Relationship Between Evidence Requirements, User Expectations, and Actual Experiences: Usability Evaluation of the Twazon Arabic Weight Loss App
Bibliographic record
Abstract
BACKGROUND: Saudi Arabia has faced a steady growth in the prevalence of obesity. The concurrent and ubiquitous use of mobile technology, such as smartphones and apps, provides an opportunity for the implementation of mHealth technology, a method for delivering behavioral interventions. Despite their effectiveness in promoting lifestyle and diet modification, culturally adapted weight loss apps and related interventions are lacking in Gulf Cooperation Council countries. OBJECTIVE: The objective of our study was to identify the relationship between adherence to evidence-informed practices, potential user expectations, and actual user experiences in order to enhance the understanding of the overall usability of the Twazon Arabic weight loss app. METHODS: In 2 previous studies, 39 Saudi women were recruited for focus group discussions and 240 Saudi women were recruited for an app-based weight loss intervention. Usability of the Twazon Arabic weight loss app was evaluated by analyzing the opinions and experiences of 26 participants who engaged with the Twazon app for 4 months; the System Usability Scale (SUS) and word clouds were used. The results were triangulated with potential user expectations obtained in the focus group discussion and with the findings from an Arabic app screening for evidence-informed practices. RESULTS: The average reported SUS score was 69.3. The most favored features were the calorie counter, step counter, and physical activity calorie counter. The features in need of improvement were the social network, notifications, and the Twazon Saudi Food Database. Twazon users preferred and found useful 7 of the 13 evidence-informed weight loss practices that were integrated into the features of the app. CONCLUSIONS: Triangulation identified the most notable relationship to be the disparity between user experience and 2 of the evidence-informed practices, namely a minimum weight loss goal of 0.5 to 1 kg/week and social support; no relationship was found between user expectations and evidence-informed weight loss practices. The overall usability of the Twazon Arabic weight loss app ranged between high marginal and acceptable, indicating that some improvements to the app should be considered for implementation in future app-based weight loss interventions of this kind.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".