Prosocial behavior and youth mental health outcomes: A scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: This review aims to explore the existing literature about the virtue of helping others and its association with youth mental health. Mental health of youth is rooted in their social environment. Helping others or engaging in prosocial behavior are activities that youth may participate in. The notion of helping others and its association with individual mental well-being have been well-studied for adults and older adults and to some extent in youth, however, no review has been conducted to understand the intersection of helping others and mental health in the youth population. METHODS: This review will consider all study designs that examine helping others and mental health of youth. The inclusion criteria for the review will include young individuals aged 10-24-year-old, living in any geographic location, of all gender identities, and with or without mental health issues. Grey literature and studies that only speak to outcomes related to physical well-being will be excluded. A search will be conducted in CINAHL, MEDLINE and PsycINFO. Studies published in the English language will be included with no restriction on publication time period. Articles will be screened against the inclusion criteria onto a single software by two independent reviewers. In the case of any disagreement, a third independent reviewer would resolve the conflict. FINDINGS: Data will be extracted and presented in a tabular or diagrammatic form supported by a summary. We will report our findings in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews (PRISMA-ScR). The findings of this review will provide evidence-based recommendations for promoting youth mental health and a basis for future research.
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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 | 0.096 | 0.091 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.017 | 0.015 |
| Bibliometrics | 0.023 | 0.017 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.094 | 0.018 |
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".