Associations between Prerequisite Course Completion and Race/Ethnicity, Gender, and First-Generation Status: A Single-Institution Report of the Physician Assistant Program 

Associations between Prerequisite Course Completion and Race/Ethnicity, Gender, and First-Generation Status: A Single-Institution Report of the Physician Assistant Program | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Associations between Prerequisite Course Completion and Race/Ethnicity, Gender, and First-Generation Status: A Single-Institution Report of the Physician Assistant Program Kimberly Mace, Mimoza Shehu, Annie Fox This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6098505/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Academic programs seeking to increase diversity must consider the potential that prerequisite requirements disproportionately burden individuals from diverse backgrounds. To assess this within one physician assistant program, demographics were compared between those who completed their prerequisites and those who did not. Our aim was to identify any relationship between whether applicants had completed prerequisite coursework at time of application and the applicants’ race/ethnicity, gender, and first-generation status. Methods: We conducted a retrospective review of de-identified applicants over 4 consecutive admissions cycles at one physician assistant program in the Northeast. Applicants self-reported their race/ethnicity, first-generation status, and gender. Prerequisite status for the 6 required content areas was assessed by the program. A series of logistic regression models were fit, predicting the influence of each of the demographic variables on the likelihood of prerequisites being complete. Results: Compared to White students, Black students were less likely to have completed prerequisites. Male applicants, along with applicants who did not report their gender, were less likely than female applicants to have prerequisites completed. Conclusions: These findings suggest prerequisite requirements may present a barrier for Black applicants, that is not experienced by those who are White. Findings also suggest a barrier for male applicants, and applicants who don’t report their gender, that is not experienced by females. While this data is specific to one physician assistant program, other programs and disciplines may consider similar data in their applicant pools in an exploration of strategies to support under-represented applicants to academic programs in health disciplines. admission processes under-represented minorities BACKGROUND Like many health professions in the United States, the racial composition of the physician assistant workforce differs from the population. According to 2023 data, the race composition in the US is approximately 58% White, 20% Hispanic/Latino(a), 14% Black/African American, 6% Asian, 1% American Indian/Alaska Native, and 0.3% Native Hawaiian/Pacific Islander.( 1 ) In comparison, the physician assistant (PA) workforce in the same year was 80.8% white, 6.5% Hispanic/Latino(a), 6.0% Asian, 3.3% Black/African American, 0.4% American Indian/Alaskan Native, and 0.3% Native Hawaiian/Pacific Islander.( 2 ) While discrepancies similar to this one in PA exist in other health fields, diversity has an important role in improving patient care across health systems.( 3 – 5 ) The pipeline of individuals entering PA is equally lacking diversity. In the 2019–2020 application cycle, Whites comprised approximately 72% of the applicant pool, sharply contrasting other races, with 15.6% applicants Asian, 8.7% Black, 1.2% American Indian or Alaskan Native, and 0.5% Native Hawaiian or Pacific Islander.( 6 ) Data from the Centralized Application Service for Physician Assistants (CASPA) in 2021 summarizes programs’ first-year class ethnicity as 9.5% Hispanic and race as 0.5% American Indian or Alaskan Native, 10.5% Asian, 4.9% Black, 3.1% Multiracial, 0.2% Native Hawaiian or Pacific Islander, and 69.8% White.( 7 ) Existing literature on PA applicants confirms that individuals from under-represented minorities matriculate less frequently. In CASPA data from 2012–2020, non-native English speaking applicants( 8 ) and non-US citizen applicants( 9 ) have lower odds of matriculation. While this suggests individuals from under-represented minorities may struggle to matriculate in PA programs, identifying the principal cause is challenging and, arguably, more important for identifying solutions. Foundational coursework is a staple for PA program admissions. The American Academy of Physician Associate’s Career Central lists 12 content areas that are prerequisites for “most entry-level PA programs.”( 10 ) Assuming one, three-credit course in each content area, the prerequisites listed represent 36 credits which would take a full-time student three semesters. Many programs require multiple courses within those content areas (e.g. Anatomy & Physiology 1 and Anatomy & Physiology 2). These requirements are significant and may represent a challenge for all prospective applicants.( 11 ) Prerequisites courses seemingly prepare learners with foundational knowledge needed for future coursework. Prior to professional training, prerequisites provide a measure to predict learner success and inform admissions decisions. While there is inter-disciplinary evidence that prerequisite grades can predict success,( 12 , 13 ) what defines success is important. Existing research predominantly categorizes success using academic markers like professional grade point average and credentialing exam scores which would seemingly benefit those with prior academic success. Importantly, a recent concept paper suggested that these functions of prerequisites are underscored by several assumptions.( 11 ) This work ultimately theorized that the cost and complexities of prerequisites create barriers that disproportionately impact individuals from under-represented minorities.( 11 ) There is no existing literature that concludes if prerequisites do present such a barrier. One strategy to assess the merit of this theory is to compare demographics between groups of individuals who completed their prerequisites to groups of individuals who did not. Our work aims to evaluate the applicants of one PA program in an urban Northeast setting to identify if a relationship exists between applicants’ race/ethnicity, gender, or first-generation status and whether they completed prerequisite coursework. METHODS Procedure We conducted a retrospective cohort analysis on applicants to the Massachusetts General Hospital (MGH) Institute of Health Professions Physician Assistant program during a 4-year period from 2020–2023. De-identified data was obtained from CASPA. In July 2024, the study was reviewed by the Mass General Brigham Institutional Review Board and was determined not to meet the criteria for human subject research, subsequently not requiring formal approval. Measures Demographic data for multiple characteristics was reviewed. Applicants self-reported their race/ethnicity, first-generation status, and gender. For race/ethnicity, our data was aligned with current guidelines for the Integrated Postsecondary Education Data System.