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      Enhancing the Effectiveness of Consumer-Focused Health Information Technology Systems Through eHealth Literacy: A Framework for Understanding Users' Needs

      research-article
      , MD, PhD 1 , , , PhD 2 , , PhD 3 , , MSc 1 , , PhD 4
      (Reviewer), (Reviewer), (Reviewer)
      JMIR Human Factors
      Gunther Eysenbach
      eHealth literacy, requirements, user involvement

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          Abstract

          Background

          eHealth systems and applications are increasingly focused on supporting consumers to directly engage with and use health care services. Involving end users in the design of these systems is critical to ensure a generation of usable and effective eHealth products and systems. Often the end users engaged for these participatory design processes are not actual representatives of the general population, and developers may have limited understanding about how well they might represent the full range of intended users of the eHealth products. As a consequence, resulting information technology (IT) designs may not accommodate the needs, skills, cognitive capacities, and/or contexts of use of the intended broader population of health consumers. This may result in challenges for consumers who use the health IT systems, and could lead to limitations in adoption if the diversity of user attributes has not been adequately considered by health IT designers.

          Objective

          The objective of this paper is to propose how users’ needs and competences can be taken into account when designing new information and communications technology solutions in health care by expanding the user-task-context matrix model with the domains of a new concept of eHealth literacy.

          Methods

          This approach expands an existing method for supporting health IT system development, which advocates use of a three-dimensional user-task-context matrix to comprehensively identify the users of health IT systems, and what their needs and requirements are under differing contexts of use. The extension of this model involved including knowledge about users’ competences within the seven domains of eHealth literacy, which had been identified based on systematic engagement with computer scientists, academics, health professionals, and patients recruited from various patient organizations and primary care. A concept map was constructed based on a structured brainstorm procedure, card sorting, and computational analysis.

          Results

          The new eHealth literacy concept (based on 7 domains) was incorporated as a key factor in expanding the user-task-context matrix to describe and qualify user requirements and understanding related to eHealth literacy. This resulted in an expanded framework and a five-step process, which can support health IT designers in understanding and more accurately addressing end-users’ needs, capabilities, and contexts to improve effectiveness and broader applicability of consumer-focused health IT systems. It is anticipated that the framework will also be useful for policy makers involved in the planning, procuring, and funding of eHealth infrastructure, applications, and services.

          Conclusions

          Developing effective eHealth products requires complete understanding of the end-users’ needs from multiple perspectives. In this paper, we have proposed and detailed a framework for modeling users’ needs for designing eHealth systems that merges prior work in development of a user-task-context matrix with the emerging area of eHealth literacy. This framework is intended to be used to guide design of eHealth technologies and to make requirements explicitly related to eHealth literacy, enabling a generation of well-targeted, fit-for-purpose, equitable, and effective products and systems.

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          Most cited references30

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          User involvement: A review of the benefits and challenges

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            eHealth Literacy 2.0: Problems and Opportunities With an Evolving Concept

            As the use of eHealth grows and diversifies globally, the concept of eHealth literacy – a foundational skill set that underpins the use of information and communication technologies (ICT) for health – becomes more important than ever to understand and advance. EHealth literacy draws our collective attention to the knowledge and complex skill set that is often taken for granted when people interact with technology to address information, focusing our attention on learning and usability issues from the clinical through to population health level. Just as the field of eHealth is dynamic and evolving, so too is the context where eHealth literacy is applied and understood. The original Lily Model of eHealth literacy and scale used to assess it were developed at a time when the first generation of web tools gained prominence before the rise of social media. The rapid shifts in the informational landscape created by Web 2.0 tools and environments suggests it might be time to revisit the concept of eHealth Literacy and consider what a second release might look like.
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              Misleading Health-Related Information Promoted Through Video-Based Social Media: Anorexia on YouTube

              Introduction The amount of information being uploaded onto social video platforms, such as YouTube, Vimeo, and Veoh, continues to spiral, making it increasingly difficult to discern reliable health information from misleading content. There are thousands of YouTube videos promoting misleading information about anorexia (eg, anorexia as a healthy lifestyle). Objective The aim of this study was to investigate anorexia-related misinformation disseminated through YouTube videos. Methods We retrieved YouTube videos related to anorexia using the keywords anorexia, anorexia nervosa, proana, and thinspo on October 10, 2011.Three doctors reviewed 140 videos with approximately 11 hours of video content, classifying them as informative, pro-anorexia, or others. By informative we mean content describing the health consequences of anorexia and advice on how to recover from it; by pro-anorexia we mean videos promoting anorexia as a fashion, a source of beauty, and that share tips and methods for becoming and remaining anorexic. The 40 most-viewed videos (20 informative and 20 pro-anorexia videos) were assessed to gauge viewer behavior. Results The interrater agreement of classification was moderate (Fleiss’ kappa=0.5), with 29.3% (n=41) being rated as pro-anorexia, 55.7% (n=78) as informative, and 15.0% (n=21) as others. Pro-anorexia videos were favored 3 times more than informative videos (odds ratio [OR] 3.3, 95% CI 3.3-3.4, P<.001). Conclusions Pro-anorexia information was identified in 29.3% of anorexia-related videos. Pro-anorexia videos are less common than informative videos; however, in proportional terms, pro-anorexia content is more highly favored and rated by its viewers. Efforts should focus on raising awareness, particularly among teenagers, about the trustworthiness of online information about beauty and healthy lifestyles. Health authorities producing videos to combat anorexia should consider involving celebrities and models to reach a wider audience. More research is needed to study the characteristics of pro-anorexia videos in order to develop algorithms that will automatically detect and filter those videos before they become popular.
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                Author and article information

                Contributors
                Journal
                JMIR Hum Factors
                JMIR Hum Factors
                JMIR Human Factors
                JMIR Human Factors
                Gunther Eysenbach (JMIR Publications Inc., Toronto, Canada )
                2292-9495
                Jan-Jun 2015
                20 May 2015
                : 2
                : 1
                : e9
                Affiliations
                [1] 1Department of Public Health, University of Copenhagen CopenhagenDenmark
                [2] 2School of Health Information Science University of Victoria Victoria, BCCanada
                [3] 3Deakin Population Health Strategic Research Centre, Deakin University MelbourneAustralia
                [4] 4eHealth Services Research Group, University of Tasmania HobartAustralia
                Author notes
                Corresponding Author: Lars Kayser lk@ 123456sund.ku.dk
                Author information
                http://orcid.org/0000-0002-0909-4088
                http://orcid.org/0000-0002-2557-9288
                http://orcid.org/0000-0002-9081-2699
                http://orcid.org/0000-0002-1681-4338
                http://orcid.org/0000-0003-4504-2338
                Article
                v2i1e9
                10.2196/humanfactors.3696
                4797661
                27025228
                12b0a0b6-840d-455f-b4fc-beff2e5d9f93
                ©Lars Kayser, Andre Kushniruk, Richard H Osborne, Ole Norgaard, Paul Turner. Originally published in JMIR Human Factors (http://humanfactors.jmir.org), 20.05.2015.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Human Factors, is properly cited. The complete bibliographic information, a link to the original publication on http://humanfactors.jmir.org, as well as this copyright and license information must be included.

                History
                : 16 July 2014
                : 19 October 2014
                : 15 January 2015
                : 26 April 2015
                Categories
                Original Paper
                Original Paper

                ehealth literacy,requirements,user involvement
                ehealth literacy, requirements, user involvement

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