Digital mental health intervention for schizophrenia spectrum and psychotic disorders: Protocol for a pragmatic feasibility study of Horyzons-Canada
Bibliographic record
Abstract
Background: Schizophrenia spectrum and other psychotic disorders (SSPD) are among the most debilitating of all mental disorders. While the evidence for psychosocial interventions such as cognitive behavioral therapy and peer support has significantly improved, access to these services remains limited. This paper describes a protocol for a pragmatic feasibility study of a digital mental health intervention (HoryzonsCa) that provides access to evidence-based psychosocial interventions, social networking, and clinical and peer support services through a secured, web-based platform for adults diagnosed with SSPD. Objective: The objectives are: (1) Adapt and translate HoryzonsCa for implementation in English and French; (2) Develop an implementation and training strategy; (3) Assess the acceptability, safety, and demand of HoryzonsCa; (4) Assess clinical outcomes and perceived impacts; (5) Examine the experiences and process of adapting and implementing HoryzonsCa; (6) Explore the role of sociocultural and demographic factors on HoryzonsCa outcomes and implementation. Methods: This feasibility study will use a single-group, pre-post, mixed-methods (QUAN-QUAL convergent) research design, with assessments at baseline and 12 weeks. The study aims to recruit 100 individuals (ages 18-50) diagnosed with SSPD from two healthcare settings in Canada. Data collection includes interview-based psychometric measures, self-reports, focus groups, and interviews with participants. The study will also collect qualitative data from moderators and the research team, and will be conducted entirely remotely. Conclusions: This study has been prospectively registered and is underway. It will provide timely information on the feasibility and potential impacts of using digital mental health services for individuals with chronic mental health conditions. Trial Registration: ISRCTN12561259; https://doi.org/10.1186/ISRCTN12561259 (250/max 250 words).
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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 | 0.044 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.060 | 0.006 |
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".