( 14 ) Individuals were first asked if they identified as Hispanic and then asked to select to select one or more of the following races: American Indian, Asian, Black, Pacific Islander, or White. Individuals who selected Hispanic were coded as Hispanic. For those not identifying as Hispanic, individuals who selected a single race were coded as that race and individuals who selected multiple races were coded as Multirace. For first-generation status, applicants were asked to select Yes/No to the statement, “I am the first generation in my family to attend college (neither my mother nor my father attended college).” Applicants were able to identify their gender at the time of application including an option of ‘decline to answer.’ Because demographics were not required for final application submission, “not reported” was a potential response. The prerequisites required by the program during this time period are presented in Table 1 . There were 6 content areas for a total of 30 credits. Prerequisite status was assessed by the program for each applicant and reported as complete or incomplete. Application requirements for this program prohibit learners from being considered for admission with any outstanding prerequisites. For example, a prospective student applying for a fall start to the program would need to have all prerequisites complete prior to the application deadline (typically the preceding fall) to be considered for admission. Therefore, all learners in these cohorts who did not have completed prerequisites were denied admission. Table 1 Prerequisites required by the PA program at MGH Institute of Health Professions Topic Area Credits Lab Required Human Anatomy & Physiology 8 Yes Biology 4 Yes Microbiology 4 Yes Chemistry 8 Yes Psychology 3 No Statistics 3 No Analyses To investigate any associations between an applicant’s demographics and their likelihood of having completed prerequisites, we fit a series of logistic regression models, predicting the likelihood of prerequisites being complete. Independent variable predictors in the model included: gender, first-generation status, and race/ethnicity. Preliminary models also controlled for the effects of cohort year. However, no differences were found for year, and it was removed from all models. To ensure accurate modeling of categorical data, racial/ethnic and gender groups with small n s (American Indian ( n = 2), Pacific Islander ( n = 3), and those who selected ‘decline to answer’ for their gender ( n = 12) were removed from analyses. RESULTS Sample Characteristics There were 5254 applicants across 4 cycles with 17% ( n = 916) in 2020, 24% ( n = 1258) in 2021, 30% ( n = 1578) in 2022, and 29% ( n = 1502) in 2023. Of all applicants, 70% ( n = 3663) had prerequisites complete and 30% ( n = 1591) did not. 25% of all applicants ( n = 1303) self-identified as first in their family to go to college. Across the cycles, the percentage of applicants that identified their race/ethnicity were 0% American Indian ( n = 2), 17% Asian ( n = 900), 5% Black ( n = 273), 12% Hispanic ( n = 609), 4% Multi-race ( n = 186), 0% ( n = 3) Pacific Islander, and 59% ( n = 3121) White, with 3% ( n = 160) not reported. Female applicants accounted for 68% ( n = 3551) of the group, male applicants 17% ( n = 903) transgender/gender-non confirming/non-binary applicants represented 0% (n = 20), 0% (n = 12) declined to answer, and 15% ( n = 768) of applicants did not report their gender. Table 2 details applicant demographics by prerequisite status. Table 2 Applicant demographics and prerequisite status Prerequisites Complete n (% demographic) Prerequisites Incomplete n (% demographic) Total n (% applicants) Race / Ethnicity American Indian 0 (0%) 2 (100%) 2 (0%) Asian 655 (73%) 245 (27%) 900 (17%) Black 150 (55%) 123 (45%) 273 (5%) Hispanic 411 (67%) 198 (33%) 609 (12%) Multirace 129 (69%) 57 (31%) 186 (4%) Not reported 108 (68%) 52 (33%) 160 (3%) Pacific Islander 1 (33%) 2 (67%) 3 (0%) White 2209 (71%) 912 (29%) 3121 (59%) Gender Female 2531 (71%) 1020 (29%) 3551 (68%) Male 608 (67%) 295 (33%) 903 (17%) Transgender, Gender non- conforming, non- binary 12 (60%) 8 (40%) 20 (0%) Not reported 505 (66%) 263 (34%) 768 (15%) Declined to answer 7 (58%) 5 (42%) 12 (0%) First Generation Yes 881 (68%) 422 (32%) 1303 (25%) No 2782 (70%) 1169 (30%) 3951 (75%) TOTAL 3663 (70%) 1591 (30%) 5254 (100%) Logistic Regressions Table 3 contains the results of the logistic regression model. Compared to White students, Black students were less likely to have their prerequisites complete. Compared to female students, males and those who did not report their gender were less likely to complete prerequisites, holding race and first-generation status constant. There was no difference for those who identified as first-generation with respect to the likelihood of having prerequisites complete. Table 3 Odds ratios based on applicant demographics Predictor Odds Ratios CI p Race / Ethnicity Asian 1.17 0.98–1.38 0.081 Black 0.52 0.41–0.68 < 0.001* Hispanic 0.89 0.73–1.08 0.220 Multirace 0.96 0.70–1.34 0.808 Not reported 0.94 0.67–1.35 0.743 Gender Male 0.84 0.72–0.98 0.031 Transgender, Gender non- conforming, non-binary 0.59 0.24–1.52 0.257 Not reported 0.76 0.64–0.91 0.002* First Generation Yes 0.91 0.79–1.05 0.182 *p < 0.05, CI = Confidence Intervals DISCUSSION Our findings suggest that prerequisites may present a challenge for some groups of individuals applying to the MGH Institute physician assistant program. Specifically, Black students, male students, and those who did not provide gender designations were less likely to have prerequisites completed at the time of application. Cost and complexity associated with prerequisite coursework are two important considerations in these findings. For applicants with outstanding prerequisites, the associated cost and time commitment of satisfying those requirements may present an unsurmountable barrier. This barrier is likely to disadvantage individuals from lower socioeconomic backgrounds who generally have less tolerance for debt and delayed income.