Continuing Education to Go: Capacity Building in Psychotherapies for Front-Line Mental Health Workers in Underserviced Communities
Bibliographic record
Abstract
OBJECTIVE: To address the gaps between need and access, and between treatment guidelines and their implementation for mental illness, through capacity building of front-line health workers. METHODS: Following a learning needs assessment, work-based continuing education courses in evidence-supported psychotherapies were developed for front-line workers in underserviced community settings. The 5-hour courses on the fundamentals of cognitive-behavioural therapy, interpersonal psychotherapy, motivational interviewing, and dialectical behaviour therapy each included videotaped captioned simulations, interactive lesson plans, and clinical practice behaviour reminders. Two courses, sequentially offered in 7 underserviced settings, were subjected to a mixed methods evaluation. Ninety-three nonmedical front-line workers enrolled in the program. Repeated measures analysis of variance was used to assess pre- and postintervention changes in knowledge and self-efficacy. Qualitative data from 5 semistructured focus groups with 25 participants were also analyzed. RESULTS: Significant pre- and postintervention changes in knowledge (P < 0.001) were found in course completers. Counselling self-efficacy improved in participants who took the first course offered (P = 0.001). Dropouts were much less frequent in peer-led, small-group learning than in a self-directed format. Qualitative analysis revealed improved confidence, morale, self-reported practice behaviour changes, and increased comfort in working with difficult clients. CONCLUSION: This work-based, multimodal, interactive, interprofessional curriculum for knowledge translation of psychotherapeutic techniques is feasible and helpful. A peer-led group format is preferred over self-directed learning. Its application can build capacity of front-line health workers in helping patients who suffer from common mental disorders.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".