A Web-Based Training Program for School Staff to Respond to Self-Harm: Design and Development of the Supportive Response to Self-Harm Program
Bibliographic record
Abstract
BACKGROUND: Self-harm is common among adolescents and is a major public health concern. School staff may be the first adults to notice a young person's self-harm and are well placed to provide support or signpost students to help. However, school staff often report that they do not feel equipped or confident to support students. Despite the need, there is a lack of evidence-based training about self-harm for school staff. A web-based training program would provide schools with a flexible and cost-effective method of increasing staff knowledge, skills, and confidence in how to respond to students who self-harm. OBJECTIVE: The main objective of this study was to coproduce an evidence-based training program for school staff to improve their skills and confidence in responding to students who self-harm (Supportive Response to Self-Harm [SORTS]). This paper describes the design and development process of an initial prototype coproduced with stakeholders to ensure that the intervention meets their requirements. METHODS: Using a user-centered design and person-based approach, the SORTS prototype was informed by (1) a review of research literature, existing guidelines, and policies; (2) coproduction discussions with the technical provider and subject matter experts (mental health, education, and self-harm); (3) findings from focus groups with young people; and (4) coproduction workshops with school staff. Thematic analysis using the framework method was applied. RESULTS: Coproduction sessions with experts and the technical provider enabled us to produce a draft of the training content, a wireframe, and example high-fidelity user interface designs. Analysis of focus groups and workshops generated four key themes: (1) need for a training program; (2) acceptability, practicality, and implementation; (3) design, content, and navigation; and (4) adaptations and improvements. The findings showed that there is a clear need for a web-based training program about self-harm in schools, and the proposed program content and design were useful, practical, and acceptable. Consultations with stakeholders informed the iterative development of the prototype. CONCLUSIONS: SORTS is a web-based training program for school staff to appropriately respond to students who self-harm that is based on research evidence and developed in collaboration with stakeholders. The SORTS program will equip school staff with the skills and strategies to respond in a supportive way to students who self-harm and encourage schools to adopt a whole-school approach to self-harm. Further research is needed to complete the intervention development based on the feedback from this study and evaluate the program's effectiveness. If found to be effective, the SORTS program could be implemented in schools and other youth organizations.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".