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The internet is playing an increasing role in medicine and health (Conrad & Stults, 2010; Riegelman & Persily, 2001). One manifestation of this development is the emergence of health internet-registers, the uses and impacts of which have been described and reviewed in a number of articles (see Drolet, & Johnson, 2008; van der Veer, de Keizer, Ravelli, Tenkink, & Jager, 2010). Such web-based registers have been developed and utilized for various different diseases, conditions, and disorders, such as: Diabetes (e.g., McKay, King, Eakin, Seeley, & Glasgow, 2001), Stroke (e.g., Asplund, Asberg, Norrving, Stegmayr, Terent, & Wester, 2003), and Autism Spectrum Disorders (e.g., Daniels, Rosenberg, Anderson, Law, Marvin, & Law, 2012). In Multiple Sclerosis (MS), there are several such internet-registers (Hurwitz, 2011); for example, the pilot UK MS Register (Ford, Jones, Middleton, Lockhart-Jones, Maramba, Noble, Osborne, & Lyons, 2012; Osborne, Noble, Lockhart, Middleton, Thompson, Maramba, Jones, & Ford, 2012). Such registers have potential to reach great numbers of people (see Epstein & Klinkenberg, 2002), and act as repositories for collecting wide-ranging data sets that can be updated regularly (e.g., Evans, & Mathur, 2005), generating an extremely useful clinical and research tool (see Daniels et al., 2012; van der Veer et al., 2010). Given their potential, it is vital to understand how these registers can be made as effective and efficient as possible.
There are recognized limitations to using the internet as a data-gathering vehicle for medicine and health. The internet is not accessible to all, leading to the ‘digital divide’ (Brodie, Flournoy, Altman, Blendon, Benson, & Rosenbaum, 2000; Watson, Bell, Kvedar, & Grant, 2008). For instance, some older people do not have access to the internet (over 40% of people older than 65 have never used the internet; Williams, 2011), nor, if they do have internet access, do they generally use it as regularly as younger people. However, this particular aspect of the ‘digital divide’ may be reducing over time (in 2000, 91% of those over 65 had not used the internet; ONS, 2000). For MS, this may not represent a major limitation, as, unlike some other chronic conditions (e.g., stroke), MS is not a condition that affects older people disproportionately (the average age of clinical onset is 30-33, and the greatest prevalence is 30-60; Acheson, 1977).
Such limitations aside, the internet community represents a large potential population that can be reached easily and quickly. However, even within the population accessible through internet-registers, there are still barriers to the usability and usefulness of such data-collecting methods. Internet-registers may be limited by the quality of the information that they collect, for instance in the range and quality of the questionnaires and measures deployed (Ebers, 2010). Another potential barrier to registers’ use and quality is their engagement of clinicians and patients (Carr, Howells, Chang, Hirji, & English, 2009; Powell, 2004). Therefore, it is important to identify barriers to use to eradicate as many obstacles as possible, and develop registers that are optimally useful and encourage respondents to return, providing continuing longitudinal data. The focus here will be on barriers, identified by people with MS, to using an internet-register.