Gisbert Wilhelm Teepe1, Ashish Da Fonseca2, Birgit Kleim3,4, Nicholas C Jacobson5, Alicia Salamanca Sanabria6, Lorainne Tudor Car7, Elgar Fleisch1,2, Tobias Kowatsch1,2,6,8. 1. Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/58, Zurich, CH. 2. Centre for Digital Health Interventions, Institute of Technology Management, University of St. Gallen, St. Gallen, CH. 3. Department of Experimental Psychopathology and Psychotherapy, University of Zurich, Zurich, CH. 4. Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zurich, Zurich, CH. 5. Center for Technology and Behavioral Health, Departments of Biomedical Data Science and Psychiatry, Geisel School of Medicine, Dartmouth College, Hanover, US. 6. Future Health Technologies, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore-ETH Centre, Singapore, SG. 7. Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, SG. 8. Saw Swee Hock School of Public Health, National University of Singapore, Singapore, SG.
Abstract
BACKGROUND: There is an increasing number of smartphone applications (apps) focusing on prevention, treatment, and diagnosis of depression. A promising approach to increase the effectiveness while reducing the individual's burden is the use of just-in-time adaptive intervention (JITAI) mechanisms. JITAIs are designed to improve the effectiveness of the intervention and reduce the burden of the person using the intervention by providing the right type of support at the right time. The right type and right time are determined by measuring the state of vulnerability and the state of receptivity. OBJECTIVE: With this work, we systematically assess the use of JITAI mechanisms in popular apps for individuals with depression. METHODS: We systematically searched for apps addressing depression in the Apple App Store, the Google Play Store, and in curated lists from the Anxiety and Depression Association of America, the United Kingdom National Health Service, and the American Psychological Association in August 2020. Relevant apps were ranked according to the number of reviews (Apple App Store) or downloads (Google Play Store). For each app, two authors separately reviewed all publications concerning the app found within scientific databases (PubMed, Cochrane Register of Controlled Trials, PsycINFO, Google Scholar, IEEExplore, Web of Science, ACM Portal, and Science Direct), publications cited on the app's website, information on the app's website, and the app itself. All types of measurements (e.g., open questions, closed questions, device analytics) found in the apps were recorded. These measurements found were reviewed to investigate whether they were used to tailor content or timing along the JITAI mechanisms, to indicate progress, or as part of a component (e.g., describing a stressful situation). RESULTS: None of the 28 reviewed apps used JITAI mechanisms to tailor content to situations, states, or individuals. Three apps did not use any measurements, 20 apps exclusively used self-reports that are insufficient to leverage the full potential of JITAIs, and the five apps employing self-reports and passive measurements used them as progress or task indicators only. While 23 of the 68 reviewed publications investigated the effectiveness and 14 publications investigated the efficacy of the apps, not one publication mentioned or evaluated JITAI mechanisms. CONCLUSIONS: Promising JITAI mechanisms have not yet been translated into mainstream depression apps. While the wide range of passive measurements available from smartphones were very rarely used, self-reported outcomes were used by 20 apps. However, in both cases, the measured outcomes were not used to tailor along a state of vulnerability or receptivity. Due to this lack of tailoring to individual, states, or situation, we argue that the apps cannot be considered as JITAIs. The lack of publications investigating whether JITAI mechanisms lead to an increase of the apps' effectiveness or efficacy highlights the need for further research, especially in real-world apps.
BACKGROUND: There is an increasing number of smartphone applications (apps) focusing on prevention, treatment, and diagnosis of depression. A promising approach to increase the effectiveness while reducing the individual's burden is the use of just-in-time adaptive intervention (JITAI) mechanisms. JITAIs are designed to improve the effectiveness of the intervention and reduce the burden of the person using the intervention by providing the right type of support at the right time. The right type and right time are determined by measuring the state of vulnerability and the state of receptivity. OBJECTIVE: With this work, we systematically assess the use of JITAI mechanisms in popular apps for individuals with depression. METHODS: We systematically searched for apps addressing depression in the Apple App Store, the Google Play Store, and in curated lists from the Anxiety and Depression Association of America, the United Kingdom National Health Service, and the American Psychological Association in August 2020. Relevant apps were ranked according to the number of reviews (Apple App Store) or downloads (Google Play Store). For each app, two authors separately reviewed all publications concerning the app found within scientific databases (PubMed, Cochrane Register of Controlled Trials, PsycINFO, Google Scholar, IEEExplore, Web of Science, ACM Portal, and Science Direct), publications cited on the app's website, information on the app's website, and the app itself. All types of measurements (e.g., open questions, closed questions, device analytics) found in the apps were recorded. These measurements found were reviewed to investigate whether they were used to tailor content or timing along the JITAI mechanisms, to indicate progress, or as part of a component (e.g., describing a stressful situation). RESULTS: None of the 28 reviewed apps used JITAI mechanisms to tailor content to situations, states, or individuals. Three apps did not use any measurements, 20 apps exclusively used self-reports that are insufficient to leverage the full potential of JITAIs, and the five apps employing self-reports and passive measurements used them as progress or task indicators only. While 23 of the 68 reviewed publications investigated the effectiveness and 14 publications investigated the efficacy of the apps, not one publication mentioned or evaluated JITAI mechanisms. CONCLUSIONS: Promising JITAI mechanisms have not yet been translated into mainstream depression apps. While the wide range of passive measurements available from smartphones were very rarely used, self-reported outcomes were used by 20 apps. However, in both cases, the measured outcomes were not used to tailor along a state of vulnerability or receptivity. Due to this lack of tailoring to individual, states, or situation, we argue that the apps cannot be considered as JITAIs. The lack of publications investigating whether JITAI mechanisms lead to an increase of the apps' effectiveness or efficacy highlights the need for further research, especially in real-world apps.
Authors: Jacqueline Louise Mair; Tobias Kowatsch; Roman Keller; Sven Hartmann; Gisbert Wilhelm Teepe; Kim-Morgaine Lohse; Aishah Alattas; Lorainne Tudor Car; Falk Müller-Riemenschneider; Florian von Wangenheim Journal: J Med Internet Res Date: 2022-01-07 Impact factor: 5.428