How others respond to non‐suicidal <scp>self‐injury</scp> disclosure: A systematic review
Bibliographic record
Abstract
Abstract Non‐suicidal self‐injury (NSSI) is an increasing health concern. Despite the potential benefits of disclosing the behaviour, many decide not to do so because of the fear of negative social reactions. In this review, we examined the existing research on reported and perceived reactions to NSSI disclosure with the aim of identifying how an individual who discloses their NSSI perceives others' responses to this disclosure, with the ultimate goal of understanding how these reactions may impact those who disclose their NSSI. Among the initial 275 studies, 10 fit the inclusion criteria. Three studies reported perceived responses by individuals who had disclosed their NSSI; six studies examined self‐reported responses by others; one study focused on disclosures online. Individuals who disclosed their NSSI often received negative responses, which caused them to withdraw from seeking further help. On the other hand, recipients' reactions to NSSI disclosure varied based on NSSI characteristics such as its perceived cause and/or underlying motivation. Results highlight the importance of providing support rather than searching for the underlying drives of NSSI.
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".