Introducing problem-solving therapy training into Southwestern Ontario
Bibliographic record
Abstract
Purpose The purpose of this paper is to introduce problem-solving therapy (PST) training to an Ontario health region. The aim of this pilot project was to increase psychotherapy access by training community-based outreach clinicians and to understand their satisfaction with the training program as well as their confidence in applying the principles of PST. Design/methodology/approach Clinicians from Southwestern Ontario who provide community-based mental health outreach services to older adults were invited to participate in this training opportunity. Selection was based on their existing client base, the geographic area they served, and self-reported foreseeable PST training benefits. Selected individuals received an eight-hour in-person didactic session, eight one-hour case-based learning opportunities, and individual case supervision. Acquired knowledge, perceived confidence in their skills, level of adherence to PST principles in clinical interactions, and satisfaction with the training program itself were measured. Findings Of the 36 applicants, eight trainees were selected. All trainees completed their training and seven were successfully certified in PST. Trainees indicated a high level of satisfaction with the training experience. According to the evaluation tools, trainee confidence in providing PST significantly increased, though there was no statistically significant change in knowledge. Originality/value This study provides the first evidence that PST can be introduced within a regional geriatric mental health service in Canada. The training involved both in-person training, web-based conferencing sessions and a supervisory component. The training lasted 16 hours and resulted in staff skill development in an evidence-based psychotherapy modality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".