Cargando…

Gender, Soft Skills, and Patient Experience in Online Physician Reviews: A Large-Scale Text Analysis

BACKGROUND: Online physician reviews are an important source of information for prospective patients. In addition, they represent an untapped resource for studying the effects of gender on the doctor-patient relationship. Understanding gender differences in online reviews is important because it may...

Descripción completa

Detalles Bibliográficos
Autores principales: Dunivin, Zackary, Zadunayski, Lindsay, Baskota, Ujjwal, Siek, Katie, Mankoff, Jennifer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7426798/
https://www.ncbi.nlm.nih.gov/pubmed/32729844
http://dx.doi.org/10.2196/14455
_version_ 1783570758019055616
author Dunivin, Zackary
Zadunayski, Lindsay
Baskota, Ujjwal
Siek, Katie
Mankoff, Jennifer
author_facet Dunivin, Zackary
Zadunayski, Lindsay
Baskota, Ujjwal
Siek, Katie
Mankoff, Jennifer
author_sort Dunivin, Zackary
collection PubMed
description BACKGROUND: Online physician reviews are an important source of information for prospective patients. In addition, they represent an untapped resource for studying the effects of gender on the doctor-patient relationship. Understanding gender differences in online reviews is important because it may impact the value of those reviews to patients. Documenting gender differences in patient experience may also help to improve the doctor-patient relationship. This is the first large-scale study of physician reviews to extensively investigate gender bias in online reviews or offer recommendations for improvements to online review systems to correct for gender bias and aid patients in selecting a physician. OBJECTIVE: This study examines 154,305 reviews from across the United States for all medical specialties. Our analysis includes a qualitative and quantitative examination of review content and physician rating with regard to doctor and reviewer gender. METHODS: A total of 154,305 reviews were sampled from Google Place reviews. Reviewer and doctor gender were inferred from names. Reviews were coded for overall patient experience (negative or positive) by collapsing a 5-star scale and coded for general categories (process, positive/negative soft skills), which were further subdivided into themes. Computational text processing methods were employed to apply this codebook to the entire data set, rendering it tractable to quantitative methods. Specifically, we estimated binary regression models to examine relationships between physician rating, patient experience themes, physician gender, and reviewer gender). RESULTS: Female reviewers wrote 60% more reviews than men. Male reviewers were more likely to give negative reviews (odds ratio [OR] 1.15, 95% CI 1.10-1.19; P<.001). Reviews of female physicians were considerably more negative than those of male physicians (OR 1.99, 95% CI 1.94-2.14; P<.001). Soft skills were more likely to be mentioned in the reviews written by female reviewers and about female physicians. Negative reviews of female doctors were more likely to mention candor (OR 1.61, 95% CI 1.42-1.82; P<.001) and amicability (OR 1.63, 95% CI 1.47-1.90; P<.001). Disrespect was associated with both female physicians (OR 1.42, 95% CI 1.35-1.51; P<.001) and female reviewers (OR 1.27, 95% CI 1.19-1.35; P<.001). Female patients were less likely to report disrespect from female doctors than expected from the base ORs (OR 1.19, 95% CI 1.04-1.32; P=.008), but this effect overrode only the effect for female reviewers. CONCLUSIONS: This work reinforces findings in the extensive literature on gender differences and gender bias in patient-physician interaction. Its novel contribution lies in highlighting gender differences in online reviews. These reviews inform patients’ choice of doctor and thus affect both patients and physicians. The evidence of gender bias documented here suggests review sites may be improved by providing information about gender differences, controlling for gender when presenting composite ratings for physicians, and helping users write less biased reviews.
format Online
Article
Text
id pubmed-7426798
