The role of self-blame and responsibility in adjustment to inflammatory bowel disease.
Bibliographic record
Abstract
OBJECTIVE: S. C. Roesch and B. Weiner's (2001) theoretical model of adjustment to chronic illness was adapted to examine the role of attributions, avoidant coping strategies, and disease severity in the psychological adjustment of people with inflammatory bowel disease (IBD). RESEARCH METHOD AND DESIGN: People with IBD (N = 259) completed an online survey including measures of health-related self-blame and responsibility attributions, disease severity, avoidant coping strategies, and psychological adjustment indexes (coping efficacy, acceptance, and helplessness). RESULTS: Structural equation modeling revealed that avoidant coping mediated the relationship between attributions and psychological adjustment. Attributions of self-blame were directly related to increased avoidant coping, which was in turn associated with poor adjustment. Beliefs about responsibility were associated with decreased use of avoidant coping strategies and subsequently improved psychological adjustment. Higher scores on disease severity were linked to the use of avoidant coping strategies and poor psychological adjustment. CONCLUSIONS: Distinguishing between self-blame and responsibility attributions has important implications for understanding the psychological adjustment of individuals with IBD and may be useful for creating intervention strategies aimed at enhancing the psychological functioning of people with IBD.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".