Coding linguistic elements in clinical interactions: a step-by-step guide for analyzing communication form

Mistiaen P, van Osch M, van Vliet L, Howick J, Bishop FL, di Blasi Z, et al. The effect of patient-practitioner communication on pain: a systematic review. Eur J Pain. 2016;20:675–88.

Howick J, Moscrop A, Mebius A, Fanshawe TR, Lewith G, Bishop FL, et al. Effects of empathic and positive communication in healthcare consultations: a systematic review and meta-analysis. J R Soc Med. 2018;111:240–52.

Hansen E, Zech N. Nocebo effects and negative suggestions in daily clinical practice – forms, impact and approaches to avoid them. Front Pharmacol. 2019;10:1–10.

Roter D, Larson S. The Roter interaction analysis system (RIAS): utility and flexibility for analysis of medical interactions. Patient Educ Couns. 2002;46:243–51.

del Piccolo L, de Haes H, Heaven C, Jansen J, Verheul W, Bensing J, et al. Development of the Verona coding definitions of emotional sequences to code health providers’ responses (VR-CoDES-P) to patient cues and concerns. Patient Educ Couns. 2011;82:149–55.

Zimmermann C, del Piccolo L, Bensing J, Bergvik S, de Haes H, Eide H, et al. Coding patient emotional cues and concerns in medical consultations: the Verona coding definitions of emotional sequences (VR-CoDES). Patient Educ Couns. 2011;82:141–8.

Höglander J, Eklund JH, Spreeuwenberg P, Eide H, Sundler AJ, Roter D, et al. Exploring patient-centered aspects of home care communication: A cross-sectional study. BMC Nurs. 2020;19(91):1–10.

Beach MC, Park J, Han D, Evans C, Moore RD, Saha S. Clinician response to patient emotion: impact on subsequent communication and visit length. Ann Fam Med. 2021;19:515–20.

Allen M. The Sage encyclopedia of communication research methods: Sage; 2017.

Burgers C, Beukeboom CJ, Sparks L, Diepeveen V. How (not) to inform patients about drug use: use and effects of negations in Dutch patient information leaflets. Pharmacoepidemiol Drug Saf. 2015;24:137–43.

Stortenbeker I, Houwen J, Lucassen P, Stappers H, Assendelft W, van Dulmen S, et al. Quantifying positive communication: Doctor’s language and patient anxiety in primary care consultations. Patient Educ Couns. 2018;101:1577–84.

Heritage J, Robinson JD, Elliott MN, Beckett M, Wilkes M. Reducing patients’ unmet concerns in primary care: the difference one word can make. J Gen Intern Med. 2007;22:1429–33.

Parry R, Land V, Seymour J. How to communicate with patients about future illness progression and end of life: a systematic review. BMJ Support Palliat Care. 2014;4:331.

Land V, Parry R, Seymour J. Communication practices that encourage and constrain shared decision making in health-care encounters: systematic review of conversation analytic research. Health Expect. 2017;20:1228–47.

Nordfalk JM, Gulbrandsen P, Gerwing J, Nylenna M, Menichetti J. Development of a measurement system for complex oral information transfer in medical consultations. BMC Med Res Methodol. 2019;19:1–9.

Stortenbeker I, olde Hartman T, Kwerreveld A, Stommel W, van Dulmen S, Das E. Unexplained versus explained symptoms: the difference is not in patients’ language use. A quantitative analysis of linguistic markers. J Psychosom Res. 2022;152:110667.

Stortenbeker I, Houwen J, van Dulmen S, olde Hartman T, Das E. Quantifying implicit uncertainty in primary care consultations: a systematic comparison of communication about medically explained versus unexplained symptoms. Patient Educ Couns. 2019;102:2349–52.

Schwabe M, Howell S, Reuber M. Differential diagnosis of seizure disorders: a conversation analytic approach. Soc Sci Med. 2007;65:712–24.

Lester JN, Muskett T, O’Reilly M. Naturally occurring data versus researcher-generated data. In: O’Reilly M, Lester JN, Muskett T, editors. A practical guide to social interaction research in autism spectrum disorders. London: Palgrave Macmillan UK; 2017. p. 87–116.

Downe-Wamboldt B. Content analysis: method, applications, and issues. Health Care Women Int. 1992;13:313–21.

Plug I, van Dulmen S, Stommel W, olde Hartman T, Das E. When interruptions do not harm the medical interaction: a quantitative analysis of physicians’ and patients’ interruptions in clinical practice. Ann Fam Med. 2022. in press.

Burgelman J, Pascu C, Szkuta K, von Schomberg R, Karalopoulos A, Repanas K, et al. Open science, open data, and open scholarship: European policies to make science fit for the twenty-first century. Front Big Data. 2019;2:1–6.

Haven TL, van Grootel L. Preregistering qualitative research. Account Res. 2019;26:229–44.

Krippendorff K. Content analysis: an introduction to its methodology. 3rd ed. Los Angeles: Sage; 2013.

