutrient-dense dietary
patterns may be used to reduce depressive symptoms in people with
Major Depressive Disorder
Recommendation Grade: 3
Strength of evidence: Low; Grade C1
Acceptability: Good
Clinical recommendation was based on: 4C2 randomised controlled trials
(N?395 participants) (Jacka et al. 2017; Parletta et al. 2018; Francis
et al. 2019; Bayes et al. 2022)
Effect size: Moderate to large (Standardized mean difference ?
0.65C01.16)
Risk of Bias assessment: High Risk of Bias
18 W. MARX ET AL.
have used a Mediterranean style dietary pattern, this
does not suggest that a Mediterranean diet is essential
or superior to other healthy dietary patterns. Indeed,
there is a range of healthy dietary patterns that are
associated with reduced MDD risk. These include the
Dietary Approaches to Stop Hypertension (DASH) diet,
dietary patterns characterised by low levels of inflam-
mation or another dietary classification, as well as
healthy traditional dietary patterns (Lassale et al. 2019;
Marx et al. 2021). Instead, the evidence suggests that
any dietary pattern that emphasises the consumption
of nutrient dense, unprocessed foods may be effica-
cious for reducing depressive symptoms. Therefore,
dietary advice and prescription should be individual-
ised with specific consideration of ethical, spiritual
and/or religious preferences, comorbidities, food intol-
erances and allergies, taste preferences, and socioeco-
nomic status. Furthermore, there is a lack of clinical
trial evidence to suggest that more restrictive diets
(e.g. ketogenic diet, vegan) that require exclusion of
commonly consumed food groups are effective and
are not currently recommended for the purpose of
addressing mental health indications.
Opie et al.(Opie et al. 2017) provides further detail
regarding dietary recommendations and can be sum-
marised as adhering to nutrient-dense dietary patterns
that include increased consumption of fruits, vegeta-
bles, legumes, wholegrain cereals, nuts, and lean
meat, while reducing consumption of processed foods.
The consumption of omega-3 rich foods such as fatty
fish is another recommendation that is supported by
previous guidelines (Opie et al. 2017; Guu et al. 2019).
An expanded summary can be seen in Box 6. A com-
mon and important practical concern is the price of
healthier foods. A systematic review and meta-analysis
of 27 studies from 10 countries found that the health-
iest diets cost on average $1.50/day more than the
unhealthiest diets, or approximately $10/week (Rao
et al. 2013). Accessibility and food security is another
crucially important concern that can only be partially
offset by individual or communal preparation, hence
requiring greater emphasis on public health, govern-
ments, and industry to adequately respond.
4.5.3.2. Dose, frequency, intensity. An important con-
sideration in the provision of dietary counselling for
people with MDD is that full adherence to a specific
dietary pattern is not essential to improve depressive
symptoms and is likely an unreasonable expectation,
particularly where depressive symptoms are severe,
resources are limited and/or where motivation and
capacity is low. Indeed, current dietary intervention
studies in MDD focussed on individualised improve-
ment in diet quality rather than full adherence (Jacka
et al. 2017; Parletta et al. 2018).
Strategies to improve diet quality that were incor-
porated in these interventions included ‘swaps’
whereby participants were encouraged to replace cur-
rently consumed nutrient-poor food items with nutri-
ent-dense alternatives (e.g. replacing white rice with
brown rice). The SMILES trial demonstrated that partic-
ipants made significant dietary changes by reducing
their discretionary items by on average 21.8 items
(SD16) per week (Jacka et al. 2017).
4.5.3.3. Assessment considerations. Screening tools
have been developed that aid in identifying people
with low diet quality and may assist with initial discus-
sions regarding diet interventions. All tools have bene-
fits and limitations, and common amongst all self-
reported tools is the potential of recall bias. Where
feasible, dietary assessments conducted by trained
professionals (e.g. dieticians) will likely provide greater
precision. The use of assessment tools and prompting
questions is further discussed in the section 6 of
this document.
4.5.3.4. Weight loss dietary advice. The clinical trial
evidence on dietary interventions suggests that
Box 6. Clinical advice and tips for diet.
C15 Encourage adherence to nutrient-dense, minimally processed diet-
ary patterns, such as the Mediterranean diet
C15 Incorporate joy, social connection, and mindfulness into the ‘food
experience’ where possible
C15 Where required and available, refer to a trained dietician
C15 Increase consumption of fruits, vegetables, legumes, wholegrains,
nuts, seeds, herbs and spices as tolerated
C15 Cooking in bulk and freezing, planning meals in advance, and
buying frozen vegetables, canned and dried legumes, and tinned
fish can be affordable, convenient, and nutrient dense
C15 Include a high consumption of foods rich in omega-3 polyunsat-
urated fatty acids and fibre
C15 Limit intake of ultra-processed foods and discretionary foods, and
replace ultra-processed foods with minimally processed nutri-
tious foods
C15 Consume red meat in moderation and opt for lean sources rather
than processed and/or fatty cuts, considering the individual’s cul-
tural-religious background
C15 Include extra virgin olive oil as the main source of cooking and
added oil
C15 Consume the daily recommended water intake
C15 Avoid excessive alcohol consumption
Partially adapted from Opie et al. (2017)
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 19
improvement in depressive symptoms can be
achieved independent of weight loss (Jacka et al.
2017; Parletta et al. 2018; Francis et al. 2019).
Therefore, ad libitum dietary advice that focuses on
healthy eating strategies rather than weight loss or
calorie restriction can be provided for the manage-
ment of depressive symptoms. However, people with
mental disorders have significantly higher levels of
comorbidities and metabolic disorders compared to
the general population and certain psychotropic medi-
cations may increase appetite and reduce satiety. In
these circumstances, weight maintenance and man-
agement strategies may be warranted for the manage-
ment of physical comorbidities where risk of
metabolic disorders is present.
4.5.3.5. Dietary supplement use. The use of dietary
supplements is a related area with considerable public
interest. Formal clinical guidelines regarding the use
of nutraceutical interventions in psychiatry have been
recently published by the WFSBP and can be accessed
elsewhere (Sarris et al. 2022). Due to the considerable
benefit of a healthy diet to physical and metabolic
health, dietary interventions should be prioritised over
supplementation with individual nutrients. However,
supplementation may be warranted in situations
where dietary interventions may not be feasible (dur-
ing severe acute episodes, limited access to nutrition
counselling support), when treating confirmed nutrient
deficiencies, or in combination with a whole of
diet approach.
4.5.3.6. Therapeutic approaches in dietary counsel-
ling. MDD may affect dietary adherence, food prefer-
ences, and appetite, as a direct result of MDD or due
to medications given to treat MDD. Factors such as
fatigue, reduced motivation, and apathy may also
reduce the effectiveness of dietary interventions that
are not suited to the individual’s cognitive and motiv-
ational capacity (Kwan et al. 2014). Cognitive barriers,
motivational difficulties, and disorganised lifestyles are
additional challenges that may reduce the effective-
ness of dietary interventions, particularly in those with
more severe mental illness (Kwan et al. 2014).
Furthermore, MDD (and mental illness more broadly)
is associated with comorbidities such as obesity and
diabetes that require specific dietetic considerations.
As discussed by Kwan et al (Kwan et al. 2014), the use
of motivational interviewing, incorporating multimodal
techniques, improving awareness of nutrition require-
ments, and providing individualised and structured
eating advice are some techniques that can be
incorporated to overcome these challenges. Dieticians
are trained to provide appropriate nutritional manage-
ment and may help ensure sustainable dietary
improvements.
4.5.4. Resources
C15 The International Society of Nutritional Psychiatry
Research (ISNPR) (ISNPR – International Society for
Nutritional Research 2021). The ISNPR is a global
network for researchers that aims to promote the
generation and translation of high-quality evidence
for nutritional approaches to the prevention and
treatment of mental disorders.
C15 A modified Mediterranean dietary intervention for
adults with major depression: Dietary protocol and
feasibility data from the SMILES trial (Opie et al.
2018). This publication provides a detailed guide of
the dietary intervention used for the SMILES trial
and may serve as a valuable reference for future
clinical trial design as well as a guide to providing
dietary interventions in clinical practice.
C15 Food and Mood: Improving Mental Health Through
Diet and Nutrition (FutureLearn 2021). A free online
course available to the general public on the cur-
rent evidence regarding dietary interventions in
mental health.
C15 Feeding melancholic microbes: MyNewGut recom-
mendations on diet and mood (Dinan et al. 2019).
Further information regarding specific components
of healthy dietary patterns and current evidence
for their potential role in MDD.
C15 Clinician guidelines for the treatment of psychiatric
disorders with nutraceuticals and phytoceuticals: The
World Federation of Societies of Biological Psychiatry
(WFSBP) and Canadian Network for Mood and
Anxiety Treatments (CANMAT) Taskforce (Sarris et al.
2022). Recently published clinical guidelines on
dietary supplement interventions in men-
tal disorders
4.6. Sleep-related interventions
4.6.1. Background literature
MDD and sleep have a bidirectional relationship in
that poor sleep contributes to depression and depres-
sion results in poor sleep. Most people with acute
MDD report difficulties initiating and/or maintaining
sleep. The prevalence of insomnia symptoms in peo-
ple with MDD is estimated at 80-90% (McCall et al.
2000; Novick et al. 2005), and diagnosable insomnia is
present in as many as two-thirds (Geoffroy et al.
2018). The DSM-5 recognises sleep changes (‘insomnia
20 W. MARX ET AL.
or hypersomnia nearly every day’) as symptomatic of a
major depressive episode (American Psychiatric
Association 2013). Sleep disturbances in a major
depressive episode correlate with MDD severity
(Soehner et al. 2014), are a significant driver of distress
and impaired quality of life (Mayers et al. 2003), and
are independently associated with suicidal ideation
and suicide attempts (Pigeon et al. 2012).
The presence of insomnia increases the risk of sub-
sequent MDD onset by approximately 3 times (Breslau
et al. 1996; Morphy et al. 2007; Hertenstein et al.
2019). Residual sleep disturbances are common after
acute phase treatment for MDD (Romera et al. 2013)
and increase the risk of future depressive relapse
(Dombrovski et al. 2007; Franzen and Buysse 2008).
Sleep difficulties also predict a poor response to
guideline-based care for MDD such as CBT (Asarnow
and Manber 2019). The converse is also the case: MDD
predicts and can trigger insomnia disorder (Franzen
and Buysse 2008), which will require its own inde-
pendent attention once MDD is successfully treated
(Sweetman et al. 2021). This is particularly important
as residual symptoms of insomnia, despite successful
treatment of MDD, are associated with an increased
risk of relapse (Combs K et al. 2014).
Bidirectional causal relationships between insomnia
and MDD have been demonstrated in a Mendelian
randomisation study by Cai and colleagues (Cai et al.
2021). Interestingly, the genetic liability of insomnia
on MDD was much larger than vice versa, with the
authors concluding the disparity is consistent with the
utility of sleep interventions as therapies for neurode-
generative and psychiatric disorders. These findings
parallel experimental and quasi-experimental research
showing that sleep deprivation increases negative
affect and decreases positive affect in response to
goal-enhancing events (Harvey et al. 2011; Konjarski
et al. 2018).
A recent systematic review and meta-analysis of
N?65 relevant clinical trials (72 interventions,
N?8608 participants) confirms that sleep is also a
modifiable risk factor for MDD (Scott et al. 2021). Scott
et al. found improvements in depressive symptoms by
sleep-focussed interventions to be mediated through
improved sleep quality (g?C00.47, 95%CI [C00.57,
C00.37], p<0.001 after outliers removed to decrease
heterogeneity) (Scott et al. 2021). Insomnia symptoms
are therefore an important target for improving MDD
outcomes, with MDD benefits dependent on sleep
improvements (similar findings are reported elsewhere
(Bei et al. 2018; Henry et al. 2021)). Effective
approaches for sleep problems may augment MDD
treatment in acute and maintenance phases (Freeman
et al. 2020).
4.6.2. Clinical recommendations
4.6.3. Clinical considerations
4.6.3.1. Considerations in the management of
MDD and insomnia symptoms. MDD treatment and
insomnia treatment may be offered concurrently or
sequentially, with choice of initial treatment depend-
ing on individual preference, presenting symptoms
and severity, history, lifestyle factors and other comor-
bidities. If treatment does commence with a focus on
MDD, CBT-I should be re-considered if the comorbid
insomnia is a barrier to antidepressant treatment or
appears to be maintained by insomnia-specific factors
such as unproductive beliefs about sleep and poor
sleep hygiene practices. Insomnia management can be
accessed by referral to a CBT-I trained psychologist in
some healthcare systems.
