Factors influencing the implementation of mental health recovery into services: a systematic mixed studies review
Bibliographic record
Abstract
BACKGROUND: Countries around the world have committed in policy to transforming their mental health services towards a recovery orientation. How has mental health recovery been implemented into services for adults, and what factors influence the implementation of recovery-oriented services? METHODS: This systematic mixed studies review followed a convergent qualitative synthesis design and used the best-fit framework synthesis method. Librarians ran searches in Ovid- MEDLINE, Ovid-EMBASE, Ovid-PsycInfo, EBSCO-CINAHL Plus with Full Text, ProQuest Dissertations and Theses, Cochrane Library, and Scopus. Two reviewers independently screened studies for inclusion or exclusion using DistillerSR. Qualitative, quantitative, and mixed methods peer-reviewed studies published since 1998 were included if they reported a new effort to transform adult mental health services towards a recovery orientation, and reported findings related to implementation experience, process, or factors. Data was extracted in NVivo12 to the 38 constructs of the Consolidated Framework for Implementation Research (CFIR). The synthesis included a within-case and a cross-case thematic analysis of data coded to each CFIR construct. Cases were types of recovery-oriented innovations. RESULTS: Seventy studies met our inclusion criteria. These were grouped into seven types of recovery-oriented innovations (cases) for within-case and cross-case synthesis. Themes illustrating common implementation factors across innovations are presented by CFIR domain: Intervention Characteristics (flexibility, relationship building, lived experience); Inner Setting (traditional biomedical vs. recovery-oriented approach, the importance of organizational and policy commitment to recovery-transformation, staff turnover, lack of resources to support personal recovery goals, information gaps about new roles and procedures, interpersonal relationships), Characteristics of Individuals (variability in knowledge about recovery, characteristics of recovery-oriented service providers); Process (the importance of planning, early and continuous engagement with stakeholders). Very little data from included studies was extracted to the outer setting domain, and therefore, we present only some initial observations and note that further research on outer setting implementation factors is needed. CONCLUSION: The CFIR required some adaptation for use as an implementation framework in this review. The common implementation factors presented are an important starting point for stakeholders to consider when implementing recovery-oriented services.
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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 | 0.066 | 0.195 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.022 | 0.025 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".