Classification Model Development for Factor Pathway Leading to Online Health Intention Behavior

• In Event: HEALTHCARE MANAGEMENT: Machine Learning in Healthcare

Abstract

This study employs fuzzy-set qualitative comparative analysis (fsQCA) and neural networks (NN) in a sequence using online health care (eHealth) data. fsQCA can identify pathways that lead to eHealth behavior by utilizing the input conditions such as health information orientation, need for online social interaction, internet self-efficacy, internet use behavior, social media eHealth literacy and demographics. NN is applied to create classification models for pathways identified by fsQCA. The study offers recommendations to healthcare executives in educational or corporate organizations on how to develop and deliver eHealth information and potentially improve young adults’ well-being by positively influencing their eHealth behavioral intentions.

Authors

• Edwin Wang, University of Massachusetts Boston

• Adeela Gulzari, University of North Texas

• Victor Prybutok, University of North Texas

• Gayle Prybutok, University of North Texas