4.6.3.2. Clinically significant sleep disturbance
should be treated as a common comorbidity of
MDD. Current editions of both relevant international
diagnostic taxonomies highlight the need for focussed
clinical attention on sleep disorders, irrespective of the
presence of psychiatric or medical conditions (Seow
et al. 2018). In relation to insomnia, the legacy distinc-
tion between ‘primary’ and ‘secondary’ insomnia was
removed from DSM-5 (Reynolds and O’Hara 2013) and
the International Classification of Sleep Disorders,
Third Edition (ICSD-3) (Sateia 2014). Clinicians are
instead encouraged to recognise bidirectional relation-
ships between sleep and MDD, and actively pursue
insomnia as a potential comorbidity of MDD warrant-
ing diagnosis and attention in its own right (Seow
et al. 2018; Grima et al. 2019).
4.6.3.3. Assessment and screening of comorbid
sleep disturbances. Sleep disturbance is a common
Statement: Cognitive behavioural therapy for insomnia (CBT-I) could be
used to reduce depressive symptoms in people with Major Depressive
Disorder (Grade B evidence).
Recommendation Grade: 2
Strength of evidence: Limited; Grade B
Acceptability: Good
Clinical recommendation was based on: 1C2 Meta-analysis (k?8 studies,
N?491 participants) (Selvanathan et al. 2021)
Reported effect size: Medium effect size (standardized mean difference ?
0.5)
Risk of bias assessment: Low ROB meta-analyses of high ROB
individual trials.
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 21
reason for seeking primary care treatment, and sleep
interventions can be viewed as less stigmatised than
mental health treatments (Aikens and Rouse 2005;
Gee B et al. 2019). A recent practice review in the
Australian context presents detailed clinical recom-
mendations for optimal management of comorbid
MDD and insomnia (Sweetman et al. 2021). Noting
that the majority of people with MDD in primary care
are likely to present with both MDD and insomnia,
Sweetman et al.(Sweetman et al. 2021) recommended
that people with MDD be assessed for insomnia, and
vice versa. We extend this recommendation to include
assessment for, and specific treatment of, any sleep
problems comorbid with MDD (assessment described
below) (Sarfan et al. 2021). Importantly, those present-
ing with major depressive episodes must be actively
probed for an underlying bipolar diathesis, because
the stimulus control and sleep restriction components
of sleep interventions, such as cognitive behavioural
therapy for insomnia (CBT-I), may need modification
for people at risk of elevated mood states (Gottlieb
et al. 2019; Morton and Murray 2020). Clinical features
of bipolar diathesis are family history, history of hypo-
manic symptoms, history of treatment-resistant MDD,
and antidepressant-related hypomania (McIntyre et al.
2019). Symptoms of hypomania can be probed using
the Hypomanic Personality Scale (Eckblad and
Chapman 1986) or 7 Up 7 Down inventory
(Youngstrom et al. 2013).
4.6.3.4. Assessment considerations. Sleep parameters
can be measured subjectively and objectively. Sleep
variables typically include sleep onset latency (SOL;
time needed to fall asleep), wake after sleep onset
(WASO; periods of wakefulness after sleep onset),
total sleep time (TST; the amount of time asleep in
bed); time in bed (TIB; the amount of time spent in
bed, including non-sleep activities); sleep efficiency
(SE; TST/TIB C2 100%); number of awakenings (NOA);
and subjective sleep quality. Self-report sleep meas-
ures include insomnia severity measured by sleep
diaries(Carney et al. 2012) the Insomnia Severity
Index (ISI) (Bastien et al. 2001) and the Pittsburgh
Sleep Quality Index (PSQI) (Buysse et al. 1989),
sleep-related cognitions measured by the
Dysfunctional Beliefs and Attitudes about Sleep
(DBAS-16) (Morin et al. 2007), and daytime sleepi-
ness measured by the Epworth Sleepiness Scale
(ESS) (Johns 1991). The diagnosis of insomnia can
be made on self-report of sleep difficulties.
Actigraphic measurement may be useful to improve
precision of the characterisation of sleep, and
therapeutic targeting of poor sleep hygiene. Referral
to a sleep specialist, and an overnight sleep study is
recommended if there are queries about other
causes of disturbed sleep (e.g. restless leg syndrome,
sleep apnea). See Implementation Considerations
section for further discussion of assessment tools.
4.6.3.5. The use of CBT-I in the context of MDD.
Insomnia may be an important therapeutic target to
assist management of depressive symptoms in people
with diagnosed MDD (Henry et al. 2021). Three recent
systematic reviews have investigated the antidepres-
sant effects of CBT-I amongst people diagnosed with
insomnia and subsyndromal depressive symptoms
(Ballesio et al. 2018; Benz et al. 2020; Ho et al. 2020).
A recent systematic review and meta-analysis of 8
randomised controlled trials in people with MDD and
insomnia reported that CBT-I provided benefit to both
depressive and insomnia symptoms with a moderate
effect size (Selvanathan et al. 2021). Digital CBT-I,
especially in fully automated format, has received sig-
nificant attention over the past decade (Krystal 2021),
and is elevated here because of its recognised transla-
tional potential (Kraepelien et al. 2021). There are
emerging intervention studies that suggest that such
interventions may be beneficial for both people with
subsyndromal and MDD (Blom et al. 2015; Ye et al.
2015; Blom et al. 2017; Chan et al. 2021; Henry
et al. 2021).
4.6.3.6. Sleep hygiene type and style. Maintaining
good sleep hygiene habits can help people with
MDD improve their sleep quality. Sleep education
resources can be integrated into their daily routines.
Despite a lack of robust evidence of the effective-
ness of sleep hygiene in the management of MDD,
one meta-analysis found that sleep hygiene was
associated with sleep improvement, although a
definitive conclusion could not be drawn (Chung K-F
et al. 2018). Clinicians can consider verbal advice of
sleep hygiene as an appropriate and easily imple-
mented strategy to adjunct conventional interven-
tions in general practice. Nonetheless, there is no
consensus regarding the most effective elements,
optimal dose, or frequency. Many versions of sleep
hygiene strategies are available. Box 7 provides a
sample of these strategies. A clear explanation of
the underlying mechanism of each sleep hygiene
recommendation may enhance treatment adherence.
This can, in turn, be supported by completion of
self-rated sleep hygiene tools (see Table 3 in sec-
tion 6).
22 W. MARX ET AL.
4.6.4. Resources
C15 How to Sleep Better (Mental Health Foundation
2022). Downloadable pamphlet on sleep hygiene
developed by Mental Health Foundation UK
4.7. Loneliness and social support related
interventions
4.7.1. Background literature
Whilst loneliness may be experienced more commonly
by some groups (e.g. older adults), it can be experi-
enced at any age (Australian Institute of Health and
Welfare 2021). Loneliness is not exclusively an object-
ively measured construct (e.g. number of people living
in a household); rather, it has been defined as a
‘negative psychological response to a discrepancy
between the social relationships one desires (expecta-
tions) and the relationships one actually has (objective,
real ones)’ (Yanguas et al. 2018).
Greater loneliness may predict poorer MDD out-
comes (Wang J et al. 2018). For example, a review of
34 longitudinal quantitative studies examining the
relationship between baseline measures of loneliness
and poor perceived social support and outcomes at
follow-up found that people with MDD who perceive
their social support as poorer have worse symptoms,
recovery and social functioning (Wang J et al. 2018).
For people with MDD, the odds of being lonely may
be up to 10 times greater than the general popula-
tion. These odds increase for those with additional
psychiatric disorders (Meltzer et al. 2013). Furthermore,
loneliness is also associated with other psychiatric dis-
orders including those that involve psychotic symp-
toms and paranoia (Solmi et al. 2020). Loneliness has
been linked to increased suicidality with those
experiencing severe loneliness being 17 times more
likely to have made a suicide attempt in the past
12months (Stickley and Koyanagi 2016). An absence
of social support and poor social functioning can pre-
dict poor treatment response, depressive symptoms,
early dropout from treatment, and risk of MDD relapse
(Kawachi and Berkman 2001; Solmi et al. 2020).
Conversely, membership of social groups can protect
against developing MDD, alleviate existing MDD, and
prevent MDD relapse (Cruwys et al. 2013). The rela-
tionship between loneliness and depression is also
likely bidirectional, as depression commonly presents
with social withdrawal.
A related concept to loneliness is social support,
which can be defined as ‘the care that is either pro-
vided or perceived to be readily available in times of
need’ and can be measured objectively (Haslam et al.
2015). An important distinction to be made is that
one may have objectively many avenues for provided
social support while still feeling unsupported, resulting
in a low rating of perceived social support (Santini
et al. 2015; Mann et al. 2017). While perceived and
provided social support are interrelated concepts, they
do not necessarily occur together (Mann et al. 2017).
Indeed, previous observational studies have reported a
much stronger body of evidence associating perceived
social support with depressive symptoms than pro-
vided social support (Santini et al. 2015). Furthermore,
intervention studies have investigated the effect of
various interventions that address both objective and
perceived social support with a recent review
Box 7. Clinical advice and tips for sleep hygiene.
C15 Where required and available, refer to a sleep specialist
C15 Individuals should avoid going to bed unless tired
C15 Establish a consistent sleep schedule on both weeknights
and weekends
C15 Aim for at least 7h of sleep
C15 Reduce screen time and other sources of bright/artificial lighting
before bedtime
C15 Reduce fluid intake before bedtime particularly, caffeinated and/
or alcoholic beverages
C15 Introduce relaxing activities prior to going to bed (e.g. mindful-
ness-based meditation)
C15 Individuals should ensure the place of sleep is relaxing, dark, and
is at a comfortable temperature
Box 8. Clinical advice and tips to address loneliness and
social support.
C15 Explore options for using digital platforms to generate positive
social connections, role models, peer support, and generating in-
person social connections
C15 Use behaviour change techniques to support reconnecting with
past and present beneficial social connections that have gone
dormant, and establishing new social connections through shared
values and interests
C15 Assess for and address negative cognitions related to
social engagement
C15 Assess social media use and related behaviours. Assessment tools
related to problematic internet use may aid this (Tiego
et al. 2021)
C15 Specific populations (e.g. older adults, CALD communities) and
people experiencing major life events (e.g. retirement, job loss)
are at a greater risk of loneliness
C15 Social prescribing models, where available, may be beneficial in
addressing loneliness
C15 Interventions should be personalised to individual circumstances
and preferences (e.g religiosity, spirituality) and may incorporate
other lifestyle domains (e.g. team sport)
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 23
concluding that while these interventions had some
success in improving objective measures, no interven-
tion style was clearly effective in improving perceived
social outcomes (Mann et al. 2017; Ma et al. 2020).
Hence, as a result, the strength of evidence for this
clinical recommendation is limited to expert opinion
due to the lack of clear research on how perceived
and provided social support can be genuinely imple-
mented to lead to improvements in those with MDD
(see Box 8 for clinical tips and advice). However, given
the presence of evidence indicating loneliness and
social support as crucial concepts to understand
because of their relationship to human physical, men-
tal and social wellbeing, especially in the contempor-
ary COVID-19 era, this is an urgent area of future
clinical research.
4.7.2. Clinical recommendations
4.7.3. Clinical considerations
4.7.3.1. Type and context of intervention. Mann
et al.(Mann et al. 2017) recently provided an overview
of currently investigated interventions for loneliness
and social isolation and categorised existing interven-
tions into four broad categories that address: (1) social
skills; (2) existing social support; (3) opportunities for
new social contact; and (4) maladaptive social cogni-
tions. Their review concluded that, while cognitive
interventions that address ‘maladaptive’ cognitions
held the most promise, there is insufficient evidence
to recommend one intervention over another. This
was corroborated by Ma et al.(Ma et al. 2020)ina
recent review of loneliness and social isolation inter-
ventions for people with mental illness where they
reported that, while some interventions, particularly
those that used psychoeducation and supported
socialisation interventions, had some evidence in
improving objective measures of social isolation, few
studies had investigated subjective feelings and, of
those that did, few reported positive results. Given the
lack of clear evidence for a particular style of interven-
tion to address loneliness in those with MDD, any
intervention needs to be based on individualised clin-
ical judgement until further evidence is generated.
