Journal
JMIR MHEALTH AND UHEALTH
Volume 9, Issue 10, Pages -Publisher
JMIR PUBLICATIONS, INC
DOI: 10.2196/26712
Keywords
mental health; cognitive behavioral therapy; mobile apps; anxiety; stress; mHealth; mobile phone
Funding
- Science Foundation Ireland [17/RC-PHD/3488]
- European Regional Development Fund [13/RC/2106_P2]
- Science Foundation Ireland (SFI) [17/RC-PhD/3488] Funding Source: Science Foundation Ireland (SFI)
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This study aims to review how anxiety apps deliver cognitive behavioral elements and their functionalities to support user engagement and tailoring based on user needs. The findings suggest that anxiety apps offer various functionalities and engagement features, but support for engagement is uneven and options for personalization are limited.
Background: A range of mobile apps for anxiety have been developed in response to the high prevalence of anxiety disorders. Although the number of publicly available apps for anxiety is increasing, attrition rates among mobile apps are high. These apps must be engaging and relevant to end users to be effective; thus, engagement features and the ability to tailor delivery to the needs of individual users are key. However, our understanding of the functionality of these apps concerning engagement and tailoring features is limited. Objective: The aim of this study is to review how cognitive behavioral elements are delivered by anxiety apps and their functionalities to support user engagement and tailoring based on user needs. Methods: A systematic search for anxiety apps described as being based on cognitive behavioral therapy (CBT) was conducted on Android and iPhone marketplaces. Apps were included if they mentioned the use of CBT for anxiety-related disorders. We identified 597 apps, of which 36 met the inclusion criteria and were reviewed through direct use. Results: Cognitive behavioral apps for anxiety incorporate a variety of functionalities, offer several engagement features, and integrate low-intensity CBT exercises. However, the provision of features to support engagement is highly uneven, and support is provided only for low-intensity CBT treatment. Cognitive behavioral elements combine various modalities to deliver intervention content and support the interactive delivery of these elements. Options for personalization are limited and restricted to goal selection upon beginning use or based on self-monitoring entries. Apps do not appear to provide individualized content to users based on their input. Conclusions: Engagement and tailoring features can be significantly expanded in existing apps, which make limited use of social features and clinical support and do not use sophisticated features such as personalization based on sensor data. To guide the evolution of these interventions, further research is needed to explore the effectiveness of different types of engagement features and approaches to tailoring therapeutic content.
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