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We first use a bidirectional long short-term memory 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: nonengagement, selective attention-driven engagement, and sustained attention-driven engagement. Videos with low medical information result in nonengagement; 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.<\/jats:p>","DOI":"10.25300\/misq\/2020\/15107","type":"journal-article","created":{"date-parts":[[2020,3,4]],"date-time":"2020-03-04T16:13:37Z","timestamp":1583338417000},"page":"257-284","source":"Crossref","is-referenced-by-count":85,"title":["Go To YouTube and Call Me in the Morning: Use of Social Media for Chronic Conditions"],"prefix":"10.25300","volume":"44","author":[{"given":"Xiao","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Information Systems, W. P. Carey School of Business, Arizona State University, Tempe, AZ 85287 U.S.A."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Eller College of Management, University of Arizona, Tucson, AZ 85721-0108 U.S.A."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anjana","family":"Susarla","sequence":"additional","affiliation":[{"name":"Eli Broad College of Business, Michigan State University, East Lansing, MI 48824 U.S.A."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rema","family":"Padman","sequence":"additional","affiliation":[{"name":"Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, PA 15213-3890 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