4.7.3.2. Assessment considerations. While loneliness
can be experienced by any individual, particular
groups are at a higher risk. Identification of such indi-
viduals may allow for early intervention to be put in
place. Individuals who have recently experienced a
significant ‘transition point’ are at a greater risk of
loneliness and this may present as MDD. Transition
points include changes in employment (e.g. retire-
ment, job loss), relationships (e.g. death of a partner,
relationship breakup), location (moving communities),
and health status (e.g. chronic disease diagnosis, new
disability) (Lim, Eres, et al. 2020). Furthermore, older
adults are at greater risk of loneliness compared to
the general population due to several factors such as
retirement and increased risk of physical comorbidity,
which may bring changes to their usual social and
community connections. Other populations include
Culturally and Linguistically Diverse (CALD) and
expatriate communities where social connections may
not yet be established and where barriers such as dif-
ferences in language and culture may be apparent.
4.7.3.3. Indirect intervention via other lifestyle fac-
tors. In addition to interventions that may directly tar-
get social isolation and loneliness, use of interventions
that address other lifestyle factors may indirectly
address feelings of loneliness. Increasing physical
activity, for example, may help address feelings of
loneliness through increased social exposure (e.g. exer-
cise classes) and social connection (e.g. team sports).
Furthermore, returning to work or volunteering oppor-
tunities may provide stable avenues for social inter-
action (Filges et al. 2020). There is also an important
element to cooking, food preparation and dining that
can foster both nutrition and social engagement.
4.7.3.4. Avenues and programs for social engage-
ments. Awareness of available resources and pro-
grams that are locally available and that can improve
social support can allow for individualised recommen-
dations for those experiencing loneliness. Such ave-
nues might include community groups such as church
groups, hobbies, and support groups; sports clubs;
family, friends, and spouses; and volunteering oppor-
tunities. Engaging with allied health professionals may
provide additional field-specific resources for
social engagement.
A related concept is ‘Social Prescribing’ which
involves connecting individuals from within the pri-
mary care setting with community organisations and
resources with the help of dedicated linkage workers.
Despite it being recently widely adopted in countries
Statement: Improving social support and reducing loneliness may be used
to reduce depressive symptoms in people with Major
Depressive Disorder
Recommendation Grade: 3
Strength of evidence: Low; Grade C3
Acceptability: Good
Clinical recommendation was based on: Expert opinion
Risk of bias assessment: Not applicable
24 W. MARX ET AL.
such as the UK, there are currently limited studies that
support the use of social prescribing for the treatment
of MDD (Bickerdike et al. 2017). However, short-term
improvements in MDD have been found and those
participating in social prescribing interventions have
reported general improvements in feelings of loneli-
ness and social isolation (Bickerdike et al. 2017).
4.7.3.5. Addressing barriers to social connection. In
addition to facilitating avenues for social connection,
sustainable uptake is contingent on addressing the
barriers to engaging with such avenues. Potential bar-
riers to forming social connection may include factors
such as limited physical access to social resources,
digital literacy, geographic location, cultural norms
and customs and financial constraints. Furthermore,
psychosocial factors such as social anxiety may pre-
vent social engagement despite the availability of
adequate avenues for engagement. Feelings of loneli-
ness can be accompanied by self-stigmatisation, per-
ceived stigma from others, feelings of failure and a
loss of self-esteem. One proposed strategy for address-
ing such stigma is through peer support where indi-
viduals can engage with people with lived experience
of loneliness and/or MDD (Lim, Badcock, et al. 2020). It
is also acknowledged that finding enjoyment, meaning
and purpose in life can be challenging for those living
with MDD and this may be a barrier in uptake to such
programs. Clinicians should work to support the per-
son in the context of their episode trajectory, espe-
cially where co-morbid social anxiety, or physical or
psychosocial disability, is present.
4.7.3.6. Social media, social connection, and mental
health. Research has started to explore the impacts of
social networking and use of social media on mental
health. A 2016 systematic review found that positive
interactions, social support, and social connectedness
on social media platforms were consistently related to
lower levels of depression and anxiety, and negative
interaction and social comparisons on social media plat-
forms were related to higher levels of depression and
anxiety (Seabrook et al. 2016). These findings suggest
that it may be more important to understand how social
networking is used rather than the type of social media
itself. However, given the highly designed and refined
nature of social media platforms to encourage use, it
can be challenging for users to solely use them in a
beneficial manner, especially for people experiencing
MDD. A recent 2021 meta-analysis of social media and
depression symptoms was the first to consider the
multi-dimensional nature of social media use (time
spent using social media, intensity of use, and problem-
atic social media use) (Cunningham et al. 2021). It found
depression symptoms were significantly, but weakly,
associated with time spent using social media and
intensity of use. However, the association of depression
symptoms to problematic social media use was moder-
ate (r?0.29). ‘Problematic social media use’ is a term
being increasingly used in clinical and research arenas.
While definitions vary, problematic social media use
reflects a pattern of use that is characterised by behav-
ioural and psychological features of addiction, involving
a compulsion to engage despite the potential negative
consequences, engaging without realising, using in bed
and using quickly on waking. Hence, for the clinician,
these are useful habits to elicit when taking a history of
social media use where either reduction, abstinence or
redirection to positive uses can be offered (e.g. social
connection with groups of shared and benevolent val-
ues, as an educational tool), and counselling around
social comparisons and negative interactions can be
offered along with relevant psychotherapy, as required.
4.7.4. Resources
C15 A life less lonely: the state of the art in interventions
to reduce loneliness in people with mental health
problems. A detailed review of current formal inter-
ventions for addressing loneliness and provides a
list of UK-based social prescribing programs (Mann
et al. 2017).
C15 Ending Loneliness Together (Ending Loneliness
Together 2020). An Australian-based initiative that
provides resources for addressing loneliness
C15 British Geriatrics Society and Royal College of
Psychiatrists Position Statement on Loneliness and
Social Isolation (British Geriatrics Society 2019).
4.8. Green space interaction
4.8.1. Background literature
Although precise definitions differ, green space, or
nature-based interventions, refer to interventions
designed to increase an individual’s exposure to vegeta-
tion-rich environments or bodies of water (also some-
times referred to as blue space) (Taylor and Hochuli
2017). These environments can be urban based (e.g.
parks, backyards) or natural environments (e.g. beaches,
forests) (Shanahan et al. 2019). Increased exposure to
green space is associated with reduced odds of depres-
sive symptoms in observational studies (Gascon et al.
2017; Houlden et al. 2018). Multiple mechanisms of
action have been proposed that relate to evolutionary
factors, bioactive compounds within the natural
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 25
environment, divergence from habitual patterns of nor-
mal experience, and promotion of physical activity
(Aerts et al. 2018; Zhang R et al. 2021). Limited interven-
tion studies largely in non-clinical samples have also
reported improvements in stress, quality of life, and
mood (Roberts et al. 2019). Furthermore, there are a
small number of studies, predominantly using a single
arm study design, that have reported various green
space interventions improve depressive symptoms in
people with MDD (Barton et al. 2012; Berman et al.
2012; Korpela et al. 2016; Vujcic et al. 2017).
Due to the limited clinical intervention data, par-
ticularly in those with a clinical diagnosis of MDD, firm
recommendations regarding typical intervention fac-
tors such as dose, type, and frequency are premature.
However, due to the high acceptability and low risk of
green space interaction and likely benefits to other
lifestyle domains (e.g. increased physical activity, social
interaction), encouraging interaction with green space
should be considered as a component of care (see
Box 9 for practical advice and tips).
4.8.2. Clinical recommendations:
4.8.3. Clinical considerations
4.8.3.1. Type and context of intervention. There is
insufficient evidence to suggest that a particular green
space setting is more therapeutic than another. Due
to the wide variety of green space settings (e.g. parks,
gardens, forests) and modes of exposure (e.g. walking,
running, sitting), recommendations should be individu-
alised with consideration for individual level (preferen-
ces, capacity, mobility, socioeconomic status, location),
and area level factors (pollution, neighbourhood or
cultural safety, access). Similarly, individualised discus-
sion regarding the mode of green space interaction is
warranted to ensure sustained participation. Indeed,
while some evidence suggests that passive immersion
in green spaces (e.g. walking or sitting) can yield
health benefits (Lovell et al. 2015), there is some evi-
dence that structured programs, taking place within
green spaces, may be more effective than only chang-
ing the person’s physical environment (Hunter et al.
2015). These include horticultural or garden therapy
(Genter et al. 2015; Cipriani et al. 2017), walking
groups (Hanson and Jones 2015), wilderness therapy
(Combs KM et al. 2016; Harper et al. 2019), and out-
door sports and activities (e.g. hiking, camping, swim-
ming, tai chi). In these settings, the presence of
trained facilitators is a key component to the pro-
gram’s success (Bloomfield 2017; Masterton et al.
2020). An additional benefit of participation in a struc-
tured program is that they are usually undertaken in
settings that promote social interaction. Indeed, partic-
ipants of green space interventions report the feeling
of community was the most valuable component of
the program which makes it difficult to elucidate the
direct and indirect benefits of such approaches
(Fieldhouse 2003; Hassink et al. 2010; Barley et al.
2012; Adevi and M?rtensson 2013).
4.8.3.2. Dose, frequency, intensity. Previous reviews
have contained recommendations about the required
‘dose’ of green space exposure from which to achieve
mental health benefit. Authors conclude that a min-
imum 10-20minutes per exposure may be required
time to provide psychological and/or physiological
benefits to mental health outcomes (Meredith et al.
2020). A recent longitudinal study found that well-
being increased significantly with weekly contact with
nature C21 120min (White et al. 2019). People with
MDD should be encouraged to simply increase their
exposure to green space above their current habitual
exposure rather than prescriptive advice on a set time.
A related factor is ‘nature intensity’ (also referred to as
‘vegetation complexity’), describing the level of
Statement: Support regarding individualised interaction with green
spaces or participation in a green space-focussed program may be
used to reduce depressive symptoms in people with Major
Depressive Disorder
Recommendation Grade: 3
Strength of evidence: Low; Grade C1
Acceptability: Good
Clinical recommendation was based on: 2 randomised controlled trial
and 2 non-randomised clinical trials (N?116 participants) (Barton
et al. 2012; Berman et al. 2012; Korpela et al. 2016; Vujcic et al. 2017)
Reported effect size: Small to Large (Multiple effect size metrics used)
(Barton et al. 2012; Berman et al. 2012; Korpela et al. 2016; Vujcic
et al. 2017)
Risk of bias assessment: High ROB
Box 9. Clinical advice and tips for green space interaction.
C15 Explore individual and area level factors when initiating green
space-related behaviour change to promote uptake and
sustainability
C15 Even small levels of green space exposure may provide benefit
and so encouraging small bouts of green space exposure may
help aid in establishing new routines.
C15 Encourage forms of green space exposure that the individual
finds enjoyable and relaxing
C15 Seek out formal programs where available such as walking
groups, garden tours, and outdoor mindfulness and exer-
cise programs
C15 Encourage incorporating social components to green space
exposure such as engaging with friends and/or family members
C15 Incorporating natural elements into current living environment
can increase green space exposure where outdoor exposure is
not possible or overwhelming
26 W. MARX ET AL.
biodiversity of a specific green space environment and
how this may affect possible benefits to mental health
(Lovell et al. 2014). The evidence supporting a positive
association between nature intensity and mental well-
being is, however, limited (Houlden et al. 2018).
Instead, factors relevant to individual preferences,
feasibility and accessibility should be prioritised
(Shanahan et al. 2015).
4.8.3.3. Sunlight exposure and depressive symp-
toms. Related to the potentially beneficial effect of
green space environments is the emerging evidence
for sun exposure for improving depressive symptoms.
Possible mechanisms relate to the increased produc-
tion of vitamin D and serotonin synthesis as well as
modulation of relevant immune pathways (Slominski
et al. 2005). Regular sunlight exposure may also bene-
fit sleep interventions through regulation of the circa-
dian rhythm, which can be disrupted in people with
MDD (McClung 2011). A growing number of observa-
tional and intervention studies suggest that ultraviolet
light exposure may improve measures of depressive
symptoms and mood (Lam et al. 2016; Veleva et al.
2018). While much of the intervention evidence relates
to the use of bright light therapies within controlled
environments, rather than regular sunlight exposure,
this suggests that encouraging green space interaction
that also incorporates sun exposure may have additive
benefits to reducing depressive symptoms.
