Evaluation of a motivational interviewing informed workshop for trainees in a diabetes prevention program in the community
Bibliographic record
Abstract
Objectives: Utilizing Kirkpatrick's four-level model this study presents the evaluation of a two-day Motivational Interviewing (MI) informed workshop on trainee's satisfaction, MI-knowledge, MI-skills, and applying MI in a community-based diabetes prevention program. Methods: Four students provided feedback on the content of the MI-informed workshop. Seven other trainees took part in its evaluation. MI-skills were evaluated using a vignette (Helpfulness Response Questionnaire; HRQ) at pre- and post-workshop. The Motivational Interviewing Competency Assessment (MICA) was used to code trainee's audio recordings with clients from the diabetes prevention program. The MICA provides a total score for MI competency and scores on seven MI categories. Results: Average age was 24 years (SD = 2.8), 85% were women, and 57.2% had less than a bachelor degree. The workshop was perceived as highly satisfactory (M = 4.7, SD = 0.41, out of 5). MI-knowledge and MI-confidence increased from pre- to post-workshop (p < .001, ?2p= .95 and p = .003, ?2p = .79, respectively). As expected, the HRQ reflective statements increased relative to asking questions from pre- [R/OQ]=27/25 to post-workshop[R/OQ]=40/29. Despite the short training, 50% of the trainees' MI-skills were classified as client-centered (MICA ?3/5) on all MI categories, but the trainees did not reach overall level of MI competency (MICA ?8/10), with M = 5.8 (SD = .99). Conclusions: Consistent with previous research, this brief training improved MI-knowledge and MI-skills, but it was less effective for overall application of MI. Future work will integrate booster sessions to evaluate the addition of supervised practice on outcomes.Acknowledgments: This work was supported by a CIHR Foundation Grant (#333266), Michael Smith Foundation Health Research Scholar Award (#5917), and EI was supported by Michael Smith Foundation Health Research Postdoctoral Fellowship Award. We would like to thank the Centre for Collaboration, Motivation and Innovation for their expertise and support from the Ministry of Health.
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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 | 0.007 | 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 | 0.000 |
| 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".