Hope as a Process in Understanding Positive Mood and Suicide Protection
Bibliographic record
Abstract
Abstract. Background: According to the broaden-and-build model of positive mood, positive emotions are believed to broaden cognition resources and build psychological resiliency, to help incur positive psychological outcomes. Aim: We examined hope as a potential mediator of the association between positive mood and suicide protection (viz., life satisfaction and reasons for living) in adults. We hypothesized that positive mood would be associated with greater suicide protection through broadening hope agency and building hope pathways. Method: A sample of 320 college students completed measures of positive emotions, hope, and suicide protection. Results: Results from bootstrapped mediation testing indicated that hope agency, but not hope pathways, partially or fully mediated the relationship between positive mood and suicide protection. Limitations: It is not clear whether these findings are generalizable to a more diverse adult population. Also, it is not possible to rule out alternative causal models involving positive emotions and suicide protection. Conclusion: These findings provide some promising preliminary evidence for how positive emotions might help build hope agency to foster greater suicide protection in adults.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".