4.8.4. Resources
C15 ParkRx (Parkrx 2019). Provides further resources and
toolkits for green space interventions and further
information on USA-based models of implementation
C15 New Zealand’s Ministry of Health Green Script pro-
gram (Ministry of Health New Zealand 2021). An
example of a health service initiative that incorpo-
rates green space focussed interventions
5. Future research needs in lifestyle-based
mental health approaches for Major
Depressive Disorder
Despite a growing evidence base that supports the use
of lifestyle-based approaches in mental health care, there
is a clear need for further research to improve the
strength of evidence, refine understanding of the most
effective elements, and to inform best practice. This is
evidenced by the recommendations (section 4)devel-
oped for the present guideline document where most
recommendations were based on Low or Limited
strength of evidence and two recommendations based
on expert opinion. The primary reason for the Low or
Limited strength of evidence for most domains was due
to recommendations being based on evidence with a
high risk of bias, preventing any recommendation receiv-
ing a Grade A strength of evidence as per the WFSBP
grading recommendations (Hasan et al. 2019). This is a
key limitation in behavioural interventions in general,
where important design features such as double blind-
ing are inherently difficult to incorporate. To help guide
future research efforts and to promote further research
in this field, we have identified key areas of future
research needs that are applicable across lifestyle
interventions.
5.1. Larger trials in people with diagnosed MDD
While many lifestyle-based approaches included in
these guidelines have a larger body of evidence for
subsyndromal depressive symptoms and related out-
comes (e.g. quality of life, stress), there are a limited
number of studies comprising people with MDD for
the majority of included interventions. Further studies
with people with MDD are important to ensure that
interventions are feasible and effective for individuals
with greater severity and acuity of symptoms and
within the medical and sociodemographic context of
their mental health setting. Furthermore, most studies
conducted have been in relatively small sample sizes
and conducted over a small timeframe (typically 1-
3months). Larger and long-term (>1year) studies are
needed to inform the sustainability and scalability of
interventions. This is particularly relevant to lifestyle-
based approaches where behavioural maintenance
can dissipate over longer time periods. Furthermore,
the use of a traditional randomised controlled trial
study design to assess lifestyle intervention may be
relatively resource intensive and present feasibility
challenges for conducting larger trials. Researchers
should consider if alternative study designs such as
stepped wedge cluster randomised trials may
be warranted.
5.2. Further understanding of relevant biological
mechanisms of action
Identifying the biological and psychosocial mecha-
nisms of action of lifestyle-based approaches is essen-
tial for tailoring interventions treatment response.
Previous reviews of individual lifestyle domains have
identified numerous potential pathways through
which lifestyle-based approaches could plausibly affect
mental health such as the gut microbiome and the
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 27
tryptophan-kynurenine metabolism (Kandola et al.
2019; Marx et al. 2021) but much of this knowledge
base comes from preclinical animal studies. To
advance our understanding of optimal lifestyle-based
approaches for depression, robust studies in human
populations are required.
5.3. Effectiveness and implementation studies are
required to inform translation
We acknowledge growing ontological (validity of trad-
itional binary diagnoses) and epistemological (e.g. dis-
tinctions between efficacy and effectiveness trials)
concerns relevant to the studies included in these
guidelines. For example, the use of rigorously con-
trolled randomised controlled trials (i.e. efficacy stud-
ies) may comprise largely homogeneous cohorts (i.e.
major depressive disorder [MDD] diagnostic criteria)
with homogeneous outcomes (reductions in depres-
sive symptoms) that may not reflect ‘real world’
experience. While randomised controlled trials that
investigate the efficacy of an intervention are gener-
ally considered gold-standard, a notable limitation of
such designs is the limited external validity or real-
world effectiveness of the study results (Rothwell
2005). This is largely due to the homogeneous partici-
pant population and intensive, controlled delivery of
the intervention that may not be easily implemented
outside of a research setting. This becomes particularly
relevant to lifestyle-based approaches where, despite
many studies demonstrating efficacy, the translation
of such interventions requires that these interventions
are also scalable and can be implemented in a ‘real-
world’ setting with existing clinical care structures and
more complex presentations. As such, rigorous and
large-scale effectiveness trials are needed.
Implementation research is also required to assess
individual, environmental, and organisational level fac-
tors that enable or hinder translation of interventions
into clinical practice and to assess strategies that miti-
gate these factors (Deenik et al. 2020).
While effectiveness and implementation research is
often considered and evaluated as separate constructs,
the use of novel effectiveness-implementation hybrid
designs may help reduce the time required for
research results to be translated into clinical practice
(Curran et al. 2012). Furthermore, the use of co-design
and co-production principles that come from mean-
ingful partnerships with those with lived experience of
MDD, their families, carers, clinicians, and other rele-
vant stakeholders is required to ensure interventions
are meaningful, suitable, and sustainable (Deenik
et al. 2020).
5.4. Further assessment of cost effectiveness of
lifestyle-based approaches
In addition to the need to further expand the evi-
dence base for lifestyle-based approaches to MDD,
cost effectiveness research is critical to the translation
and implementation of lifestyle-based approaches.
Understanding the economic and resource require-
ments of implementing such interventions, how and
who funds these models of care and the economic
benefits that they may provide is critical especially in
resource poor settings. Some studies have embedded
cost-effectiveness analyses into intervention studies
(Chatterton et al. 2018; Segal et al. 2020); however,
further data are required particularly within different
health settings (e.g. primary, secondary, tertiary)
and regions.
5.5. Identification of optimal dose, frequency, and
delivery mode
There are limited data regarding the optimal ‘dose’,
frequency, and mode of delivery (e.g. digital vs face to
face, group-based vs individual) with respect to life-
style-based interventions for MDD. Furthermore, multi-
component lifestyle-based approaches have been
shown to be successful models of delivery in other
settings of chronic disease management (O’Neil,
Hawkes, et al. 2014) and recent meta-analysis suggest
that multi-component lifestyle interventions may also
provide a small but beneficial effect on depressive
symptoms (GC19omez-GC19omez et al. 2020; Wong et al.
2021). While there are limited studies in people with
diagnosed MDD, emerging meta-analyses suggest that
the effect may be greater in these populations com-
pared to the effect seen in analyses that included
other populations (GC19omez-GC19omez et al. 2020; Wong
et al. 2021). Finally, while evidence is emerging for
some lifestyle-based approaches, further non-inferiority
studies are required to inform how lifestyle-based
approaches perform when compared to currently rec-
ommended therapies (e.g. psychotherapy, antidepres-
sants) given that many of the existing RCTs in this
field use no-intervention passive controls (e.g. usual
care) as this will inform recommendations regarding
the use of lifestyle-based approaches as an adjunctive
or stand-alone therapy (e.g. (Young et al. 2022)).
28 W. MARX ET AL.
6. Implementation of lifestyle-based
approaches for Major Depressive Disorder
6.1. Implementation barriers, limitations,
and challenges
In addition to the future research needs that are
required to address the current research gaps (dis-
cussed in section 5), there are major health system-
level translational challenges that present as barriers
to the implementation of lifestyle-based approaches in
the clinical setting. These include, but are not limited
to, the lack of training in lifestyle approaches and
financial support for existing health professionals in
the mental health space, the potential presence of
substantial clinical and financial barriers (both provider
and people with MDD), the scarcity of research that
provides best practice guidance in the translation into
the current mental health service delivery context, and
how to develop, evaluate and scale new services. This
section aims to explore these barriers in greater detail
to provide an overview of the challenges to optimal
service delivery and to inform future inquiry and trans-
lational research in the implementation of lifestyle-
based approaches in MDD.
Health systems worldwide are highly varied and
have different challenges in rolling out ‘optimal’ life-
style approaches to depression management. We rec-
ognise that the extent to which lifestyle-based mental
health care is feasible and adopted is highly variable
based on a number of factors related to the individual
(e.g. resources, social conditions, time, culture, person-
ality, motivation, symptom severity/acuity, entry point
into the mental health care system, past experiences),
the clinician (e.g. motivation, financial reimbursement
model, time, personal values or beliefs, self-efficacy,
training), the setting (e.g. culture, resources and avail-
ability of staff, continuity of care, organisational will),
and macro level factors (e.g. mental health as a gov-
ernment or area level priority, socio-economic and
political context, stigma, social media and competing
health messaging). Adding to these complexities is
that health care systems around the world face further
challenges related to changing health profiles and
needs of their populations as people are living longer
with chronic conditions (Calder et al. 2019). This is
especially evident in low and middle income countries
where 80% of deaths from chronic conditions occur
(and where the majority of the global population
resides) (World Health Organization 2005).
These barriers can present significant challenges to
health professionals implementing lifestyle and social
care interventions more broadly, and it calls for
innovation in the mental health service and models of
care, just as has been recommended for chronic dis-
ease management (Productivity Commission 2021). For
example, primary care physicians, such as general
practitioners in countries like Australia and UK, provide
mental health care to C2475% of those seeking such
help (Australian Institute of Health Welfare 2021), with
mental health concerns being the single most com-
mon reason individuals visit a general practitioner
(The Royal Australian College of General Practitioners
2018). However, general practitioners manage 2.1–3.6
problems on average per short consult of C2415 mins,
leaving little time or funding-imperative for lifestyle
and social approaches (Beaudoin et al. 2001; Stuart
et al. 2019). Studies in the USA and Australia provide
some indication of how infrequently lifestyle factors
are addressed, with preventive counselling/advice
about nutrition and weight, exercise, smoking, life-
style, prevention, and/or alcohol, together given in
only 8 per 100 encounters. Also, the duration of such
counselling made up a small minority of the total con-
sultation time (Ory et al. 2007; Britt et al. 2015). A
2019 systematic review examining the extent to which
nutrition is taught in medical education found that
‘nutrition is insufficiently incorporated into medical
education, regardless of country, setting, or year of
medical education’ (Crowley et al. 2019). Primary care
providers also cite a lack of knowledge, skill and confi-
dence, competing pressures on time, limited referral
options, lack of specific funding, and a lack of support-
ive organisational infrastructure (Denney-Wilson et al.
2010). Hence, these barriers must be proactively
addressed, and health professionals must be sup-
ported with targeted training, systemic support, and
funding to adapt to and overcome these signifi-
cant challenges.
To overcome the significant potential barriers that
service users and providers may experience, mental
health services, including primary care services, are
often exploring and leading in the design and imple-
mentation of new models of care. However, to date,
the implementation of lifestyle-based approaches and
innovation in service delivery has largely been
‘grassroots’ in nature, with new in-person and digital
models of health service delivery being led by inde-
pendent and relatively disconnected research bodies,
clinical practices, and community organisations in
response to the barriers cited, service pressures, and
public and provider demand and entrepreneurism.
Whilst it is outside the scope of these guidelines to
evaluate such models that address the previously cited
barriers across different countries, jurisdictions, and
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 29
health care contexts, there exist certain common prac-
tices to optimise health provider time, financial sus-
tainability, and referral options via:
C15 Targeted workforce development outside the trad-
itional roles that may be more cost and time effect-
ive in both training and service provision. This
includes peer coaches utilising health coaching
techniques, community or ‘link’ workers for social
prescribing and social services, cultural health
workers, peer support workers with an area of spe-
cialisation, peer navigators to assist in the naviga-
tion of a complex health system, and ‘peer
bridgers’ who support the transition from hospital
to community
C15 Effective and efficient clinical programs such as in-
person and digital group visits/shared medical
appointments, and online platforms that improve
outcomes whilst aiming to also enhance peer-
peer support
C15 Establishing an interdisciplinary team with comple-
mentary expertise, that emphasises skill and know-
ledge sharing, to achieve shared goals (Choi BC
and Pak 2006).
C15 Use of lower-cost technology where possible to
automate, personalise, economise, and enhance
care coordination of services, including virtual care,
telehealth, apps, wearables, online programs, text
services, decision support software and artificial
intelligence
C15 Diverse engagement with communities and professio-
nals outside of health care (e.g. cultural and lived
experience representatives, built environment design-
ers, technology, industry, government) in service co-
design, delivery, governance, and evaluation
C15 Generating greater referral and service options and
specific funding for proactive care that includes
prevention and early intervention outside trad-
itional clinical settings such as direct-to community,
workplace, and school mental health and well-
being programs
C15 Alternative funding models including public fund-
ing, private health insurance, value-based health
care, membership, and subscription models.
