Learning to be Proficient? A Structural Model of User Dynamic Engagement in E-Health Interventions

33 Pages Posted: 21 Apr 2022

See all articles by Tongxin Zhou

Tongxin Zhou

Arizona State University (ASU) - Department of Information Systems

Yingfei Wang

University of Washington - Michael G. Foster School of Business

Lu (Lucy) Yan

Indiana University - Kelley School of Business - Department of Operation & Decision Technologies

Yong Tan

University of Washington - Michael G. Foster School of Business

Date Written: March 24, 2022

Abstract

User attrition has been a major challenge confronted by eHealth interventions. In this study, we aim to examine how individuals dynamically engage in eHealth interventions to shed light on users’ continued participation. In the participation process, users’ intervention perceptions play an important role in affecting their subsequent participation decisions. To capture the updates in individuals’ intervention perceptions and the associated behavior dynamics, we establish a hierarchical Bayesian learning framework to structurally characterize individuals’ decision-making processes. Through analysis of a 4-month dataset collected for users’ intervention participation in an online weight-loss platform, our study provides empirical evidence for individuals’ learning behaviors in online health management. That is, we show that although individuals tend to have inaccurate perceptions of intervention effectiveness initially, they can significantly improve their intervention perceptions during continuous participation. Despite this learning, we find that users’ learning efficiency can vary across intervention types, depending on the level of noise contained in the intervention experiences. When users are unable to accurately infer the effectiveness of eHealth interventions, they are more likely to discontinue their usage in subsequent periods. Therefore, to help users improve their learning efficiency, we further propose several learning schemes to help individuals “de-noise” their intervention experiences. Our empirical estimation also reveals individual heterogeneity in experienced intervention effectiveness and users’ preference structure for descriptive intervention features. These findings provide various implications for user engagement and healthcare platform design.

Keywords: personal health management, lifestyle change, eHealth interventions, Bayesian learning, perceptions of interventions, dynamic participation

Suggested Citation

Zhou, Tongxin and Wang, Yingfei and Yan, Lu (Lucy) and Tan, Yong, Learning to be Proficient? A Structural Model of User Dynamic Engagement in E-Health Interventions (March 24, 2022). Available at SSRN: https://ssrn.com/abstract=4066017 or http://dx.doi.org/10.2139/ssrn.4066017

Tongxin Zhou (Contact Author)

Arizona State University (ASU) - Department of Information Systems ( email )

Tempe, AZ
United States

Yingfei Wang

University of Washington - Michael G. Foster School of Business ( email )

Box 353200
Seattle, WA 98195-3200
United States

Lu (Lucy) Yan

Indiana University - Kelley School of Business - Department of Operation & Decision Technologies ( email )

Department of Operations and Decision Technologies
1309 E. Tenth Street
Bloomington, IN 47401
United States

Yong Tan

University of Washington - Michael G. Foster School of Business ( email )

Box 353226
Seattle, WA 98195-3226
United States

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