Modified Delphi Process to Identify Research Priorities and Measures for Adult Lifestyle Programs to Address Type 2 Diabetes and Other Cardiometabolic Risk Conditions
Bibliographic record
Abstract
OBJECTIVES: Clinical and community guidelines recommend lifestyle (i.e. diet and physical activity) interventions for cardiometabolic conditions (including type 2 diabetes), yet current evidence suggests limited and variable services in primary care and public health settings. New implementation research studies are needed to ensure maximal effectiveness, equity and efficiency across all population subgroups and within the context of health systems. Such work will benefit from use of similar core measures and outcome indicators across studies. This Delphi process was undertaken by a new interdisciplinary volunteer researcher network to identify research priorities and core measures for such studies. METHODS: Interested network members completed 2 rounds of a modified Delphi process delivered through online questionnaire and teleconferences. Consensus was defined as the median and interquartile range within the top third of a 9-point scale. RESULTS: Twenty-five of 53 (47%) members and 18 (34%) participants completed the round 1 and round 2 surveys, respectively. Of 22 possible research priorities, 4 were rated high priority with consensus, including evaluating the efficacy and effectiveness of interventions in place, improving existing interventions for sustainability and clinical and public health research to advance existing knowledge to develop new capacities. Only 15 of the 93 measures and indicators proposed achieved similar consensus. CONCLUSIONS: This first effort confirms broad agreement on research priorities and limited agreement on core indicators/measures. The results provide a starting point for further development of common measures for implementation research in lifestyle studies addressing cardiometabolic conditions.
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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 | 0.150 | 0.130 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".