RELATIONSHIP BETWEEN COPING STRATEGIES, PERSONALITY TRAITS AND PSYCHOLOGICAL DISTRESS IN BAM EARTHQUAKE SURVIVORS
Bibliographic record
Abstract
Background: After each natural disaster a comprehensive treatment protocol is needed for volunteers of healthcare personnel of the disaster zone. The aim of this study was to emphasize the psychological aspects of coping strategies, personality, psychological distress and pain of patients survived the Bam earthquake. Methods: Eighty-six patients who had suffered several kinds of psycho-cognitive and emotional impairment of the Post-traumatic stress disorder (PTSD) were selected six months after the earthquake. They completed a battery of questionnaires including the Hospital Anxiety and Depression Scale (HADS), Ways of Coping Checklist, Eysenck Personality Questionnaire (EPQ), and McGill Pain Questionnaire (MPQ). Multiple regression analyses and Correlation Analyses were applied for inclusion and exclusion of variables. Correlations were reported between the HADS, EPQ and MPQ. Results: Both anxiety and depression showed significant positive correlations with five of the dimensions of MPQ. High levels of neuroticism were associated with greater use of denial and passivity. Psychoticism was negatively associated with external support, given the social withdrawal to be associated with psychoticism. Correlation analysis confirmed that high neuroticism was related to greater degrees of emotional distress. Anxiety and depression were both associated with increased scores in denial and passivity. Female patients were found to score significantly higher than males on the factor of “relying on external support”. Conclusion: The main problems of patients that survived from Bam earthquake were emotional distress, coping deficiency and adjustment disorders. It seems that psychological intervention might be more effective than the conventional medical treatments that were administered in the hospital.
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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".