Think Aloud Testing of a Smartphone App for Lifestyle Change Among Persons at Risk of Type 2 Diabetes: Usability Study
Bibliographic record
Abstract
BACKGROUND: Type 2 diabetes mellitus (DM2) is a leading cause of morbidity and mortality worldwide and is considered a global epidemic. Despite the growing evidence on the effectiveness of mobile health interventions in the management of DM2, the evidence on the effect of mobile health interventions in prevention of DM2 is sparse. Therefore, we have developed an app aiming to promote initiation of behavioral change and adherence to healthy behavior. Before commencing a small-scale randomized controlled trial to assess the feasibility of using an app for initiation and adherence of healthy behavior in people at risk of DM2, testing the usability of the app in the target population is warranted. OBJECTIVE: The aim of this study was to assess the usability of an app among people at risk of DM2. METHODS: A qualitative study with the use of a think aloud (TA) procedure was conducted from April to November 2022. The TA procedure consisted of 10 problem-solving tasks and a semistructured interview which was carried out after the tasks. These interviews served to gain more in-depth knowledge of the users experience of the problem-solving tasks. The TA-sessions and the postactivity interviews were recorded and transcribed verbatim, and the data were coded and analyzed following the principles of thematic analysis. RESULTS: In total, 7 people at risk of DM2 with a median age of 66 (range 41-75) years participated in this study. The analysis resulted in the following themes: (1) user interface design; and (2) suggestions for improvements of the functionality of the app. CONCLUSIONS: Overall, the participants were satisfied with the usability of the app. Through the TA-sessions, real time perspective on the appeal, relevance, and utility of the app were gained. Only minor changes to the functionality of the prototype app were reported as necessary to improve the usability of the app. Points of guidance from the participants in this study have been adopted and incorporated into the final design of the app now being assessed for feasibility in a small-scale randomized controlled trial.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".