C15 Harnessing and adapting the structures and mech-
anisms within a health care setting that already
exist for individuals with chronic physical health
conditions and make them available for application
to mental health conditions like MDD
However, the challenge of scaling and diffusing any
innovation into mainstream mental health care
remains. The relatively new and rapidly growing field
of implementation science provides several theories,
models, and frameworks (TMFs) for the development,
implementation, evaluation, and scaling of new mod-
els of care. Regardless of the size or stage of the spe-
cific program, these frameworks can be useful in
identifying determinants of success or failure and
matching implementation strategies to produce repro-
ducible outcomes. One such tool that can be used to
consider and justify the selection of TMFs for a given
project is the Theory Comparison and Selection Tool
(T-CaST) (Birken et al. 2018), a paper and web-enabled
tool that includes 16 specific criteria. Health care sys-
tems can be highly complex and locally contextual,
with various guides (e.g. (Agency for Clinical
Innovation 2013)) indicating that those championing
new models may benefit from having realistic expecta-
tions as to the time and complexity involved, develop-
ing a team, aligning with existing strategies, seeking
support from leadership, and planning for long term
sustainability. Hence, it is frequently recommended
that new models of care should be delivered adhering
as close as is practically relevant and possible to these
theories, models, and frameworks. Without appropriate
design, implementation, and evaluation, it is unlikely
models of care will receive ongoing support and be
scaled effectively, hence significantly limiting
their impact.
6.2. Future implementation considerations
As demonstrated in Figure 3, there are a range of clin-
ical and implementation factors that should be consid-
ered when integrating lifestyle-based approaches into
clinical care. We have devised a series of 10 considera-
tions for the future implementation of these guide-
lines (Summarised in Table 4) and will discuss each
consideration individually in the following section. We
acknowledge these considerations act more as princi-
ples and ideal ‘goals-posts’ to guide the long-term
evolution of research and clinical practice rather than
what is currently in widespread practice. We also
acknowledge the vast and intersecting factors, such as
the aforementioned barriers and the need to adapt to
local contexts that influence the uptake of lifestyle-
based approaches to mental health care into practice.
As stated, these considerations were developed by
taskforce consensus and did not follow the previously
mentioned systematic review procedure.
Implementation consideration #1: Lifestyle assess-
ment and interventions are foundational to mental
health care and may form a starting point for treatment
30 W. MARX ET AL.
(sequential approach) and/or accompany psychological,
pharmaceutical, or procedural interventions (adjunctive
approach) to improve mental and physical health out-
comes and mitigate adverse outcomes.
Given the supportive evidence for the included life-
style interventions for managing MDD and the highly
favourable safety profile, lifestyle-based approaches
should be considered as a core component of mental
health care with the capacity to additionally benefit
comorbid physical disorders. The extent to which the
lifestyle therapies of diet, exercise, sleep and sub-
stance cessation are foundational refers to care that
‘needs to be undertaken to facilitate functional recov-
ery’ as per its definition in RANZCP guidelines (Malhi
et al. 2021). The integration of lifestyle assessment
and interventions as core components of care should
not be viewed as being at the expense of pharmaco-
therapy or psychotherapy. Rather, this approach is
intended to constitute a core component of treatment
that is either initiated before commencing other thera-
pies or to build upon other therapies where appropri-
ate or required (see Figure 4). For some people with
MDD, this might be the first step in a stepped care
approach that draws upon other therapies, while, for
others, it might be suitable in isolation. The feasibility
of enactment of lifestyle-based approaches is also
likely to be dependent upon the point in a person’s
entry into the health care system, the clinician with
whom they engage, the setting, and the trajectory of
their journey.
The RANZCP guidelines state that lifestyle therapies
initiated during the initial phase of treatment are to
Figure 3. Core implementation considerations, factors, and lifestyle interventions for lifestyle-based mental health care. To yield
the greatest benefits from lifestyle-based mental health care, it requires personalised individual and group clinical approaches
enabled by health service and model of care innovation including health coaching, digital technology, interdisciplinary teams,
group and peer-based supports, adapted in the context of socio-economic, cultural and environmental determinants. Each lifestyle
intervention is colour coded for grade of evidence (dark green?grade B, light green?grade C, yellow?expert opinion).
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 31
be framed against a backdrop of implementing educa-
tion, psychological, and social supports like addressing
risk and monitoring outcomes (Malhi et al. 2021).
Framing and applying lifestyle-based care as a key part
of recovery and ongoing illness management is likely
to promote uptake by people with MDD, akin to the
waythisapproachisharnessedinmoreconventional
chronic disease management programs. Where pharma-
cological or psychological therapies are already being
utilised, conveying the likely cumulative benefits of ini-
tiating lifestyle changes, especially where side effects
have been evident (e.g. weight gain, change in meta-
bolic profile), is advantageous. There is also emerging
evidence of productivity gains owing to lifestyle-based
mental health care related to work performance and
fewer absences from work (Chatterton et al. 2018).
Implementation consideration #2: Combining mul-
tiple lifestyle-based approaches (e.g. dietary and exercise
interventions) may enhance treatment response.
However, personalised considerations based on individ-
ual (e.g. motivation, acuity) and clinical (e.g. capacity,
expertise) circumstances are required.
Lifestyle based mental health care is not a single inter-
vention but rather several interacting layers that involve
lifestyle domains combined with implementation. No
single layer is without limitations, hence the require-
ment for a cumulative and diverse lifestyle and social
management process. The more each of these aspects
are cultivated within an individual’s life, environments,
and health care, the greater the opportunity for earlier
intervention, potential to prevent disease progression
and relapse, enhance resilience against adverse internal
or external events and improve mental, physical, and
social wellbeing (see Figure 5).
Multi-targeted, lifestyle-based programs that acknow-
ledge the importance of a range of lifestyle factors in
illness management and relapse prevention have been
successfully implemented in other areas of chronic dis-
ease management including in diabetes (e.g. structured
diabetes prevention programs, diabetes educator con-
sultations) (Li et al. 2008) and cardiovascular disease
(e.g. cardiac rehabilitation) (Medina-Inojosa et al. 2021).
Targeting multiple lifestyle factors in the management
of MDD requires consideration of many factors. Like
other conditions, these may include an individual’s cap-
acity or receptiveness to consider multiple behavioural
targets especially where other therapies, co-morbidities
or intensive medication regimens are present; self-effi-
cacy and motivation; and proficiency, confidence,
health literacy or preference for a lifestyle pillar. Further
considerations include those regarding potential
Figure 4. Stepped Care Model of lifestyle-based mental health care. Lifestyle and psychological approaches are to be discussed
with all people with Major Depression Disorder. Lifestyle assessment and interventions can be considered core and foundational
components of care based on their strong safety profile and evidence of effect on mental, physical and social wellbeing. These
approaches can be combined with other evidence-based therapies with the goal of functional recovery.
32 W. MARX ET AL.
contraindications and safety concerns including com-
mon medical comorbidities (e.g. unstable angina, heart
failure, and dietary and exercise restrictions around fluid
and sodium), medications (e.g. anti-glycemic and anti-
hypertensives in lifestyle changes and weight loss),
allergies and food intolerances, and aerobic capacity
and exercise tolerance of older individuals. More spe-
cific to individuals with MDD are factors related to their
illness including helplessness and hopelessness, inter-
ruptions to appetite and sleep, and the trajectory of
their MDD. Examples of the synergistic effect of lifestyle
approaches more commonly experienced in clinical
practice have included:
C15 Addressing sleep disorders, which subsequently
improves daytime functioning and energy levels
thereby facilitating increases in physical activity.
C15 Increases in physical activity being a point of
awareness for smoking-induced reduced fitness
and hence motivation for smoking cessation.
C15 Using physical activity interventions to help smok-
ing cessation.
Increasingly, psychologists and other mental health
clinicians are incorporating lifestyle targets into their
therapeutic practice. The principles of CBT can readily
apply to or incorporate lifestyle targets, ranging from
specific CBT for insomnia programs, to sleep hygiene
principles and behavioural modifications (such as sleep
logs, reducing caffeine, changing habits associated
with poor sleep, changing bedtimes, increasing phys-
ical activity). Moreover, applying the principles of CBT
(whereby an individual’s underlying thoughts, feelings
and behaviours are addressed and applied to aspects
of their lifestyle) can promote long-term sustainability
of those behaviours (O’Neil et al. 2015). These practi-
ces should be done in accordance with the discipline
specific professional standards, core competencies and
frameworks of that setting or in the context of a
multi-disciplinary team if possible.
Figure 5. A Swiss cheese model of Lifestyle-based mental health care. Lifestyle-based mental health care is not a single interven-
tion but rather several mutually supportive and interacting approaches that involve lifestyle domains (covered in section 4)com-
bined with models of care including interdisciplinary teams, peers and carers, health coaching behaviour change approaches, and
digital technology (covered in section 6). The more each of these layers are cultivated and built within a person’s life and environ-
ments, the greater the likelihood of preventing disease progression, enhancing resilience against adverse internal or external
events, and improving mental, physical and social wellbeing. This is illustrated by disease progression (thick black line) being miti-
gated by the additional layers of lifestyle approaches and implementation considerations. Each lifestyle intervention is colour
coded for grade of evidence (dark green?grade B, light green?grade C, yellow?expert opinion).
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 33
Table 3. Available formal assessment tools and suggested prompting questions related to specific lifestyle domains
a
.
Domain Formal assessment tools Example prompting questions as part of clinical assessment
Physical Activity C15 SIMPAQ (Rosenbaum and Ward 2016)
C15 Digital devices (e.g. Smart devices) and
step counters
‘How many minutes/hours of physical activity do you do a day?’
‘Which days, when and why?’
‘What form of physical activity do you do and enjoy?’
‘Are you sedentary for prolonged periods during the day?’
Diet C15 Food Frequency Questionnaires
C15 24-h recall
C15 3–7-day food diary e.g. 2 workdays/1 weekend day
C15 Digital tools: DietID, chronometer
For more complex dietary assessment considerations
please see resources section
‘Can you tell me about the last meal you ate?’
‘What do you usually eat for breakfast, lunch and dinner?’
‘Where and when do you usually eat your main meals?’
‘What snacks do you eat and when?’
‘What do you usually drink throughout the day?’
Sleep General sleep assessments
C15 Epworth Sleepiness Scale (Johns 1991)
C15 Sleep Hygiene Index(Mastin et al. 2006)
C15 Morningness-Eveningness Questionnaire (Horne
and
€
Ostberg 1976)
C15 Pittsburgh Sleep Quality Index (Buysse et al. 1989)
C15 SLEEP-50 (Spoormaker et al. 2005)
C15 Sleep diary or use of wearable
C15 Polysomnography
Others depending on specific sleep disorder:
C15 STOP BANG (Chung F et al. 2016)
C15 Insomnia Severity Index (Bastien et al. 2001)
C15 International Restless Legs Scale (Group
IRLSS 2003)
‘How many hours do you usually sleep per night?’
‘Tell me about what you usually do before going to bed’
‘How would you rate the quality of your sleep?’
‘How refreshed do you feel from your sleep?’
‘Do you nap during the day? If so, for what reason?’
Smoking cessation C15 Heaviness of smoking index (Borland et al. 2010)
C15 Fagerstrom Test for Cigarette
Dependence(Heatherton et al. 1991)
‘How many cigarettes do you smoke per day?’
‘How long from waking until your first cigarette?’
‘Where and when do you smoke?’
‘What age did you start smoking?’
‘Have you tried to quit before?’
‘What are the benefits of smoking? What do you ‘get’ from
smoking?’
‘What are the cons?’
Alcohol C15 The AUDIT-C (Bush et al. 1998)
C15 The Severity of Alcohol Dependence Questionnaire
(Stockwell et al. 1983)
‘How many alcoholic drinks do you consume on an average
day?’
‘When?’ (This must be specified between weekdays and
weekends as hazardous ‘binge’ drinking isolated to weekends
may be present)
‘What have been the positive and negative consequences
of drinking?’
Other drugs C15 ASSIST tool (Group WAW 2002)
C15 Leeds Dependence Questionnaire (Raistrick
et al. 1994)
C15 Severity Dependence Scale (Gossop et al. 1995)
‘What substances do you use?’
‘What are the benefits of them? What do you ‘get’ from them?’
‘What are the cons?’
Gambling C15 Problem Gambling Severity Index
(Holtgraves 2009)
C15 Canadian Problem Gambling Index (Ferris and
Wynne 2001)
‘Do you or anyone in your family have an issue with gambling?’
‘What are the benefits?’
‘What are the cons?’
‘What has the (biopsychosocial-cultural-spiritual) impact been?’
Work-directed interventions C15 Workplace Stressors Assessment Questionnaire
b
(Mahmood et al. 2010)
C15 Work Environment Subscales of the Work Health
Check questionnaire
b
(Gadinger et al. 2012)
‘Do you currently work or volunteer?’
‘What are the (biopsychosocial) benefits?’
