aligns with their sex assigned at birth. “Nonbinary” is an umbrella term for gender identities that are not exclusively man or woman; rather, they could be a blend of both or neither. Other words that people use for nonbinary identities include agender, bigender, gender-expansive, or genderqueer. Table 1 outlines the considerations and actions taken by the D&T Task Force members to create a survey with inclusive and current terminology.
Inclusive Language Around Race and Ethnicity
The next intentional “so what” category the task force sought to capture demographic information about the MCMLA population was race/ethnicity. Like individuals who belong to a sexual minority group, those in a racial minority face disparities such as health, employment, and environmental. Like terms used for SOGI, terms used to refer to racial and ethnic groups continue to change and evolve over time. To have a responsive survey, it is important to use the racial/ethnic categories that the participants use themselves whenever possible, allowing for personal preference or an updated preferred designation as some designations are considered outdated. Race refers to the physical differences seen in groups or cultures that are considered socially significant, where ethnicity refers to the shared cultural characteristics such as language, beliefs, and practices. The U.S. Census Bureau considers race and ethnicity two separate things. The Census Bureau allows individuals to report themselves as: White; Black or African American; Asian; American Indian and Alaska Native; Native Hawaiian and other Pacific Island; or some other race. Respondents can report multiple races. Ethnicity on the other hand refers to a group of people that share a common descent, history, and/or homeland [7]. And because Hispanic/Latinos may be of any race(s), the U.S. Census groups Latinos or Hispanics further breaks down the ethnic group “Hispanic/Latino” into races as well. Race is considered a social construct that it is not consistently acknowledged across cultures. In an effort to be more culturally inclusive, MCMLA chose to include three categories in the survey-ethnic background, nationality, and race [8].
Inclusive Language Around Disability Status
The task force was once again faced with the issue of why they were collecting data when they looked at asking MCMLA members if they had a disability. The original MAC survey asked participants if they had no disability, prefer not to answer, limited cognitive or physical condition or other. Worldwide, about 15% of the world population and about 12.6% of the US population have a disability [9]. The American Community Survey defines disability as having hearing difficulty, cognitive difficulty, ambulatory difficulty, self-care difficulty, or independent living difficulty [10]. Our professional ethics, as expressed by the American Library Association, also make it clear that meeting the needs of disabled patrons and workers should be made a priority [11]. The task force concluded that asking members to disclose if they had a disability (as was done in the MAC survey) was not inclusive of the disabilities that have been increasingly recognized as disabilities in recent times. For example, “depression, a mood disorder that is marked by varying degrees of sadness,” would not fall under the two main disabilities listed on the survey question as is [12]. The task force determined their “so what” for asking about disabilities was to better understand the MCMLA membership conference spaces’ accessibility needs, specifically mobility for in-person conferences and audiovisual needs for both in-person and virtual. A suggestion was made for the task force to change the wording from asking an individual that self identifies with a disability how it impacts their daily lives to instead providing a blank box for folks to fill in with their needs. Therefore, the task force decided to reformat the disability question in the following way: Do you have a disability that impacts your interactions with MCMLA? If yes, tell us how you experience the impact and tell us what we can do to improve accessibility.
The open-ended responses in our survey provided feedback on the pilot survey itself that will aid us in refining our survey questions should we choose to administer the survey again in the future. In addition, the qualitative feedback collected may assist others interested in developing similar surveys. The collected data included in this article focuses on feedback on the survey itself rather than other aspects collected by the survey to provide guidance for other groups seeking to conduct similar surveys of their membership.
LESSONS LEARNED
When collecting data and sending surveys, we realized that there would be things that worked well and things that did not. Here are some of the lessons learned for people who might be interested in conducting their own survey in the future.
One major takeaway was learning that providing fewer options specifically as it pertained to the SOGI questions was more inclusive than providing more options. We reduced the number of options that had been offered originally on the MAC survey and added an “other” option with an area for participants to enter in their preferred method to describe themselves. We’ve found that the terms people prefer to describe themselves often go beyond the standard response options typically used in surveys. If we don’t allow respondents the space to identify themselves more accurately, we risk misrepresenting the communities we aim to understand—and may unintentionally reinforce existing social inequalities.
