C D Hoppe1,2, J E Cade1, M Carter1. 1. Nutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, Leeds, UK. 2. Department of Nutrition and Dietetics, King's College London, London, UK.
Abstract
BACKGROUND: Mobile applications (apps) could support diabetes management through dietary, weight and blood glucose self-monitoring, as well as by promoting behaviour change. The present study aimed to evaluate diabetes apps for content, functions and behaviour change techniques (BCTs). METHODS: Diabetes self-management apps for Android smartphones were searched for on the Google Play Store. Ten apps each from the following search terms were included; 'diabetes', 'diabetes type 1', 'diabetes type 2', 'gestational diabetes'. Apps were evaluated by being scored according to their number of functions and BCTs, price, and user rating. RESULTS: The mean (SD) number of functions was 8.9 (5.9) out of a possible maximum of 27. Furthermore, the mean (SD) number of BCTs was 4.4 (2.6) out of a possible maximum of 26. Apps with optimum BCT had significantly more functions [13.8; 95% confidence interval (CI) = 11.9-15.9] than apps that did not (4.7; 95% CI = 3.2-6.2; P < 0.01) and significantly more BCTs (5.8; 95% CI = 4.8-7.0) than apps without (3.1; 95% CI = 2.2-4.1; P < 0.01). Additionally, apps with optimum BCT also cost more than other apps. In the adjusted models, highly rated apps had an average of 4.8 (95% CI = 0.9-8.7; P = 0.02) more functions than lower rated apps. CONCLUSIONS: 'Diabetes apps' include few functions or BCTs compared to the maximum score possible. Apps with optimum BCTs could indicate higher quality. App developers should consider including both specific functions and BCTs in 'diabetes apps' to make them more helpful. More research is needed to understand the components of an effective app for people with diabetes.
BACKGROUND: Mobile applications (apps) could support diabetes management through dietary, weight and blood glucose self-monitoring, as well as by promoting behaviour change. The present study aimed to evaluate diabetes apps for content, functions and behaviour change techniques (BCTs). METHODS: Diabetes self-management apps for Android smartphones were searched for on the Google Play Store. Ten apps each from the following search terms were included; 'diabetes', 'diabetes type 1', 'diabetes type 2', 'gestational diabetes'. Apps were evaluated by being scored according to their number of functions and BCTs, price, and user rating. RESULTS: The mean (SD) number of functions was 8.9 (5.9) out of a possible maximum of 27. Furthermore, the mean (SD) number of BCTs was 4.4 (2.6) out of a possible maximum of 26. Apps with optimum BCT had significantly more functions [13.8; 95% confidence interval (CI) = 11.9-15.9] than apps that did not (4.7; 95% CI = 3.2-6.2; P < 0.01) and significantly more BCTs (5.8; 95% CI = 4.8-7.0) than apps without (3.1; 95% CI = 2.2-4.1; P < 0.01). Additionally, apps with optimum BCT also cost more than other apps. In the adjusted models, highly rated apps had an average of 4.8 (95% CI = 0.9-8.7; P = 0.02) more functions than lower rated apps. CONCLUSIONS: 'Diabetes apps' include few functions or BCTs compared to the maximum score possible. Apps with optimum BCTs could indicate higher quality. App developers should consider including both specific functions and BCTs in 'diabetes apps' to make them more helpful. More research is needed to understand the components of an effective app for people with diabetes.
Authors: Martin Hensher; Paul Cooper; Sithara Wanni Arachchige Dona; Mary Rose Angeles; Dieu Nguyen; Natalie Heynsbergh; Mary Lou Chatterton; Anna Peeters Journal: J Am Med Inform Assoc Date: 2021-06-12 Impact factor: 4.497