Linguistic change in an online support group
AuthorMcDonald, Daniel James
AffiliationSchool of Languages and Linguistics
Melbourne Medical School Collected Works
Document TypePhD thesis
Access StatusOnly available to University of Melbourne staff and students, login required
© 2016 Dr Daniel James McDonald
Online support groups (OSGs) are popular sources of both health information and social support. Though early research into OSGs highlighted a concern that non-expert members may give harmful advice, more recent studies have typically shown that engagement with OSGs can increase consumer satisfaction with the treatment process, enhance wellbeing, and ultimately improve health outcomes. OSGs are well-researched within applied linguistics. Qualitative studies have focussed on member roles within OSGs, as well as the ways in which group members discursively construct their identities, especially with respect to their illness. These approaches have generated rich insights into consumer healthcare discourse that can inform strategies for fostering consumer-centred care. Qualitative approaches, however, are resource-intensive, di cult to reproduce, and limited in terms of generalisability and representativeness. Quantitative and computational approaches are able to overcome these shortcomings, adding transparency, reproducibility, scalability, and reducing the potential for researcher bias. Current computational approaches to consumer healthcare discourse, however, tend to rely on simplified conceptualisations of language, prioritising lexis over grammar, and thus ignoring the central role played by grammar in the meaning-making process. To address current methodological shortcomings in OSG discourse research, this thesis presents an interdisciplinary, corpus-based investigation of lexicogrammatical and discourse-semantic choices made by members over the course of membership in an online bipolar disorder support community. 8.2 million words in over 66,000 posts from approximately 3,500 members were transformed into a metadata-rich, grammatically annotated corpus and investigated from a systemic-functional linguistic (SFL) perspective using purpose-built corpus/computational linguistic tools. An analysis of MOOD and MODALITY choices made over ten stages of membership highlights differences in the ways members negotiate role-relationships, with changes in Mood Type, Modality and Speech Function reflecting a longitudinal increase in the provision of advice and social support. An analysis of the TRANSITIVITY system shows longitudinal changes in the kinds of participants and processes construed by Forum members, as well as changes in how these participants and processes behave lexicogrammatically. The diagnosis Event, for example, is represented by newcomers as a process and modi ed temporally; at later stages of membership, it is more often reconstrued as a participant in discourse, framed in terms of veracity. Longitudinal shifts were also observed in the preferred ways of ascribing/attributing bipolar disorder to Forum members: new members use bing forms (I’m bipolar), while veteran members prefer having constructions (I have bipolar). The thesis has implications for corpus linguistics, systemic-functional linguistic theory, and healthcare communication research. For corpus linguistics and corpus-assisted discourse studies, the main contribution is corpkit, an open-source software tool designed to build and analyse parsed and metadata-rich corpora. it is suggested that the developed tools and methods can circumvent theoretically problematic current practices, and increase the accuracy and automatability of the analytical process. For healthcare communication research, the case study demonstrates the importance of expanding the conceptualisation and analysis of the consumer healthcare journey to include intra–consumer communication that occurs outside of hospitals and clinics. The thesis also advances an argument that the emerging eld of clinical natural language processing stands to benefit from increased engagement with functional linguistic theory and insights generated within the qualitative paradigm. I argue that combining the insights from functional linguistics and discourse analysis with automated computational workflows is a step toward an important future goal of improvement of consumer health outcomes through analysis of large, digital collections of spoken and written healthcare discourse.
Keywordsonline support groups; systemic functional linguistics; corpus linguistics; computational linguistics; discourse; lexicogrammar
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