As for survey design though the original Diversity Survey from MAC had been created using Qualtrics, we chose to use Redcap since that was the tool in which we had access that had the level of data security we wanted. As we collected data and tried to analyze the results, we found that the task force members were not versed in Redcap, and it was difficult to learn as you go. Therefore, we recommend that one of your team members be familiar with the tool being used for gathering the data. However, the ability to privatize the data is essential, and therefore, if you must choose between familiarity of a tool over data security, we will always recommend prioritizing data security. When considering improving the usability of the survey, we chose to use conditional IF/THEN logic, so follow-up questions only appeared when relevant, minimizing screen clutter. A visible progress bar was also added to help participants track their completion status, and an easy-to-find exit button provided a sense of control and accessibility throughout the process.
When first creating a diversity survey, the D&I task force recommends taking the time to establish the purpose, or your “so what,” and establish a guideline for what the data can and will be used for, including who will have access to the data, where it will be stored, for how long, etc. As with any other survey that involves humans, make sure to disclose those guidelines to participants so they know how their information is being used, where it is being kept, and that they have the option to opt out of participation at any time. If you are offering your participants an incentive to participate, establish what the incentive will be, who will fund it, how incentives will be awarded etc. ahead of time so that all information can be disclosed from the very beginning. Make sure to send reminders and updates on response rates to all chapter members on a regular basis through a variety of communication methods – we used social media, email, and the chapter newsletter.
One of our questions focused on MCMLA's education efforts, asking survey participants about which areas of diversity, equity, and inclusion need to be better addressed in the educational programs offered by MCMLA. The available options included age, gender/gender identity, disability, ethnic background, nationality, perceived socioeconomic status, race, religion, and sexual orientation. We included an "Other" option where respondents could write in additional areas. One participant noted "weight/size is not a protected class, and yet 60%+ of the country is overweight or obese." This participant's feedback encourages us and others to consider adding in weight/size as another aspect of diversity that could be captured in surveys and should be considered in educational offerings.
At the end of our survey, we had an option where respondents could offer "Additional Comments." One participant noted, "I can't answer a lot of these the way they are written - I haven't experience[d] or observed anything in MCMLA relating to race because almost everyone I interact with or see here is of the same general background as myself... We should consult members with diverse backgrounds while avoiding pigeon-holing them or forcing them into doing a lot of extra work." We appreciate this participant's feedback and note that this may be a limitation in the data that was collected in the survey. In any revised, future surveys, it may be necessary to consider the wording of the questions to recognize that there may be a limitation in the diversity of interactions our MCMLA members have in organizational activities.
CONCLUSION
In designing and implementing the MCMLA Diversity and Inclusion survey, the task force was committed to approaching the work with care, intention, and a willingness to learn. By building upon the foundation laid by the MAC-MLA and thoughtfully adapting survey language and design, the task force created a tool that reflects current understandings of inclusive terminology and ethical data collection. The lessons learned throughout this process—especially around the importance of asking “so what” at each step—offer valuable insights for others seeking to assess and improve the inclusivity of their organizations. As MCMLA continues its diversity, equity, and inclusion journey, this survey serves as both a starting point for deeper conversations and a model for other chapters and associations working to create more welcoming and representative library communities.
Researchers’ Positionalities Statement
The authors of this study represent a variety of personal backgrounds, including diverse races and ethnicities, sexual orientations, family structures, socio-economic levels, and professional roles. They have experience serving on DEI committees within professional associations and at their institutions. They do not, however, purport to represent all communities within the umbrella of DEI efforts as they can only speak to their own experiences and backgrounds (e.g., the authorship of this paper is comprised entirely of cisgender females and therefore cannot speak to the experiences of transgender individuals or cisgender men). The discussions laid out in this study should continue to seek to invite all to the table so more perspectives can be included.
Data Availability Statement
There is no data associated with this article.
References
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Authors’ Affiliations
Margarita Shawcross, maggie.shawcross@unco.edu, https://orcid.org/0000-0001-7891-8135, University of Northern Colorado
Brenda Linares, AHIP, blinares@umkc.edu, https://orcid.org/0000-0002-9394-4531, Associate Dean of Library Services, University of Missouri at Kansas City, Kansas City, MO
Emily Vardell, evardell@emporia.edu, https://orcid.org/0000-0002-3037-4789, Associate Professor, School of Library and Information Management, Emporia State University, Emporia, KS
Jennifer Brady, jbrady@sbuniv.edu, https://orcid.org/0000-0001-5203-7284, Head Librarian, Zalk Veterinary Medical Library, University of Missouri, Columbia, MO
Yumin Jiang. yumin.jiang@cuanschutz.edu. https://orcid.org/0009-0000-3848-9110. Department Head, Collection Management, University of Colorado Anschutz Medical Campus. Aurora, CO
Received January 2025; accepted June 2025
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