Assessing the Fit of a Digitally Delivered National Diabetes Prevention Program Among Rural Living Adults: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Rural living adults are disproportionately affected by type 2 diabetes compared to their urban counterparts. The Centers for Disease Control and Prevention's National Diabetes Prevention Program (National DPP) is an evidence-based intervention that reduces the risk of type 2 diabetes through increased physical activity and modest weight loss, but overall reach remains limited, specifically in rural communities. OBJECTIVE: This qualitative study aimed to examine the fit of the National DPP delivered digitally using Zoom or Facebook to rural living adults at risk for type 2 diabetes. METHODS: Focus group scripts assessed the characteristics and perceptions of rural adults at risk for type 2 diabetes, infrastructure supports for implementation and sustainability, and external factors that could influence program fit. A reflexive thematic analysis was conducted separately on coded transcripts for each focus group. Themes were then deductively linked to the Practical, Robust Implementation and Sustainability Model domains. RESULTS: Two focus groups were conducted with 14 participants after participating in the National DPP for 6 months, delivered through Zoom (n=9) or Facebook (n=5). Participants highlighted positive relationships between Practical, Robust Implementation and Sustainability Model constructs related to participant characteristics (ie, value of health improvements, weight loss, and reduced medication dependence as primary motivators) and perceptions of compatibility (ie, content alignment with participant needs) as well as infrastructure (ie, digital platforms provided better access) with program success in reach and engagement. Conversely, both formats were negatively impacted by interruptions in internet connectivity. External factors, such as referral pathways from local health care providers, could improve program reach. When considering differences between implementation infrastructure, Zoom facilitated greater social engagement and accountability compared to Facebook. CONCLUSIONS: This study identified contextual factors influencing the fit of digitally delivering the National DPP to rural living adults, including opportunities for using existing connections and health motivations to help improve acceptability, while tailoring curriculum, modality, and technology may improve appropriateness for rural populations. TRIAL REGISTRATION: ClinicalTrials.gov NCT05387434; https://clinicaltrials.gov/study/NCT05387434.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".