Social support and loneliness
c
C15 LSNS-6 tool (Lubben et al. 2006)
C15 UCLA Loneliness scale (Russell 1996)
C15 Multidimensional Scale of Perceived Social Support
(Zimet et al. 1988)
‘How often do you see friends and/or family?’
‘Who can you count on to listen to you when you need to
talk?’
‘What are the benefits and barriers of connecting with your
friends and/or family?’
‘Could you tell me about your use of social media?’
‘With social media, do you feel a compulsion to engage,
engage without realizing, use in bed and/or use quickly
on waking?’
Green space –‘How much time do you spend in a green or blue space in a
week?’
‘What green and blue spaces are safe and accessible for you?’
‘How do you feel after spending time outdoors?’
Stress C15 Brief Resilience Scale (Smith BW et al. 2008)
C15 Connor Davidson Resilience Scale (Connor and
Davidson 2003)
C15 Perceived Stress Scale (Cohen S et al. 1983)
C15 Depression Anxiety Stress Scale (Lovibond and
Lovibond 1995)
‘What are the sources of stress in your life?’
‘What impact do you think these are having on you?’
‘How do you reduce and manage stress?’
‘What helps you reduce, buffer against or manage stress?’
(continued)
34 W. MARX ET AL.
However, in some cases, identifying a lifestyle pillar of
interest and working with the individuals to focus on
one manageable target may be more achievable and
feasible than addressing multiple lifestyle factors in tan-
dem. Indeed, clinicians who support behaviour change
often report ‘small and early wins’ for people with MDD
to be important steps in developing confidence and
self-efficacy. Hence, the individual needs, interests, self-
efficacy, locus of control, intention, and motivation might
guide the focus of the target behaviour(s) of interest. A
practical tool for helping identify which behavioural
change techniques to use with an individual with MDD
can be found in the resources section of this document.
Implementation consideration #3: Assessment of life-
style factors (using either formal tools or clinical inter-
view) should be conducted for all people with MDD,
both before and after intervention, as a means of
assessing current lifestyle status and measuring progress
in lifestyle changes and quality of care.
The purpose of assessing an individual’s lifestyle (e.g.
diet, exercise, substance use and sleep) at treatment
commencement and at a suitable follow-up period is
three-fold. First, this process helps both individuals with
MDD and clinician recognise the ‘baseline level’ from
which change can occur and to determine which life-
style domain(s) require focus (thereby tailoring care
accordingly). Second, it provides individuals tangible
evidence of improvement or change over the treatment
period that can enhance confidence, self-efficacy, and
motivation, which predict longer term behavioural
adoption. Third, it allows for quality improvement activ-
ities to occur at clinician or service level.
There is a range of methods to address lifestyle fac-
tors that vary in their sophistication, time intensity,
and user friendliness. For widely used lifestyle inter-
ventions like physical activity, there are measures that
have been specifically designed for and validated with
mental disorder populations such as the five-item
Simple Physical Activity Questionnaire (SIMPAQ)
(Rosenbaum and Ward 2016). There are also specific
measures of sleep hygiene such as the Sleep Hygiene
Index, a 13-item self-report tool used to assess the
practice of sleep hygiene behaviours. Dietary assess-
ment can be difficult and intensive to measure using
existing validated tools and the suitability of a tool
depends on numerous factors. However, using a 24-h
recall or average dietary intake is a relatively feasible
method to provide an informal overview of eating
habits, though it is important to be aware of inherent
recall and intention bias. It is particularly important to
ask about highly processed foods and liquid calorie
ingestion such as soft drinks, as these are commonly
consumed, calorie dense, nutritionally devoid, and lack
the ability to produce satiety. Furthermore, some med-
ications commonly used to treat MDD, such as mirta-
zapine, can alter appetite; hence, asking about
cravings (in particular, night-time meals) can be
informative. Specifically, knowing why you are assess-
ing diet, what it is you want to measure, demograph-
ics (age, participant literacy level), and time pressures
is important. A helpful resource to make these deci-
sions can be found in the resources section. There are
also dietary recall tools that include nicotine and alco-
hol consumption, which can be favourable in the
interest of efficiency. Where formal alcohol and other
drug assessment is required, we recommend the
accompanying guidelines for comorbid AOD and
Mental Illness (Marel et al. 2016). There are ways to
measure social support including the LSNS-6 tool and
UCLA Loneliness scale, and mindfulness can be meas-
ured using tools like the Frieburg Mindfulness
Inventory (Russell 1996; Lubben et al. 2006; Walach
et al. 2006). However, the length of such tools should
Table 3. Continued.
Domain Formal assessment tools Example prompting questions as part of clinical assessment
Resilience C15 Resilience Scale (Wagnild 2009)
C15 Predictive 6-Factor Resilience Scale (Rossouw and
Rossouw 2016)
‘How do you adapt and cope with adversities in life?
‘How do you rate your ability to bounce back and stay
motivated during adversities?’
‘What lifestyle and social supports do you have in life to help
you in difficult times?’
‘What mental and physical wellbeing practices do you use in
times of adversity?’
‘Does a sense of vision and purpose help you in times
of adversity?’
Social needs C15 The American Academy of Family Physicians Social
Needs Screening Tool (O’Gurek and Henke 2018)
a
This table can serve as a non-exhaustive resource for previously used tools and proposed questions. Clinical guidance is required to inform the use of
any particular assessment tool.
b
In line with previous guidelines (Mazza et al. 2019), these tools are not recommended to be used as standalone tools but may be incorporated into a
clinical assessment.
c
Further discussion regarding relevant assessment tools are provided by Ma et al. (2020)
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 35
be noted. Emerging areas of lifestyle-based interven-
tions, like use of green space, do not have formal
assessment tools that have been validated or are com-
monly used in the mental health care setting, but
prompting questions that can be integrated into clin-
ical assessment (see Table 3) can still be informative.
Assessment is not a ‘one-off’; sustained lifestyle
behaviours are unlikely to result from episodic care
but need active assessment and monitoring. Multiple
guidelines in chronic diseases recommend frequent
assessment and follow-up to support sustained
improvements. For example, the NHMRC Clinical
Practice Guidelines for the Management of
Overweight and Obesity in Adults, Adolescents and
Children in Australia recommend arranging fortnightly
review for the first three months, and a plan for con-
tinuing monitoring for at least 12months (National
Health and Medical Research Council 2013). Specific
timeframes must be tailored to meet individual needs
and may not need to be this intensive, but this pro-
vides some reference as to the need for relatively fre-
quent supported shared management rather than
uncoordinated and reactive care. The main concern
with such intensive assessment and monitoring is
resource use (time, workforce, cost), access/availability
and opportunity costs. In these cases, referral to an
online program, group program (in-person or online),
already established lifestyle program (e.g. community
program, sports group), or additional health care staff
(nurse, peer support worker, health coach) to provide
ongoing monitoring, education, self-management, and
peer support should be considered.
Implementation consideration #4: Formal assessment
and consideration of social needs (e.g. housing, utilities,
food, childcare) should be conducted to guide the provi-
sion of lifestyle-based approaches.
The social and environmental determinants of mental
ill-health and MDD (e.g. housing, socioeconomic sta-
tus, education, air pollution) are of crucial importance
to assess and address, where possible. There is evi-
dence that the distribution of depression (as well as
anxiety) follows a gradient of economic disadvantage
across society and that this relationship may be bidir-
ectional (Campion et al. 2013). A systematic review of
common mental disorders and poverty in low and
middle-income countries found that over 70% of the
115 included studies reported positive associations
between a variety of poverty measures and common
mental disorders (Lund et al. 2010).
The ‘Doctors for Health Equity’ 2016 report, led by
the UCL Institute of Health Equity, states that ‘Health
professionals are witnesses to inequalities and see the
outcomes on a daily basis. However, their potential
impact on these inequalities, through action on the
social determinants of health, is often under-devel-
oped’ (Institute of Health Equity and World Medical
Association 2016). Clinicians need to be aware of the
impact of these determinants, assessing and consider-
ing them in management. Involving people from
diverse SES backgrounds, individuals and groups with
lived experience, and social worker professionals in
service design and delivery, training and research can
inform the tailoring of health services to be more able
to effectively address social needs (Andermann 2016).
The American Academy of Family Physicians pro-
vides a social needs screening tool (see Table 3),
which can be useful for clinicians working in mental
health. Because of financial constraints and evidence-
translation issues that can affect an individual’s ability
Table 4. Future implementation considerations.
1. Lifestyle assessment and interventions are foundational to mental health care and may form a starting point for treatment (sequential approach)
and/or accompany psychological, pharmaceutical, or procedural interventions (adjunctive approach) to improve mental and physical health
outcomes and mitigate adverse outcomes.
2. Combining multiple lifestyle-based approaches (e.g. dietary and exercise interventions) may enhance treatment response. However, personalised
considerations based on individual (e.g. motivation, acuity) and clinical (e.g. capacity, expertise) circumstances are required.
3. Assessment of lifestyle factors (using either formal tools or clinical interview) should be conducted for all people with MDD, both before and after
intervention, as a means of assessing current lifestyle status and measuring progress in lifestyle changes and quality of care.
4. Formal assessment and consideration of social needs (e.g. housing, utilities, food, childcare) should be conducted to guide the provision of lifestyle-
based approaches.
5. A person-centered, individualised approach, based on need and preference, incorporating behaviour change techniques and applying a
biopsychosocial model, may aid the delivery and maintenance of lifestyle-based mental health care for people with MDD.
6. Assessment and intervention plans informed by a culturally safe, culturally aware, and responsive approach may be beneficial to outcomes and
improve access to high-quality lifestyle-based mental health care.
7. Including peer support workers, family, friends, and carers may aid the uptake and maintenance of lifestyle-based mental health care for people
with MDD.
8. Self-management supported by digital delivery is a potentially feasible, low-cost paradigm for translation of lifestyle-based approaches into health
systems worldwide
9. If available, lifestyle interventions that involve relevant allied health professionals (e.g. exercise physiologists, dieticians) may be more beneficial for
improving mental health than those that do not.
10. Substance use should be assessed and, where available, existing alcohol and other drug guidelines should be employed to appropriately support
cessation or minimisation using established therapeutic approaches.
36 W. MARX ET AL.
to receive long-term lifestyle-based mental health care
and, indeed, for clinicians to provide this, community
linkages are critical. This is particularly true of those
experiencing MDD due to socioeconomic status issues.
For example, a recent study found 40% of those with
mental illness are food insecure, making it more diffi-
cult for them to use lifestyle strategies to manage
their mental health (Teasdale et al. 2021). This is
where social prescribing can be employed, where
available, as it may address social, economic and
environmental factors related to health inequalities.
Of course, out-of-pocket expenses incurred by indi-
viduals are often a barrier to accessing mental health
care and specifically physician- or allied health profes-
sional-led lifestyle-based mental health care.
Economic, geographic and insurance-related consider-
ations may present as a perceived barrier to uptake
and sustainability. Until such time that this approach
is offered as mainstream treatment that is subsidised,
the former issues of concern will remain.
Implementation consideration #5: A person-centered,
individualised approach, based on need and preference,
incorporating behaviour change techniques and apply-
ing a biopsychosocial model, may aid the delivery and
maintenance of lifestyle-based mental health care for
people with MDD.
Behaviour change can be difficult, and clinicians are
encouraged to become familiar with the range of
well-researched approaches to behaviour change in
health. There are a wide variety of behaviour change
models, theories, and techniques including capability-
motivation-opportunity-behaviour (COM-B), the trans-
theoretical model of change, self-determination the-
ory, social cognitive theory, appreciative inquiry, 5 A’s
(Assess, Advise, Agree, Assist, Arrange), socioecological
model, and many more.
In practice, a combination of these can be used
based on a biopsychosocial-cultural understanding
and may include the establishment of a strong thera-
peutic relationship, supported self-management,
SMART (specific, measurable, achievable, realistic,
timely) goal setting, behavioural activation (Ekers et al.
2014), problem solving, self-efficacy, asset or strength-
based approaches, social support, regular monitoring
and identifying the driving values of the person with
MDD. Environmental modification is considered in the
COM-B behavioural framework, including optimising a
person’s physical micro-environment context (e.g.
home, workplace settings), to be more conducive to
health promoting behaviours and/or creating barriers
to disease promoting behaviours. There is also a grow-
ing recognition and literature on the role of built
environment design in delivery of mental health care
to enhance outcomes and service user satisfaction,
and we recommend these aspects be strongly consid-
ered as they are often a neglected but important fac-
tors (Liddicoat et al. 2020).
