ArticleJMIR mental health2019
Cocreative Development of the QoL-ME: A Visual and Personalized Quality of Life Assessment App for People With Severe Mental Health Problems.
Article in JMIR mental health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- An Evaluation of the Evidence on Mobile Health Applications for Mental Health, Substance Use and Delinquency in Justice-Involved Adults and Youth: a Scoping Review.Research on child and adolescent psychopathology · 2025Article
- Human-Centered Design Approaches in Digital Mental Health Interventions: Exploratory Mapping Review.JMIR mental health · 2022Review
- Data Visualization for Chronic Neurological and Mental Health Condition Self-management: Systematic Review of User Perspectives.JMIR mental health · 2022Review
- The Extent of User Involvement in the Design of Self-tracking Technology for Bipolar Disorder: Literature Review.JMIR mental health · 2021Review
- Ensuring patient and public involvement in the transition to AI-assisted mental health care: A systematic scoping review and agenda for design justice.Health expectations : an international journal of public participation in health care and health policy · 2021Article
- Key Variables for Effective eHealth Designs for Individuals With and Without Mental Health Disorders: 2^12-4 Fractional Factorial Experiment.Journal of medical Internet research · 2021Article
- Psychometric Properties of the QoL-ME: A Visual and Personalized Quality of Life Assessment App for People With Severe Mental Health Problems.Frontiers in psychiatry · 2021Article
- Effect of Age, Breed, and Sex on the Health-Related Quality of Life of Owner Assessed Healthy Dogs.Frontiers in veterinary science · 2021Article
- Visual and Personalized Quality of Life Assessment App for People With Severe Mental Health Problems: Qualitative Evaluation.JMIR mental health · 2020Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundQuality of life (QoL) is a prominent outcome measure in mental health. However, conventional methods for QoL assessment rely heavily on language-based communication and therefore may not be optimal for all individuals with severe mental health problems. In addition, QoL assessment is usually based on a fixed number of life domains. This approach conflicts with the notion that QoL is influenced by individual values and preferences. A digital assessment app facilitates both the accessibility and personalization of QoL assessment and may, therefore, help to further advance QoL assessment among individuals with severe mental health problems.
objectiveThis study focused on the development of an innovative, visual, and personalized QoL assessment app for people with severe mental health problems: the QoL-ME.
methodsThis study targeted 3 groups of individuals with severe mental health problems: (1) people with psychiatric problems, (2) people treated in forensic psychiatry, and (3) people who are homeless. A group of 59 participants contributed to the 6 iterations of the cocreative development of the QoL-ME. In the brainstorming stage, consisting of the first iteration, participants' previous experiences with questionnaires and mobile apps were explored. Participants gave their feedback on initial designs and wireframes in the second to fourth iterations that made up the design stage. In the usability stage that comprised the final 2 iterations, the usability of the QoL-ME was evaluated.
resultsIn the brainstorming stage, participants stressed the importance of privacy and data security and of receiving feedback when answering questionnaires. Participants in the design stage indicated a preference for paging over scrolling, linear navigation, a clean and minimalist layout, the use of touchscreen functionality in various modes of interaction, and the use of visual analog scales. The usability evaluation in the usability stage revealed good to excellent usability.
conclusionsThe cocreative development of the QoL-ME resulted in an app that corresponds to the preferences of participants and has strong usability. Further research is needed to evaluate the psychometric quality of the QoL-ME and to investigate its usefulness in practice.
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