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      Assessment of Adaptive Engagement and Support Model for People With Chronic Health Conditions in Online Health Communities: Combined Content Analysis

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          Abstract

          Background

          With the pervasiveness of social media, online health communities (OHCs) are an important tool for facilitating information sharing and support among people with chronic health conditions. Importantly, OHCs offer insight into conversations about the lived experiences of people with particular health conditions. Little is known about the aspects of OHCs that are important to maintain safe and productive conversations that support health.

          Objective

          This study aimed to assess the provision of social support and the role of active moderation in OHCs developed in accordance with and managed by an adaptive engagement model. This study also aimed to identify key elements of the model that are central to the development, maintenance, and adaptation of OHCs for people with chronic health conditions.

          Methods

          This study used combined content analysis, a mixed methods approach, to analyze sampled Facebook post comments from 6 OHCs to understand how key aspects of the adaptive engagement model facilitate different types of social support. OHCs included in this study are for people living with multiple sclerosis, migraine, irritable bowel syndrome, rheumatoid arthritis, lung cancer, and prostate cancer. An exploratory approach was used in the analysis, and initial codes were grouped into thematic categories and then confirmed through thematic network analysis using the Dedoose qualitative analysis software tool. Thematic categories were compared for similarities and differences for each of the 6 OHCs and by topic discussed.

          Results

          Data on the reach and engagement of the Facebook posts and the analysis of the sample of 5881 comments demonstrate that people with chronic health conditions want to engage on the web and find value in supporting and sharing their experiences with others. Most comments made in these Facebook posts were expressions of social support for others living with the same health condition (3405/5881, 57.89%). Among the comments with an element of support, those where community members validated the knowledge or experiences of others were most frequent (1587/3405, 46.61%), followed by the expression of empathy and understanding (1089/3405, 31.98%). Even among posts with more factual content, such as insurance coverage issues, user comments still had frequent expressions of support for others (80/213, 37.5%).

          Conclusions

          The analysis of this OHC adaptive engagement model in action shows that the foundational elements—social support, engagement, and moderation—can effectively be used to provide a rich and dynamic community experience for individuals with chronic health conditions. Social support is demonstrated in a variety of ways, including sharing information or validating information shared by others, expressions of empathy, and sharing encouraging statements with others.

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          Most cited references80

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          The relationship between social support and physiological processes: a review with emphasis on underlying mechanisms and implications for health.

          In this review, the authors examine the evidence linking social support to physiological processes and characterize the potential mechanisms responsible for these covariations. A review of 81 studies revealed that social support was reliably related to beneficial effects on aspects of the cardiovascular, endocrine, and immune systems. An analysis of potential mechanisms underlying these associations revealed that (a) potential health-related behaviors do not appear to be responsible for these associations; (b) stress-buffering effects operate in some studies; (c) familial sources of support may be important; and (d) emotional support appears to be at least 1 important dimension of social support. Recommendations and directions for future research include the importance of conceptualizing social support as a multidimensional construct, examination of potential mechanisms across levels of analyses, and attention to the physiological process of interest.
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            Social Media Use in the United States: Implications for Health Communication

            Background Given the rapid changes in the communication landscape brought about by participative Internet use and social media, it is important to develop a better understanding of these technologies and their impact on health communication. The first step in this effort is to identify the characteristics of current social media users. Up-to-date reporting of current social media use will help monitor the growth of social media and inform health promotion/communication efforts aiming to effectively utilize social media. Objective The purpose of the study is to identify the sociodemographic and health-related factors associated with current adult social media users in the United States. Methods Data came from the 2007 iteration of the Health Information National Trends Study (HINTS, N = 7674). HINTS is a nationally representative cross-sectional survey on health-related communication trends and practices. Survey respondents who reported having accessed the Internet (N = 5078) were asked whether, over the past year, they had (1) participated in an online support group, (2) written in a blog, (3) visited a social networking site. Bivariate and multivariate logistic regression analyses were conducted to identify predictors of each type of social media use. Results Approximately 69% of US adults reported having access to the Internet in 2007. Among Internet users, 5% participated in an online support group, 7% reported blogging, and 23% used a social networking site. Multivariate analysis found that younger age was the only significant predictor of blogging and social networking site participation; a statistically significant linear relationship was observed, with younger categories reporting more frequent use. Younger age, poorer subjective health, and a personal cancer experience predicted support group participation. In general, social media are penetrating the US population independent of education, race/ethnicity, or health care access. Conclusions Recent growth of social media is not uniformly distributed across age groups; therefore, health communication programs utilizing social media must first consider the age of the targeted population to help ensure that messages reach the intended audience. While racial/ethnic and health status–related disparities exist in Internet access, among those with Internet access, these characteristics do not affect social media use. This finding suggests that the new technologies, represented by social media, may be changing the communication pattern throughout the United States.
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              The influence of social support on chronic illness self-management: a review and directions for research.

              A review of the empirical literature examining the relationship between social support and chronic illness self-management identified 29 articles, of which 22 were quantitative and 7 were qualitative. The majority of research in this area concerns diabetes self-management, with a few studies examining asthma, heart disease, and epilepsy management. Taken together, these studies provide evidence for a modest positive relationship between social support and chronic illness self-management, especially for diabetes. Dietary behavior appears to be particularly susceptible to social influences. In addition, social network members have potentially important negative influences on self-management There is a need to elucidate the underlying mechanisms by which support influences self-management and to examine whether this relationship varies by illness, type of support, and behavior. There is also a need to understand how the social environment may influence self-management in ways other than the provision of social support
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J. Med. Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                July 2020
                7 July 2020
                : 22
                : 7
                : e17338
                Affiliations
                [1 ] Health Union, LLC Philadelphia, PA United States
                [2 ] Department of Health Behavior Gillings School of Global Public Health University of North Carolina at Chapel Hill Chapel Hill, NC United States
                Author notes
                Corresponding Author: Brian M Green brian.m.green@ 123456health-union.com
                Author information
                https://orcid.org/0000-0003-0633-7651
                https://orcid.org/0000-0002-6901-9362
                https://orcid.org/0000-0002-7497-9480
                https://orcid.org/0000-0002-2542-303X
                https://orcid.org/0000-0003-4053-6689
                https://orcid.org/0000-0002-4089-7508
                Article
                v22i7e17338
                10.2196/17338
                7380984
                32492651
                0643813f-0e40-49b5-9315-63eaf441fb33
                ©Brian M Green, Katelyn Tente Van Horn, Ketki Gupte, Megan Evans, Sara Hayes, Amrita Bhowmick. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 07.07.2020.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), 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.

                History
                : 8 December 2019
                : 6 January 2020
                : 1 March 2020
                : 3 June 2020
                Categories
                Original Paper
                Original Paper

                Medicine
                social media,social support,health education,qualitative research,patient empowerment
                Medicine
                social media, social support, health education, qualitative research, patient empowerment

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