Understanding the Impact of Adverse Childhood Experiences on Non-suicidal Self-Injury in Youth: A Systematic Review
Bibliographic record
Abstract
Objective: Non-suicidal self-injury (NSSI), defined as a deliberate destruction of one's own body without a suicidal intent, is a global public health issue. Adverse childhood events (ACEs) have been shown to be associated with various mental illnesses; however, to date the impact of such events on NSSI in youth has not been reviewed. Methods: We conducted a systematic review, searched 5 databases for published articles evaluating ACE and NSSI in youth less than or equal to 21 years of age. After screening 247 articles, we included 21 unique articles in this systematic review. Results: Increasing ACE score, physical, sexual or emotional abuse, parental neglect and substance use, parental separation or dysfunctional family, and death of a close family member had statistically significant correlation with NSSI. Conclusion: Non-suicidal self-injury is an impairing diagnosis with far reaching psychiatric manifestations and repercussions. Practitioners having high clinical suspicion for ACEs in youth with NSSI must intervene early by administering the ACEs questionnaire. Effective treatment of NSSI in those with ACEs with psychotherapy significantly improves outcomes and prevents suicide in youth.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".