Coping, Social Support, and Suicide Attempts Among Homeless Adolescents
Bibliographic record
Abstract
Abstract. Background: Homeless youth are a population at risk for suicidal behavior. Despite growing knowledge about risk factors, protective factors against suicidal behavior among this population are still poorly understood. Aims: To explore differences in coping and social support between homeless adolescents who attempted suicide and those who did not. Method: In total, 76 homeless adolescents from eight different shelters provided information about their suicidal behaviors over the previous year and filled out coping and social support questionnaires. Results: Homeless adolescents who had not attempted suicide perceived more social support (tangible assistance and guidance). Conversely, youth who had attempted suicide reported using more nonproductive strategies of coping (tension reduction, keep to self, and self-blame). Tangible assistance and tension reduction were found to be the strongest predictors. Limitations: As most of these youth were not homeless for a long time, care should be taken in generalizing these results to adolescents with longer histories of homelessness. Conclusion: Productive coping does not seem to constitute a sufficient personal resource to protect homeless adolescents from suicide attempts. Nonproductive coping could, however, be considered a serious risk factor. Consequently, promoting homeless youths' ability to find environmental resources, especially tangible assistance, could be the most valuable approach.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".