Antecedents of privacy calculus components in virtual health communities
Introduction
With the rapid growth of social media technologies over the past decade, social networking websites that revolve around health and wellness topics are being increasingly adopted by individuals for health communications. For example, MedHelp.org with 17 million unique users per month, and DailyStrength.org with more than 500 support groups such as those related to cancer, diabetes, and depression, are among the major health-related websites in the United States. These health-specific online communities, called virtual health communities (VHCs), (Welbourne, Blanchard, & Wadsworth, 2013) or health online social networks (Sadovykh, Sundaram, & Piramuthu, 2015), provide users with various communication platforms such as physician-rating, medicine-rating, ask-an-expert, and discussion boards (Kordzadeh & Warren, 2013). Discussion boards, for instance, enable individuals to initiate discussion threads by posting questions concerning health and wellness topics. Users of these websites post replies to the threads and share their relevant knowledge and experience with the thread initiators, as well as other users who join the threads. Thus, health consumers such as patients and their families, friends, and caregivers exchange information and emotional support with each other in a convenient yet inexpensive way (Chou, Lin, & Huang, 2016).
The results of recent national surveys have confirmed the growing adoption of social media platforms for health communications. A survey conducted by the Pew Research Center (Fox & Duggan, 2013) revealed that 26% of adult internet users in that study had gone online to look at someone else’s health-related experience in the past year. Additionally, 16% of the respondents indicated that they looked online for other individuals with similar medical conditions to theirs. The results also demonstrated that 40% of the respondents had shared their health-related experiences in online environments (Fox & Duggan, 2013). Accordingly, the user-generated health-related knowledge shared in VHCs helps the community members learn from others’ experiences to make informed health decisions such as what doctor to choose, what medication to take, and how to cope with medical conditions (e.g., cancer and alcoholism) effectively (Sadovykh et al., 2015).
A major aspect of health communications via social media platforms is communicating personal health information (PHI) such as information related to one’s medical procedures, diagnosis, symptoms, medications, test results, and one’s feelings about their medical conditions. People engage in this form of PHI disclosure because of the benefits that this behavior may provide to them (Welbourne et al., 2013). Expecting to receive better support from the community, feeling emotionally relieved, and providing more useful information to the community are among the perceived benefits of PHI disclosure in online environments (Rodgers and Chen, 2005, Welbourne et al., 2013). However, sharing PHI in publicly available social media environments may entail privacy risks and concerns for information providers. For example, disclosing information about one’s medical conditions may lead to social stigma, job loss, or even criminal prosecutions in the cases such as drug abuse (Anderson and Agarwal, 2011, Beckerman and Foundation, 2008).
The trade-off between the expected outcomes and privacy concerns associated with communicating PHI in social media platforms are elucidated by the privacy calculus model (Culnan and Armstrong, 1999, Dinev and Hart, 2006). The two opposing factors in this theoretical model determines whether or not an individual engages in PHI disclosure behaviors. The privacy calculus balance between the drivers and barriers to PHI disclosure by individuals may vary. Those who are less concerned about their PHI privacy and expect to receive more benefits of PHI sharing may participate actively and share PHI more prevalently in online discussions. Whereas, those who exhibit a greater level of privacy concern may participate at a minimum level. The former group will help the community to prosper and succeed; while, the latter group may not contribute to the growth of the community. Thus, in order for community developers and providers to be able to boost user participation and enhance community growth, they need to understand the factors that impact the two opposing sides of the privacy calculus model in the context of health social media. In this research, we address this issue and investigate the potential determinants of the privacy calculus components. In particular, we examine the role of age, health status, and affective commitment.
The remainder of this article is structured as follows. The second section discusses the theoretical background of this research. The third section presents the research model and hypotheses. The fourth section describes the method. The fifth section discusses the results of our data analysis. Finally, the last two sections summarize the results and their implications, and also provide suggestions for future research.
