In the Conversation Analysis SIG, members will find a vibrant, diverse community of researchers interested in the application of conversation analysis (CA) to clinical encounters. We are focused on building connections, sharing knowledge, and advancing the field through collaboration and innovation.

CA is a qualitative research method rooted in sociology and linguistics that is used for the systematic study of talk in interaction. Originating in the 1960s, CA was pioneered by Harvey Sacks, Emanuel Schegloff and Gail Jefferson, with a foundation in ethnomethodology – the study of the everyday methods people use to make sense of their social worlds. The premise of CA is that communication is co-constructed in real time and that participants orient to normative structures such as turn-taking, sequence organization, and preference organization as they converse. These structures help participants navigate social interactions and can reveal implicit expectations and power dynamics. By examining recordings of naturally occurring conversations, CA can uncover how these dynamics play out in the real world and shape our conversations and our daily lives.  

Initially applied to suicide prevention calls and later to everyday social interaction (e.g., among friends), CA has been adapted to explore a range of institutional interactions including clinician-patient communication, where since the 1980s it has become a vital tool for understanding the dynamics of clinical encounters. Clinical conversations are distinct from everyday talk because they occur in institutional settings with asymmetrical power relationships and goal-oriented agendas. But like everyday talk, clinical encounters unfold in sequences of interactional moves – palpable decision points speakers face in how to get their point across or accomplish their goals. CA assumes – and has empirically demonstrated – “order at all points,” meaning that every choice speakers make, from word choice to intonation, grammar, and even the timing of silences, contributes to the flow and meaning of a conversation in systematic ways. CA allows researchers to dissect these details to uncover underlying structures and patterns in talk that shape the delivery and reception of care, as well as healthcare quality, equity, and downstream health outcomes.

Early applications of CA in clinical care examined general practice consultations for new health concerns, focusing on how clinicians and patients negotiate activities such as problem presentation, diagnosis, treatment recommendation, and closing. Since then, CA studies in clinical care have proliferated across clinical settings, including primary care for chronic conditions such as diabetes; surgery; emergency care; oncology; neurology; palliative care; genetic counseling; physiotherapy; telemedicine; and more. CA offers several advantages in the analysis of clinician-patient communication. Unlike other methods that rely on self-report, post-interaction interviews, or quantitative coding based on pre-existing coding schemes, CA is used to examine the interaction itself, uncovering the real-world practices clinicians and patients use to negotiate meaning in real time.

As the field of study continues to evolve, conversation analysts are increasingly combining CA with other methods both qualitative and quantitative, linking specific communication practices to conversational and clinical outcomes, and integrating CA findings into clinical trials to evaluate the effectiveness of communication interventions. Studies have demonstrated, for instance, how framing non-antibiotic treatment recommendations for viral upper respiratory infections as for a particular treatment rather than against the alternative improves uptake (Stivers 2005); that asking patients if they have some vs any additional questions reduces unmet concerns (Heritage et al. 2007); and that framing recommendations for a weight loss program as a positive opportunity rather than focusing on the negative effects of obesity increases patient attendance (Albury et al. 2020). Such findings can be used to inform clinical education and communication training. By highlighting effective communicative practices, CA contributes to the development of more patient-centered care and provides evidence for policy makers and healthcare institutions interested in improving the quality and safety of clinical encounters.

Our plan:

The Conversation Analysis SIG will provide community and networking opportunities for those engaged in or interested in using CA in health communication research, with the aim of increasing the presence of CA and CA-informed research across ICCH/EACH/ACH. Our primary goal is to spark collaboration by creating a welcoming space focused on creating new connections and sharing knowledge and expertise.

We plan to accomplish this by:

1. Organizing meetings of the SIG during the annual ICCH meetings as a primary site for in-person networking

2. Gathering information on the needs of the community of researchers practicing or interested in incorporating CA into their research on healthcare communication

3. Facilitating collaboration and learning among SIG members by connecting virtually throughout the year and conducting CA symposia/workshops/panels/data sessions at annual meetings.

Officers:

SIG Contact: amcarth1@jhmi.edu

To learn more:

Overviews of CA

Schegloff, E. A. (2007). Sequence organization in interaction: A primer in conversation analysis. Cambridge University Press.

Sidnell, J., & Stivers, T. (Eds.). (2012). The handbook of conversation analysis. John Wiley & Sons.

Ten Have, P. (2007). Doing conversation analysis (2nd ed.). Sage Publications.

Overviews of CA in healthcare communication

Barnes RK. Conversation Analysis of Communication in Medical Care: Description and Beyond. Research on Language & Social Interaction. 2019;52(3):300-15.

Drew, P., Chatwin, J., & Collins, S. (2001). Conversation analysis: A method for research into interactions between patients and health-care professionals. Health Expectations, 4(1), 58–70. https://doi.org/10.1046/j.1369-6513.2001.00125.

Heritage, J., & Maynard, D. W. (Eds.). (2006). Communication in medical care: Interaction between primary care physicians and patients (Vol. 20). Cambridge University Press.

Koenig, CJ and Beach, WA. (2021) Patient-Provider Communication. In Oxford Bibliographies in Communication. P. Moy (Ed.) New York: Oxford University Press.

Parry, R., & Barnes, R. K. (2024). Conversation-Analytic Research on Communication in Healthcare: Growth, Gaps, and Potential. Research on Language and Social Interaction, 57(1), 1–6. https://doi.org/10.1080/08351813.2024.2305037

Robinson JD, Clift R, Kendrick KH, Raymond CW, eds. (2024) The Cambridge Handbook of Methods in Conversation Analysis. Cambridge University Press.

Tietbohl CK & White AEC (2022). Making conversation analysis accessible: A conceptual guide for health services researchers. Qualitative Health Research, 32(8-9), 1246-1258.

White, S.J. (2019). Conversation analysis: an introduction to methodology, data collection, and analysis. In P. Liamputtong (Ed.), Handbook of research methods in health social sciences (pp. 471-490). Springer, Springer Nature.

Full citations for 3 papers cited above

Albury, C., Webb, H., Stokoe, E., Ziebland, S., Koshiaris, C., Lee, J. J., & Aveyard, P. (2023). Relationship between clinician language and the success of behavioral weight loss interventions: a mixed-methods cohort study. Annals of internal medicine, 176(11), 1437-1447.

Heritage, J., Robinson, J. D., Elliott, M. N., Beckett, M., & Wilkes, M. (2007). Reducing patients’ unmet concerns in primary care: the difference one word can make. Journal of general internal medicine, 22, 1429-1433.

Stivers T. Non-Antibiotic Treatment Recommendations: Delivery Formats and Implications for Parent Resistance. Social Science & Medicine. 2005;60(5):949–64.