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Inaccurate Health Information

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In this era of abundant and accessible health information especially through health portals and websites, Unvalidated Sources of Health Information (USHI) like health information presented through social network sites (SNS), blogs, forums, private websites and the likes, also pervade the web. Many times, the information on these platforms are incomplete, incorrect, outdated or plainly misleading and can be perilous to their consumers [1]. Patients, relatives of patients, or friends of patients utilize these platforms for a plethora of reasons ranging from guidance on major and minor health decisions to the desire for support from other users [30]. Support, as used here, could be emotional, social or financial and is usually gained by patients …show more content…

Nevertheless, the use of social networks, forums, and blogs, as platforms for USHI has continued to thrive in the healthcare sphere [18]. As a consequence, the health risks that the consumption of inaccurate health information portends, is a source of concern to stakeholders in the healthcare industry [1, 2, 19, 20]. Sometimes these inaccurate health information are ensconced in content to deliberately mislead people [1, 3], however, many a times they are not (at least not deliberately) …show more content…

However, unlike other research that attempt to predict the adoption or success of technologies based on predefined constructs (antecedents), we argue that the most useful studies on USHI will be those that attempt to “reverse-engineer” its success, going even beyond standard antecedents with a view to identifying key components that inform those antecedents which in turn result in the success of the technology. This approach as proposed by Benbasat and Barki [26] for the technology acceptance model is believed to be able to help generate actionable information on how to “create” the antecedents to the desired success of information technology artifacts. Some applicable theories that can be reverse-engineered

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