Chapter 11 introduces the concept of legitimation in discourse and considers how it might function, and be studied, in the context of health(care) communication. First, we look at how contributors to the online parenting forum Mumsnet use labels denoting attitudes towards vaccinations. We point out how labels that involve opposition to vaccinations, such as ‘anti-vaxxer’ tend to collocate with negation, and then consider how people justify negating the applicability of the label to themselves. This reveals a range of different concerns around vaccinations. We then draw on a study of patient feedback in which we examined how patients legitimate their perspectives and the evaluations they gave in their feedback. For example, this included patients representing themselves as experienced users of healthcare services. Additionally, some patients used aspects of their identities to position themselves as requiring attention, while others used techniques such as employing second person pronouns to imply that their experiences could be generalised to other patients.

Chapter 7 considers how language change over short timespans can be examined using corpus-assisted methods. We present three case studies. The first study involves a corpus of patient feedback relating to cancer care, collected for four consecutive years. A technique called the coefficient of variation was used to identify lexical items that had increased or decreased over time. The second study considered UK newspaper articles about obesity. To examine changing themes over time, we employed a combination of keyness and concordance analyses to identify which themes in the corpus were becoming more or less popular over time. Additionally, the analysis considered time in a different way, by using the concept of the annual news cycle. To this end, the corpus was divided into 12 parts, consisting of articles published according to a particular month, and the same type of analysis was applied to each part. The third case study involves an analysis of a corpus of forum posts about anxiety. Time was considered in terms of the age of the poster and in terms of the number of contributions that a poster had made to the forum, and differences were found depending on both approaches to time.

Chapter 6 shows how it is possible to use demographic metadata to study identities in health-related corpora. We present two case studies, based on research on patient feedback on NHS services in England. The first study compares how cancer patients of different age and sex groups evaluate healthcare services and, specifically, how they use distinct linguistic and rhetorical strategies to do this. The corpus was encoded with demographic metadata which allowed the researchers to explore the language used by people of different age and sex identity groups. For the second study, a different corpus of more general patient feedback was used, one which did not contain demographic information metadata. Instead, targeted searches were used to identify patients’ demographic characteristics based on cases where they made those characteristics explicit within their feedback. In contrasting these case studies, we also evaluate the two different approaches taken, considering the affordances and limitations of both. Taken together, the case studies demonstrate how language and identity can be explored in corpora with and without reliable demographic metadata.

Chapter 2 is concerned with research questions. We discuss the different processes through which research questions can be identified and developed in corpus-based research on health communication. Three case studies are considered. The first study involved the analysis of press representations of obesity. In this study, the researchers developed their own research questions in a variety of ways, including by drawing from the non-linguistic literature on obesity. The second study focused on the McGill Pain Questionnaire – a well-known language-based diagnostic tool for pain. A pain consultant asked the researchers if they could help understand why some patients find it difficult to respond to some sections of the questionnaire. In response, the researchers formulated a series of questions that could be answered using corpus linguistic tools, and identified some issues with the questionnaire that address the pain consultant’s concerns. The third study involved the analysis of patient feedback on the UK’s National Health Service. The researchers were approached by the NHS Feedback Team and given 12 questions that they were commissioned to answer by means of corpus linguistic methods.