As discussed, barriers to the adoption of lifestyle-
based approaches can include individual (e.g. per-
ceived benefits, self-efficacy), socio-economic (e.g. lack
of resources, insecure environment), or clinician and/or
healthcare system factors (e.g. time limits, cost,
access). People with MDD may experience additional
complications that reduce adherence, including mental
illness–related factors (e.g. anhedonia), side effects of
medication (e.g. sedation), cognitive factors (e.g. dis-
tortions, impairments), psychosocial factors (e.g. social
isolation), socio-economic (e.g. poverty, access to fresh
food, green space, safe neighborhoods), and clinician
factors (e.g. lack of clinician training). Improving long-
term adherence to treatment recommendations
requires addressing factors at multiple biopsychoso-
cial-cultural levels, shared determination of treatment
plans, and detailed personalisation.
Lifestyle-based approaches may offer a novel
method by which to engage typically disengaged ser-
vice users in more traditional mental health treatment.
They may help to overcome some of the existing bar-
riers to their engagement with traditional mental
health services such as mental health stigma. Goal set-
ting activities that identify perceived and real threats
to uptake and adherence need to be explicitly
addressed. This is especially true when working with
individuals who may be experiencing cognitive distor-
tions or other cognitive impairments. As demonstrated
in the diabetes prevention literature, structured and
comprehensive lifestyle-based programs are especially
potent while individuals are engaged, but they may
wane after cessation. For example, a 15-year follow-up
of one such trial found diluted effects after the initial
2.8years of active intervention. On the other hand,
long-term follow-up of the Finnish Diabetes
Prevention Study (a program lasting a median
4.1years with booster sessions) found long-term
effects after 7years (Lindstr€om et al. 2013). Resource
poor settings are unlikely to have capacity to cater to
such an intensive and protracted schedule; however,
the increasing involvement of peer workers, group
modalities and health coaches may reduce financial
and logistical barriers. Promisingly, since the conduct
of these studies, there has been an advent in the dis-
semination of online programs, smart phones, and
other technologies to reinforce on-going participation
and promote habit formation. This is especially true in
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 37
the context of COVID-19, whereby face-to-face pro-
grams may have halted or have been supplemented
with telehealth and digital platforms. For example,
some health coaching pilots combining face-to-face
and telehealth support have developed protocols
requiring only 10-15minute follow-up consultations to
adequately support behaviour change, which is a feas-
ible in many settings (Gate et al. 2016).
Implementation consideration #6: Assessment and
intervention plans informed by a culturally safe, cultur-
ally aware, and responsive approach may be beneficial
to outcomes and improve access to high-quality life-
style-based mental health care.
A lack of culturally aware, safe, and responsive services
and information is cited as a major barrier to culturally
and linguistically diverse (CALD) and Indigenous
groups (Australian Institute of Health Welfare 2020). In
Indigenous populations around the world – of which
there are estimated to be up to 500 million across 90
countries – social and emotional wellbeing can include
concepts beyond mental health and illness such as
the importance of connection to land, culture, spiritu-
ality and ancestry (Gee G et al. 2014).
In the mental health setting, cultural competence
represents understanding how cultural and individual
beliefs and values affect perceptions and understand-
ing of mental illness, the options and appropriateness
of interventions, and the relationships with mental
health service providers (Gopalkrishnan 2018).
Genuinely understanding the local culture – or culture
of origin – and concepts of mental health and well-
being may strengthen provider-service user relation-
ships, reduce stigma, make lifestyle-based approaches
more personalised and relevant (e.g. connection to
land, ‘green prescriptions’ and mindfulness), and
inform and improve the health service itself. Trust is
necessary to developing open therapeutic relation-
ships that allow people from culturally diverse back-
grounds to inform their practitioner about culturally
grounded support mechanisms as both supportive
and involved positive resources (e.g. community mem-
bers, spiritual settings, practices, groups) and for
harm-minimisation reasons (e.g. to avoid potentially
dangerous practices).
One additional concept relevant to this consider-
ation is Country-based or environmental therapy,
which, in very broad terms, advocates healing that is
conducted on Country, particularly on country to
which the individual may be culturally connected. For
example, in Australia there are a wide range of models
of care and services within Aboriginal Community
Controlled Health Organisations (ACCHOs), often with
a strong focus on biopsychosocial-cultural health,
interdisciplinary-community driven and strength-based
approaches. Elders in the community, religious leaders,
and knowledge keepers can be important contributors
to mental health care (Gopalkrishnan 2018).
Implementation consideration #7: Including peer sup-
port workers, family, friends, and carers may aid the
uptake and maintenance of lifestyle-based mental health
care for people with MDD.
A key underlying premise for peer, family, and carer
involvement is that these individuals and groups are
in a unique position to provide support that often
cannot be replicated by health-care professionals
(Mental Health Foundation 2021a). The involvement
and ongoing support of family and carers can provide
an additional layer of support to people with MDD by
encouraging people with MDD to access care, foster-
ing supportive environmental change, providing
encouragement, improving adherence to treatment
plans, and by improving social support and reducing
feelings of isolation. In addition to the need to engage
with family and carers to support people with MDD,
mental health services are encouraged to provide sup-
port for family and carers, who, due to the ongoing
nature of mental illness, report emotional exhaustion
but also report feelings of alienation and judgement
from service providers (Lawn et al. 2015).
Peer worker support generally focuses on hope,
confidence, connection, self-efficacy, and self-deter-
mination rather than illness (Orwin 2008), and hence,
is integral to the concepts of recovery, lifestyle assess-
ment and intervention, and wellbeing. It can promote
community engagement, reduced stigmatisation, and
help to address the differences in status and power
imbalances between professionals and service users
(Dennis 2003). Peer support workers are increasingly
being utilised in inpatient and community-based men-
tal health services (Pou 2020). Various models being
explored to address gaps and enhance service access
and quality, but evidence is limited (Kaleveld et al.
2020). Given that primary care services provide mental
health care to C2475% of those seeking such help in
countries like Australia (Australian Institute of Health
Welfare 2021), this is a service and research gap that
deserves greater attention. Hence, the qualitative and
quantitative outcomes of such models deserve explor-
ation and evaluation to further optimise their mean-
ingful integration into the diverse settings where
mental health care is delivered.
There are a diverse range of important roles for
peer support workers, including therapeutic roles (e.g.
education, advocacy, individual therapy, facilitating
38 W. MARX ET AL.
groups, linking with community services, addressing
social needs such as employment, education, and
housing), research roles (e.g. co-design and evalu-
ation), and throughout organisations (e.g. on manage-
ment boards, recruitment panels). For example, peer-
facilitated group programs used in mental health care
can allow for group members to provide sympathetic
understanding and provide an avenue to support or
establish social networks. Within such dynamics, a var-
iety of issues can be raised, shared, and positively
responded to, such as barriers and enablers in behav-
iour change. Like any other mental health professional,
peer support workers also need support themselves in
the form of supervision and mentoring, given the
complexity of mental health and healthcare systems.
Peer support has become an increasingly important
strategy for individuals living with mental illness, espe-
cially in cultures where intense stigma is a major bar-
rier to mental health care, and in healthcare systems
with limited resources or limited accessibility (e.g. rural
locations). This approach is popular as it can led to
positive lifestyle changes, provide a sense of continu-
ing support and connectedness and increased confi-
dence, while also helping to combat misinformation
and stigma related access to care (Pienaar and Reid
2021). It should be noted, however, that high level evi-
dence for this approach to significantly improve men-
tal health outcomes of individuals with severe mental
illness is currently lacking, with a Cochrane review
concluding that existing trial quality is poor and sub-
ject to bias (Chien et al. 2019). There is a greater need
for peer support programs that are culturally tailored
and provide rigorous effectiveness, economic and pro-
cess evaluation data across various settings.
Promisingly, the UPSIDES-RCT (2018–2022) is one such
pragmatic trial being conducted across a range of
high-, middle- and low-income countries (Germany,
UK, Israel, India, Uganda and Tanzania), which will
generate such evidence (Moran et al. 2020).
Implementation consideration #8: Self-management
supported by digital delivery is a potentially feasible,
low-cost paradigm for translation of lifestyle-based
approaches into health systems worldwide
Supported self-management is a priority area for
health services around the world (Crepaz-Keay 2010;
Nichols et al. 2020), whereby healthcare services aim
to support and empower people to manage their
ongoing physical and mental health conditions them-
selves. Whilst it is recognised that ‘the underlying driv-
ers and determinants of self-care capability are a
range of environmental, economic and social factors
that sit beyond the individual’ (Nichols et al. 2020),
there is also an identified need to optimise how
health services can enable people with MDD to be
active partners in their own care. One major element
of this shift is embracing the various forms of digital
technology to facilitate accessible, effective and more
resource-efficient supported self-management.
There are a wide variety of digital innovations that
are relevant to mental health care and that are being
explored in lifestyle-based mental health care
(Mauriello and Artz 2021), including but not limited to:
digital medical records (provider and user owned),
telemedicine, virtual care, decision support software,
use of apps with biometric and biofeedback devices,
digital education programs, social media platforms,
crowd-sourced digital databases (e.g. PatientsLikeMe),
avatars, machine learning (Pinto et al. 2013), artificial
intelligence and virtual reality. However, there are vari-
ous barriers to digital health technologies such as
digital literacy, privacy, data protection, transparency
and accountability of the commercial sector, lack of
consistency in technologies used across services,
safety, and evidence (Cummins and Schuller 2020).
Indeed, there can be a significant gap between the
claimed and hoped benefits of certain technologies
and the evidence to justify them, as can be the case
for apps and wearable biometric devices (Aji
et al. 2021).
There is growing evidence from multiple systematic
reviews that digital interventions can be effective in
improving depression, anxiety, and psychological well-
being. However, the majority of these that are avail-
able in clinical practice are mobile- and Web-based
platforms for internet cognitive behavioural therapy
(iCBT) or other psychological interventions (Garrido
et al. 2019; Lattie et al. 2019; Sasseville et al. 2021).
iCBT programs include components of behavioural
activation and hence, overlap with and can achieve
similar goals as lifestyle-based health coaching.
However, the reality is that only a select number of
digital technologies currently available in mainstream
clinical practice are specifically relevant to lifestyle-
based approaches. Hence, there is a clear need to
address this research gap and develop and evaluate
digital technologies to improve the symptoms of
depression via digital lifestyle-based approaches.
The extent to which digital platforms like social
media groups can be used to aid lifestyle change in
those with mental illness is complex. Online groups
can be a motivating factor for improving physical
activity with social comparison, more than the associ-
ated social support, being a mechanism promoting
maintenance (Zhang J et al. 2016). For other areas of
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 39
lifestyle, like dietary change, social comparison as a
behavioural strategy is not recommended to minimise
risk of disordered eating, which can be a common co-
morbidity. Digital programs that employ behavioural
economic strategies can effectively promote lifestyle-
behaviours like healthy food purchases. In South
Africa, members of a HeathyFood
TM
program who
received a rebate of between 10% of healthy food
purchases had a 6.0% rise in their ratio of healthy
food to total food expenditure (Sturm et al. 2013).
For clinicians working in mental health, some of the
more immediately available digital options include:
C15 Digital educational programs relevant to lifestyle-
based approaches, mental health, and behav-
iour change
C15 Use of digital coaching platforms to register, moni-
tor, and support lifestyle behaviours that may or
may not be paired with smartphones (e.g. pedom-
eter functions) and wearable biometric and biofeed-
back devices (heart rate monitors, calorie counters)
C15 Provision of telemedicine and virtual care for health
coaching for lifestyle behaviours. There is also a
growing interest in the use of digital group visits/
shared medical appointments in chronic disease;
however, there are no studies in individuals with
depression specifically
C15 Utilising closed social media groups (e.g. Facebook)
to combine professional and peer-based education,
motivation and social support to improve lifestyle
behaviours such as physical activity and stress
management (McKeon et al. 2021)
C15 Improving self-care of health professionals them-
selves via online course and support networks
Implementation consideration #9: If available, life-
style interventions that involve relevant allied health
professionals (e.g. exercise physiologists, dieticians) may
be more beneficial for improving mental health than
those that do not.
Allied health professionals are ideally placed to under-
stand the theoretical underpinnings and clinical nuan-
ces required to execute evidence-based lifestyle-based
care that comes from their training and accreditation.
Indeed, meta-analyses of lifestyle-based approaches
show that clinical benefit is greatest and dropout rates
lowest for programs delivered by relevant health care
professionals (Stubbs et al. 2016; Vancampfort et al.
