The Effect of Bullying Victimization on Adolescent Non-Suicidal Self-Injury: The Mediating Roles of Alexithymia and Self-Esteem
Bibliographic record
Abstract
Background & Aim: Non-suicidal self-injury (NSSI) in adolescents is a serious public health issue influenced by the interaction of multiple factors. The purpose of this study was to investigate the multiple mediating roles of alexithymia and self-esteem in the association between bullying victimization and NSSI in a sample of Chinese adolescents. Methods: A survey of 1299 adolescents from two public middle schools in Henan Province, China, was undertaken. Data were collected using the Chinese version of the Delaware bullying victimization scale-student (DBVS-S), the Toronto Alexithymia-20 Scale (TAS-20-C), the Rosenberg self-esteem scale (RSES), and the adolescent self-injury questionnaire. Besides, we performed a structural equation modeling (SEM) with latent variables using AMOS 26.0 to examine the relationship between variables and the mediating effects. Results: The SEM analysis found that not only can bullying victimization directly impact NSSI, but that alexithymia and self-esteem have a chain mediating effect in the association between bullying victimization and NSSI. This mediating effect contributed 22.47% to the total effect. Conclusion: These findings validate bullying victimization, alexithymia, and low self-esteem are important variables that affect NSSI among Chinese adolescents. Educators need to implement some prevention and intervention strategies to ameliorate the campus atmosphere and adolescents' mental health aimed at avoiding NSSI behavior in adolescence.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".