Armando J Rotondi1, Shaun M Eack2, Barbara H Hanusa3, Michael B Spring4, Gretchen L Haas5. 1. Department of Critical Care Medicine, Clinical and Translational Sciences Institute, University of Pittsburgh, Pittsburgh, PA; Mental Illness Research, Education and Clinical Center (MIRECC), Department of Veterans Affairs Medical Center, Pittsburgh, PA; Rotondi@pitt.edu. 2. School of Social Work, Psychiatry, and Clinical and Translational Sciences Institute, University of Pittsburgh, Pittsburgh, PA; 3. Mental Illness Research, Education and Clinical Center (MIRECC), and Center for Health Equity Research (CHERP), Department of Veterans Affairs Medical Center, Pittsburgh, PA; 4. School of Information Sciences, University of Pittsburgh, Pittsburgh, PA; 5. VA Pittsburgh Mental Illness Research Education and Clinical Centers (MIRECC), Department of Veterans Affairs Medical Center, Pittsburgh, PA; Western Psychiatric Institute and Clinic (WPIC), University of Pittsburgh, Pittsburgh, PA.
Abstract
OBJECTIVE: E-health applications are becoming integral components of general medical care delivery models and emerging for mental health care. Few exist for treatment of those with severe mental illness (SMI). In part, this is due to a lack of models to design such technologies for persons with cognitive impairments and lower technology experience. This study evaluated the effectiveness of an e-health design model for persons with SMI termed the Flat Explicit Design Model (FEDM). METHODS: Persons with schizophrenia (n = 38) performed tasks to evaluate the effectiveness of 5 Web site designs: 4 were prominent public Web sites, and 1 was designed according to the FEDM. Linear mixed-effects regression models were used to examine differences in usability between the Web sites. Omnibus tests of between-site differences were conducted, followed by post hoc pairwise comparisons of means to examine specific Web site differences when omnibus tests reached statistical significance. RESULTS: The Web site designed using the FEDM required less time to find information, had a higher success rate, and was rated easier to use and less frustrating than the other Web sites. The home page design of one of the other Web sites provided the best indication to users about a Web site's contents. The results are consistent with and were used to expand the FEDM. CONCLUSIONS: The FEDM provides evidence-based guidelines to design e-health applications for person with SMI, including: minimize an application's layers or hierarchy, use explicit text, employ navigational memory aids, group hyperlinks in 1 area, and minimize the number of disparate subjects an application addresses.
OBJECTIVE: E-health applications are becoming integral components of general medical care delivery models and emerging for mental health care. Few exist for treatment of those with severe mental illness (SMI). In part, this is due to a lack of models to design such technologies for persons with cognitive impairments and lower technology experience. This study evaluated the effectiveness of an e-health design model for persons with SMI termed the Flat Explicit Design Model (FEDM). METHODS:Persons with schizophrenia (n = 38) performed tasks to evaluate the effectiveness of 5 Web site designs: 4 were prominent public Web sites, and 1 was designed according to the FEDM. Linear mixed-effects regression models were used to examine differences in usability between the Web sites. Omnibus tests of between-site differences were conducted, followed by post hoc pairwise comparisons of means to examine specific Web site differences when omnibus tests reached statistical significance. RESULTS: The Web site designed using the FEDM required less time to find information, had a higher success rate, and was rated easier to use and less frustrating than the other Web sites. The home page design of one of the other Web sites provided the best indication to users about a Web site's contents. The results are consistent with and were used to expand the FEDM. CONCLUSIONS: The FEDM provides evidence-based guidelines to design e-health applications for person with SMI, including: minimize an application's layers or hierarchy, use explicit text, employ navigational memory aids, group hyperlinks in 1 area, and minimize the number of disparate subjects an application addresses.
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