Authors’ Response to Peer Reviews of “The Exchange of Informational Support in Online Health Communities at the Onset of the COVID-19 Pandemic: Content Analysis” (Preprint)

PurposeAn empirical study investigated the antecedents to perceived usefulness (PU) and its consequences in the context of smoking cessation online health communities (OHCs).Design/methodology/approachTo validate a research model for perceived informational support, perceived emotional support and perceived esteem support, the authors conducted a partial-least-squares analysis of empirical data from an online survey (N = 173) of users of two smoking cessation OHCs. The proposed model articulates these as antecedents to PU from a social support perspective, and knowledge sharing and continuance intention are expressed as consequences of PU.FindingsThe empirical study identified that the PU of smoking cessation OHCs is influenced by perceived emotional support and perceived esteem support, and perceived informational support indirectly affects PU via these factors. In turn, PU exerts a positive influence on both knowledge sharing and continuance intention. Also, knowledge sharing positively affects continuance intention.Originality/valueThe study contributes to scholarship on users' postadoption behavior in the context of smoking cessation OHCs by disentangling the antecedents to PU from a social support perspective and pinpointing some important consequences of PU. The research also has practical implications for managing smoking cessation OHCs.

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Disentangling the effects of efficacy-facilitating informational support on health resilience in online health communities based on phrase-level text analysis

Information & Management ◽

10.1016/j.im.2020.103372 ◽

2020 ◽

Vol 57 (8) ◽

pp. 103372

Author(s):

Insu Park ◽

Surendra Sarnikar ◽

Jeewon Cho

Keyword(s):

Text Analysis ◽

Informational Support ◽

Online Health Communities ◽

Health Communities

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Online Health Communities and Health Literacy

User-Driven Healthcare ◽

10.4018/978-1-4666-2770-3.ch010 ◽

2012 ◽

pp. 180-196 ◽

Cited By ~ 1

Author(s):

Erin Willis ◽

Ye Wang ◽

Shelly Rodgers

Keyword(s):

Weight Loss ◽

Content Analysis ◽

Health Literacy ◽

The Other ◽

Online Health Communities ◽

The Third ◽

Health Communities ◽

The Biggest Loser ◽

Practical Implications

The purpose of the chapter is to define health literacy and e-health literacy in the context of online health communities (OHCs). The chapter has three sections. The first section defines and discusses features of OHCs. The second section defines health literacy and e-health literacy, including domains of health literacy, which, as the authors argue, is necessary for a greater understanding of health literacy and OHCs. The third section applies the health literacy domains using The Biggest Loser League weight-loss OHC as a case study. A content analysis of posts was conducted between September 1, 2009 and December 31, 2009. Domains of health literacy were coded. Results show that functional literacy and interactive literacy were present in the OHC discussions to a greater degree than any of the other health literacy domains examined. Results are discussed in light of health literacy and e-health literacy, and practical implications of OHCs are explored.

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Understanding users’ participation in online health communities: A social capital perspective

Information Development ◽

10.1177/0266666919864620 ◽

2019 ◽

Vol 36 (3) ◽

pp. 403-413 ◽

Cited By ~ 2

Author(s):

Tao Zhou

Keyword(s):

Social Capital ◽

Emotional Support ◽

Health Knowledge ◽

Social Capital Theory ◽

Informational Support ◽

Capital Theory ◽

Online Health Communities ◽

The Social ◽

Health Communities ◽

Social Capital Perspective

Due to the intense competition, it is crucial for online health communities to facilitate users’ participation and retain them. Drawing on the social capital theory, this research examined users’ participation in online health communities. The results indicated that social support, which includes informational support and emotional support, has a significant effect on social capital, which in turn affects users’ participation including health knowledge acquisition and contribution. The results imply that online health communities need to create a supportive climate in order to develop social capital and facilitate users’ participation.

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Exploring the Factors Influencing Consumers to Voluntarily Reward Free Health Service Contributors in Online Health Communities: Empirical Study (Preprint)

10.2196/preprints.16526 ◽

2019 ◽

Author(s):

Junjie Zhou ◽

Fang Liu ◽

Tingting Zhou

Keyword(s):

Social Interaction ◽

Health Service ◽

Emotional Support ◽

Social Norm ◽

Health Knowledge ◽

Informational Support ◽

Online Health Communities ◽

Factors Influencing ◽

Norm Compliance ◽

Health Communities

BACKGROUND Rewarding health knowledge and health service contributors with money is one possible approach for the sustainable provision of health knowledge and health services in online health communities (OHCs); however, the reasons why consumers voluntarily reward free health knowledge and health service contributors are still underinvestigated. OBJECTIVE This study aimed to address the abovementioned gap by exploring the factors influencing consumers’ voluntary rewarding behaviors (VRBs) toward contributors of free health services in OHCs. METHODS On the basis of prior studies and the cognitive-experiential self-theory (CEST), we incorporated two health service content–related variables (ie, informational support and emotional support) and two interpersonal factors (ie, social norm compliance and social interaction) and built a proposed model. We crawled a dataset from a Chinese OHC for mental health, coded it, extracted nine variables, and tested the model with a negative binomial model. RESULTS The data sample included 2148 health-related questions and 12,133 answers. The empirical results indicated that the effects of informational support (β=.168; P<.001), emotional support (β=.463; P<.001), social norm compliance (β=.510; P<.001), and social interaction (β=.281; P<.001) were significant. The moderating effects of social interaction on informational support (β=.032; P=.02) and emotional support (β=−.086; P<.001) were significant. The moderating effect of social interaction on social norm compliance (β=.014; P=.38) was insignificant. CONCLUSIONS Informational support, emotional support, social norm compliance, and social interaction positively influence consumers to voluntarily reward free online health service contributors. Social interaction enhances the effect of informational support but weakens the effect of emotional support. This study contributes to the literature on knowledge sharing in OHCs by exploring the factors influencing consumers’ VRBs toward free online health service contributors and contributes to the CEST literature by verifying that the effects of experiential and rational systems on individual behaviors can vary while external factors change.

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

10.2196/preprints.17338 ◽

2019 ◽

Author(s):

Brian M Green ◽

Katelyn Tente Van Horn ◽

Ketki Gupte ◽

Megan Evans ◽

Sara Hayes ◽

...

Keyword(s):

Social Support ◽

Content Analysis ◽

Insurance Coverage ◽

Software Tool ◽

Health Condition ◽

Chronic Health Conditions ◽

Health Conditions ◽

Chronic Health ◽

Online Health Communities ◽

Health Communities

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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