Examining Resilience-Focused Interventions for Rural Populations Experiencing Chronic Stress: A Mixed Methods Systematic Review Protocol
Bibliographic record
Abstract
This article describes the protocol of a mixed methods systematic review of resilience-focused interventions for children, youth, and adults exposed to chronic stress in rural contexts that was prospectively registered with PROSPERO (reference number CRD42021292413). The review will be performed using a convergent segregated mixed methods approach within which an intervention review and a qualitative evidence synthesis will be combined, and a results-based convergent synthesis design will be used to synthesize the data extracted from all included studies. The mixed methods systematic review will conform to the guidelines outlined by the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 statement, which were used to guide the development of this review protocol and reporting of the review findings. Additionally, the Johanne Briggs Institute methodological guidelines for conducting mixed methods reviews using a segregated approach will be implemented throughout the review process. The review will contribute to a better understanding of the available resilience-focused interventions for children, youth, and adults who experience chronic stress in rural contexts by investigating what interventions work for which populations (i.e., children, youth, or adults) in what circumstances (i.e., in the context of exposure to different chronic stressors).
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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 | 0.152 | 0.140 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.014 | 0.014 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.078 | 0.016 |
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".