Prosocial sharing health-related information on social media during a health crisis: a mixed-methods approach

A health crisis pertains to critical events associated with the emergence of health threats on a large scale in the community. While past health crises have similarly affected millions, constant social media coverage regarding the recent 2014 Ebola and 2019 COVID-19 pandemics has inflamed newly emerging issues relating to information overload and information of poor quality. During these health crises, online users have prosocially shared extensive health-related information (HRI) on social media with the belief that their information can support other users in providing early warnings about new diseases, raising social awareness, and spreading public health campaigns. Given the significant uses of social media in health crisis communication, there is scarce research discovering the motivations for prosocial sharing of HRI on social media in the health crisis context. Additionally, recent studies have discovered extensive information issues aroused in recent health crises without a clear investigation of the impacts of information risk perception on HRI-sharing behaviour. These give rise to a need for an empirical study exploring how the assessments of health and information quality risks and other motivational factors can affect prosocial sharing of HRI on social media during a health crisis. Based on the research gaps, this research proposes and tests a theoretical model of dual exchanging-protective motivations for prosocial sharing of HRI on social media during a health crisis. Specifically, the research explains the relationships between online users’ perceptions of health and information quality risks, motivational factors, and prosocial sharing of HRI. The developed research model was derived from the fear appeal model and social exchange theory. In particular, the fear appeal model suggested two stages of threat appraisal (i.e., perceptions of risks) and coping appraisal (i.e., online sharing as a coping measure) in the process underlying prosocial sharing. At the same time, social exchange theory suggested integrating social exchange factors (i.e., reciprocity and information verification cost) into the process. This research applies a sequential mixed-methods design to achieve the objectives and triangulate the research findings. The first stage of the research, as the main study (Study One), involves a quantitative approach using a survey to empirically test the theoretical model proposed from the two theories and relevant literature. The second stage, as the supporting study (Study Two), involves a qualitative approach with semi-structured interviews to check that the quantitative model developed and tested in Study One can be applied to explain prosocial sharing in a specific context, i.e., the COVID-19 pandemic in Vietnam. Additionally, the qualitative study can discover other possible factors that might be omitted from the model. In Study One, the model was validated by employing confirmatory factor analysis and partial least squares structural equation modelling on the survey data from 326 participants. The findings from the quantitative software SmartPLS 3.0 revealed that 56.7% of prosocial sharing can be explained by the research model. Specifically, perceived health risk and perceived information risk facilitated the coping appraisal and the consequent prosocial sharing behaviour. Both the protective motivations (i.e., prosocial sharing efficacy, sharing self-efficacy) and exchanging motivations (i.e., reciprocity expectation) were found to have positive impacts on prosocial sharing. In Study Two, responses from in-depth interviews with 14 Vietnamese participants from various backgrounds were analysed using thematic analysis via the qualitative software NVivo 12. The findings revealed a switching effect when online users preferred social media when obtaining and discussing HRI during the COVID-19 pandemic because of the sluggish information updates by traditional communication channels. Additionally, Study Two revealed different patterns in sharing HRI on social media before and during a health crisis. The qualitative findings supported the quantitative findings when confirming the impacts of perceived health risk, information quality risk, and dual exchanging-protective factors on prosocial sharing of HRI on social media. Moreover, other potential factors of prosocial sharing of HRI were also revealed: online recognition, qualified information accessibility, and social-oriented self. Regarding the impact of information verification cost on prosocial behaviour, the findings of Study Two provided further explanations for this relationship uncovered in Study One. Specifically, online users expressed their verification efforts before sharing, but it required less time and effort to perform the verification. Online users also revealed different verifying strategies, for example, source credibility checking and cross-checking. The study offers both theoretical and practical implications for the literature on prosocial behaviour and health crisis communication. The study unveils the motivations and the two-stage process underlying online prosocial sharing of HRI, which was under-researched in past studies. The study also extends the fear appeal model by incorporating social exchange factors and examining the extended model to explain online users’ health communications during a health crisis. The findings provide theoretical implications along with the two types of risk perceptions (i.e., health risk and information quality risk), motivational factors (social exchange factors and coping appraisal factors), and the process of prosocial sharing of HRI. Practically, for social media companies, this study confirms the common use of social media in health crisis communication and suggests further efforts to develop HRI-sharing features integrated with verification functions during health crises. The findings of this research suggest that health communicators should pay special attention to both health and information problems, which were found to have significant effects on user behaviour. Moreover, in addition to official channels, health communicators should adopt social media in disseminating health campaigns and incorporate exchanging-protective elements into their messages to enhance the sharing possibilities among online users.