Psychosis 101: evaluating a training programme for northern and remote youth mental health service providers
Bibliographic record
Abstract
BACKGROUND: Most of the early psychosis intervention (EPI) training has focused on family physicians participants. In Northern Ontario, there is a shortage of primary care. This paper will present evaluation results of a pilot training programme for rural and remote youth mental health service providers. METHOD: A mixed methods approach was used. We evaluated a 2-day workshop about EPI for non-medical mental health workers delivered onsite and simultaneously by videoconferencing. There were 19 participants across four agencies. Seven were onsite and 12 were offsite. Participants' knowledge was measured using a validated questionnaire at pre-intervention and at 3-, 6- and 9-month follow up. A repeated measures ANOVA was used to evaluate knowledge acquisition between the two modes of training. At 6 months, focus group interviews were conducted to explore their experiences of the mode of intervention delivery and evaluation. Emerging themes were iteratively derived through a series of discussions involving independent coders. RESULTS: Only 15 complete datasets were available of the 19 original participants. Differences in knowledge acquisition between the two groups did not reach statistical difference. Six-month focus group data indicated that participants improved their relationship with EPI services and they were part of a strengthened network with other providers in the region. Post-intervention, the accuracy of referrals from participating agencies increased dramatically, with an increase in proportion of referrals who were eligible for EPI services. The follow-up process engaged participants in learning and re-engaged them with the material taught during the training session. CONCLUSIONS: The results about developing service partnerships and relationship with specialist services are encouraging for policy and service decision-makers to address mental health service needs in northern and remote areas.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.000 |
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".