Section snippets
Theoretical background: privacy calculus model
Westin (1967) defines privacy as “the claim of individuals…to determine for themselves when, how, and to what extent information about them is communicated to others. (p. 7)” The potential risks associated with personal information disclosure in different contexts makes people concerned about their privacy. However, people may still engage in personal information disclosure to gain some benefits, although they are aware of the potential risks of that. As mentioned earlier, these contrary
Age
Several years ago, when social media technologies initially came into existence, young people were the predominant users of those technologies (Acquisti & Gross, 2006). In today’s era of social media, however, people at various ages are users of these communication platforms. Compared with elderly people, younger individuals may still use social media differently and show different privacy-related behaviors. In general, extant literature has revealed that age can play a major role in online
Method
To test the proposed hypotheses, we conducted a survey study and collected data from convenience samples of students, faculty, and staff at a large public university located in the southern United States. In order to enhance the diversity of the sample in terms of demographics and social media-related perceptions, beliefs, and experiences, we also collected data from a sample of visitors to clinics at a large hospital in the same area. However, the subjects from these sources were not mutually
Data analysis and results
We conducted two rounds of partial least square structural equation modeling (PLS_SEM) procedure using SmartPLS3. In the first round, we included the data collected from group 1 subjects (N = 116). In the second round, we eliminated the affective commitment construct from the model and performed another PLS-SEM using the data collected from group 2 subjects (N = 103). This would enable us to compare and contrast the results associated with those who are actual members of VHCs versus those who are
Discussion
The main objective of this study was to examine the potential antecedents of the privacy costs and expected benefits of PHI disclosure in health social media from a privacy calculus perspective. Our findings revealed that the balance between the elements of privacy calculus model can partially be determined by factors such as age, health status, and affective commitment.
The results regarding the antecedents of privacy concern is mixed. According to our results, neither age nor health status of
Conclusions
In line with the increasing use of social media technologies for peer-to-peer health communications, we adopted a privacy calculus perspective to investigate the antecedents of expected benefits and privacy concerns of communicating PHI in VHCs. According to our results, the privacy calculus trade-off in health social media can be influenced by age, health status, and affective commitment. Age and health status impact non-members’ privacy concerns but not members’ privacy concerns. Instead,
References (55)
- et al.
Patients’ and health professionals’ use of social media in health care: motives, barriers and expectations
Patient Education and Counseling
(2013) - et al.
Intentional social action in virtual communities
Journal of Interactive Marketing
(2002) - et al.
The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online
Decision Support Systems
(2010) - et al.
Understanding knowledge sharing in virtual communities: an integration of social capital and social cognitive theories
Decision Support Systems
(2006) - et al.
Fairness and devotion go far: integrating online justice and value co-creation in virtual communities
International Journal of Information Management
(2016) - et al.
An analysis of social support exchanges in online HIV/AIDS self-help groups
Computers in Human Behavior
(2009) - et al.
Social media self-efficacy and information evaluation online
Computers in Human Behavior
(2014) - et al.
A three-component conceptualization of organizational commitment
Human Resource Management Review
(1991) - et al.
Some antecedents and effects of trust in virtual communities
Journal of Strategic Information Systems
(2002) - et al.
Just what the doctor ordered: the role of information sensitivity and trust in reducing medical information privacy concern
Journal of Business Research
(2004)
Do decision-making structure and sequence exist in health online social networks?
Decision Support Systems
Understanding online behavioural advertising: user knowledge: privacy concerns and online coping behaviour in Europe
Computers in Human Behavior
Motivations in virtual health communities and their relationship to community, connectedness and stress
Computers in Human Behavior
Cultivating the sense of belonging and motivating user participation in virtual communities: a social capital perspective
International Journal of Information Management
Imagined communities: awareness, information sharing, and privacy on the Facebook
Paper Presented at the Privacy Enhancing Technologies Conference.
