Design and Usability Evaluation of Social Mobile Diabetes Management System in the Gulf Region
Bibliographic record
Abstract
BACKGROUND: The prevalence of diabetes in the Gulf States is one of the highest globally. It is estimated that 20% of the population in the region has been diagnosed with diabetes and according to the International Diabetes Federation (IDF), five of the IDF's "top 10" countries for diabetes prevalence in 2011 and projected for 2030 are in this region. In recent years, there have been an increasing number of clinical studies advocating the use of mobile phone technology for diabetes self-management with improved clinical outcomes. However, there are few studies to date addressing the application of mobile diabetes management in the Gulf region, particularly in the Kingdom of Saudi Arabia (KSA), where there is exponential increase in mobile phone usage and access to social networking. OBJECTIVE: The objective of this paper is to present the design and development of a new mobile health system for social behavioral change and management tailored for Saudi patients with diabetes called Saudi Arabia Networking for Aiding Diabetes (SANAD). A usability study for the SANAD system is presented to validate the acceptability of using mobile technologies among patients with diabetes in the KSA and the Gulf region. METHODS: The SANAD system was developed using mobile phone technology with diabetes management and social networking modules. For the usability study the Questionnaire for User Interaction Satisfaction was used to evaluate the usability aspect of the SANAD system. A total of 33 users with type 2 diabetes participated in the study. RESULTS: The key modules of the SANAD system consist of (1) a mobile diabetes management module; (2) a social networking module; and (3) a cognitive behavioral therapy module for behavioral change issues. The preliminary results of the usability study indicated general acceptance of the patients in using the system with higher usability rating in patients with type 2 diabetes. CONCLUSIONS: We found that the acceptability of the system was high among Saudi patients with diabetes, and ongoing work in this research area is underway to conduct a clinical pilot study in the KSA for patients with type 2 diabetes. The wide deployment of such a system is timely and required in the Gulf region due to the wide use of mobile phones and social networking mediums.
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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 | 0.028 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".