Development, Implementation, and Formative Evaluation of Pre-licensure Workshops Using Participatory Action Research to Facilitate Interprofessional, Client-Centred Mental Healthcare
Bibliographic record
Abstract
Background: This study presents a formative evaluation of nine pre-licensure workshops to educate on interprofessional, client-centred mental healthcare. The workshops, informed by the conceptual framework of Orchard, Curran, and Kabene had two key objectives: to stimulate networking and to socialize healthcare providers in working together.Methods and Findings: A participatory action research (PAR) methodology was used for workshop planning and evaluation. Descriptive surveys and feedback forms using closed- and open-ended questions were used to examine whether the intended population was reached, to determine participant satisfaction, and to investigate to what level program objectives had been implemented. Students (625) from different disciplines attended two-hour after-class workshops. The results indicated that students were interested in learning about interprofessionalism and satisfied in the knowledge, attitude, and skills (practice) they received from the workshops. Participants indicated that they had or intended to use some of their learning about interprofessional practice. Key successful approaches, such as the partnership with psychiatric consumers, were incorporated into later workshop series.Conclusions: The workshops demonstrated that interprofessional workshops can be one training component for pre-licensure students and can increase academic interest in interprofessional education.
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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 | 0.082 | 0.094 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".