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More Work Needed to Increase Racial, Ethnic Diversity in Biostatistics, Epidemiology Departments

1 October 2022 One Comment
Melody Goodman

Melody Goodman

Melody Goodman, Jemar Bather, Xiangying Chu, Marcello Pagano, Christine Plepys, and Ronnie Sebro recently published a paper titled “Racial and Ethnic Diversity Among Students, Graduates, and Faculty in Biostatistics and Epidemiology, 2010–2020” in Public Health Reports. The paper describes a follow-up to their 2020 study that reviewed changes in the racial and ethnic composition of public health students, graduates, and faculty among Association of Schools and Programs of Public Health (ASPPH) member institutions.

The researchers stated that “although more Hispanic/Latino students are enrolled in and graduating from biostatistics and epidemiology departments at ASPPH member institutions, we found no change among faculty. More work is needed to recruit and retain other (American Indian/Alaska Native, Black or African American, Native Hawaiian/Other Pacific Islander) underrepresented students and faculty.”

We had a few questions for lead author Melody Goodman, who is the associate dean for research and professor of biostatistics at New York University School of Global Public Health. Goodman leads the Quantitative Public Health Data Literacy Training program and is the director of the new Center for Anti-Racism, Social Justice, and Public Health at the NYU School of Global Public Health. Her work focuses on educating the general public about quantitative public health data literacy.

What prompted you and the other authors to follow up on the 2020 study?

After the initial study, which looked at public health overall, we had a specific interest in biostatistics and epidemiology. Many of the co-authors are biostatisticians. We were really interested in looking at our discipline. We also know many biostatistics departments are actively engaged in activities (e.g., summer programs, training grants) to diversify the field, so we wanted to see where things are.

What was the effect of your 2020 study on public health departments?

For public health departments, there are some promising results based on the increasing diversity of the student population. This will impact the diversity of the public health workforce.

What has been the reaction to your 2022 paper?

The paper is still quite new but has received a favorable response on Twitter and other social media, for what that’s worth.

What did you learn personally from doing this study? Did any of the findings surprise you? What most concerns you about what you found? What’s most encouraging?

I thought we would have made more progress in the last 10 years, so this study showed me that there is still a lot of work to do and we all need to be participating in these efforts. I think the increasing diversity of public health students is the most encouraging result, but there is still work to do in this area.

Your research focused on biostatistics departments in 40 ASPPH institutions. If you have discussed your results with colleagues in statistics departments and other biostatistics departments, do they report similar data?

I’ve really been discussing this work with ASPPH member institutions. There is not much benefit in comparison when we know we have work to do in this area. Instead, let’s be intentional about this work and foster collaboration instead of competition. I think this is why the work of professional organizations (e.g., ASA) plays a key role in connecting us all toward a common goal.

In the study, you noted “large-scale interventions are needed to increase pathways into public health fields for diverse students and faculty.” Describe large-scale interventions biostatisticians and data scientists can begin implementing in their departments and on campuses?

In some respects, I think we are on the right track but we need to push this existing work further.

  • More postbaccalaureate programs for students who are interested in graduate work but did not complete all the undergraduate prerequisites
  • Summer bootcamps that help bolster skills needed to succeed in graduate studies in statistics and data science
  • Summer pipeline programs that offer supplemental training in the foundational undergraduate coursework (e.g., calculus, linear algebra)
  • Graduate programs that accept coursework from summer bootcamps and pipeline programs as an alternative to prerequisites and/or supplement with their own training

In your opinion, how do we better recruit and retain underrepresented students and faculty? Why is this important?

I don’t think anyone has figured this out yet just based on the data in the paper. That said, following are some lessons learned from the Quantitative Public Health Data Literacy Training:

  • Create environments that are welcoming and engaging. We play music at the beginning of each session of the data literacy training and invite students to join our data party. Yes, just like the course syllabus, we spend time curating a playlist with the right songs to create the vibe we want. Racialized minorities are pushed out of STEM disciplines starting in elementary school and continuing through secondary education. It is important to create spaces for them and welcome.
  • Create diverse learning environments. We have created training cohorts that are diverse but predominantly Black and Latino/a/x. We think this is crucial for foundational learning and provides a safe environment to ask questions. For departments, I think this could be translated into small learning communities (e.g., formal study groups). It can truly feel isolating when you are the only one in the room who looks like you, and everyone benefits from diverse learning environments.
  • Provide ample support for students to receive help. We often have 10 or so course assistants for the data literacy training. This is about a 10:1 student to course assistant ratio—much lower than what is seen in a typical academic environment. It also means there were 10 office hours a week for students to choose from.
  • Use technology to support communication. The students and course assistants use Slack to communicate. If you need help outside of office hours, you can send a Slack message at any time and there is a whole community of class members and course assistants there to answer.
  • “What I hear, I forget. What I see, I remember. What I do, I understand.” Training should be hands-on. If you go to a dance class, you expect to dance, not watch the teacher dance. The same is true for a cooking class, and the same should be true with any data science or statistics course.
  • Affirm students when they have challenges. When students tell me my course is hard, I agree with them and then tell them they can do hard things.

I truly believe diversifying the field (data science and statistics) is an ethical imperative, given the implications of data in our society.

In your opinion, what can biostatisticians and data scientists do to help educate the general public about quantitative public health data literacy?

We did an iteration of the quantitative public health data literacy training (Cohort II February 2021) for the general public. It was a four-session version, with each session lasting two hours. It was one of the most rewarding experiences of my career. Those of us who have these skills have to train others. There is now a basic competency level needed to absorb the information being presented. Who better than us to provide this training to the general public?

Do you have plans to continue your research on the racial and ethnic composition of public health disciplines?

Yes, right now we are working on a paper looking at diversity in environmental sciences … stay tuned.

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One Comment »

  • Richard Hanson said:

    Rather than racial diversity, schools should be focused on fostering *intellectual* diversity. The Diversity, Inclusion, and Equity movement is Orwellian: it’s the opposite of what it says it is. “Diversity, inclusion, and equity” refers to ideological uniformity, exclusion, and discrimination.

    see https://fakenous.substack.com/p/who-cares-about-diversity