Examining interprofessional collaboration, patient care, student training, and the effectiveness of individual cognitive behavioural therapy provided at an urban family health team
Bibliographic record
Abstract
Mental illness is highly prevalent in Canada and costs the Canadian economy and health care system billions each year. Yet, Canadians generally do not have access to evidence-based psychotherapy that is considered a frontline treatment in countries such as the United Kingdom and Australia. Family health teams (FHTs) have been proposed as a way to improve access to mental health treatment. Yet, limited research has been conducted on the inclusion of Psychology into FHTs or the training of graduate students in this emerging field. To address this research gap, the novel treatment delivery and student training model at the Ryerson University Psychology Training Clinic (PTC) and St. Michael’s Hospital’s FHTs was examined in two studies. First, a pilot study examined the effectiveness of individual CBT provided by graduate students to patients with a primary anxiety or depressive disorder. Eighty percent of participants either no longer met diagnostic criteria for their primary mental disorder or were in partial remission. They experienced a significant reduction in symptoms of overall mental health, depression, and anxiety. As well, participants expressed a high level of satisfaction with the services received and reported having a positive working alliance with their student psychotherapist. Results indicate that student-delivered psychotherapy in a FHT setting is an effective treatment delivery model. Second, a two-part mixed methods study was conducted evaluating perspectives on patient care, interprofessionalism, and student training through an online study and individual interviews with health care providers, clinical supervisors, graduate students, and patients. Results from this study indicate that the PTC was a positive addition to the FHTs that improved access and provided patients with high quality mental health services. Generally, high levels of interprofessionalism were reported, though some drawbacks and individual differences were noted. The PTC was described as a valuable training experience. The importance of supervision and specific interprofessional and FHT training was highlighted. Findings from these studies represent a worthwhile contribution to the FHT and primary care psychology literature. Furthermore, the inclusion of Psychology and student trainees into a FHT appears to be a successful, viable option to improve access to effective mental health services.
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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 | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".