Author ORCID Identifier
https://orcid.org/0000-0002-6856-7631
Date of Award
Spring 3-31-2023
Document Type
Thesis (Ph.D.)
Department or Program
Health Policy and Clinical Practice
First Advisor
Glyn Elwyn, MB BCH, PhD, MSc
Second Advisor
Marie-Anne Durand, PhD, MSc, MPhil
Third Advisor
JoAnna K. Leyenaar, MD, PhD, MPH
Abstract
Statement of the Problem
Good communication in clinical encounters is a key component of quality healthcare. Improving clinician communication would benefit all populations, however patients with lower health literacy or who are socially disadvantaged stand to benefit the most due to the complex content in clinical encounters. Shared decision-making can improve outcomes, but shared decision-making cannot occur without good clinician communication. In this dissertation, I reviewed interventions for facilitating shared decision-making for socially disadvantaged patients. Then, I examined the use of spoken plain language, or clinician use of familiar, clear verbal language when communicating with patients, and developed a prototype for measuring clinician spoken plain language.
Methods
First, I conducted a systematic review and meta-analysis of trials that compared decision-making interventions to usual care for patient-reported and other outcomes. I also examined whether these interventions improved outcomes more for socially disadvantaged populations. Then, I conducted a qualitative analysis of clinical encounters to determine the relevant components of spoken plain language. Finally, I assessed these and other variables across an existing dataset of encounters and undertook a factor analysis to determine the final set of variables for inclusion in a potential measure of spoken plain language.
Results
In the systematic review, I found 38 decision-making interventions that improved patient-reported knowledge, patient-clinician communication, reduced decisional conflict, and the proportion of people undecided. Overall, the interventions did not improve outcomes more for socially disadvantaged populations. In the qualitative analysis, I found two measurable elements of clinician spoken plain language: the degree to which clinicians explain medical terms and break down information into simple phrases and units of speech (turns). In the quantitative analysis, I found four unique constructs to measure: speech speed, turn length, turn complexity, and word complexity.
Conclusions
Interventions to facilitate shared decision making for socially disadvantaged populations improved outcomes but did not improve inequalities. The potential measure for evaluating the extent to which clinicians use spoken plain language is ready for further testing, which should include the feasibility of automation and the delivery of results back to clinicians for self-reflection and improvement.
Original Citation
Chapter 2 is published:
Yen RW, Smith J, Engel J, et al. A Systematic Review and Meta-Analysis of Patient Decision Aids for Socially Disadvantaged Populations: Update from the International Patient Decision Aid Standards (IDPAS). Med Decis Making. Published online June 21, 2021:0272989X211020317. doi:10.1177/0272989X211020317
Recommended Citation
Yen, Renata W., "Exploring Communication in Healthcare Through Decision-Making Interventions and a Novel Measure of Clinician Spoken Plain Language" (2023). Dartmouth College Ph.D Dissertations. 191.
https://digitalcommons.dartmouth.edu/dissertations/191
Comments
Fourth advisor: A. James O’Malley, PhD
External advisor: Debra L. Roter, DrPH, MPH