Fuller-tyszkiewicz, Matthew, Richardson, Ben, Klein, Britt, Skouteris, Helen, Christensen, Helen, Austin, David, Castle, David, Mihalopoulos, Cathrine, O'Donnell, Renee, Arulkadacham, Lilani, Shatte, Adrian, and Ware, Anna (2018) A Mobile App–Based Intervention for Depression: End-User and Expert Usability Testing Study. JMIR Mental Health, 5 (3). e54.

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Abstract

Background: Despite the growing number of mental health apps available for smartphones, the perceived usability of these apps from the perspectives of end users or health care experts has rarely been reported. This information is vital, particularly for self-guided mHealth interventions, as perceptions of navigability and quality of content are likely to impact participant engagement and treatment compliance.

Objective: The aim of this study was to conduct a usability evaluation of a personalized, self-guided, app-based intervention for depression.

Methods: Participants were administered the System Usability Scale and open-ended questions as part of a semistructured interview. There were 15 participants equally divided into 3 groups: (1) individuals with clinical depression who were the target audience for the app, (2) mental health professionals, and (3) researchers who specialize in the area of eHealth interventions and/or depression research.

Results: The end-user group rated the app highly, both in quantitative and qualitative assessments. The 2 expert groups highlighted the self-monitoring features and range of established psychological treatment options (such as behavioral activation and cognitive restructuring) but had concerns that the amount and layout of content may be difficult for end users to navigate in a self-directed fashion. The end-user data did not confirm these concerns.

Conclusions: Encouraging participant engagement via self-monitoring and feedback, as well as personalized messaging, may be a viable way to maintain participation in self-guided interventions. Further evaluation is necessary to determine whether levels of engagement with these features enhance treatment effects.

Item ID:	81632
Item Type:	Article (Research - C1)
ISSN:	2368-7959
Keywords:	depression; eHealth; mHealth; young adult
Copyright Information:	©Matthew Fuller-Tyszkiewicz, Ben Richardson, Britt Klein, Helen Skouteris, Helen Christensen, David Austin, David Castle, Cathrine Mihalopoulos, Renee O'Donnell, Lilani Arulkadacham, Adrian Shatte, Anna Ware. Originally published in JMIR Mental Health (http://mental.jmir.org), 23.08.2018. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on http://mental.jmir.org/, as well as this copyright and license information must be included.
Date Deposited:	01 May 2024 03:02
FoR Codes:	46 INFORMATION AND COMPUTING SCIENCES > 4608 Human-centred computing > 460806 Human-computer interaction @ 80% 52 PSYCHOLOGY > 5203 Clinical and health psychology > 520399 Clinical and health psychology not elsewhere classified @ 20%
SEO Codes:	20 HEALTH > 2004 Public health (excl. specific population health) > 200409 Mental health @ 80% 22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220407 Human-computer interaction @ 20%
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