Fostering Engagement With Health and Housing Innovation: Development of Participant Personas in a Social Housing Cohort

人格 业务 心理健康 测量数据收集 人口 营销 心理学 社会学 医学 环境卫生 计算机科学 统计 数学 心理治疗师 人机交互
作者
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,Tim Taylor
出处
期刊:JMIR public health and surveillance [JMIR Publications]
卷期号:7 (2): e25037-e25037 被引量:13
标识
DOI:10.2196/25037
摘要

Background Personas, based on customer or population data, are widely used to inform design decisions in the commercial sector. The variety of methods available means that personas can be produced from projects of different types and scale. Objective This study aims to experiment with the use of personas that bring together data from a survey, household air measurements and electricity usage sensors, and an interview within a research and innovation project, with the aim of supporting eHealth and eWell-being product, process, and service development through broadening the engagement with and understanding of the data about the local community. Methods The project participants were social housing residents (adults only) living in central Cornwall, a rural unitary authority in the United Kingdom. A total of 329 households were recruited between September 2017 and November 2018, with 235 (71.4%) providing complete baseline survey data on demographics, socioeconomic position, household composition, home environment, technology ownership, pet ownership, smoking, social cohesion, volunteering, caring, mental well-being, physical and mental health–related quality of life, and activity. K-prototype cluster analysis was used to identify 8 clusters among the baseline survey responses. The sensor and interview data were subsequently analyzed by cluster and the insights from all 3 data sources were brought together to produce the personas, known as the Smartline Archetypes. Results The Smartline Archetypes proved to be an engaging way of presenting data, accessible to a broader group of stakeholders than those who accessed the raw anonymized data, thereby providing a vehicle for greater research engagement, innovation, and impact. Conclusions Through the adoption of a tool widely used in practice, research projects could generate greater policy and practical impact, while also becoming more transparent and open to the public.
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