Age and gender effects on non-suicidal self-injury, and their interplay with psychological distress
Bibliographic record
Abstract
INTRODUCTION: NSSI (non-suicidal self-injury) is an important public health issue, with high prevalence and associations with future mental illness and suicide. To date, no large single study has tested age and gender effects on NSSI and their interplay with psychological distress. METHOD: NSSI and psychological distress were ascertained by questionnaire in a community study of 2368 young people aged 14-25; proportions at each age and of each gender were approximately equal. RESULTS: There was a significant quadratic interaction between age and gender on last month NSSI prevalence (p = 0.025): NSSI was more common in females ages 16-19, but there were no significant gender differences at younger/older ages. General distress partially mediated the effects of age and gender on NSSI. The association between general distress and NSSI was not significantly moderated by age, gender nor their interactions. CONCLUSIONS: Gender difference in NSSI is not a static gap, but evolves across time, widening in mid-adolescence and disappearing by early adulthood. Part of the reason for that gender gap being present at those ages is the increase levels of distress in young women at those ages. There was no evidence that the effects of general distress on NSSI differed by age/gender.
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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 | 0.005 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".