Gender in Online Doctor Reviews

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. Journal of Medical Internet Research. 2020;22(7):e14455.

This study examines 154,305 Google reviews from across the United States for all medical specialties. Many patients use online physician reviews but we need to understand effects of gender on review content. Reviewer gender was inferred from names.

Reviews were coded for overall patient experience (negative or positive) by collapsing a 5-star scale and for general categories (process, positive/negative soft skills). We estimated binary regression models to examine relationships between physician rating, patient experience themes, physician gender, and reviewer gender.

We found considerable bias against female physicians: Reviews of female physicians were considerably more negative than those of male physicians (OR 1.99; P<.001). Critiques of female physicians more often focused on soft skills such as amicability, disrespect and candor. Negative reviews typically have words such as “rude, arrogant, and condescending”

Reviews written by female patients were also more likely to mention disrespect (OR 1.27, P<.001), but female patients were less likely to report disrespect from female doctors than expected.

Finally, patient experiences with the bureaucratic process also impacted reviews. This includes issues like cost of care. Overall, lower patient satisfaction is correlated with high physician dominance (e.g., poor information sharing or using medical jargon)

Limitations of our work include the lack of definitive (or non-binary) information about gender; and the fact that we do not know about the actual outcomes of treatment for reviewers.

Even so, it seems critical that readers attend to the who the reviewers are when reading online reviews. Review sites may also want to provide information about gender differences, control for gender when presenting composite ratings for physicians, and helping users write less biased reviews. Reviewers should be aware of their own gender biases and assess reviews for this (http://slowe.github.io/genderbias/).

Living Disability Theory

A picture of a carved wooden cane in greens and blues

It was my honor this year to participate in an auto-ethnographic effort to explore accessibility research from a combination of personal and theoretical perspectives. In the process, and thanks to my amazing co-authors, I learned so much about myself, disability studies, ableism and accessibility.

Best Paper Award Hoffman, M., Kasnitz, D., Mankoff, J. and Bennett, C. l. (2020) Living Disability Theory: Reflections on Access, Research, and Design. In Proceedings of ASSETS 2020, 4:1-4:13

Abstract: Accessibility research and disability studies are intertwined fields focused on, respectively, building a world more inclusive of people with disability and understanding and elevating the lived experiences of disabled people. Accessibility research tends to focus on creating technology related to impairment, while disability studies focuses on understanding disability and advocating against ableist systems. Our paper presents a reflexive analysis of the experiences of three accessibility researchers and one disability studies scholar. We focus on moments when our disability was misunderstood and causes such as expecting clearly defined impairments. We derive three themes: ableism in research, oversimplification of disability, and human relationships around disability. From these themes, we suggest paths toward more strongly integrating disability studies perspectives and disabled people into accessibility research.

Wenjun Chen

Wenjun Chen is a senior student double majoring in Computer Science and Informatics. Her passion lies in leveraging behavioral data from the web, social media, and social interactions to generate actionable insights to address social good and enhance people’s lives. She is currently working on the RainClassroom Data Mining Project in the lab.

Jonathan Zhao

I am a junior majoring in Applied & Computational Mathematical Science. With interests and enthusiasm in data science and information technology, I’m studying coursework related with math, statistics, and computer science, and practicing programming and data manipulation work. To learn how we apply data to solve problems and approach research goals, I am currently working on the UWEXP study to help improve the way of handling and processing the survey data.

Kathryn Lum

Kathryn Lum is a third year undergraduate majoring in Computer Science at the University of Washington – Seattle. She is interested in the intersection of technology and social good. Under Kelly Mack and Megan Hofmann, Kathryn is working on the tactile maps project, researching the use of tactile maps in navigation for people with visual impairments.

Tim Li

Tim is a second-year undergraduate majoring in Statistics. His passion lies in data science and human-computer interaction. He is currently working on the UWEXP project to develop technologies that collect and improve student’s experience.

Jessica Birchfield

Jessica Birchfield is a junior majoring in Computer Science with a Chinese minor.  She is passionate about using technology to address human needs and enhance people’s lives.  Her interests include fabrication, computer animation, and computer graphics.  She is currently working on the Tactile Maps project in the lab.

Jerry Cao

Jerry is a PhD student at the Paul G. Allen School for Computer Science & Engineering at the University of Washington. He conducts research in the Make4All Lab and UbiComp Lab, where he’s advised by Jennifer Mankoff and Shwetak Patel.

His research focuses on improving healthcare accessibility by creating assistive technologies using digital fabrication and wearable sensing. He also works in the pure fabrication space, creating novel 3D-printable sensors and optimizing the strength of 3D-printed parts.

Website: https://jerrycao22.github.io/

Jacque Li

Jacque is a senior studying Computer Science and minor in Mathematics, and also works as a Student Ambassador in the Paul G. Allen School of Computer Science and Engineering, promoting computing and technical education to under-resourced and under-represented K-12 students. With a broad curiosity of how technology and computing influences interpersonal interactions, she is currently working on the UWEXP study to help develop the mobile technology used to collect student data, encompassing her diverse interests in mobile and accessible technologies, education, and personal health and wellness.

Han Zhang

Han is a PhD student in the Paul G. Allen School of Computer Science & Engineering. She is advised by Prof Jennifer Mankoff (Computer Science) and Prof Anind K. Dey (Information School).

Her research is human-centered, focusing on understanding human behaviors and designing AI systems that promote well-being, accessibility, and learning. For more details, please visit her personal website.