Evidence map›Paper›PMID 38070297›Full record

ArticlePatient education and counseling2024

Validating computer-generated measures of linguistic style matching and accommodation in patient-clinician communication.

Salar Khaleghzadegan, Michael Rosen, Anne Links, Alya Ahmad, Molly Kilcullen, Emily Boss, Mary Catherine Beach, Somnath Saha

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Article in Patient education and counseling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Salar KhaleghzadeganArmstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Medicine, Baltimore, MD, USA; The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA. Electronic address: skhaleg1@jhmi.edu.
Michael RosenArmstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Anne LinksDepartment of Otolaryngology-Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Alya AhmadDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, USA.
Molly KilcullenArmstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Emily BossDepartment of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Mary Catherine BeachDepartment of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, USA.
Somnath SahaDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, USA; Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland, USA.

Funding

Developing Novel Linguistic Analytic Methods to Optimize Relationship Quality and Equity in HIV CareR21MH126714 · NIMH · JOHNS HOPKINS UNIVERSITY · PI BEACH, MARY CATHERINE · 2021 to 2022
$450k
Understanding Clinician-Parent Interaction to Reduce Disparities and Improve Quality of Pediatric Surgical CareR21HD108565 · NICHD · JOHNS HOPKINS UNIVERSITY · PI BOSS, EMILY FRANCES · 2023 to 2024
$347k
Applying Novel Analytic Methods to Address the Impact of Race on Patient-Provider CommunicationI21HX003376 · VA · PORTLAND VA MEDICAL CENTER · PI SAHA, SOMNATH · 2021 to 2025
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HSRD VA I21 HX003376NICHD NIH HHS R21 HD108565NIMH NIH HHS R21 MH126714
6 · The paper itself

Abstract

objectiveTo explore the validity of computer-analyzed linguistic style matching (LSM) in patient-clinician communication.

methodsUsing 330 transcribed HIV patient encounters, we quantified word use with Linguistic Inquiry and Word Count (LIWC), a dictionary-based text analysis software. We measured LSM by calculating the degree to which clinicians matched patients in the use of LIWC "function words" (e.g., articles, pronouns). We tested associations of different LSM metrics with patients' perceptions that their clinicians spoke similiarly to them.

resultsWe developed 3 measures of LSM: 1) at the whole-visit level; (2) at the turn-by-turn level; and (3) using a "rolling-window" approach, measuring matching between clusters of 8 turns per conversant. None of these measures was associated with patient-rated speech similarity. However, we found that increasing trajectories of LSM, from beginning to end of the visit, were associated with higher patient-rated speech similarity (β 0.35, CI 0.06, 0.64), compared to unchanging trajectories.

conclusionsOur findings point to the potential value of clinicians' adapting their communication style to match their patients, over the course of the visit. PRACTICE IMPLICATIONS: With further validation, computer-based linguistic analyses may prove an efficient tool for generating data on communication patterns and providing feedback to clinicians in real time.

Indexed as

HIV InfectionsCommunicationComputersHumansLanguageLinguisticsLinguistic accommodationLinguistic style matchingPatient-clinician communicationPatient perception

Identifiers

PMID38070297
PMCPMC11349046

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