Explaining the Effects of Psychological Factors: Trauma Exposure, Dissociation, Emotion Dysregulation and Alexithymia on Deliberate Self-harm with the Mediating Roles of Dissociation and Emotion Dysregulation
Bibliographic record
Abstract
Background and aims: Self-Harm, also known as nonsuicidal self-injury or self-mutilation is the intentional, direct act of harming the body tissue without suicidal intentions. Being of a violent and primitive nature, self-harm is a crucial clinical problem which cause great concern among clinicians. This study aims to examine relationship between deliberate selfharm and psychological variables including trauma exposure, dissociation, emotion dysregulation, Alexithymia with the mediating roles of dissociation and emotion dysregulation. Materials and methods: For this purpose, 200 (female 114, male 86) medical students of Shahid Beheshti University of Medical Sciences, in Tehran, Iran were selected and assessed in terms of deliberate self-harm inventory DSHI, dissociative experiences scale-II DES-II, childhood trauma questionnaire CTQ, Difficulties in emotion regulation scale DERS, and Toronto Alexithymia Scale TAS which were totally 114 items. Data analysis was done based on Partial Least Squares Structural Equation Modeling PLS-SEM and the use of Partial Least Squares of software. Results: The results revealed trauma exposure directly affects emotion dysregulation, dissociation, and deliberate self-harm with the Significant t values measures: 10.087, 9.450, 2.075, and β-value: 0.512, 0.564, 0.161 respectively. Moreover, trauma exposure has an indirect effect on deliberate self-harm by mediating role of emotion dysregulation and dissociation with the respectively t values: 2.363, 3.459 and β-value: 0.102, 0.227. In addition, emotion dysregulation and dissociation have a direct effect on deliberate self-harm with the t values: 2.440, 4.035, and β-value: 0.198, 0.403 respectively. Finally, Alexithymia with t value =0.759, and β-value=0.041 do not affect deliberate self-harm significantly. Conclusion: It was predicted that higher exposure to trauma would be related to increased levels of emotion dysregulation, dissociation followed by deliberate self-harm. So the findings of the study at hand provide more evidence on the significant effect of trauma exposure, emotion dysregulation, and dissociation on deliberate self-harm. They also support the mediating role of emotion dysregulation and dissociation as chief functions of deliberate self-harm.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".