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
Bibliographic record
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 taskforce members. The focus of the guidelines was eight lifestyle domains: physical activity and exercise, smoking cessation, work-directed interventions, mindfulness-based and stress management therapies, diet, sleep, loneliness and social support, and green space interaction. The following 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 recommendations of these guidelines support the need for further research to address existing gaps in 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.070 | 0.135 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.013 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.011 | 0.006 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".