Article Preview
TopIntroduction
Online health communities (OHC) enable users to interact between each other and exchange health information and support (Liu et al., 2018; Liu et al., 2020a). Due to the advantages such as convenience and ubiquity, OHC have been popular among users. A recent report indicated that about 21.7% of internet users have adopted online medical services (CNNIC, 2021). Attracted by the great market potential, many firms have entered the market and created their OHC platforms. Among them, a few reputable OHC such as Chunyu and DXY have achieved success. Especially, the outbreak of COVID-19 has expedited OHC development as people stay at home and turn to OHC for health information and services. A main purpose of users’ participating in OHC is to seek health information, which gives them guidance and advice on certain diseases (Li and Wang, 2018). However, users often hesitate to adopt this information due to their doubt on the information credibility. They worry whether the information source is reliable and the information posted on OHC is accurate. If they lack the intention to adopt and follow this information, they may discontinue their usage, which may undermine the sustainable development of OHC. Thus, OHC need to understand the factors affecting users’ information adoption intention in order to facilitate their usage behaviour.
Previous research has examined OHC users’ knowledge sharing (Yan et al., 2016; Zhang et al., 2017b; Meng et al., 2021), health information disclosure (Kordzadeh and Warren, 2017; Zhang et al., 2018), and value co-creation (Liu et al., 2020b). Various factors such as social support, motivations, and privacy concern are found to affect OHC user behaviour. However, it has seldom examined users’ information adoption intention. As noted earlier, users’ information adoption is crucial to the success of OHC. If users are not willing to adopt the information posted on OHC, they may feel that OHC are useless to their life and drop their usage. This may lead to the failure of OHC. Thus, it is necessary to identify the determinants of OHC users’ information adoption intention.
The purpose of this research is to examine OHC users’ information adoption intention. We integrate both perspectives of information factors and social interaction to examine their effects on user behaviour. On one hand, information factors such as argument quality and source credibility may affect users’ adoption decision. Both factors of argument quality and source credibility are drawn from the elaboration likelihood model (ELM) (Bhattacherjee and Sanford, 2006). Argument quality reflects information quality, whereas source credibility reflects the trustworthiness of information source. Users always expect to obtain credible and quality information from OHC. They cannot adopt unreliable information or poor quality information related to health.
On the other hand, users conduct frequent interactions between each other and develop social relationships on OHC. Then an individual user’s behaviour may receive influence from other members in the community. We propose that perceived similarity and perceived familiarity, both of which reflect social interaction (Liu et al., 2016), have an effect on users’ information adoption. Perceived similarity reflects the similarity between users’ views on diseases and treatment, whereas perceived familiarity reflects the interaction experience between users. In addition, we included both perceived usefulness and trust into the model to explore their effects on users’ adoption intention. We expect that the results can disclose the mechanism underlying OHC users’ information adoption and advance our understanding of OHC user behaviour.