Mental Health Recovery Narratives and Their Impact on Recipients: Systematic Review and Narrative Synthesis
Bibliographic record
Abstract
OBJECTIVE: Mental health recovery narratives are often shared in peer support work and antistigma campaigns. Internet technology provides access to an almost unlimited number of narratives, and yet little is known about how they affect recipients. The aim of this study was to develop a conceptual framework characterizing the impact of recovery narratives on recipients. METHOD: = 7). A conceptual framework was generated through a thematic analysis of included articles, augmented by consultation with a Lived Experience Advisory Panel. RESULTS: In total, 8137 articles were screened. Five articles were included. Forms of impact were connectedness, understanding of recovery, reduction in stigma, validation of personal experience, affective responses, and behavioural responses. Impact was moderated by characteristics of the recipient, context, and narrative. Increases in eating disorder behaviours were identified as a harmful response specific to recipients with eating disorders. CONCLUSIONS: Mental health recovery narratives can promote recovery. Recovery narratives might be useful for clients with limited access to peers and in online interventions targeted at reducing social isolation in rural or remote locations, but support is needed for the processing of the strong emotions that can arise. Caution is needed for use with specific clinical populations. Protocol registration: Prospero-CRD42018090923.
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How this classification was reachedexpand
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".