The digitization of healthcare: boundary risks, emotion, and consumer willingness to disclose personal health information
Information Systems Research
Adoption of electronic health records in the presence of privacy concerns: the elaboration likelihood model and individual persuasion
MIS Quarterly
Using the internet for health-related activities: findings from a national probability sample
Journal of Medical Internet Research
Research note—the impact of community commitment on participation in online communities
Information Systems Research
Emotional approach coping and the effects of online peer-Led support group participation among patients with Breast cancer: a longitudinal study
Journal of Medical Internet Research
A delicate balance: behavioral health, patient privacy and the need to know
Validation in information systems research: a state-of-the-art assessment
MIS Quarterly
A socio-technical approach to knowledge contribution behavior: an empirical investigation of social networking sites users
International Journal of Information Management
An exploratory investigation of the relationships between consumer characteristicvs and information privacy
Marketing Management Journal
Social media use in the United States: implications for health communication
Journal of Medical Internet Research
Online social networking for health: how online social networking benefits patients
Paper presented at the international communication association virtual conference
Cited by (46)
A systematic analysis of failures in protecting personal health data: A scoping review
2024, International Journal of Information ManagementThe mediating role of perceived risks and benefits when self-disclosing: A study of social media trust and FoMO
2023, Computers and SecurityCitation Excerpt :Consequently, individuals perceive a loss of privacy as the price to pay for the benefits acquired when disclosing personal information on social media (Hui et al., 2006). Given its applicability within the context of behavioral studies, privacy calculus has been adapted in a variety of contexts, including e-commerce (Culnan and Armstrong, 1999), privacy concerns and trust (Dinev and Hart, 2006), virtual health communities (Kordzadeh et al., 2016), mobile apps (Wang et al., 2016), continued use, and IoT services (Kim et al., 2019). Notably, privacy calculus has been a popular choice among social media researchers (Krasnova et al., 2010, 2012; Min and Kim, 2015; Dienlin and Metzger, 2016), many of whom theorize the behavioral influence of social media using adapted versions.
One for all, all for one: Social considerations in user acceptance of contact tracing apps using longitudinal evidence from Germany and Switzerland
2022, International Journal of Information ManagementCitation Excerpt :Building on prior studies that have tested the privacy calculus model in the context of privacy-invasive IS such as social media (e.g., Krasnova, Spiekermann, Koroleva, & Hildebrand, 2010; Sun, Wang, Shen, & Zhang, 2015), we extend the boundaries of privacy calculus beyond the consideration of individual factors by taking into account the social factors. At the context level, with regard to our research site, we add to the literature on e-health and specifically CTA adoption, which to date has mainly focused on individual-level privacy risks (e.g., Kordzadeh, Warren, & Seifi, 2016; Wang, Duong, & Chen, 2016). Specifically, our contribution lies in illuminating the effects of the social risks (operationalized in this study as fear of mass surveillance) posed by a new digital CT solution in the eyes of users (De, Pandey & Pal, 2020).
Effect of privacy concerns and engagement on social support behaviour in online health community platforms
2022, Technological Forecasting and Social ChangeCitation Excerpt :However, existing literature has provided evidence of privacy related issues in different contexts, but scant attention has been paid to the impact of privacy concerns in the OHCs context (Shirazi et al., 2021; Zhang et al., 2018). While OHC literature has provided evidence on the impact of privacy concerns on trust (Bansal and Gefen, 2010), personal health information disclosure (Zhang et al., 2018), knowledge sharing intentions (Dang et al., 2020), or antecedents of privacy calculus model (Kordzadeh et al., 2016), it provides limited clues whether privacy concerns can influence individuals social support exchange behaviour in OHC platforms. Therefore, investigating the impact of privacy concern drivers (i.e., perceived control of information and privacy risk) on OHC members' social support exchange behaviour is critical.
Do ethics drive value co-creation behavior in online health communities?
2024, Information Technology and People