Sex Differences in the Global Prevalence of Nonsuicidal Self-Injury in Adolescents
Bibliographic record
Abstract
Importance: Nonsuicidal self-injury (NSSI) is a strong predictor of suicide attempts. The prevalence of NSSI has been increasing among female adolescents in North America and Europe, but less is known about trends in other geographical regions. Objective: To examine sex differences in the prevalence of NSSI among adolescents within and between geographical regions. Data Sources: MEDLINE and PsycINFO were searched using the keywords adolescents, self-injury, sex factors, and synonyms for articles published in English between January 1, 2000, and May 10, 2022. Study Selection: Studies were included if they presented original data (any study design), included adolescents aged 10 to 19 years, reported results stratified by sex, and explicitly defined self-injury as behaviors occurring without suicidal intent. Data Extraction and Synthesis: This meta-analysis was registered with PROSPERO and conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Articles were assessed for quality by 2 independent coders (F.M. and J.A.). A random-effects model was used to calculate prevalence. Data were analyzed from July 2022 to April 2023. Main Outcomes and Measures: The prevalence of NSSI in male and female adolescents within and between regions was the main outcome. Odds ratios (OR) with 95% CIs were calculated for community samples. Results: Eight hundred and two studies were screened, and 38 were included (266 491 participants). Across 17 countries, the pooled prevalence of NSSI was 17.7% (female:male OR, 1.60; 95% CI, 1.29-1.98). NSSI was twice as prevalent among female adolescents compared with male adolescents in North America (OR, 2.49; 95% CI, 2.16-2.86) and Europe (OR, 2.08; 95% CI, 1.69-2.58), but not in Asia (OR, 1.00; 95% CI, 0.71-1.41). Conclusions and Relevance: In this meta-analysis of sex differences in global prevalence of NSSI, the female predominance of NSSI observed among adolescents in North America and Europe aligned with rising rates of suicide in these populations. The comparable prevalence of NSSI among male and female adolescents in Asia also aligned with the lower male-to-female suicide ratio compared with other countries. More research is needed to characterize regional (and potentially cultural) sex differences among adolescents with NSSI to prevent and treat the behavior and to understand the possible interplay with corresponding regional trends in suicide.
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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 | 0.016 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.014 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".