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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Apr 21, 2019
Open Peer Review Period: Apr 23, 2019 - Jun 18, 2019
Date Accepted: Apr 28, 2020
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

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

Dunivin Z, Zadunayski L, Baskota U, Siek K, Mankoff J

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

J Med Internet Res 2020;22(7):e14455

DOI: 10.2196/14455

PMID: 32729844

PMCID: 7426798

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

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

  • Zackary Dunivin; 
  • Lindsay Zadunayski; 
  • Ujjwal Baskota; 
  • Katie Siek; 
  • Jennifer Mankoff

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.


 Citation

Please cite as:

Dunivin Z, Zadunayski L, Baskota U, Siek K, Mankoff J

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

J Med Internet Res 2020;22(7):e14455

DOI: 10.2196/14455

PMID: 32729844

PMCID: 7426798

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