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 with heart failure
patients, then recommended a generic ten-step personas development process.
Methods strengths and limitations of the study and of personas development
generally are discussed.