( 15 ) Further, the lack of standardization among PA programs creates a great deal of complexity. Those considering applying to multiple programs are likely to encounter different prerequisite course requirements, different practices regarding acceptable coursework, and variable policies as to whether application with outstanding prerequisites is permissible. While our program has a modest prerequisite course requirement, learners who began applications to our institution may ultimately have elected to apply to other institutions with flexible policies about accepting prerequisites after application or where certain prerequisites aren’t needed. Cost and complexity alone, however, cannot explain variability based on demographics. To explore further, we conducted a literature review. Ackerman-Barger et al.( 16 ) reviewed 5 application cycles from a single program between 2016–2019 and found results that differed from ours. These researchers reviewed common reasons for denial for approximately 7000 applicants, including exploration into demographic factors.( 16 ) Missing prerequisites was the third most common reason for denial, representing the rationale for 13.5% of their sample (far below low application score which was present for 44.7% of applicants).( 16 ) Their results identified that missing prerequisites were less common for individuals who were Black, Latino, and Pacific Islander compared to those were non-Black.( 16 ) The group also reported that denials due to prerequisites were not related to other aspects of diversity including first-generation status, economic standing, English as a primary language, or participation in academic enrichment programs.( 16 ) While our review did not include all of these variables, our finding that first generation status was not associated with incomplete prerequisites mirrors this work. Our current findings align with other studies of under-represented minorities applying to PA programs. Although not specific to prerequisite coursework, a 2022 study by Cuenca et al. collected data on experiences of diverse individuals (e.g. those identifying as URM, a sexual or gender minority, low socioeconomic status, or person with disability).( 17 ) This study noted that concerns about bias during the application process was a commonly noted barrier among these groups. The data from Cuenca et al may partially explain our findings with respect to race and those who did not report gender. If learners from these diverse groups have questions about prerequisite requirements and fear discrimination, they may avoid clarifying those requirements prior to application. Cuenca et al.’s work ultimately included only participants matriculated in PA programs and may have missed key data from those that didn’t apply or were denied admission.( 17 ) The influence of prerequisite courses on the likelihood of acceptance into PA programs has been evaluated previously in the context of minoritized groups. Data suggests that individuals from under-represented minorities are more likely to complete their prerequisites at community colleges. Further, those with academic histories that include community college are less likely to be offered admission into PA programs. These findings underscore the need of PA programs to evaluate policies and typical practices related to prerequisite coursework, aiming to identify potential and inadvertent barriers.( 18 ) We were unable to find any prior research supporting a difference in prerequisite completion rate for males when compared to female applicants. Over the last decade, the percentage of men in the physician assistants work force has declined. Males accounted for 38.3% PA graduates in 2001( 19 ) but represented only 23.9% of program matriculants in 2021.( 7 ) While it seems unlikely that prerequisites would impact males and females in different ways, this is important data to consider in the discipline’s aim to mirror population gender. With an overall goal to train future providers who resemble the patient population, programs should strive to recognize and mitigate potential barriers that inhibit qualified individuals from applying and matriculating into PA programs. Minimizing the cost and complexity associated with admissions requirements that may disadvantage certain groups is an important starting place. Programs should examine admissions data annually for relevant trends including frequently missing coursework and disparities in completion rates or grades earned between demographic groups. Prerequisite coursework should be carefully reviewed with an eye toward minimizing and standardizing the number of credit hours needed for matriculation. Programs should also consider allowing outstanding prerequisites at the time of application, and instead require completion prior to matriculation. Further analysis could be done on student success once admitted, including completion of the program, performance during the program, and score on licensing exam. Importantly, meaningful non-academic measures of student success should be tracked including retention in the profession, research contributions, and service to under-represented communities, professional organizations, and academic programs. Limitations This work is most limited by the fact that the conclusions are based on applicant data from one physician assistant program. The prerequisites required and policies related to prerequisites (e.g. applying with outstanding prerequisites) are uniquely determined by programs and our results may not be broadly generalizable. While future research should explore prerequisite status across programs, the lack of standardization regarding course requirements will present a hurdle. We would recommend examination of completion rate for individual courses or content areas both to further understand barriers for various demographics and to enhance understanding of the utility of various requirements. We were unable to evaluate all important aspects of diversity in this work, including but not limited to socioeconomic status, language and nationality, sexual orientation, age, disability status, and/or religion. These elements could reasonably alter or contribute to our understanding of prerequisite coursework as a barrier for aspiring PAs from under-represented minorities. Future research may consider different elements of diversity. Finally, while our data identifies differences for Black applicants, male applicants, and applicants who did not provide gender designations, we are unable to identify what may have contributed to these groups being less likely to have completed necessary prerequisites. Future research would benefit from a qualitative component to better capture this important information. CONCLUSIONS Between 2020–2023, individuals applying to the MGH Institute Physician Assistant program who are Black, male, and those who did not report their gender were less likely to have their prerequisites completed, compared to White or female applicants, respectively. Prerequisite coursework may present a disproportionate barrier for individuals from under-represented minorities which could subsequently