Evaluating a motivational interviewing training for facilitators of a prediabetes prevention program
Bibliographic record
Abstract
Small Steps for Big Changes (SSBC) is an evidence-based counselling lifestyle program for individuals with prediabetes. The program uses motivational interviewing (MI), a client-centered counselling approach with demonstrated potential to facilitate behaviour change and maintenance. All SSBC facilitators take part in MI training prior to program facilitation. The ~24-hour MI training includes a 2-day workshop, shadowing, reverse shadowing and feedback during the SSBC sessions. The study purpose was to ask the SSBC facilitators to identify barriers and provide feedback on the MI training and their experiencing with using MI when facilitating the SSBC program. Semi-structured interviews were conducted with seven facilitators 6-months after their initial MI training workshop. Interviews were analyzed using thematic inductive analysis. The MI training was well received, and the facilitators felt ready to use the MI skills to independently facilitate the SBCC program. Facilitators valued the shadowing, reverse shadowing, and debriefing as beneficial and practical MI experiences. Many facilitators believed that MI was a helpful counselling style conducive to their clients' behaviour change. Facilitators valued the program meetings and informal feedback provided throughout their time as a facilitator for SSBC. Suggestions included offering booster sessions for MI training and receiving intermittent feedback on MI skills to help maintain MI skills over time. Results from this evaluation will be used to optimize SSBC and improve maintenance of MI skills overtime. An optimized training program may increase the MI skills of facilitators, which has the potential to impact their clients' success in the SSBC program in the future.
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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) | 0.001 | 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".