A Serious Game for Young People With First Episode Psychosis (OnTrack>The Game): Qualitative Findings of a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Several studies have shown the benefits of coordinated specialty care (CSC) for individuals with first episode psychosis; however, pathways to care are marred by lack of knowledge, stigma, and difficulties with treatment engagement. Serious games or video interventions may provide a way to address these factors. OBJECTIVE: This study focuses on qualitative results of a randomized controlled trial comparing OnTrack>The Game (OTG) with recovery videos (RVs) on engagement, stigma, empowerment, hope, recovery, and understanding of psychosis in clients receiving CSC. Clinicians are also interviewed regarding their perceptions of the interventions and suggestions for improvement. METHODS: A total of 16 clients aged 16-30 years, with first episode psychosis attending a CSC program in New York State, and 9 clinicians participated in the qualitative interviews. Interviews were analyzed using the rapid identification of themes from audio recordings method. RESULTS: For clients, themes included relatability of game content, an increased sense of hope and the possibility of recovery, decreased self-stigma and public stigma, increased understanding of the importance of social support, and increased empowerment in the OTG group. Clinicians had a preference for RV and provided suggestions for dissemination and implementation. CONCLUSIONS: Themes that may help inform future research in this area, particularly regarding dissemination and implementation of OTG and RV, emerged. TRIAL REGISTRATION: ClinicalTrials.gov NCT03390491; https://clinicaltrials.gov/ct2/show/NCT03390491.
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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 | 0.079 | 0.126 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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".