Implementation of peer support in mental health services: A systematic review of the literature.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Peer support within mental health services has a growing evidence base and aligns with current policies of recovery-oriented care. Despite these advantages, widespread implementation of peer support remains limited, likely due to various methodological and implementation issues. Researchers have noted the importance of utilizing an implementation framework to understand best practices for implementation. Therefore, the purpose of the current study was to synthesize the existing literature on the implementation of peer support interventions and identify barriers and facilitators using an implementation framework. The Consolidated Framework for Implementation Research (CFIR) was used to organize the literature obtained in the systematic search and synthesize best practices for implementation. The systematic search identified 19 published articles that were coded for relevant information including implementation barriers and facilitators. The review highlighted a number of important elements for implementation within the CFIR domains, including clear role definition, a flexible organizational culture, and education for peer and nonpeer staff. Implementation barriers included an organizational culture without a recovery focus, allied practitioners' beliefs about peer support, and an unclear peer role. The results of this review provide a summary of best practices for the implementation of peer support in mental health services that can be used by researchers and service providers in future implementation. These practices should continue to be tested and reworked as the climate of recovery-oriented services within mental health organizations evolves. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it