contribute to disproportionate representation in the profession. PA programs should aim to explore similar data within their own applicant pools for the purposes of identifying if differences exist based on demographics. Most importantly, programs identifying potential challenges should work to employ concrete strategies to remove barriers, promoting increased diversity in the discipline. Abbreviations PA Physician Assistant CASPA Centralized Application Service for Physician Assistants MGH Massachusetts General Hospital Declarations Ethics approval and consent to participate This project was reviewed by the Mass General Brigham Institutional Review Board (IRB) and was determined not to meet the criteria for human subject research, as the data were completely de-identified and cannot be linked back to any students. The project was exempt from IRB review. Clinical trial number Not applicable Consent for publication The authors report no conflict of interest and give consent for publication. Competing interests The authors declare that they have no competing interests. Funding There was no funding for this work. Author Contribution KM contributed to the conceptualization of the study and contributed to data analysis and interpretation. MS contributed to data collection and interpretation. AF contributed to data analysis and interpretation. All authors contributed to drafting, revising, reading, and approving the final manuscript. Acknowledgements Not applicable Availability of data and materials Data generalized or analyzed during this study are included in the published article. The datasets underlying this article is available from the corresponding author on request. References Quick Facts: United States Census Bureau. 2023 [Available from: https://www.census.gov/quickfacts/ . Accessed February 23, 2025. Kozikowski A, Bruza-Augatis M, Morton-Rias D, Quella A, Fleming S, Bradley-Guidry C, et al. The Importance of Diversity in the Physician Assistant/Associate Workforce: Examining the Profession's Growth and Trends in Demographic Composition. J Med Regul. 2024;110(1):7–19. Stanford F. The importance of diversity and inclusion in the healthcare workforce. J Natl Med Assoc. 2020;112(3):247–9. Bradley-Guidry C, Burwell N, Dorough R, Bester V, Kayingo G, Suzuki S. An assessment of physician assistant student diversity in the United States: a snapshot for the healthcare workforce. BMC Med Ed. 2022;22(680):1–12. Gomez L, Bernet P. Diversity improves performance and outcomes. J Natl Med Assoc. 2019;111(4):383–92. VanderMeulen S, Snyder J, Kohlhepp W, Mustone Alexander J, Straker H, Bowser J, et al. Pipeline to the physician assistant profession: a look to the future. J Physician Assist Educ. 2022;33:e1–10. Physician Assistant Education Association. Program Report 36. PAEA Research. 2023. Najmabadi S, Valentin V, Rolls J, Showstark M, Elrod L, Barry C, et al. Non-native English-speaking applicants and the likelihood of physiican assistant program matriculation. Med Educ Online. 2024;29:1–11. Showstark M, Bessette M, Barry C, Najmabadi S, Rolls J, Hamilton C, et al. PA applicant US citizenship status and likelihood of program matriculation. BMC Med Ed. 2022;22(887):1–9. Become a PA. American Academy of Physician Associates; [Available from: https://www.aapa.org/career-central/become-a-pa/ . Accessed February 24, 2025. Mace K, Rogers K, Brown S. The Current State of Prerequisite Coursework in Health Professions Education: Function, Assumptions, and Best Practices for a Path Forward. J Allied Health. 2024;53(3):E157–66. Wilcox R, Lawson K. Predicting performance in health professions education programs from admissions information - comparisons of other professions with pharmacy. Curr Pharm Teach Learn. 2018;10:529–41. Wolden M, Hill B, Voorhees S. Predicting success for student physical therapists on the national physical therapy examination: systematic review and meta-analysis. Phys Ther. 2020;100(1):73–89. Collecting Race and Ethnicity Data from Students. and Staff Using the New Categories: National Center for Education Statistics. Accessed January 6, 2025. Chestnut R, Anderson G, Buncher O, Dietrich M, Rosenberg J, Ross L. Are prerequisite courses barriers to pharmacy admission or the keys to student success. Am J Pharm Educ. 2022;86(10):1059–63. Ackerman-Barger K, London M, Yi A, Wilson M, Fine J, Kayingo G. Understanding early admission processes: implications for physician assistant workforce diversity and healthcare equity. J Physician Assist Educ. 2022;33(2):119–21. Cuenca J, Ganser K, Luck M, Smith N, McCall T. Diversity in the physician assistant pipeline: experiences and barriers in admissions and PA school. J Physician Assist Educ. 2022;33(3):171–8. Luo Q, Erikson C, Chitwood R, Yuen C. Does community college attendance affect matriculation to a physician assistant program? A pathway to increase diversity in the health professions. Acad Med. 2022;91(1):121–8. Physician Assistant Education Association. Program Report 18. PAEA Research. 2001. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6098505","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":425491204,"identity":"98c7557b-9719-4959-968b-431d286609d1","order_by":0,"name":"Kimberly Mace","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYBACCTBZwcBgwMwDYjETq+UMyVoY24BaGIjVIjnt8MMPH+dts9vOznvsAUOFdWIDIS3S0mnGkjO33U7e2cyXbsBwJp2wFjnpBDNmXqAWg8M8ZhKMbYeJ0ZL+jfnvHJiWf0RokZbOMWNmbLhtB9HSQIQWydk5xZI9x24nALWYGyQcSzcmqEXidvrGDz9qbtsbnD9j9uBDjbUsQS0wAHIPG0MCscpBwJ4BpGUUjIJRMApGATYAAFijPLdmT5x7AAAAAElFTkSuQmCC","orcid":"","institution":"MGH Institute of Health Professions","correspondingAuthor":true,"prefix":"","firstName":"Kimberly","middleName":"","lastName":"Mace","suffix":""},{"id":425491205,"identity":"55cb2567-c5da-4aed-bdb6-b578ce57d7db","order_by":1,"name":"Mimoza Shehu","email":"","orcid":"","institution":"MGH Institute of Health Professions","correspondingAuthor":false,"prefix":"","firstName":"Mimoza","middleName":"","lastName":"Shehu","suffix":""},{"id":425491206,"identity":"1f75314a-fb9a-4d08-abdc-72a09692a8c1","order_by":2,"name":"Annie Fox","email":"","orcid":"","institution":"MGH Institute of Health Professions","correspondingAuthor":false,"prefix":"","firstName":"Annie","middleName":"","lastName":"Fox","suffix":""}],"badges":[],"createdAt":"2025-02-24 16:19:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6098505/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6098505/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78511487,"identity":"cd6d2d25-0379-43e2-a853-f628a5ab2f2d","added_by":"auto","created_at":"2025-03-14 09:46:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":659100,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6098505/v1/7e6d8f41-5daa-4035-8419-19146946fbaf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Associations between Prerequisite Course Completion and Race/Ethnicity, Gender, and First-Generation Status: A Single-Institution Report of the Physician Assistant Program ","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eLike many health professions in the United States, the racial composition of the physician assistant workforce differs from the population. According to 2023 data, the race composition in the US is approximately 58% White, 20% Hispanic/Latino(a), 14% Black/African American, 6% Asian, 1% American Indian/Alaska Native, and 0.3% Native Hawaiian/Pacific Islander.