Adapting Behavioral Interventions for Social Media Delivery
UMass Chan Affiliations
Prevention Research CenterDepartment of Quantitative Health Sciences
Department of Medicine, Division of Preventive and Behavioral Medicine
Document Type
Journal ArticlePublication Date
2016-01-29Keywords
behavioral interventionshealth behavior
online social networks
social media
UMCCTS funding
Behavior and Behavior Mechanisms
Health Psychology
Telemedicine
Metadata
Show full item recordAbstract
Patients are increasingly using online social networks (ie, social media) to connect with other patients and health care professionals--a trend called peer-to-peer health care. Because online social networks provide a means for health care professionals to communicate with patients, and for patients to communicate with each other, an opportunity exists to use social media as a modality to deliver behavioral interventions. Social media-delivered behavioral interventions have the potential to reduce the expense of behavioral interventions by eliminating visits, as well as increase our access to patients by becoming embedded in their social media feeds. Trials of online social network-delivered behavioral interventions have shown promise, but much is unknown about intervention development and methodology. In this paper, we discuss the process by which investigators can translate behavioral interventions for social media delivery. We present a model that describes the steps and decision points in this process, including the necessary training and reporting requirements. We also discuss issues pertinent to social media-delivered interventions, including cost, scalability, and privacy. Finally, we identify areas of research that are needed to optimize this emerging behavioral intervention modality.Source
J Med Internet Res. 2016 Jan 29;18(1):e24. doi: 10.2196/jmir.5086. Link to article on publisher's site
DOI
10.2196/jmir.5086Permanent Link to this Item
http://hdl.handle.net/20.500.14038/39952PubMed ID
26825969Related Resources
Rights
Copyright Sherry Pagoto, Molly E Waring, Christine N May, Eric Y Ding, Werner H Kunz, Rashelle Hayes, Jessica L Oleski. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.Scopus Count
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