Predicting intentions to seek health information online : an integrated model.

As a society, there is a growing trend towards health wellness and proactive health behaviours, one fundamental health behaviours is health information seeking. In the recent years, individuals have increasingly turned to health information seeking through an online system over other channels of information (Tu, 2011). The potential impact and value of online health information has also been recognised by researchers, health professionals, and public and private organisations across the world (Goldzweig et al., 2013). In 2017, more than $1.5 billion was invested in online health information initiatives in the US (Jain et al., 2017), and in New Zealand, the health information website, Health Navigator New Zealand, received nationwide support and funding from 16 district health boards. However, many of these online health initiatives have not experienced the expected uptake from consumers, and these initiatives are costly for the online system providers. Therefore it is important to understand the factors that influence individuals’ intentions to seek health information using online systems. Some studies have adapted established theory to explain intentions towards online health information seeking, while other studies have focused on exploring salient factors, many of which are vastly different to those modelled in established theory. However, few studies have provided a comprehensive model combining these factors together, and in particular, little attention has been given to incorporating information- and system-related factors from the technological environment. This study aims to address this gap in the current understanding of online health information seeking, by focusing on the information and system factors that influence intentions to seek health information online. To achieve this, the literature was reviewed and a theoretical model was developed from key concepts and theories (Theory of Planned Behaviour (Ajzen, 1991), Technology Acceptance Model (Davis, 1989) and Wixom and Todd’s (2005) User Satisfaction and Technology Acceptance Model), which included information quality, system quality, source credibility, information satisfaction, system satisfaction, perceived usefulness, perceived ease of use, attitude, self-efficacy, social influence, past use, and intentions. Hypotheses were developed to understand the importance and impact of each model construct, and the data collected from health information seekers in New Zealand was analysed using Partial Least Squares Path Modeling. The results of the analysis showed support for the integration of information- and system-related factors in understanding intentions to seek health information using online systems and provided a broad view of online health information seeking intentions from both social psychology and information systems perspectives. This incorporation and emphasis of information- and system-related factors can inform online health information system providers to design, develop, and improve their systems to target the specific factors important to online health information seekers