JCPSLP Vol 18 no 2 July 2016

of health-information searchers reported starting at a general search engine (Fox & Duggan, 2013), with Google being the most preferred by far. Thirteen per cent started at a familiar health hub (e.g., WebMD), while others follow recommendations from friends or family (Fox & Duggan, 2013). In a review of search trend research from 1997 to 2003, Spink and Jansen (2004) reported that around 1 in 3 web searchers used only one search term, and that 2 in 3 web users did not reformulate or modify their terms after an initial query. Few searchers make use of advanced features, such as Boolean operators. Users on average viewed only 5 documents per query, and most did not look beyond the second page of results (Spink & Jansen, 2004). Finally, only a quarter of health searches consistently check for the source and recency of on-line information (Fox, 2006). While it would appear that the search strategies of the average user are not sophisticated, there are certain exceptions. Parents of children with disability or health conditions, for instance, exercise greater caution on average than other on-line health searchers. Parents of children with hearing impairment interviewed by Porter and Edirippulige (2007) expressed a desire for more unbiased, objective, and evidence-based information available to families on-line. Parents spent longer on each search than non-parents, visited multiple sites, and were more likely to check their findings with a health professional (Porter & Edirippulige, 2007). The on-line search behaviours of parents have been examined extensively. Parents of children with genetic disorders interviewed by Roche and Skinner (2009) reported high rates of health-related internet use, with 83% of parents receiving on-line information about their child’s condition, and 69% searching for this information themselves. Like most health searchers, parents typically begin their searches in engines, using keywords relating to their child’s symptoms or diagnostic label (Porter & Edirippulige, 2007; Roche & Skinner, 2009). Their reasons for searching the Internet vary greatly. In a UK survey of 788 carers of children with disability, 72% of those who had used the Internet had searched for general information on benefits, services, or their child’s medical condition, while 36% had used it to locate and make contact with specific service providers (Blackburn & Read, 2005). While many parents report success in locating relevant information, their success often depends on the type of guidance being sought. For some parents in Roche and Skinner’s study (2009), Internet searches about their child’s condition resulted in unwanted clinical images, genetic information or prognostic predictions, while guidance around broader issues such as inclusion was scant. As one parent reflected: “[The Internet] doesn’t really have what I’m looking for. I know what’s it’s like to be the parent of [an affected] child. I need to know [how to] help them succeed, help them be productive citizens” (p. 124). In Porter and Edirippulige’s study (2007), parents of Australian children with hearing loss wanted more on-line information on topics such as education, intervention, and technology options, and guidance around family support services, as well as personal stories from other families. Parents of children who use AAC technology have described similar information needs (Anderson, Balandin, & Stancliffe, 2016). In their review paper concerning parents of children with disability, Zaidman-Zait and Jamieson (2007) stress that professionals should be: “aware of the Web sites most likely to be accessed by the parents with whom they work … parents may be accumulating both information and misinformation” (p. 20). The same could easily be said for

AAC consumers, and yet there is a dearth of research into the on-line information search behaviours of people who use AAC and their support networks. Further, despite the large amount of AAC information available on the web little is known about its visibility and accessibility to naïve stakeholders (i.e., first-time AAC searchers). The aim of this study was to examine the range, relevance, and credibility of AAC information retrieved as the result of conducting a series of keyword searches, using the popular search engine Google. Research questions The study sought to answer the following questions, using descriptive analysis of search-engine results: • When a naïve (first-time) keyword search relating to AAC is performed: – what percentage of the resulting websites bear relevance to Australian AAC stakeholders? – what is the primary purpose of resulting websites, and how does this vary based on the type of search performed? • For sites with the primary purpose of information or knowledge translation: – which populations and ages does the information focus on? – how do the sites perform against common credibility measures? – is there any relationship between these credibility measures? Method To sample the range of asynchronous AAC resources available, we conducted a targeted English-language search from an Australian location, using the popular engine Google (www.google.com.au). Our method was largely borrowed from the field of search-engine optimisation (SEO) research. Engines such as Google employ a set of rules (search algorithms) to determine the placement of websites in the resulting hierarchy. These algorithms are based on a number of factors (e.g., the number and source of links to the site, the number of social media shares, and the frequency of traffic), with some factors weighted as more important than others. In the current study, SEO keyword methods were applied to predict the public search behaviours associated with a specific concept (AAC). Selection of search terms When a member of the general public is looking for information on AAC, which keywords are they likely to search? We probed this initial question using the free keyword research tool from SEOBook: http://tools. seobook.com/keyword-tools/seobook/. This tool shows the approximate usage frequencies of keyword search strings, based on data published by Google and Yahoo. Two keyword branches (communication and communication device) were used as starter strings for this investigation. Table 1 lists the first five AAC-related terms that appeared in the top-100 keywords containing these two search strings. In addition to these 10 terms, the acronym “AAC” and three terms relating to diagnostic populations who frequently use AAC (aphasia, autism, and cerebral palsy) were included. A final term, communication app , was also included. Although this term did not appear within the top-100 keywords for communication, the recent rise in mobile AAC technology warrants its use in this study. The full list of terms and their usage frequencies can be seen in table 1.

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JCPSLP Volume 18, Number 2 2016

Journal of Clinical Practice in Speech-Language Pathology