Design and Methods for a Comparative Effectiveness Pilot Study: Virtual World vs. Face-to-Face Diabetes Self-Management
Bibliographic record
Abstract
BACKGROUND: Type 2 diabetes (diabetes) is a serious threat to public health in the United States and disproportionally affects many racial/ethnic minority groups, including African Americans. Limited access to treatment and high attrition rates further contribute to health disparities in diabetes-related morbidity and mortality among minorities. Greater opportunities for increasing access and decreasing barriers to treatment are needed. Technology-based interventions have potential for accomplishing this goal but evidence of feasibility and potential effectiveness is lacking, especially for populations that traditionally have limited educational attainment and low computer literacy. OBJECTIVE: This paper describes the design and methods of a pilot randomized clinical trial that will compare the feasibility and potential efficacy of delivering a diabetes self-management intervention via a virtual world vs. a face-to-face format. METHODS: Study participants (n=100) will be African American women with uncontrolled type 2 diabetes recruited from primary care practices and affiliated health centers at a large safety net hospital in Massachusetts. Participants will be randomized into a virtual world-based (VW) intervention condition or a face-to-face control condition. Both conditions provide the same theory-based curriculum and equivalent exposure to the self-management program (eight group sessions), and both will be delivered by a single intervention team (a dietitian and a diabetes educator). Assessments will be conducted at baseline and 4 months. Feasibility will be determined by evaluating the degree to which participants engage in the VW-based intervention compared to face to face (number of sessions completed). Potential efficacy will be determined by comparing change in physiological (glycemic control) and behavioral (self-reported dietary intake, physical activity, blood glucose self-monitoring, and medication adherence) outcomes between the experimental and control groups. RESULTS: The primary outcomes of interest are feasibility of the VW intervention and its potential efficacy on glucose control and diabetes self-management behaviors, compared to the face-to-face condition. Analysis will use a two-sample Kolmogorov-Smirnov test for changes in variable distribution. P values will be calculated using binomial tests for proportions and t tests for continuous variables. CONCLUSIONS: If the intervention is found to be feasible and promising, it will be tested in a larger RCT.
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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 | 0.064 | 0.071 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.042 | 0.004 |
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".