Coping, meaning in life, and suicidal manifestations: Examining gender differences*
Bibliographic record
Abstract
Abstract Life meaning and coping strategies were investigated as statistical predictors of suicidal manifestations in a sample of 298 university undergraduates. Participants completed measures of hopelessness, sense of coherence, purpose in life, coping for stressful situations, suicide ideation, prior suicide attempts, and self‐reported likelihood of future suicidal behavior. Moderated multiple regression techniques examined the incremental validity of life meaning by coping interactions for predicting each suicide variable separately by gender. The interaction of sense of coherence and emotion‐oriented coping made a unique, significant contribution to the statistical prediction of all suicide variables for women. For men, the interaction between sense of coherence and emotion‐oriented coping contributed significantly to the statistical prediction of suicide ideation. All interactions remained significant when hopelessness was statistically controlled. The hypothesis that life meaning acts as a buffer between coping style and suicidal manifestations was partially supported. Implications for suicide prevention and intervention are discussed. © 2003 Wiley Periodicals, Inc. J Clin Psychol, 2003.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".