Prosocial behavior interventions implemented among undergraduate student populations: a scoping review
Bibliographic record
Abstract
INTRODUCTION: Undergraduate students face a multitude of unique stressors which can affect their mental health and well-being. Finding ways to promote positive mental health among students is critical. Engagement in prosocial behavior is one way to buffer against such negative mental health outcomes. OBJECTIVES: The objective of this scoping review was to determine what is known from the literature regarding the use of prosocial behavior interventions for undergraduate students' mental health and well-being. METHODS: Five databases were searched (i.e., MEDLINE, EMBASE, PsycINFO, Scopus, CINAHL) and articles were screened independently and simultaneously by 2 researchers. Seven articles met the eligibility criteria and were included in this review. RESULTS: Three main themes and two subthemes were identified: (1) Types of Prosocial Behaviors Employed; (2) Recipients of Prosocial Behavior; and (3) Study Design and Intervention Impact (subthemes: Intervention Design and The Impact of Prosocial Behavior Interventions on Health Outcomes). CONCLUSIONS: The findings underscore prosocial behavior as a potential strategy to promote positive health outcomes in undergraduate students.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".