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-74267982020-08-24 Gender, Soft Skills, and Patient Experience in Online Physician Reviews: A Large-Scale Text Analysis Dunivin, Zackary Zadunayski, Lindsay Baskota, Ujjwal Siek, Katie Mankoff, Jennifer J Med Internet Res Original Paper BACKGROUND: Online physician reviews are an important source of information for prospective patients. In addition, they represent an untapped resource for studying the effects of gender on the doctor-patient relationship. Understanding gender differences in online reviews is important because it may impact the value of those reviews to patients. Documenting gender differences in patient experience may also help to improve the doctor-patient relationship. This is the first large-scale study of physician reviews to extensively investigate gender bias in online reviews or offer recommendations for improvements to online review systems to correct for gender bias and aid patients in selecting a physician. OBJECTIVE: This study examines 154,305 reviews from across the United States for all medical specialties. Our analysis includes a qualitative and quantitative examination of review content and physician rating with regard to doctor and reviewer gender. METHODS: A total of 154,305 reviews were sampled from Google Place reviews. Reviewer and doctor gender were inferred from names. Reviews were coded for overall patient experience (negative or positive) by collapsing a 5-star scale and coded for general categories (process, positive/negative soft skills), which were further subdivided into themes. Computational text processing methods were employed to apply this codebook to the entire data set, rendering it tractable to quantitative methods. Specifically, we estimated binary regression models to examine relationships between physician rating, patient experience themes, physician gender, and reviewer gender). RESULTS: Female reviewers wrote 60% more reviews than men. Male reviewers were more likely to give negative reviews (odds ratio [OR] 1.15, 95% CI 1.10-1.19; P<.001). Reviews of female physicians were considerably more negative than those of male physicians (OR 1.99, 95% CI 1.94-2.14; P<.001). Soft skills were more likely to be mentioned in the reviews written by female reviewers and about female physicians. Negative reviews of female doctors were more likely to mention candor (OR 1.61, 95% CI 1.42-1.82; P<.001) and amicability (OR 1.63, 95% CI 1.47-1.90; P<.001). Disrespect was associated with both female physicians (OR 1.42, 95% CI 1.35-1.51; P<.001) and female reviewers (OR 1.27, 95% CI 1.19-1.35; P<.001). Female patients were less likely to report disrespect from female doctors than expected from the base ORs (OR 1.19, 95% CI 1.04-1.32; P=.008), but this effect overrode only the effect for female reviewers. CONCLUSIONS: This work reinforces findings in the extensive literature on gender differences and gender bias in patient-physician interaction. Its novel contribution lies in highlighting gender differences in online reviews. These reviews inform patients’ choice of doctor and thus affect both patients and physicians. The evidence of gender bias documented here suggests review sites may be improved by providing information about gender differences, controlling for gender when presenting composite ratings for physicians, and helping users write less biased reviews. JMIR Publications 2020-07-30 /pmc/articles/PMC7426798/ /pubmed/32729844 http://dx.doi.org/10.2196/14455 Text en ©Zackary Dunivin, Lindsay Zadunayski, Ujjwal Baskota, Katie Siek, Jennifer Mankoff. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 30.07.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Dunivin, Zackary
Zadunayski, Lindsay
Baskota, Ujjwal
Siek, Katie
Mankoff, Jennifer
Gender, Soft Skills, and Patient Experience in Online Physician Reviews: A Large-Scale Text Analysis
title Gender, Soft Skills, and Patient Experience in Online Physician Reviews: A Large-Scale Text Analysis
title_full Gender, Soft Skills, and Patient Experience in Online Physician Reviews: A Large-Scale Text Analysis
title_fullStr Gender, Soft Skills, and Patient Experience in Online Physician Reviews: A Large-Scale Text Analysis
title_full_unstemmed Gender, Soft Skills, and Patient Experience in Online Physician Reviews: A Large-Scale Text Analysis
title_short Gender, Soft Skills, and Patient Experience in Online Physician Reviews: A Large-Scale Text Analysis
title_sort gender, soft skills, and patient experience in online physician reviews: a large-scale text analysis
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7426798/
https://www.ncbi.nlm.nih.gov/pubmed/32729844
http://dx.doi.org/10.2196/14455
work_keys_str_mv AT dunivinzackary gendersoftskillsandpatientexperienceinonlinephysicianreviewsalargescaletextanalysis
AT zadunayskilindsay gendersoftskillsandpatientexperienceinonlinephysicianreviewsalargescaletextanalysis
AT baskotaujjwal gendersoftskillsandpatientexperienceinonlinephysicianreviewsalargescaletextanalysis
AT siekkatie gendersoftskillsandpatientexperienceinonlinephysicianreviewsalargescaletextanalysis
AT mankoffjennifer gendersoftskillsandpatientexperienceinonlinephysicianreviewsalargescaletextanalysis