Therapeutic Guidelines for the Self-Management of Major Depressive Disorder: Scoping Review
Bibliographic record
Abstract
BACKGROUND: Major depressive disorder contributes to the global burden of mental illness. Therapeutic guidelines promote treatment self-management and support caregivers and family members in this process. OBJECTIVE: We aimed to identify therapeutic guidelines for the symptoms of major depressive disorder. METHODS: This scoping review followed the assumptions established by the Joanna Briggs Institute and the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) protocol, carried out in 12 databases (LILACS, PubMed, SciELO, Scopus, Web of Science, b-on, BDENF, AgeLine, Cochrane, BVS, IBECS, and CINAHL) and 5 secondary gray literature sources (Google Scholar, Global ETD Search, EBSCO Open Dissertations, CAPES Catalog of Theses and Dissertations, and the Digital Library of Theses and Dissertations of the University of Sao Paulo). The eligibility criteria were based on the population, concept, and context framework: people diagnosed with major depressive disorder aged >18 years (population), therapeutic guidelines for self-management of major depressive disorder symptoms (concept), and symptoms of major depressive disorder (context). Data collection was carried out from March to July 2022 and updated in June 2024. The included studies were experimental, quasi-experimental, analytical observational, descriptive observational, qualitative, or quantitative studies; systematic reviews and meta-analyses; and scoping and literature reviews published in full without time restrictions in English, Spanish, or Portuguese. All the information, as well as the studies captured, was stored in a Microsoft Excel spreadsheet using Rayyan and the JBI Manual for Evidence Synthesis. The titles, abstracts, and full texts were carefully read and classified, extracting the results. After review by 2 independent researchers, 62 studies were selected. The results are presented descriptively, including characterization of the studies and mapping and categorization of groups and subgroups of therapeutic guidelines for self-management of major depressive disorder. RESULTS: In total, 62 studies published between 2011 and 2023 were included, where 44 (71%) came from indexed data sources and 18 (29%) were gray literature indexed on Google Scholar (13/62, 21%), doctoral theses (3/62, 5%), and master's dissertations (2/62, 3%). Among the therapeutic guidelines identified, mapped, and categorized, 7 major groups were identified for self-management: psychotherapy (32/62, 52%), adoption of healthy habits (25/62, 40%), integrative and complementary practices (17/62, 27%), relaxation techniques (9/62, 14%), consultation with a health professional (14/62, 22%), pharmacological therapy (9/62, 14%), and leisure or pleasurable activities (4/62, 6%). CONCLUSIONS: It was possible to identify therapeutic guidelines to promote self-management of major depressive disorder in the adult population. Therapeutic guidance is an important resource for patients, their families, and the community, making patients the protagonists of their own health. For health professionals, therapeutic guidelines become tools that help develop skills and competencies for care among patients, thus ensuring their ability to self-manage major depressive disorder.
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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 | 0.060 | 0.201 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.032 | 0.026 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".