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) In comparison, the physician assistant (PA) workforce in the same year was 80.8% white, 6.5% Hispanic/Latino(a), 6.0% Asian, 3.3% Black/African American, 0.4% American Indian/Alaskan Native, and 0.3% Native Hawaiian/Pacific Islander.(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) While discrepancies similar to this one in PA exist in other health fields, diversity has an important role in improving patient care across health systems.(\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe pipeline of individuals entering PA is equally lacking diversity. In the 2019\u0026ndash;2020 application cycle, Whites comprised approximately 72% of the applicant pool, sharply contrasting other races, with 15.6% applicants Asian, 8.7% Black, 1.2% American Indian or Alaskan Native, and 0.5% Native Hawaiian or Pacific Islander.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) Data from the Centralized Application Service for Physician Assistants (CASPA) in 2021 summarizes programs\u0026rsquo; first-year class ethnicity as 9.5% Hispanic and race as 0.5% American Indian or Alaskan Native, 10.5% Asian, 4.9% Black, 3.1% Multiracial, 0.2% Native Hawaiian or Pacific Islander, and 69.8% White.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eExisting literature on PA applicants confirms that individuals from under-represented minorities matriculate less frequently. In CASPA data from 2012\u0026ndash;2020, non-native English speaking applicants(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) and non-US citizen applicants(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) have lower odds of matriculation. While this suggests individuals from under-represented minorities may struggle to matriculate in PA programs, identifying the principal cause is challenging and, arguably, more important for identifying solutions.\u003c/p\u003e \u003cp\u003eFoundational coursework is a staple for PA program admissions. The American Academy of Physician Associate\u0026rsquo;s Career Central lists 12 content areas that are prerequisites for \u0026ldquo;most entry-level PA programs.\u0026rdquo;(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) Assuming one, three-credit course in each content area, the prerequisites listed represent 36 credits which would take a full-time student three semesters. Many programs require multiple courses within those content areas (e.g. Anatomy \u0026amp; Physiology 1 and Anatomy \u0026amp; Physiology 2). These requirements are significant and may represent a challenge for all prospective applicants.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003cp\u003ePrerequisites courses seemingly prepare learners with foundational knowledge needed for future coursework. Prior to professional training, prerequisites provide a measure to predict learner success and inform admissions decisions. While there is inter-disciplinary evidence that prerequisite grades can predict success,(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) what defines success is important. Existing research predominantly categorizes success using academic markers like professional grade point average and credentialing exam scores which would seemingly benefit those with prior academic success. Importantly, a recent concept paper suggested that these functions of prerequisites are underscored by several assumptions.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) This work ultimately theorized that the cost and complexities of prerequisites create barriers that disproportionately impact individuals from under-represented minorities.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThere is no existing literature that concludes if prerequisites do present such a barrier. One strategy to assess the merit of this theory is to compare demographics between groups of individuals who completed their prerequisites to groups of individuals who did not. Our work aims to evaluate the applicants of one PA program in an urban Northeast setting to identify if a relationship exists between applicants\u0026rsquo; race/ethnicity, gender, or first-generation status and whether they completed prerequisite coursework.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eProcedure\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective cohort analysis on applicants to the Massachusetts General Hospital (MGH) Institute of Health Professions Physician Assistant program during a 4-year period from 2020\u0026ndash;2023. De-identified data was obtained from CASPA. In July 2024, the study was reviewed by the Mass General Brigham Institutional Review Board and was determined not to meet the criteria for human subject research, subsequently not requiring formal approval.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eDemographic data for multiple characteristics was reviewed. Applicants self-reported their race/ethnicity, first-generation status, and gender. For race/ethnicity, our data was aligned with current guidelines for the Integrated Postsecondary Education Data System.(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) Individuals were first asked if they identified as Hispanic and then asked to select to select one or more of the following races: American Indian, Asian, Black, Pacific Islander, or White. Individuals who selected Hispanic were coded as Hispanic. For those not identifying as Hispanic, individuals who selected a single race were coded as that race and individuals who selected multiple races were coded as Multirace. For first-generation status, applicants were asked to select Yes/No to the statement, \u0026ldquo;I am the first generation in my family to attend college (neither my mother nor my father attended college).\u0026rdquo; Applicants were able to identify their gender at the time of application including an option of \u0026lsquo;decline to answer.\u0026rsquo; Because demographics were not required for final application submission, \u0026ldquo;not reported\u0026rdquo; was a potential response.