Community-Embedded Positive Mental Health Promotion Programs for the General Population: A Scoping Review Protocol
Bibliographic record
Abstract
Introduction: Positive mental health promotion (PMHP) is an emerging field within community mental health. Programming and policy efforts devoted to promoting mental health are developing. These efforts are varied in scope and nature, and there is little consensus on evidence-based best practices. Objective: To chart the body of literature on PMHP programming and to document the current PMHP in one Canadian province to provide insight into the types, scope, and nature of the programs currently and historically available to community residents in this province. Inclusion criteria: Peer-reviewed literature relevant to community mental health promotion, and grey literature that contains details of community-based programs accessible to the general population in that community. Methods: A preliminary search strategy in PubMed, EBSCO, and PsycInfo was developed with a librarian and a JBI-trained researcher. Primary studies published in English after 2000 evaluating or documenting PMHPs will be included. Grey literature from an environmental scan of existing local programs will be included. Data to be extracted includes study methodology and methods, program scope, content, materials, evaluation and outcomes.
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.
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 | 0.087 | 0.061 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.020 | 0.017 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.071 | 0.011 |
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".