Strategies and impacts of patient and family engagement in collaborative mental healthcare: protocol for a systematic and realist review
Bibliographic record
Abstract
INTRODUCTION: Collaborative mental healthcare (CMHC) has garnered worldwide interest as an effective, team-based approach to managing common mental disorders in primary care. However, questions remain about how CMHC works and why it works in some circumstances but not others. In this study, we will review the evidence on one understudied but potentially critical component of CMHC, namely the engagement of patients and families in care. Our aims are to describe the strategies used to engage people with depression or anxiety disorders and their families in CMHC and understand how these strategies work, for whom and in what circumstances. METHODS AND ANALYSIS: We are conducting a review with systematic and realist review components. Review part 1 seeks to identify and describe the patient and family engagement strategies featured in CMHC interventions based on systematic searches and descriptive analysis of these interventions. We will use a 2012 Cochrane review of CMHC as a starting point and perform new searches in multiple databases and trial registers to retrieve more recent CMHC intervention studies. In review part 2, we will build and refine programme theories for each of these engagement strategies. Initial theory building will proceed iteratively through content expert consultations, electronic searches for theoretical literature and review team brainstorming sessions. Cluster searches will then retrieve additional data on contexts, mechanisms and outcomes associated with engagement strategies, and pairs of review authors will analyse and synthesise the evidence and adjust initial programme theories. ETHICS AND DISSEMINATION: Our review follows a participatory approach with multiple knowledge users and persons with lived experience of mental illness. These partners will help us develop and tailor project outputs, including publications, policy briefs, training materials and guidance on how to make CMHC more patient-centred and family-centred. PROSPERO REGISTRATION NUMBER: CRD42015025522.
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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 | 0.139 | 0.156 |
| Meta-epidemiology (narrow) | 0.007 | 0.007 |
| Meta-epidemiology (broad) | 0.018 | 0.022 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.073 | 0.012 |
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".