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  • chi22b-sub3550-i33 accepted manuscript

    Rights statement: © ACM, 2022. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems https://doi.org/10.1145/3491102.3517498

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User perspectives and ethical experiences of apps for depression: A qualitative analysis of user reviews

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Publication date5/05/2022
Host publicationConference on Human Factors in Computing Systems (CHI'22)
Place of PublicationNew York
PublisherACM
Number of pages24
ISBN (Electronic)9781450391573
<mark>Original language</mark>English

Abstract

Apps for depression have the potential to innovate mental health care and increase access to treatment. Yet, concerns abound with disparities between academic development of apps and those available direct-to-consumers through the app marketplace. Reviews have highlighted ethical shortcomings of these self-management tools, with a need for greater insight into how ethical issues may be experienced by users. We addressed these gaps by exploring user reviews of apps for depression to better understand user experiences and ethical issues. We conducted a thematic analysis of 2,217 user reviews sampled from 40 depression apps in Google Play and Apple App Store, totalling over 77,500 words. Users reported both positive and negative experiences, with ethical implications evident in areas of benefits, adverse events, access, usability and design, support, commercial models, autonomy, privacy, and transparency. We conclude by presenting an ethical framework for developing apps for depression and navigating their ethical tensions.

Bibliographic note

© ACM, 2022. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems https://doi.org/10.1145/3491102.3517498