“Learning with each other, about each other”: Interdisciplinary learning among genetic counseling students and clinical health psychology residents
Bibliographic record
Abstract
Interprofessional collaborative healthcare is known to improve provider satisfaction and retention, as well as patient safety and quality of care. The specific knowledge, skills, and attitudes required to work in these environments are best taught interprofessionally. Despite having considerable overlap in training, orientation, and populations served, it is rare for trainees from genetic counseling and clinical health psychology to interact and learn together. In 2017, we developed an innovative week-long clinical health psychology rotation for students in the University of Manitoba MSc in Genetic Counselling Program, which aims to enrich psychotherapeutic/counseling knowledge and skills, as well as gain familiarity with the work of clinical psychologists. This rotation incorporates didactic teaching, observation, and structured reflection. Didactic teaching includes topics such as psychological assessment, adaptation to life-altering news, skills for managing intense emotional responses, and counseling for change. Observations of clinical health psychologists and clinical health psychology residents occur in a range of health settings. Structured reflection is practiced in both oral and written formats. Finally, both groups of trainees participate in an interprofessional case seminar series. Feedback from this experience has been very promising, and it was identified as a strength in the program's accreditation review. Adaptations over time include refining the clinical exposures to increase breadth and relevance, increasing the contact between the trainees from the two professions and enhancing the case seminar series to be more learner-driven and to focus on explicit interprofessional skills and themes. In addition to expected results, this rotation has led to some unanticipated findings, including an emergent emphasis on the social determinants of health and the need to work collaboratively for systemic change. Further, psychology residents have identified that it benefits them to learn more about genetic counseling and expressed interest in potential reciprocal learning opportunities in genetics clinics.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".