An examination of nonsuicidal self-injury disclosures in a high-risk university sample
Bibliographic record
Abstract
Objective: There is a lack of research examining factors that promote the disclosure of nonsuicidal self-injury (NSSI) among post-secondary students. However, elucidating which factors facilitate disclosures among students – particularly students with high risk NSSI – is important given that disclosure may facilitate access to care. Methods: Participants included 149 post-secondary students with recent NSSI (81% women, Mage = 19.96) who reported on their disclosures, as well as several potential correlates of disclosure. Results: Eighty-seven percent of respondents had disclosed NSSI, often to several informal sources. Students with higher willingness to disclose personally distressing information, perceived levels of social support, stressful experiences, and frequency of NSSI engagement were more likely to disclose NSSI to more types of sources and more unique individuals. Conclusion: Results suggest that disclosure is an ongoing process rather than a single event, and underscore the importance of teaching effective NSSI disclosure responses to campus community members.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".