Typology of Mental Health Peer Support Work Components: Systematised Review and Expert Consultation
Bibliographic record
Abstract
Abstract The employment of mental health peer support (PS) is recommended in national and international mental health policy, and widely implemented across many countries. The key components of PS remain to be identified. This study aimed to develop a typology of components involved in one-to-one PS for adults in mental health services. A systematised review was performed to establish a preliminary long list of candidate components, followed by expert consultation ( n = 21) to refine the list. Forty-two publications were full-text reviewed, comprising 26 trial reports, nine training manuals, and seven change model papers. Two hundred forty-two candidate components were identified, which were thematically synthesised to 16 components and eight sub-components, categorised into four themes: recruitment, preparation, practice, and PS worker wellbeing. Our typology can inform reflection and planning of PS practice, and allow more rigorous and synthesised studies, such as component network meta-analyses, to characterise the impact of each component and their interactions.
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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 | 0.264 | 0.498 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.044 | 0.036 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".