Identifying and Exploring Sustainability Determinants of Mental Health Recovery-Oriented Interventions: A Mixed Methods Study Protocol
Bibliographic record
Abstract
Mental health recovery is the new paradigm in the mental health service delivery system worldwide. Recovery-oriented services go beyond traditional clinical care that is centered on symptom remission, aiming to help people: restore social connections with other individuals and the community; develop hope and optimism for the future; reconstruct an identity beyond that of a "mental patient"; discover meaning in life; and feel empowered to gain control over treatment (CHIME framework). Over the last ten years, several efforts at implementation of recovery-oriented interventions have been documented in the scientific literature. However, little attention has been given to their sustainability, even though it is reported that not all health interventions can fully sustain their activities beyond the initial implementation phase. The aim of this mixed methods case study is to better understand the factors that determine the sustainability of two recovery-oriented interventions (peer support and recovery training) after their roll-out in four organizations in Canada that provide community housing for adults with mental health challenges. Qualitative and quantitative data will be collected from managers, service providers, and implementation team members that oversaw the implementation process along with organizational documents. Data collection and analysis will be guided by the Consolidated Framework for Sustainability Constructs in Healthcare, the Framework for Reporting Adaptations and Modifications, and the Program Sustainability Assessment Tool. Findings will expand our current evidence base on the intersection of sustainability and mental health recovery interventions that remains under-explored.
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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 | 0.101 | 0.063 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.054 | 0.009 |
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".