The Web-Based Recognise and Respond Gatekeeper Training Program: Noninferiority Randomized Trial
Bibliographic record
Abstract
Background: Gatekeeper training teaches community members to identify individuals at risk of suicide and assist them with help-seeking. A new online program, Recognise and Respond (R&R), was developed to address the need for a program specific to the Australian context, created in consultation with clinicians, researchers, and people with a lived experience of suicide. Objective: This study aimed to evaluate whether the R&R gatekeeper training is noninferior to the established Question, Persuade, Refer (QPR) online program, in improving confidence to identify and support individuals experiencing suicidal thoughts. Secondary objectives examined the short- and medium-term effects of R&R on attitudes toward suicide prevention and knowledge of appropriate responses to signs of suicide. Methods: A total of 524 participants were enrolled at baseline and were then randomized to receive access to either R&R (n=263) or QPR (n=261). The primary outcome-gatekeeper confidence in identifying and supporting an individual experiencing suicidal thoughts-was assessed using a noninferiority framework. Secondary outcomes, including attitudes toward suicide prevention and knowledge of appropriate responses to signs of suicide, were assessed using superiority testing. Outcomes were assessed via online surveys at baseline, postintervention, and the 3-month follow-up. The trial was conducted entirely online, with no face-to-face contact with participants. Data were analyzed using mixed effects linear models. Results: Participants in both groups reported significant improvements in confidence across time indicating noninferiority of the R&R program. Both groups showed significant improvements on attitudes and knowledge scores at postintervention and the 3-month follow-up, 3. to baseline. Improvement in attitude scores between baseline and postintervention and follow-up were greater for the QPR group compared to the R&R group. Gains at postintervention were maintained at follow-up for both groups considering all outcomes. There were no other between-group differences. Conclusions: The findings demonstrate that R&R is as effective as QPR online in improving gatekeeper confidence to identify and support someone having thoughts of 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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".