Repressive/Defensive Coping, Identity Confusion and Social Stress in Non-Suicidal Self-injury among Psychiatric Patients
Bibliographic record
Abstract
Objective The present study aims to investigate the relationship between repressive defensive coping, identity confusion and social stress among non suicidal self-injury patients in psychiatric population. Method Between group cross sectional research design was used to collect the data of 70 participants (Men=27 and Women=43) with age ranging from 20-35 (Mean age=27.3, S.D=4.9). Data was collected from Government and Private Hospitals.Following tools were used to measure variables Ottawa Self-injury Inventory (OSI) (Nixon & Cloutier, 2005), Rational/ Emotional Defensiveness Scale (R/ED) (Swan, Carmelli, Dame, Rosenman & Spielberger, 1991), Brief Fear of Negative Evaluation (BFNE-II) (Carleton, Collimore & Asmundon, 2007) and Erickson Psychosocial Stage Inventory (EPSI)(Rosenthal, Gurney & Moore, 1981). Results Results revealed that repressive defensive coping and identity is negatively related to NSSI while social stress was positively related to NSSI. Prediction analysis revealed that anti-emotionality, identity synthesis, confusion and social stress were significant predictors of non-suicidal self- injury. Conclusion Present research reveals some of the major contributing factors and features of non-suicidal self- injury along with coping and stress of the individuals that will help the professionals to understand the phenomena and provide better assistance.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".