\u003c/p\u003e \u003cp\u003eThe prerequisites required by the program during this time period are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. There were 6 content areas for a total of 30 credits. Prerequisite status was assessed by the program for each applicant and reported as complete or incomplete. Application requirements for this program prohibit learners from being considered for admission with any outstanding prerequisites. For example, a prospective student applying for a fall start to the program would need to have all prerequisites complete \u003cem\u003eprior\u003c/em\u003e to the application deadline (typically the preceding fall) to be considered for admission. Therefore, all learners in these cohorts who did not have completed prerequisites were denied admission.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrerequisites required by the PA program at MGH Institute of Health Professions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCredits\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLab Required\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman Anatomy \u0026amp; Physiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicrobiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemistry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eAnalyses\u003c/h3\u003e\n\u003cp\u003eTo investigate any associations between an applicant\u0026rsquo;s demographics and their likelihood of having completed prerequisites, we fit a series of logistic regression models, predicting the likelihood of prerequisites being complete. Independent variable predictors in the model included: gender, first-generation status, and race/ethnicity. Preliminary models also controlled for the effects of cohort year. However, no differences were found for year, and it was removed from all models. To ensure accurate modeling of categorical data, racial/ethnic and gender groups with small \u003cem\u003en\u003c/em\u003es (American Indian (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2), Pacific Islander (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3), and those who selected \u0026lsquo;decline to answer\u0026rsquo; for their gender (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;12) were removed from analyses.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSample Characteristics\u003c/h2\u003e \u003cp\u003eThere were 5254 applicants across 4 cycles with 17% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;916) in 2020, 24% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1258) in 2021, 30% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1578) in 2022, and 29% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1502) in 2023. Of all applicants, 70% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3663) had prerequisites complete and 30% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1591) did not. 25% of all applicants (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1303) self-identified as first in their family to go to college. Across the cycles, the percentage of applicants that identified their race/ethnicity were 0% American Indian (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2), 17% Asian (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;900), 5% Black (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;273), 12% Hispanic (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;609), 4% Multi-race (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;186), 0% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3) Pacific Islander, and 59% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3121) White, with 3% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;160) not reported. Female applicants accounted for 68% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3551) of the group, male applicants 17% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;903) transgender/gender-non confirming/non-binary applicants represented 0% (n\u0026thinsp;=\u0026thinsp;20), 0% \u003cem\u003e(n\u0026thinsp;=\u0026thinsp;12)\u003c/em\u003e declined to answer, and 15% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;768) of applicants did not report their gender. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e details applicant demographics by prerequisite status.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eApplicant demographics and prerequisite status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrerequisites Complete\u003c/p\u003e \u003cp\u003en (% demographic)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrerequisites Incomplete\u003c/p\u003e \u003cp\u003en (% demographic)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003en (% applicants)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace / Ethnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmerican Indian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e655 (73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e245 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e900 (17%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150 (55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123 (45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e273 (5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e411 (67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e198 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e609 (12%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultirace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 (69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186 (4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160 (3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2209 (71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e912 (29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3121 (59%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2531 (71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1020 (29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3551 (68%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e608 (67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e295 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e903 (17%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransgender,\u003c/p\u003e \u003cp\u003eGender non-\u003c/p\u003e \u003cp\u003econforming, non-\u003c/p\u003e \u003cp\u003ebinary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e505 (66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e263 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e768 (15%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeclined to answer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFirst Generation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e881 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e422 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1303 (25%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2782 (70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1169 (30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3951 (75%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTOTAL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3663 (70%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1591 (30%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5254 (100%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLogistic Regressions\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e contains the results of the logistic regression model. Compared to White students, Black students were less likely to have their prerequisites complete. Compared to female students, males and those who did not report their gender were less likely to complete prerequisites, holding race and first-generation status constant. There was no difference for those who identified as first-generation with respect to the likelihood of having prerequisites complete.