The Usability of Diabetes MAP: A Web-delivered Intervention for Improving Medication Adherence
Bibliographic record
Abstract
BACKGROUND: Web-delivered interventions are a feasible approach to health promotion. However, if a website is poorly designed, difficult to navigate, and has technical bugs, it will not be used as intended. Usability testing prior to evaluating a website's benefits can identify barriers to user engagement and maximize future use. OBJECTIVE: We developed a Web-delivered intervention called Diabetes Medication Adherence Promotion (Diabetes MAP) and used a mixed-methods approach to test its usability prior to evaluating its efficacy on medication adherence and glycemic control in a randomized controlled trial. METHODS: We recruited English-speaking adults with type 2 diabetes mellitus (T2DM) from an academic medical center who were prescribed diabetes medications. A trained research assistant administered a baseline survey, collected medical record information, and instructed participants on how to access Diabetes MAP. Participants were asked to use the site independently for 2 weeks and to provide survey and/or focus group feedback on their experience. We analyzed survey data descriptively and qualitative data thematically to identify participants' favorable and unfavorable experiences, characterize usability concerns, and solicit recommendations for improving Diabetes MAP. RESULTS: Enrolled participants (N=32) were an average of 51.7 ± 11.8 years old, 66% (21/32) female, 60% (19/32) non-Hispanic White, 88% (28/32) had more than 12 years of education, half had household incomes over $50,000, and 78% (25/32) were privately insured. Average duration of diagnosed diabetes was 7.8 ± 6.3 years, average A1c was 7.4 ± 2.0, and 38% (12/32) were prescribed insulin. Of enrolled participants, 91% (29/32) provided survey and/or focus group feedback about Diabetes MAP. On the survey, participants agreed website information was clear and easy to understand, but in focus groups they reported navigational challenges and difficulty overcoming user errors (eg, entering data in an unspecified format). Participants also reported difficulty accessing the site and, once accessed, using all of its features. Participants recommended improving the site's user interface to facilitate quick, efficient access to all features and content. CONCLUSIONS: Adults with T2DM rated the Diabetes MAP website favorably on surveys, but focus groups gave more in-depth feedback on the user experience (eg, difficulty accessing the site, maximizing all of the site's features and content, and recovering from errors). Appropriate usability testing methods ensure Web-delivered interventions work as intended and any benefits are not diminished by usability challenges.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".