Childhood emotional maltreatment affects depression of adolescents with mood disorders: the mediating role of functions of non-suicidal self-injury
Bibliographic record
Abstract
BACKGROUND: Childhood emotional maltreatment, non-suicidal self-injury and depression are prevalent among adolescents with mood disorders. While existing model indicated that childhood emotional maltreatment, functions of non-suicidal self-injury and depression are interrelated, not much is understood about the interplay of functions of non-suicidal self-injury in the relationship between childhood emotional maltreatment and depression. Thus, the goal of this research was to ascertain how functions of non-suicidal self-injury relate to childhood emotional maltreatment and depression. METHODS: The participants were adolescents with mood disorders from three hospitals in Sichuan Province, data was collected using self-administered questionnaires, including the Childhood Trauma Questionnaire, Ottawa Self-injury Inventory-Functions, and Childhood Depression Inventory. SPSS26.0 software and PROCESS v3.3 model 4 were used for analysis. RESULTS: =14.8, SD = 1.62) participated in the research. The functions of non-suicidal self-injury (r = 0.289, P < 0.01) and depression (r = 0.475, P < 0.01) were considerably positively connected with childhood emotional maltreatment, and the functions of non-suicidal self-injury were strongly positively correlated with depression (r = 0.364, P < 0.01). The direct impact of childhood emotional maltreatment on depression in adolescents was found to be significant (95% CI 0.434, 0.828) in the mediated effects model. Additionally, the indirect effect of childhood emotional maltreatment on depression through functions of non-suicidal self-injury was found to be significant (95% CI 0.055, 0.236), with a mediating effect value of 17.58%. CONCLUSION: Childhood emotional maltreatment has a direct impact on depression, but it also has an indirect influence through mediation roles of functions of non-suicidal self-injury. Medical staff should take care of the mental health of adolescents hospitalized for mood disorders so that they can clarify the role of functions of NSSI in lowering depressive symptoms and improving quality of life and create more targeted and effective intervention plans.
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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 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".