The BEACON Study: Protocol for a cluster randomized controlled trial of a service to deliver smartphone-assisted problem-solving therapy compared to usual care in men who present with intentional self-harm to Emergency Departments in Ontario
Bibliographic record
Abstract
Abstract Background Patients who present to Emergency Departments (ED) after intentional self-harm receive variable levels care in Ontario. Many are not assessed by a mental health professional following discharge from ED and do not receive psychological services available in the community as many of these services are not covered by the provincial health insurance. Patients who present with intentional self-harm to hospital are more likely to die by suicide and premature death by other means compared to the general population. This risk is elevated in men, who represent two-thirds of those who die by suicide in Ontario. One way of potentially addressing this gap is to offer problem-solving therapy (PST) designed specifically for men, facilitated by the use of a patient facing smartphone application and a clinician facing dashboard. This attempts to blend the use of face to face therapy and technology to create an effective intervention after self-harm.Methods This is a pragmatic, multicentre pre- and post-design cluster randomized controlled trial (cRCT) comparing the provision of a suicide prevention intervention to usual care, in men who present to the ED with self-harm. The study intervention is composed of: 1) staff education; 2) resource materials for men who present to the ED with self-harm; and, 3) the option to refer patients to a blended PST service for the treatment of self-harm. The primary outcome to be assessed is a composite of the incidence of suicides and/or re-presentations to any ED in Ontario for self-harm in the year after presentation with self-harm. Secondary outcome measures include: total number of suicides; re-presentations to any ED in Ontario for the repetition of self-harm; re-presentations to any ED in Ontario for any reason; other health system use including use of primary care and hospital outpatient appointments; mortality not related to suicide; and, health system costs over one year. All outcomes will be measured from provincial health administrative databases available at the Institute for Clinical and Evaluative Sciences (IC/ES).
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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 | 0.033 | 0.032 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.079 | 0.010 |
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".