Selting M. The construction of units in conversational talk. Lang Soc. 2000;29:477–517.

Clayman S. Turn-constructional units and the transition-relevant place. In: Sidnell J, Stivers T, editors. The handbook of conversation analysis. Oxford: Wiley-Blackwell; 2012. p. 151–66.

Liebrecht C. Intens Krachtig. Stilistische intensiveerders in evaluatieve teksten [Intensely powerful. Stylistic intensifiers in evaluative texts - PhD thesis]. Radboud University; 2015.

Roberts K, Dowell A, Nie J. Attempting rigour and replicability in thematic analysis of qualitative research data: a case study of codebook development. BMC Med Res Methodol. 2019;19:66.

Burla L, Knierim B, Barth J, Liewald K, Duetz M, Abel T. From text to codings: intercoder reliability assessment in qualitative content analysis. Nurs Res. 2008;57:113–7.

O’Connor C, Joffe H. Intercoder reliability in qualitative research: debates and practical guidelines. Int J Qual Methods. 2020;19:1–13.

Roter D. Communication patterns of primary care physicians. JAMA. 1997;277:350–6.

Popping R. On agreement indices for nominal data. In: Saris WE, Gallhofer IN, editors. Sociometric research: Volume 1, data collection and scaling: St. Martin’s Press; 1988. p. 90–105.

McHugh ML. Interrater reliability: the kappa statistic. Biochem Med (Zagreb). 2012;22:276–82.

Bell A, Fairbrother M, Jones K. Fixed and random effects models: making an informed choice. Qual Quant. 2019;53:1051–74.

Hayes AF. A primer on multilevel modeling. Hum Commun Res. 2006;32:385–410.

Houwen J, Lucassen P, Stappers H, Assendelft P, van Dulmen S, olde Hartman T. Medically unexplained symptoms: the person, the symptoms and the dialogue. Fam Pract. 2017;34:245–51.

Reuber M, Monzoni C, Sharrack B, Plug L. Using interactional and linguistic analysis to distinguish between epileptic and psychogenic nonepileptic seizures: a prospective, blinded multirater study. Epilepsy Behav. 2009;16:139–44.

Schwabe M, Reuber M, Schondienst M, Gulich E. Listening to people with seizures: how can linguistic analysis help in the differential diagnosis of seizure disorders? Commun Med. 2008;5:59–72.

Gol JM, Burger H, Janssens KAM, Slaets JPJ, Gans ROB, Rosmalen JGM. PROFSS: a screening tool for early identification of functional somatic symptoms. J Psychosom Res. 2014;77:504–9.

Balabanovic J, Hayton P. Engaging patients with “medically unexplained symptoms” in psychological therapy: an integrative and transdiagnostic approach. Psychol Psychother Theory Res Pract. 2020;93:347–66.

Ainiwaer A, Zhang S, Ainiwaer X, Ma F. Effects of message framing on cancer prevention and detection behaviors, intentions, and attitudes: systematic review and meta-analysis. J Med Internet Res. 2021;23:e27634.

Webster RK, Weinman J, Rubin GJ. Explaining all without causing unnecessary harm: is there scope for positively framing medical risk information? Patient Educ Couns. 2019;102:602–3.

Claréus B, Renström EA. Physicians’ gender bias in the diagnostic assessment of medically unexplained symptoms and its effect on patient–physician relations. Scand J Psychol. 2019;60:338–47.

FitzGerald C, Hurst S. Implicit bias in healthcare professionals: a systematic review. BMC Med Ethics. 2017;18:19.

Beukeboom CJ, Finkenauer C, Wigboldus DH. The negation bias: when negations signal stereotypic expectancies. J Pers Soc Psychol. 2010;99:978–92.

Lavrakas P. Encyclopedia of survey research methods. California: Sage; 2008.

Rose S, Spinks N, Canhoto AI. Management research: applying the principles. 1st ed. New York: Routledge; 2015.

Beaudart C, Hiligsmann M, Li N, Lewiecki EM, Silverman S. Effective communication regarding risk of fracture for individuals at risk of fragility fracture: a scoping review. Osteoporos Int. 2022;33:13–26.

Gale NK, Heath G, Cameron E, Rashid S, Redwood S. Using the framework method for the analysis of qualitative data in multi-disciplinary health research. BMC Med Res Methodol. 2013;13:1–8.

Voutilainen A. Part-of-speech tagging. In: Mitkov R, editor. The Oxford handbook of computational linguistics. 1st ed. Oxford: Oxford University Press; 2012.

Rivera Zavala R, Martinez P. The impact of pretrained language models on negation and speculation detection in cross-lingual medical text: comparative study. JMIR Med Inform. 2020;8:e18953.

Patterson BW, Jacobsohn GC, Shah MN, Song Y, Maru A, Venkatesh AK, et al. Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department. BMC Med Inform Decision Making. 2019;19:1–8.

Pilny A, McAninch K, Slone A, Moore K. Using supervised machine learning in automated content analysis: an example using relational uncertainty. Commun Methods Meas. 2019;13:287–304.