ArticleJMIR human factors2017
Designing eHealth Applications to Reduce Cognitive Effort for Persons With Severe Mental Illness: Page Complexity, Navigation Simplicity, and Comprehensibility.
Article in JMIR human factors, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02032680 (Comparison of E-Health vs. In-Person Delivered Family Psychoeducation Treatment), which is not on this map. Cited by 20 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Comparison of E-Health vs. In-Person Delivered Family Psychoeducation Treatment
Who cites it
20 citing papers in PubMed.
- Trial
- Understanding pregnant women's intention to use mobile health apps and its determinants: applying the UTAUT model in a mixed-methods study.BMC primary care · 2025Article
- Exploring Mental Health Content Moderation and Well-Being Tools on Social Media Platforms: Walkthrough Analysis.JMIR human factors · 2025Article
- Formative Evaluation of Suicide Prevention Websites for Men: Qualitative Study with Men at Risk of Suicide and with Potential Gatekeepers.JMIR formative research · 2025Article
- A Mobile Health App (ChillTime) Promoting Emotion Regulation in Dual Disorders: Acceptability and Feasibility Pilot Study.JMIR formative research · 2023Article
- Assessing a digital peer support self-management intervention for adults with serious mental illness: feasibility, acceptability, and preliminary effectiveness.Journal of mental health (Abingdon, England) · 2022Article
- An e-Mental Health Resource for COVID-19-Associated Stress Reduction: Mixed Methods Study of Reach, Usability, and User Perceptions.JMIR mental health · 2022Article
- Do cognitive impairments limit treatment gains in a standalone digital intervention for psychosis? A test of the digital divide.Schizophrenia research. Cognition · 2022Article
- Digital Technologies for Schizophrenia Management: A Descriptive Review.Science and engineering ethics · 2021Review
- 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
- Acceptability and Usability of Mobile Apps for Smoking Cessation Among Young Adults With Psychotic Disorders and Other Serious Mental Illness.Frontiers in psychiatry · 2021Article
- Co-production of the quality of patient-centered outcomes research partnerships instrument for people with mental health conditions.Patient experience journal · 2021Article
- Visual and Personalized Quality of Life Assessment App for People With Severe Mental Health Problems: Qualitative Evaluation.JMIR mental health · 2020Article
- Value of Eye-Tracking Data for Classification of Information Processing-Intensive Handling Tasks: Quasi-Experimental Study on Cognition and User Interface Design.JMIR human factors · 2020Article
- Development of the Motivation and Skills Support (MASS) social goal attainment smartphone app for (and with) people with schizophrenia.Journal of behavioral and cognitive therapy · 2020Article
- Brief, Web-Based Interventions to Motivate Smokers With Schizophrenia: Randomized Trial.JMIR mental health · 2020Article
- Pilot study of a mobile smoking cessation intervention for low-income smokers with serious mental illness.Journal of smoking cessation · 2019Article
- Cocreative Development of the QoL-ME: A Visual and Personalized Quality of Life Assessment App for People With Severe Mental Health Problems.JMIR mental health · 2019Article
- Review of Use and Integration of Mobile Apps Into Psychiatric Treatments.Current psychiatry reports · 2017Review
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundeHealth technologies offer great potential for improving the use and effectiveness of treatments for those with severe mental illness (SMI), including schizophrenia and schizoaffective disorder. This potential can be muted by poor design. There is limited research on designing eHealth technologies for those with SMI, others with cognitive impairments, and those who are not technology savvy. We previously tested a design model, the Flat Explicit Design Model (FEDM), to create eHealth interventions for individuals with SMI. Subsequently, we developed the design concept page complexity, defined via the design variables we created of distinct topic areas, distinct navigation areas, and number of columns used to organize contents and the variables of text reading level, text reading ease (a newly added variable to the FEDM), and the number of hyperlinks and number of words on a page.
objectiveThe objective of our study was to report the influence that the 19 variables of the FEDM have on the ability of individuals with SMI to use a website, ratings of a website's ease of use, and performance on a novel usability task we created termed as content disclosure (a measure of the influence of a homepage's design on the understanding user's gain of a website). Finally, we assessed the performance of 3 groups or dimensions we developed that organize the 19 variables of the FEDM, termed as page complexity, navigational simplicity, and comprehensibility.
methodsWe measured 4 website usability outcomes: ability to find information, time to find information, ease of use, and a user's ability to accurately judge a website's contents. A total of 38 persons with SMI (chart diagnosis of schizophrenia or schizoaffective disorder) and 5 mental health websites were used to evaluate the importance of the new design concepts, as well as the other variables in the FEDM.
resultsWe found that 11 of the FEDM's 19 variables were significantly associated with all 4 usability outcomes. Most other variables were significantly related to 2 or 3 of these usability outcomes. With the 5 tested websites, 7 of the 19 variables of the FEDM overlapped with other variables, resulting in 12 distinct variable groups. The 3 design dimensions had acceptable coefficient alphas. Both navigational simplicity and comprehensibility were significantly related to correctly identifying whether information was available on a website. Page complexity and navigational simplicity were significantly associated with the ability and time to find information and ease-of-use ratings.
conclusionsThe 19 variables and 3 dimensions (page complexity, navigational simplicity, and comprehensibility) of the FEDM offer evidence-based design guidance intended to reduce the cognitive effort required to effectively use eHealth applications, particularly for persons with SMI, and potentially others, including those with cognitive impairments and limited skills or experience with technology. The new variables we examined (topic areas, navigational areas, columns) offer additional and very simple ways to improve simplicity.
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