Quality evaluation of stress, anxiety and depression apps for COVID-19

Background: COVID-19 has caused increased stress, anxiety and depression with increased barriers to treatment. Mobile apps offer a potential solution, but there is no information on the quality of such apps recommended for COVID-19. This study aims to evaluate the quality of stress, anxiety and depr...

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Autores principales: Lauren Su En Li, Li Lian Wong, Kevin Yi-Lwern Yap
Formato: article
Lenguaje:EN
Publicado: Elsevier 2021
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Acceso en línea:https://doaj.org/article/763d5c79ff464137926d7c729e05985e
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Sumario:Background: COVID-19 has caused increased stress, anxiety and depression with increased barriers to treatment. Mobile apps offer a potential solution, but there is no information on the quality of such apps recommended for COVID-19. This study aims to evaluate the quality of stress, anxiety and depression apps recommended for COVID-19. Methods: A search was conducted to identify relevant apps on the iOS and Android platforms. 44 apps were evaluated using the Mobile App Rating Scale (MARS), and the American Psychiatric Association's app evaluation model for data privacy and security. Results: Overall quality scores of iOS and Android apps were 3.69 ± 0.43 and 3.66 ± 0.47. Thirty percent had good/excellent overall scores. In general, the iOS and Android versions of the apps scored best for functionality (4.21 ± 0.48, 4.12 ± 0.53), followed by aesthetics (3.84 ± 0.50, 3.78 ± 0.56), information (3.39 ± 0.54, 3.40 ± 0.60), and engagement (3.31 ± 0.81, 3.34 ± 0.84). Over half (59%) shared personal information with third parties and 14% were compliant with data protection standards. Limitations: Only free apps available in Singapore were evaluated. Our results are time sensitive due to addition, removal, and update of apps in the app stores, thus our results should be extrapolated with caution to apps from other countries and paid apps. Conclusion: Apps that addressed all three conditions had the highest overall quality scores. The top ranked apps (Sanvello, Woebot, Happify, Youper, Bloom) were of good quality, but majority were of acceptable quality and had room for improvement. App developers are encouraged to use our findings to improve and develop better quality apps.