The impact of childhood emotional abuse on non-suicidal self-injury in adolescents with mood disorders: a moderated mediation model
Bibliographic record
Abstract
Objectives: This study aims to identify factors associated with NSSI severity in adolescents with mood disorders and examine the mediating role of emotional expression difficulties and the moderating role of bullying in the relationship between childhood emotional abuse and NSSI. Methods: Using a convenience sampling method, 242 adolescents with mood disorders were surveyed with the Adolescent Self-Harm Questionnaire, Childhood Abuse Questionnaire, Toronto Alexithymia Scale, and Beck Suicidal Ideation Scale. Stepwise linear regression was performed to examine associations between NSSI severity and key predictors, including childhood trauma subtypes, alexithymia, and bullying history. The mediation and moderation effects were tested using the Hayes Process plugin. Results: The prevalence of NSSI among adolescents with mood disorders was 81.40% (n = 197). Experiences of bullying (β=0.19, P=0.001), childhood emotional abuse (β=0.25, P<0.001), and difficulties in emotional expression (β=0.25, P<0.001) were positively correlated with the severity of NSSI, while age (β=-0.12, P=0.046) was negatively correlated. Difficulties in emotional expression partially mediated the relationship between childhood emotional abuse and NSSI, with a mediation effect size of 0.25, Bootstrap 95% CI (0.02-0.10), accounting for 21% of the total effect. This mediation effect was moderated by experiences of bullying, showing a positive association between the severity of NSSI and the interaction term of emotional expression difficulties and bullying (β=3.23, P<0.001), with a moderated mediation index of 0.48 and Bootstrap 95% CI (0.08-1.14). Conclusion: Childhood emotional abuse in adolescents with mood disorders can have both direct and indirect effects on NSSI through difficulties in emotional expression, and experiences of bullying moderate the relationship between NSSI and emotional expression difficulties.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".