Adapting a Text Messaging Intervention to Improve Diabetes Medication Adherence in a Spanish-Speaking Population: Qualitative Study
Bibliographic record
Abstract
Background: Latino adults with type 2 diabetes (T2D) have higher rates of diabetes medication nonadherence than non-Hispanic White adults. REACH (Rapid Encouragement/Education And Communications for Health) is a text message platform based on the information-motivation-behavioral skills model that addresses barriers to adherence and was shown to improve adherence and glycated hemoglobin (HbA1c) levels, but it is only available in English. Objective: This study aimed to report the multiphase, stakeholder-driven adaptation of the REACH barriers to diabetes medication adherence content to a Latino population (REACH-Español). Methods: This was a qualitative study using focus groups. We identified potentially eligible patients (≥18 y old, Latino ethnicity, Spanish-language preference, and T2D diagnosis) using a Mass General Brigham Hospital query. Eligible patients were invited to participate in a focus group conducted in Spanish between April 13 and November 9, 2023. A total of 5 focus groups were conducted. Focus groups 1-3 centered on ranking 40 barriers to diabetes medication adherence (derived from REACH and the extant literature), whereas focus groups 4-5 centered on translation and cultural modifications of the original SMS text message content associated with each of the REACH barriers. Barriers were mapped onto information-motivation-behavioral constructs. We used descriptive statistics to summarize participant characteristics. Focus groups were audio-recorded, professionally transcribed, and analyzed with thematic content analysis using NVivo (Lumivero). Results: In total, 22 participants attended the focus groups. The mean (SD) age was 63.2 (11) years, 55% (n=10/22) were female, and the mean HbA1c level was 8.5%. All participants were born in Latin America or the Caribbean and spoke Spanish as their preferred language, and 54.5% (12/22) had completed middle-school education or less. Among the top 10 ranked barriers, 50% (n=5) corresponded to information, 20% (n=2) to social motivation, 20% (n=2) to behavioral skills, and 10% (n=1) to personal motivation. Personal motivation barriers (medication burden and fear of side effects) and behavioral skills (forgetting to take medication) emerged as important themes in the focus groups. Conclusions: A stakeholder-driven approach to intervention adaptation identified and prioritized relevant barriers to diabetes medication adherence among Latino adults with T2D and facilitated the adaptation of the REACH platform to a Spanish-speaking population.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".