A Rubric to Assess the Design and Intervention Quality of Randomized Controlled Trials in Health and Wellness Coaching
Why this work is in the frame
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Bibliographic record
Abstract
Objective: To collect health and wellness coaching (HWC) literature related to treatment of obesity and Type 2 Diabetes (T2D) for systematic assessment using a novel rubric. Data Source: Pubmed, CINAHL, and PsychInfo. Study Inclusion and Exclusion: Given 282 articles retrieved, only randomized and controlled trials meeting a HWC criteria-based definition were included; studies with intervention <4 months or <4 sessions were excluded. Data Extraction: Rubric assessment required details of two theoretical frameworks (i.e., study design and HWC intervention design) be extracted from each included paper. Data Synthesis: Data were derived from a 28-item rubric querying items such as sampling characteristics, statistical methods, coach characteristics, HWC strategy, and intervention fidelity. Results: 29 articles were reviewed. Inter-rater rubric scoring yielded high intraclass correlation (r = .85). Rubric assessment of HWC literature resulted in moderate scores (56.7%), with study design scoring higher than intervention design; within intervention design, T2D studies scored higher than obesity. Conclusions: A novel research design rubric is presented and successfully applied to assess HWC research related to treatment of obesity and T2D. Most studies reported beneficial clinical findings; however, rubric results revealed moderate scores for study and intervention design. Implications for future HWC research are discussed.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
| gpt | Metaresearch Domain: Methods · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | high |
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 | 0.328 | 0.090 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.021 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it