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOdds ratios based on applicant demographics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds Ratios\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace / Ethnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98\u0026ndash;1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.41\u0026ndash;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73\u0026ndash;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultirace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.70\u0026ndash;1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.808\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67\u0026ndash;1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.743\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.72\u0026ndash;0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransgender,\u003c/p\u003e \u003cp\u003eGender non-\u003c/p\u003e \u003cp\u003econforming,\u003c/p\u003e \u003cp\u003enon-binary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24\u0026ndash;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64\u0026ndash;0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFirst Generation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79\u0026ndash;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.182\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, CI\u0026thinsp;=\u0026thinsp;Confidence Intervals\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur findings suggest that prerequisites may present a challenge for some groups of individuals applying to the MGH Institute physician assistant program. Specifically, Black students, male students, and those who did not provide gender designations were less likely to have prerequisites completed at the time of application. Cost and complexity associated with prerequisite coursework are two important considerations in these findings. For applicants with outstanding prerequisites, the associated cost and time commitment of satisfying those requirements may present an unsurmountable barrier. This barrier is likely to disadvantage individuals from lower socioeconomic backgrounds who generally have less tolerance for debt and delayed income.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) Further, the lack of standardization among PA programs creates a great deal of complexity. Those considering applying to multiple programs are likely to encounter different prerequisite course requirements, different practices regarding acceptable coursework, and variable policies as to whether application with outstanding prerequisites is permissible. While our program has a modest prerequisite course requirement, learners who began applications to our institution may ultimately have elected to apply to other institutions with flexible policies about accepting prerequisites after application or where certain prerequisites aren\u0026rsquo;t needed.\u003c/p\u003e \u003cp\u003eCost and complexity alone, however, cannot explain variability based on demographics. To explore further, we conducted a literature review. Ackerman-Barger et al.(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) reviewed 5 application cycles from a single program between 2016\u0026ndash;2019 and found results that differed from ours. These researchers reviewed common reasons for denial for approximately 7000 applicants, including exploration into demographic factors.(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) Missing prerequisites was the third most common reason for denial, representing the rationale for 13.5% of their sample (far below low application score which was present for 44.7% of applicants).(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) Their results identified that missing prerequisites were \u003cem\u003eless\u003c/em\u003e common for individuals who were Black, Latino, and Pacific Islander compared to those were non-Black.(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) The group also reported that denials due to prerequisites were not related to other aspects of diversity including first-generation status, economic standing, English as a primary language, or participation in academic enrichment programs.(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) While our review did not include all of these variables, our finding that first generation status was not associated with incomplete prerequisites mirrors this work.\u003c/p\u003e \u003cp\u003eOur current findings align with other studies of under-represented minorities applying to PA programs. Although not specific to prerequisite coursework, a 2022 study by Cuenca et al. collected data on experiences of diverse individuals (e.g. those identifying as URM, a sexual or gender minority, low socioeconomic status, or person with disability).(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) This study noted that concerns about bias during the application process was a commonly noted barrier among these groups. The data from Cuenca et al may partially explain our findings with respect to race and those who did not report gender. If learners from these diverse groups have questions about prerequisite requirements and fear discrimination, they may avoid clarifying those requirements prior to application. Cuenca et al.\u0026rsquo;s work ultimately included only participants matriculated in PA programs and may have missed key data from those that didn\u0026rsquo;t apply or were denied admission.(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) The influence of prerequisite courses on the likelihood of acceptance into PA programs has been evaluated previously in the context of minoritized groups. Data suggests that individuals from under-represented minorities are more likely to complete their prerequisites at community colleges. Further, those with academic histories that include community college are less likely to be offered admission into PA programs. These findings underscore the need of PA programs to evaluate policies and typical practices related to prerequisite coursework, aiming to identify potential and inadvertent barriers.