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Mitigating Bias in Literature Searching: A View from the Health Sciences

Posted by on May 13th, 2019 Posted in: Funded Project
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View of downtown Cleveland

View of Cleveland, OH. Image  by Cleveland84 CC0

Cynthia Young, MLIS, Associate Academic Dean of Library Services at Eastern Maine Community College Library, received funding to attend the Association of College & Research Libraries (ACRL) 2019 Conference in Cleveland, OH. She contributed this blog post on the session “Improving Ourselves and Improving Care: Mitigating bias in literature searching in health sciences” presented by Rachel Stark, California State University – Sacramento, Molly Higgins, Library of Congress.

Are librarians biased in their health research with students? Is health literature biased? Those are the questions two librarians tried to answer in their research for a workshop at the Association of College & Research Libraries Conference (ACRL 2019) in Cleveland, Ohio, on April 11, 2019. The workshop was led as a teach-the-teacher type course. The intent was that librarians would adapt a similar training session at their own institutions.

The conference workshop was attended by mostly college health librarians and health science librarians from medical institutions. Participants were introduced to three types of bias including racism, microaggressions and implicit/unconscious bias. The first activity involved using mobile devices or laptops to take the Project Implicit bias tests created by Harvard University. The implicit bias tests use repetitious images and keyboard functions to learn users unconscious bias toward various minorities including but not limited to, sexuality, gender and weight. The test results often proved difficult for participants to accept, but the intent was to help them become aware of their faults in order to better serve diverse populations.

The next activity had participants write down an assumption of themselves made by a library patron. Each person then walked around the room viewing each person’s response and putting a check mark if they’d experienced the same. Several librarians in the room wrote, “I thought you were a student” or “where’s the real librarian?” Other assumptions included, “you must love to read” and “you’re Asian, you must be smart.” To further drive home the concept, participants then walked back around the room and put an X if they’d seen a library patron experience that bias. The most common assumptions centered on age, sexuality and race.

A slideshow and discussion around the results of the presenter’s research showed large biases in medical research. Many minority groups were underrepresented or in some cases were completely unrepresented in health literature. The largest group of represented individuals in health research was Caucasian males. Caucasian women were less represented than males. Other demographics were less represented. An example used was that even studying Japanese women in Japan does not necessarily represent Japanese American women in the United States.

The final activity split the room into groups to do live database searching. The scenario participants were given involved a 30-year-old, pre-diabetic Japanese American female who went to her librarian to try to find a food list that was specific to her diabetic needs, but also met her Japanese style diet. Each table was tasked with developing a PICO question and using a computer to try to best answer the reference question. The research on the topic was lacking. There were plenty of diabetic studies on diet, but most were not focused on Japanese American females.

What will I take from attending this workshop? Many things! First, I work closely with our nursing students every year. Eastern Maine Community College (EMCC) has the highest NCLEX-RN pass rate in the state of Maine, so our students perform very in-depth research for a two-year program. In future work, I will be cognizant of broadening student’s minds concerning the biases that exist in healthcare research. The workshop leaders also encouraged us to search many types of populations while searching with students. Second, during the search activity, I learned about many databases I had never used. Embase, EthnoMed, MedEdPORTAL and SPIRAL were all new resources to me. EthnoMed proved perfect for the activity search because you could filter by population and location. These newly discovered databases will be helpful for not only assisting our nursing students, but other healthcare program students we have at EMCC. Finally, Eastern Maine Community College has a diverse student population. We serve many first-generation college students, veterans, distance education students, students with disabilities and non-traditional students. It is imperative that as the sole librarian, I am serving all students to the best of my ability without making assumptions about their needs, habits or abilities. I also oversee our student employees, so my plan is to also add some training for them on serving diverse populations. In addition, I am interested in offering this type of health bias course to our nursing instructors. I believe it would be of value to them in developing their courses.

Overall, I am very grateful to NNLM-New England for giving me the opportunity to attend ACRL 2019! I attended many wonderful sessions that will help in all aspects of my work including a session on assisting patrons with an Autism Spectrum Disorder, training student employees with future workplace skills and offering faculty mini-grants to partner with a librarian on an assignment. I look forward to using all of these tools in the future.

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NNLM Region 7
University of Massachusetts Chan Medical School
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Worcester, MA 01655
(508) 856-5985

This has been funded in whole or in part with Federal funds from the Department of Health and Human Services, National Institutes of Health, National Library of Medicine, under cooperative agreement number UG4LM012347 with the University of Massachusetts Chan Medical School.

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