2016
DOI: 10.1080/10447318.2016.1265784
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Human Factors Analysis, Design, and Evaluation of Engage, a Consumer Health IT Application for Geriatric Heart Failure Self-Care

Abstract: Human factors and ergonomics (HFE) and related approaches can be used to enhance research and development of consumer-facing health IT systems, including technologies supporting the needs of people with chronic disease. We describe a multiphase HFE study of health IT supporting self-care of chronic heart failure by older adults. The study was based on HFE frameworks of “patient work” and incorporated the three broad phases of user-centered design: study or analysis; design; and evaluation. In the study phase, … Show more

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Cited by 45 publications
(95 citation statements)
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References 70 publications
(58 reference statements)
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“…Less structured methods permit the capture of a broader range of attributes and deeper understanding of each, at the cost of higher subjectivity and greater data collection and analysis effort. In our recent design of a heart failure self-care health IT, we demonstrate the value of using largely qualitative data from a multiyear study but also identify the challenges of prolonged analysis and the difficulty of incorporating a rich and heterogeneous set of findings into a single design [74]. Other health researchers have demonstrated faster health-related persona generation techniques, for example a 90-minute rapid personas development method using a single facilitated session involving multiple individuals with deep knowledge of the patient population, but not using direct patient-generated data [75].…”
Section: Discussionmentioning
confidence: 99%
“…Less structured methods permit the capture of a broader range of attributes and deeper understanding of each, at the cost of higher subjectivity and greater data collection and analysis effort. In our recent design of a heart failure self-care health IT, we demonstrate the value of using largely qualitative data from a multiyear study but also identify the challenges of prolonged analysis and the difficulty of incorporating a rich and heterogeneous set of findings into a single design [74]. Other health researchers have demonstrated faster health-related persona generation techniques, for example a 90-minute rapid personas development method using a single facilitated session involving multiple individuals with deep knowledge of the patient population, but not using direct patient-generated data [75].…”
Section: Discussionmentioning
confidence: 99%
“…Mobile health (mHealth) projects benefit from UCD by using input from patients, informal caregivers, clinicians, and other stakeholders during the project life cycle to create better designs and iteratively improve interventions, thus enhancing their usability, acceptance, and potential success when implemented [ 4 - 6 ]. Increasingly, UCD has been recommended and adopted in mHealth projects to great success [ 7 ], with many examples of mHealth for people living with HIV [ 5 , 8 ], chronic conditions [ 9 - 11 ], or mental illness [ 6 , 12 , 13 ].…”
Section: Introductionmentioning
confidence: 99%
“…Such studies are capable of informing specific interventions or producing generalizable design implications that can impact the engagement of mHealth technologies. 59 An assumption of SEIPS 2.0 is that patients and other nonprofessionals perform work or life's effortful activities towards a goal. 60 Patient work is a concept originating in social science, where three interrelated lines of work were proposed: illness-related (e.g., taking insulin); everyday life (e.g., grocery shopping); and biographical (e.g., crafting a new identity as a diabetic patient).…”
Section: Accepted M Manuscriptmentioning
confidence: 99%