5<scp>A</scp>s <scp>T</scp>eam obesity intervention in primary care: development and evaluation of shared decision‐making weight management tools
Bibliographic record
Abstract
Despite several clinical practice guidelines, there remains a considerable gap in prevention and management of obesity in primary care. To address the need for changing provider behaviour, a randomized controlled trial with convergent mixed method evaluation, the 5As Team (5AsT) study, was conducted. As part of the 5AsT intervention, the 5AsT tool kit was developed. This paper describes the development process and evaluation of these tools. Tools were co-developed by the multidisciplinary research team and the 5AsT, which included registered nurses/nurse practitioners (n = 15), mental health workers (n = 7) and registered dieticians (n = 7), who were previously randomized to the 5AsT intervention group at a primary care network in Edmonton, Alberta, Canada. The 5AsT tool development occurred through a practice/implementation-oriented, need-based, iterative process during learning collaborative sessions of the 5AsT intervention. Feedback during tool development was received through field notes and final provider evaluation was carried out through anonymous questionnaires. Twelve tools were co-developed with 5AsT. All tools were evaluated as either 'most useful' or 'moderately useful' in primary care practice by the 5AsT. Four key findings during 5AsT tool development were the need for: tools that were adaptive, tools to facilitate interdisciplinary practice, tools to help patients understand realistic expectations for weight loss and shared decision-making tools for goal setting and relapse prevention. The 5AsT tools are primary care tools which extend the utility of the 5As of obesity management framework in clinical practice.
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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 | 0.016 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".