2016; Firth et al. 2019a). Hence, including interdiscip-
linary allied health specialists can overcome know-
ledge and confidence barriers often reported by
physicians (HC19ebert et al. 2012;M€orkl et al. 2021).
However, allied health professionals are not always
accessible, available or affordable nor are all familiar
with using lifestyle therapies when delivered in a men-
tal health context. In settings where this is the case,
lifestyle-based mental health care is best supervised
by a qualified health professional whose expertise in
this area can be supported by professional develop-
ment training. For example, in the UK, ‘lifestyle medi-
cine’ courses are now available for doctors with formal
accreditation by the Royal College of General
Practitioners. The capacity for allied health profes-
sional-delivered, lifestyle-based mental health care
using digital platforms can bring this type of special-
ised care to those living with MDD, especially in set-
tings where resources are scarce. This is increasingly
important as COVID-19 places additional burden on
mental health care systems around the world, particu-
larly as global rates of MDD and anxiety have
increased since 2020 (Taquet et al. 2021).
Implementation consideration #10: Substance use
should be assessed and, where available, existing alco-
hol and other drug guidelines should be employed to
appropriately support cessation or minimisation using
established therapeutic approaches
The bidirectional relationship between mental illness and
substance use is well established: substance use is a risk
factor for mental illness development, symptom severity
and relapse, while mental illness is a risk factor for future
substance use (Davis et al. 2008). In addition, people
with substance use disorders (SUDs) also often experi-
ence high rates of comorbid acute and chronic physical
health conditions, including infections such as HIV, liver
disease, and cardiac related complications (Lin WC et al.
2011). The exact prevalence of SUDs in mental illness
and vice versa varies significantly depending on the
demographics, diagnosis, geographic setting, and socioe-
conomic status. A 2020 systematic review and meta-ana-
lysis showed the pooled prevalence of any SUD in those
with MDD was 25% (Hughes et al. 2020). In addition to
the significant impact of substance use on an individual’s
mental and physical health, there are also consequences
for close relationships and society at large.
There are many barriers to accessing care, often
compounded by high levels of stigma. It is not
uncommon for people with a SUD and therapists to
experience challenges when seeking support for peo-
ple with a dual diagnosis, as treatment is often siloed
and stigma around personal ‘moral’ responsibility is
still frequently present. As a result, there can be sub-
stantial delays to treatment in people with SUDs, lead-
ing to preventable biopsychosocial harms (Chapman
et al. 2015).
40 W. MARX ET AL.
The role of lifestyle-based approaches in MDD may
also extend into the management of substance use
disorders, though there is currently limited evidence
across lifestyle domains (Firth et al. 2020). Physical
activity is one of the more commonly studied areas of
lifestyle and may affect alcohol and/or substance use
through various biopsychosocial mechanisms (Wang D
et al. 2014; Linke and Ussher 2015), such as an
increase in positive affect, acute reduction in cravings
and urges, and an improvement in co-morbid physical
disease, MDD, and anxiety. These mechanisms are per-
tinent as substance use can be a means of ‘self-medi-
cating’ psychological distress, past and ongoing
trauma, and mental illness (Smith et al. 2017).
It is important to consider that individuals present-
ing with substance use may have many other mental,
medical and socioeconomic challenges. Hence, if avail-
able, an interdisciplinary approach that may include
medical, psychological, allied health, social work, legal,
financial, and peer support are often required. Peer
support and group programs as Alcoholics Anonymous,
Narcotics Anonymous, and SMART recovery (Self-
Management And Recovery Training), that focus on the
addictive behaviour as opposed to the substance, are
available online and in person, and are run by trained
facilitators, have shown promise (Beck et al. 2017).
Further guidance can be gained from the dedicated
clinical guidelines for the management of substance
use in the mental health setting (see Marel et al. 2016).
6.3. Resources
C15 The 2020 Royal Australian and New Zealand College
of Psychiatrists clinical practice guidelines for mood
disorders (Malhi et al. 2021). Clinical guidelines for
mood disorders, developed by the Royal Australian
and New Zealand College of Psychiatrists, that pro-
vides a model of care where lifestyle factors and
interventions are a core component of clin-
ical management.
C15 The Lift Project (The Lift Project 2022). An online
interdisciplinary intervention that aims to
improve wellbeing
C15 Mindfulness for Wellbeing and Peak Performance
(Hassed and Chambers 2016). An online course on
mindfulness via Monash University
C15 The Theory and Techniques Tool (Human Behaviour
Change Project 2022). An online tool that explores
the links between 74 Behaviour Change Techniques
(BCTs) and 26 Mechanisms of Action (MoAs).
C15 Food & Mood Centre Dietary Assessment Overview
(The Food & Mood Centre 2021). Further guidance
on dietary assessment tools in the research and
clinical setting
C15 The Lancet Psychiatry Commission: a blueprint for
protecting physical health in people with mental ill-
ness (Firth et al. 2019b). A recent Lancet commis-
sion report on physical comorbidities present with
mental illness and possible interventions for clinical
management and further research.
Acknowledgments
We wish to thank the following individuals for their valuable
feedback and review of this manuscript: Dr Mats Hallgren
PhD (Department of Global Public Health Sciences,
Karolinska Institute, Sweden); Simon Matthews FASLM MAPS
DipIBLM (Wellcoaches Australia/Singapore and Avondale
University Lifestyle Medicine and Health Research Centre); A/
Prof Megan Teychenne (Deakin University, Geelong,
Australia, Institute for Physical Activity and Nutrition (IPAN));
Professor Bob Morgan (University of Newcastle); Dr Neil
Bailey (Epworth Centre for Innovation in Mental Health);
Murat Yucel (BrainPark, Turner Institute for Brain and Mental
Health, School of Psychological Sciences, and Monash
Biomedical Imaging Facility, Monash University, Melbourne,
Victoria, Australia); Dr. Jeroen Deenik (GGz Centraal and the
School for Mental Health and Neuroscience, Maastricht
University); Heather M. Francis (Macquarie University,
Australia); Dr Dan Siskind (Metro South Addiction and
Mental Health Service, Brisbane, Australia; School of Clinical
Medicine, University of Queensland, Brisbane, Australia);
Nicola Veronese (University of Palermo, Department of
Internal Medicine, Geriatrics Section, Palermo, Italy); Beny
Lafer, MD, PhD (Department of Psychiatry, University of S~ao
Paulo Medical School, Brazil); Evan Matthews, PhD (Centre
for Health Behaviour Research, The School of Health
Sciences, Waterford Institute of Technology, Ireland); Joseph
Firth (Division of Psychology and Mental Health, University
of Manchester); Dr Rebecca Segrave (BrainPark, Turner
Institute for Brain and Mental Health & Monash Biomedical
Imaging, Monash University, Australia); Sam Hughes
(BrainPark, Monash University); Dr Farhana Mann (University
College London, UK); Joep van Agteren (Mental Health and
Wellbeing Program, South Australian Health and Medical
Research Institute (SAHMRI)).
Statement of interest
See funding section.
Funding
Wilson Foundation provided partial personnel funding for
this project but had no input into any phase of the develop-
ment. WM is currently funded by an NHMRC Investigator
Grant [#2008971] and a Multiple Sclerosis Research Australia
early-career fellowship. Wolfgang has previously received
funding from the Cancer Council Queensland and university
grants/fellowships from La Trobe University, Deakin
University, University of Queensland, and Bond University.
THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 41
Wolfgang has received industry funding and has attended
events funded by Cobram Estate Pty. Ltd. Wolfgang has
received research funding from Bega Dairy and Drinks.
Wolfgang has received travel funding from Nutrition Society
of Australia. Wolfgang has received consultancy funding
from Nutrition Research Australia and ParachuteBH.
Wolfgang has received speakers’ honoraria from The Cancer
Council Queensland and the Princess Alexandra Research
Foundation. SM has no potential financial conflicts of inter-
est to declare. SM is the pro-bono President of the
Australasian Society of Lifestyle Medicine, a GP, and Senior
Lecturer with James Cook University. MBerk is supported by
a NHMRC Senior Principal Research Fellowship [1156072]. In
the last 3years, MBerk received grant/research support from
National Health and Medical Research Council, Wellcome
Trust, Medical Research Future Fund, Victorian Medical
Research Acceleration Fund, Centre for Research Excellence
CRE, Victorian Government Department of Jobs, Precincts
and Regions and Victorian COVID-19 Research Fund. He
received honoraria/royalties from Springer, Oxford University
Press, Cambridge University Press, Allen and Unwin, EPA
Warsaw, Lundbeck, Controversias Barcelona, Servier,
Medisquire, HealthEd, ANZJP, European Psychiatric
Association, Janssen, Medplan, Milken Institute, RANZCP,
Abbott India, ASCP, Headspace, Allori for Eisai, Otsuka,
Global Congress of Biological Psychiatry India, St Bio Pharma
and Sandoz. FNJ is supported by an NHMRC Investigator
Grant [#1194982]. She has received: (1) competitive Grant/
Research support from the Brain and Behaviour Research
Institute, the National Health and Medical Research Council
(NHMRC), Australian Rotary Health, the Geelong Medical
Research Foundation, the Ian Potter Foundation, The
University of Melbourne; (2) industry support for research
from Meat and Livestock Australia, Woolworths Limited, the
A2 Milk Company, Be Fit Foods, Bega Dairy and Drinks; (3)
philanthropic support from the Fernwood Foundation,
Wilson Foundation, the JTM Foundation, the Serp Hills
Foundation, the Roberts Family Foundation, the Waterloo
Foundation and; (4) travel support and speakers honoraria
from Sanofi-Synthelabo, Janssen Cilag, Servier, Pfizer,
Network Nutrition, Angelini Farmaceutica, Eli Lilly,
Metagenics, and The Beauty Chef. Felice Jacka has written
two books for commercial publication. BS holds an National
Institute of Health Research (NIHR) Advanced fellowship
[NIHR301206, 2021-2026]. Brendon is lead/co-investigator on
active grants from the NIHR, the Medical Research Council,
Reta Lila Weston Trust For Medical Research. BS is on the
Editorial board of Ageing Research Reviews, Mental Health
and Physical Activity, The Journal of Evidence Based
Medicine and The Brazilian Journal of Psychiatry. Brendon
has received honorarium from a co-edited academic book
on exercise and mental illness, advisory work from
ParachuteBH and ASICS for unrelated work. The views
expressed are those of the author(s) and not necessarily
those of mentioned above, the NHS, the NIHR, the
Department of Health and Social Care or the MRC. FBS is
part supported by CAPES [grant #001]. Felipe Schuch has
written one book for commercial publication. AR has been a
recipient of Postdoctoral Research Fellowship from Faculty
of Health, Deakin University, Australia, and has received
research funding from Finnish Cultural Foundation, Emil
Aaltonen Foundation and Kuopio University Hospital,
Finland. She holds a university lecturer’s position at the
University of Eastern Finland. AR has received travel or
speakers’ honoraria funds from Nutrition Society of Australia,
Eastern Finland Medicine Association, University of Turku
and The Association of Clinical and Public Health
Nutritionists in Finland. GM’s research has been supported
by grants from NHMRC, CIHR, Beyondblue and the Barbara
Dicker Foundation. He has no conflicts to report. JAB is
partly funded by the National Institutes of Health
[HL125522]. AO is supported by a National Health & Medical
Research Council Emerging Leader 2 Fellowship [2009295].
She has received research funding from NHMRC, MRFF,
Heart Foundation, Meat & Livestock Australia, and Sanofi
and Honoraria from Novartis. TD is a medical advisor to
Atlantia CRO and Biohaven Pharmaceuticals. All other
authors declare no conflicts of interest.
ORCID
Wolfgang Marx http://orcid.org/0000-0002-8556-8230
Sam H. Manger http://orcid.org/0000-0001-7959-3811
Greg Murray http://orcid.org/0000-0001-7208-5603
Fiona Yan-Yee Ho http://orcid.org/0000-0001-7448-4982
Sharon Lawn http://orcid.org/0000-0002-5464-8887
Felipe Schuch http://orcid.org/0000-0002-5190-4515
Brendon Stubbs http://orcid.org/0000-0001-7387-3791
Anu Ruusunen http://orcid.org/0000-0002-1169-7478
Timothy G. Dinan http://orcid.org/0000-0002-2316-7220
Felice Jacka http://orcid.org/0000-0002-9825-0328
Michael Berk http://orcid.org/0000-0002-5554-6946
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