Go to YouTube and Call Me in the Morning: Use of Social Media for Chronic Conditions

Forthcoming, MIS Quarterly

47 Pages Posted: 30 Oct 2017 Last revised: 4 Mar 2019

See all articles by Xiao Liu

Xiao Liu

University of Utah

Bin Zhang

University of Arizona - Eller College of Management

Anjana Susarla

Michigan State University - The Eli Broad College of Business and The Eli Broad Graduate School of Management

Rema Padman

School of Information Systems and Management, The H. John Heinz III College

Date Written: February 2019

Abstract

Video sharing social media platforms, such as YouTube, offer an effective way to deliver medical information. Few studies have identified evidence-backed digital therepautics as well as technology-enabled interventions to improve the ease with which patients can retrieve medical information to manage chronic conditions. We propose an interdisciplinary lens that synthesizes deep learning methods with themes emphasized in Information Systems (IS) and Healthcare Informatics (HIS) research to examine user engagement with encoded medical information in YouTube videos. We first use a bidirectional long short-term memory (BLSTM) method to identify medical terms in videos and then classify videos based on whether they encode a high or low degree of medical information. We then employ principal component analysis on aggregate video data to discover three dimensions of collective engagement with videos: non-engagement, selective attention driven engagement, and sustained attention driven engagement. Videos with low medical information result in non-engagement; at the same time, videos with a greater amount of encoded medical information struggle to maintain sustained attention driven engagement. Our study provides healthcare practitioners and policymakers with a nuanced understanding of how users engage with medical information in video format. Our research also contributes to enhancing current public health practices by promoting normative guidelines for educational video content enabling management of chronic conditions.

Keywords: visual social media, healthcare informatics, digital therapeutics, chronic diseases, deep learning, Bidirectional Long Short-term Memory (BLSTM), Convolutional Neural Network (CNN), collective engagement

JEL Classification: C31, C20, C39

Suggested Citation

Liu, Xiao and Zhang, Bin and Susarla, Anjana and Padman, Rema, Go to YouTube and Call Me in the Morning: Use of Social Media for Chronic Conditions (February 2019). Forthcoming, MIS Quarterly. Available at SSRN: https://ssrn.com/abstract=3061149 or http://dx.doi.org/10.2139/ssrn.3061149

Xiao Liu

University of Utah ( email )

1645 E. Campus Center
Salt Lake City, UT 84112
United States

Bin Zhang

University of Arizona - Eller College of Management ( email )

1130 E. Helen St
RM430Z
Tucson, AZ 85721
United States
(520) 626-9239 (Phone)

Anjana Susarla (Contact Author)

Michigan State University - The Eli Broad College of Business and The Eli Broad Graduate School of Management ( email )

East Lansing, MI 48824-1121
United States

Rema Padman

School of Information Systems and Management, The H. John Heinz III College ( email )

Pittsburgh, PA 15213-3890
United States

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