Clinical usefulness of brief screening tool for activating weight management discussions in primary cARE (AWARE): A nationwide mixed methods pilot study
Bibliographic record
Abstract
OBJECTIVE: The Edmonton Obesity Staging System (EOSS) is based on weight related health complications among individuals with overweight and obesity requiring clinical intervention. We aimed to assess the clinical usefulness of a new screening tool based on the EOSS for activating weight management discussions in general practice. METHODS: We enrolled five General Practitioners (GPs) and 25 of their patients located nationwide in metropolitan areas of Australia to test the feasibility, acceptability, and accuracy of the new 'EOSS-2 Risk Tool', using cross-sectional and qualitative study designs. Diagnostic accuracy of the tool for the presence of EOSS ≥2 criteria was based on clinical information collected prospectively. To assess feasibility and applicability, we explored the views of GP and patient participants by thematic analysis of transcribed verbatim and de-identified data collected by semi-structured telephone interviews. RESULTS: Nineteen (76%) patients were aged ≥45 years, five (20%) were male, and 20 (80%) were classified with obesity. All 25 patients screened positive for EOSS ≥2 criteria by the tool. Interviews with patients continued until data saturation was reached resulting in a total of 23 interviews. Our thematic analysis revealed five themes: GP recognition of obesity as a health priority (GPs expressed strong interest in and understanding of its importance as a health priority); obesity stigma (GPs reported the tool helped them initiate health based and non-judgmental conversations with their patients); patient health literacy (GPs and patients reported increased awareness and understanding of weight related health risks), patient motivation for self-management (GPs and patients reported the tool helped focus on self-management of weight related complications), and applicability and scalability (GPs stated it was easy to use, relevant to a range of their patient groups, and scalable if integrated into existing patient management systems). CONCLUSION: The EOSS-2 Risk Tool is potentially clinically useful for activating weight management discussions in general practice. Further research is required to assess feasibility and applicability.
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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 | 0.024 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".