Accepted for/Published in: JMIR Mental Health
Date Submitted: Apr 24, 2020
Open Peer Review Period: Apr 24, 2020 - Jun 12, 2020
Date Accepted: Jul 29, 2020
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
What’s in it for me? Qualitative evaluation of the QoL-ME, a visual and personalized quality of life assessment App for people with severe mental health problems
ABSTRACT
Background:
The QoL-ME is a digital, visual and personalized QoL assessment App for people with severe mental health problems. Research reveals that e-mental health Apps such as the QoL-ME frequently fall short of expectations regarding their impact on daily practice. Studies often indicate that e-mental health Apps ought to respect the needs and preferences of end-users to achieve optimal user-engagement
Objective:
The degree to which the QoL-ME matches the needs and preferences of end-users was investigated in this study. Special attention is paid to whether the QoL-ME is actionable and beneficial for its users.
Methods:
Eight end-users who gained experience using the QoL-ME contributed to semi-structured interviews. An interview guide was used to direct the interviews. All interviews were audio recorded and transcribed verbatim. Transcriptions were analysed and coded thematically.
Results:
Analysis revealed three main themes 1) Obtained benefit, 2) Actionability and 3) Characteristics of the QoL-ME.
Conclusions:
The QoL-ME can be beneficial to users as it provides them with insight into their QoL and elicits reflection. Incorporating more functionalities that facilitate self-management, such as advice and strategies for improving lacking areas will likely make the App more actionable. Most of the additional characteristics of the QoL-ME, including its usability, design and content, match the needs and preferences of users.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.