Coping Strategies and Psychological Outcomes: The Moderating Effects of Personal Resiliency
Bibliographic record
Abstract
Certain coping strategies alleviate stress and promote positive psychological outcomes, whereas others exacerbate stress and promote negative psychological outcomes. However, the efficacy of any given coping strategy may also depend on personal resiliency. This study examined whether personal resiliency moderated the effects of task-oriented, avoidance-oriented, and emotion-oriented coping strategies on measures of depression, anxiety, stress, positive affect, negative affect, and satisfaction with life. Results (N = 424 undergraduates) showed higher personal resiliency was associated with greater use of task-oriented coping strategies, which were in turn associated with more adaptive outcomes, and less reliance on nonconstructive emotion-oriented strategies, which in turn were associated with poorer psychological outcomes. In addition, individual differences in personal resiliency moderated the effects of task-oriented coping on negative affect and of emotion-oriented coping on negative affect and depression. Specifically, proactive task-oriented coping was associated with greater negative affect for people lower in personal resiliency. Moreover, high personal resiliency attenuated the negative effects of emotion-oriented coping on depression and negative affect. The effects of avoidance-oriented coping were mixed and were not associated with or dependent on levels of personal resiliency.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".