Incidence of Major Depressive Disorder Relapse and Effectiveness of Pharmacologic and Psychological Interventions in Primary Care: A Systematic Review and Meta-Analysis: Incidence de la rechute du trouble dépressif majeur et efficacité des interventions pharmacologiques et psychologiques en soins primaires : revue systématique et méta-analyse
Bibliographic record
Abstract
ObjectiveThis research aims to investigate the relapse rates of major depressive disorder (MDD) within primary care and evaluate the efficacy of relapse prevention therapies. Despite primary care being the common point of contact for MDD patients, there are limited studies around this.MethodsWe included randomized controlled trials and observational studies examining MDD relapse incidence and the effect of pharmacological and non-pharmacological interventions in preventing relapse in primary care. Databases; Medline via Ovid, EMBASE, The Cochrane Library, PsycInfo (ebsco), and Clinical Trials.gov were searched from their inception until September 7, 2022. Joanna Briggs Institute (JBI) appraisal instrument for methodological quality assessment was used. A proportional data analysis estimated the MDD relapse incidence. Therapy effectiveness results were shown as odds ratios with 95% confidence intervals, with heterogeneity explored via subgroup analysis.ResultsOut of the reviewed studies, 35 met the eligibility criteria. Quality appraisal scores varied between 73% and 96%. MDD relapse incidence was divided into subgroups, revealing that both pharmacotherapy and non-pharmacotherapy led to a similar decrease in relapse rates with combination therapies showing further reduction in relapse. Subgroup analyses by study design, follow-up length, date of study and quality of study also yielded noteworthy findings.ConclusionOur findings showed that MDD relapse rates in primary care settings can be effectively reduced by pharmacotherapy, non-pharmacotherapy, or combination therapy. Some psychological interventions might also reduce relapse likelihood. More studies are needed on individual and combined treatments over longer periods to understand their long-term impacts on MDD relapse in primary care.Plain Language Summary TitleHow Often Depression Returns and How Well Treatments Work in Primary Care: A Review of Studies.
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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 | 0.026 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.029 | 0.057 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".