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Discovering Engagement Personas in a Digital Diabetes Prevention Program
Jonathan H Hori1, Elizabeth X Sia1, Kimberly G Lockwood1
1Lark Health, 2570 W El Camino Real, Mountain View, CA 94040, USA.
Behavioral Sciences (Basel, Switzerland)
|June 23, 2022
Summary
Researchers identified five distinct user engagement personas in a digital diabetes prevention program. These personas, based on longitudinal engagement patterns, varied by demographics and weight loss, aiding personalized digital health strategies.
Area of Science:
- Digital Health
- Preventive Healthcare
- Behavioral Science
Background:
- Digital health technologies are increasingly central to preventive healthcare delivery.
- Understanding user engagement is crucial for the success of digital health interventions.
- Longitudinal engagement patterns offer insights into user behavior within digital programs.
Purpose of the Study:
- To develop a quantitative approach for discovering and characterizing user engagement personas.
- To identify distinct longitudinal engagement patterns in a digital diabetes prevention program.
- To explore the relationship between engagement personas, user demographics, and health outcomes.
Main Methods:
- A two-step clustering approach was used on data from 1613 users.
- Univariate k-means clustering analyzed app- and program-feature usage separately.
- Bivariate clustering combined univariate results to define engagement personas.
Main Results:
- Univariate analyses yielded five app-feature clusters and four program-feature clusters.
- Bivariate analysis identified five unique engagement personas, representing 76% of users.
- Engagement personas demonstrated significant differences in member demographics and weight loss outcomes.
Conclusions:
- Engagement personas provide a valuable framework for understanding user behavior in digital health.
- Personalizing digital health interventions based on engagement personas can optimize user experience.
- Characterizing engagement personas can inform strategies to improve engagement and effectiveness in digital health programs.
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