Guidelines, Policies, and Recommendations for Responding to NSSI in Schools and Universities
Bibliographic record
Abstract
Abstract Nonsuicidal self-injury (NSSI; e.g., self-directed cutting, burning, or bruising without lethal intent) is a commonly occurring behavior among students in secondary and postsecondary school. Academic stressors, in addition to challenges associated with navigating adolescence and emerging adulthood, may contribute to heightened risk for NSSI among students. NSSI is associated with increased vulnerability for other mental health concerns and increased risk for suicidality, suggesting that providing early support and intervention for students who engage in NSSI is critically important. Despite the widespread prevalence of this behavior, students and staff often report feeling ill-equipped to respond and address NSSI in school-based contexts. The authors of this chapter, all members of the International Consortium on Self-injury in Educational Settings (ICSES), aim to provide the readers some guidelines and recommendations for NSSI policies in educational settings, due to the lack of research-informed policy guidelines and recommendations. Here, the authors underscore the importance of developing a school-based policy on NSSI to ensure consistent and effective identification, response, and support for students who self-injure. The authors describe the roles and responsibilities of each stakeholder (e.g., students, teachers, parents, administrators, and school mental health practitioners) in implementing a policy on NSSI. Finally, the authors provide an example of a policy specifically developed and piloted for a university in Brussels, to serve as a template that can be used across a variety of educational settings. The chapter concludes with several suggested resources and links for additional information on supporting students who self-injure in schools.
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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 | 0.174 | 0.288 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.021 | 0.022 |
| Open science | 0.014 | 0.015 |
| Research integrity | 0.046 | 0.026 |
| Insufficient payload (model declined to judge) | 0.018 | 0.011 |
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".