Richard J Holden1, Anand Kulanthaivel2, Saptarshi Purkayastha2, Kathryn M Goggins3, Sunil Kripalani4. 1. Department of BioHealth Informatics, Indiana University School of Informatics and Computing, Indianapolis, IN, USA; Indiana University Center for Aging Research (IUCAR), Regenstrief Institute, Inc., Indianapolis, IN, USA. Electronic address: rjholden@iupui.edu. 2. Department of BioHealth Informatics, Indiana University School of Informatics and Computing, Indianapolis, IN, USA. 3. Center for Effective Health Communication, Vanderbilt University Medical Center, Nashville, TN, USA; Center for Clinical Quality and Implementation Research, Vanderbilt University Medical Center, Nashville, TN, USA. 4. Center for Effective Health Communication, Vanderbilt University Medical Center, Nashville, TN, USA; Center for Clinical Quality and Implementation Research, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA.
Abstract
BACKGROUND: Personas are a canonical user-centered design method increasingly used in health informatics research. Personas-empirically-derived user archetypes-can be used by eHealth designers to gain a robust understanding of their target end users such as patients. OBJECTIVE: To develop biopsychosocial personas of older patients with heart failure using quantitative analysis of survey data. METHOD: Data were collected using standardized surveys and medical record abstraction from 32 older adults with heart failure recently hospitalized for acute heart failure exacerbation. Hierarchical cluster analysis was performed on a final dataset of n=30. Nonparametric analyses were used to identify differences between clusters on 30 clustering variables and seven outcome variables. RESULTS: Six clusters were produced, ranging in size from two to eight patients per cluster. Clusters differed significantly on these biopsychosocial domains and subdomains: demographics (age, sex); medical status (comorbid diabetes); functional status (exhaustion, household work ability, hygiene care ability, physical ability); psychological status (depression, health literacy, numeracy); technology (Internet availability); healthcare system (visit by home healthcare, trust in providers); social context (informal caregiver support, cohabitation, marital status); and economic context (employment status). Tabular and narrative persona descriptions provide an easy reference guide for informatics designers. DISCUSSION: Personas development using approaches such as clustering of structured survey data is an important tool for health informatics professionals. We describe insights from our study of patients with heart failure, then recommend a generic ten-step personas development process. Methods strengths and limitations of the study and of personas development generally are discussed.
BACKGROUND: Personas are a canonical user-centered design method increasingly used in health informatics research. Personas-empirically-derived user archetypes-can be used by eHealth designers to gain a robust understanding of their target end users such as patients. OBJECTIVE: To develop biopsychosocial personas of older patients with heart failure using quantitative analysis of survey data. METHOD: Data were collected using standardized surveys and medical record abstraction from 32 older adults with heart failure recently hospitalized for acute heart failure exacerbation. Hierarchical cluster analysis was performed on a final dataset of n=30. Nonparametric analyses were used to identify differences between clusters on 30 clustering variables and seven outcome variables. RESULTS: Six clusters were produced, ranging in size from two to eight patients per cluster. Clusters differed significantly on these biopsychosocial domains and subdomains: demographics (age, sex); medical status (comorbid diabetes); functional status (exhaustion, household work ability, hygiene care ability, physical ability); psychological status (depression, health literacy, numeracy); technology (Internet availability); healthcare system (visit by home healthcare, trust in providers); social context (informal caregiver support, cohabitation, marital status); and economic context (employment status). Tabular and narrative persona descriptions provide an easy reference guide for informatics designers. DISCUSSION: Personas development using approaches such as clustering of structured survey data is an important tool for health informatics professionals. We describe insights from our study of patients with heart failure, then recommend a generic ten-step personas development process. Methods strengths and limitations of the study and of personas development generally are discussed.
Authors: Pamela H Mitchell; Lynda Powell; James Blumenthal; Jennifer Norten; Gail Ironson; Carol Rogers Pitula; Erika Sivarajan Froelicher; Susan Czajkowski; Marston Youngblood; Marc Huber; Lisa F Berkman Journal: J Cardiopulm Rehabil Date: 2003 Nov-Dec Impact factor: 2.081
Authors: Amy E Paxton; Lisa A Strycker; Deborah J Toobert; Alice S Ammerman; Russell E Glasgow Journal: Am J Prev Med Date: 2011-01 Impact factor: 5.043
Authors: Blackford Middleton; Meryl Bloomrosen; Mark A Dente; Bill Hashmat; Ross Koppel; J Marc Overhage; Thomas H Payne; S Trent Rosenbloom; Charlotte Weaver; Jiajie Zhang Journal: J Am Med Inform Assoc Date: 2013-01-25 Impact factor: 4.497
Authors: Richard J Holden; Pascale Carayon; Ayse P Gurses; Peter Hoonakker; Ann Schoofs Hundt; A Ant Ozok; A Joy Rivera-Rodriguez Journal: Ergonomics Date: 2013-10-03 Impact factor: 2.778
Authors: Courtney R Lyles; Eugene C Nelson; Susan Frampton; Patricia C Dykes; Anupama G Cemballi; Urmimala Sarkar Journal: Ann Intern Med Date: 2020-06-02 Impact factor: 25.391
Authors: Patricia Ngantcha; Muhammad Tuan Amith; Kirk Roberts; John A Valenza; Muhammad Walji; Cui Tao Journal: Proceedings (IEEE Int Conf Bioinformatics Biomed) Date: 2021-12
Authors: Andrew James Williams; Tamaryn Menneer; Mansi Sidana; Tim Walker; Kath Maguire; Markus Mueller; Cheryl Paterson; Michael Leyshon; Catherine Leyshon; Emma Seymour; Zoë Howard; Emma Bland; Karyn Morrissey; Timothy J Taylor Journal: JMIR Public Health Surveill Date: 2021-02-16
Authors: Helen Bennetts; Larissa Arakawa Martins; Joost van Hoof; Veronica Soebarto Journal: Int J Environ Res Public Health Date: 2020-11-13 Impact factor: 3.390