Academic journal article International Journal of Cyber Society and Education

Exploring Users' Intention to Use Health Information on a Bulletin Board System

Academic journal article International Journal of Cyber Society and Education

Exploring Users' Intention to Use Health Information on a Bulletin Board System

Article excerpt

INTRODUCTION

Bulletin Board System (BBS), a popular social network community, allows people to manage and share their health information and experiences of treating their health issues. This creates a rich repository of user-generated content and becomes a popular and important source for users who need information for their health-related decisions (Adams, 2010). The system is dynamic, allowing new threads to be created and new posts to be attached to existing threads (Suzuki & Calzo, 2004). A variety of registered users, including professionals, amateurs, and beginners, can discuss topics freely on the classified boards and contribute their opinions on a certain topic. However, this digital environment has not received significant attention in research (Bond, Ahmed, Hind, Thomas, & Hewitt-Taylor, 2013). Thus, our research focuses on the health-related discussion boards on BBS.

FRAMEWORK AND HYPOTHESES FORMING

Figure 1 shows the proposed framework, and the following sections introduce the theoretical background and hypotheses building.

Cognitive fit theory, proposed by Vessey (1991), explains the fit relationships between information presentation and decision making. The 'fit' occurs when information presentation and the decision task are consistent. Mental representation is generated by reacting outside the stimulus, and the results are stored in working memory. Information presentation and the decision task both generate mental processes. If the mental processes are inconsistent, people need to make efforts to transfer information, and this extra work may deteriorate the speed of making decisions or lowering the accuracy of decisions (Rieh, 2002). When fit occurs, users need no additional efforts in handling the discrepancy. Thus, decision making can be more efficient and accurate. We include four factors: perceived readability, information presentation, information understandability, and subjective knowledge (Rajagopalan, Khanna, Leiter, Stott, Showalter, Dicker, & Lawrence, 2011) and build the following hypotheses:

Hypothesis 1: Information presentation is positively related to perceived readability when users evaluate health information on BBS.

Hypothesis 2: Information understandability is positively related to perceived readability when users evaluate health information on BBS.

Hypothesis 3: Subject knowledge is positively related to perceived readability when users evaluate health information on BBS.

Cognitive authority refers to the influences that users recognize as proper because the information is thought to be credible and worthy to believe (Rieh, 2002). It is operationalized as to the extent to which users believe that they can trust the information. It is tough for users to judge the quality of health information due to the lack of unified quality control mechanism. Therefore, by virtue of the method to judge in a realistic world, various referrals from friends, relatives, and referees and the perceptions of publishers' reputations are important resources to judge information quality. Therefore, we conceptualize the factors affecting the credibility of health information as threefold - information authority, word of mouth, and cognitive dissonance (Liu, Liu, & Li, 2012), and build the following hypotheses:

Hypothesis 4: Information authority is positively related to perceived credibility when users evaluate health information on BBS.

Hypothesis 5: Word-of-mouth is positively related to perceived credibility when users evaluate health information on BBS.

Hypothesis 6: Information diagnosticity is positively related to perceived credibility when users evaluate health information on BBS.

Expectation-confirmation theory (Oliver, 1980) presumes that consumers first form an initial expectation and then develop perceptions about the services' performance after consumption. The expectation is confirmed if the perceived efficacy matches their expectation. …

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