Collective knowledge: using a consensus conference approach to develop recommendations for physical activity and nutrition programs for persons with type 2 diabetes
Bibliographic record
Abstract
The purpose of this consensus conference was to have a lay panel of persons with type 2 diabetes (T2D) work in collaboration with an expert panel of diabetes professionals to develop strategies designed to improve dietary and physical activity adherence in persons with T2D. Lay panel participants were 15 people living with T2D. The seven experts had expertise in exercise management, cardiovascular risk factors, community-based lifestyle interventions, healthy weight strategies, the glycemic index, exercise motivation, and social, environmental and cultural interactions. All meetings were facilitated by a professional, neutral facilitator. During the conference each expert gave a 15-min presentation answering questions developed by the lay panel and all panel members worked to generate suggestions for programs and ways in which the needs of persons with T2D may be better met. A subgroup of the lay panel used the suggestions created from the conference to generate a final list of recommendations. Recommendations were categorized into (1) diagnosis/awareness (e.g., increasing awareness about T2D in the general public, need for lifelong self-monitoring post-diagnosis); (2) education for the person with diabetes (e.g., periodic "refresher" courses), professionals (e.g., regular interactions between researchers and persons with T2D so researchers better understand the needs of the affected population), and the community (e.g., support for families and employers); and (3) ongoing support (e.g., peer support groups). The recommendations from the conference can be used by researchers to design and evaluate physical activity and nutrition programs. The results can also be of use to policy makers and health promoters interested in increasing adherence to physical activity and nutrition guidelines among persons with T2D.
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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 | 0.294 | 0.300 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.014 | 0.006 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.008 | 0.020 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 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".