(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eWe were unable to find any prior research supporting a difference in prerequisite completion rate for males when compared to female applicants. Over the last decade, the percentage of men in the physician assistants work force has declined. Males accounted for 38.3% PA graduates in 2001(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) but represented only 23.9% of program matriculants in 2021.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) While it seems unlikely that prerequisites would impact males and females in different ways, this is important data to consider in the discipline\u0026rsquo;s aim to mirror population gender.\u003c/p\u003e \u003cp\u003eWith an overall goal to train future providers who resemble the patient population, programs should strive to recognize and mitigate potential barriers that inhibit qualified individuals from applying and matriculating into PA programs. Minimizing the cost and complexity associated with admissions requirements that may disadvantage certain groups is an important starting place. Programs should examine admissions data annually for relevant trends including frequently missing coursework and disparities in completion rates or grades earned between demographic groups. Prerequisite coursework should be carefully reviewed with an eye toward minimizing and standardizing the number of credit hours needed for matriculation. Programs should also consider allowing outstanding prerequisites at the time of application, and instead require completion prior to matriculation. Further analysis could be done on student success once admitted, including completion of the program, performance during the program, and score on licensing exam. Importantly, meaningful non-academic measures of student success should be tracked including retention in the profession, research contributions, and service to under-represented communities, professional organizations, and academic programs.\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eThis work is most limited by the fact that the conclusions are based on applicant data from one physician assistant program. The prerequisites required and policies related to prerequisites (e.g. applying with outstanding prerequisites) are uniquely determined by programs and our results may not be broadly generalizable. While future research should explore prerequisite status across programs, the lack of standardization regarding course requirements will present a hurdle. We would recommend examination of completion rate for individual courses or content areas both to further understand barriers for various demographics and to enhance understanding of the utility of various requirements.\u003c/p\u003e \u003cp\u003eWe were unable to evaluate all important aspects of diversity in this work, including but not limited to socioeconomic status, language and nationality, sexual orientation, age, disability status, and/or religion. These elements could reasonably alter or contribute to our understanding of prerequisite coursework as a barrier for aspiring PAs from under-represented minorities. Future research may consider different elements of diversity.\u003c/p\u003e \u003cp\u003eFinally, while our data identifies differences for Black applicants, male applicants, and applicants who did not provide gender designations, we are unable to identify what may have contributed to these groups being less likely to have completed necessary prerequisites. Future research would benefit from a qualitative component to better capture this important information.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eBetween 2020\u0026ndash;2023, individuals applying to the MGH Institute Physician Assistant program who are Black, male, and those who did not report their gender were less likely to have their prerequisites completed, compared to White or female applicants, respectively. Prerequisite coursework may present a disproportionate barrier for individuals from under-represented minorities which could subsequently contribute to disproportionate representation in the profession. PA programs should aim to explore similar data within their own applicant pools for the purposes of identifying if differences exist based on demographics. Most importantly, programs identifying potential challenges should work to employ concrete strategies to remove barriers, promoting increased diversity in the discipline.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhysician Assistant\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCASPA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCentralized Application Service for Physician Assistants\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMGH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMassachusetts General Hospital\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eThis project was reviewed by the Mass General Brigham Institutional Review Board (IRB) and was determined not to meet the criteria for human subject research, as the data were completely de-identified and cannot be linked back to any students. The project was exempt from IRB review.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eClinical trial number\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConsent for publication\u003c/h2\u003e \u003cp\u003e The authors report no conflict of interest and give consent for publication.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThere was no funding for this work.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eKM contributed to the conceptualization of the study and contributed to data analysis and interpretation. MS contributed to data collection and interpretation. AF contributed to data analysis and interpretation. All authors contributed to drafting, revising, reading, and approving the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eData generalized or analyzed during this study are included in the published article. The datasets underlying this article is available from the corresponding author on request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eQuick Facts: United States Census Bureau. 2023 [Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.census.gov/quickfacts/\u003c/span\u003e\u003cspan address=\"https://www.census.gov/quickfacts/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed February 23, 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKozikowski A, Bruza-Augatis M, Morton-Rias D, Quella A, Fleming S, Bradley-Guidry C, et al. The Importance of Diversity in the Physician Assistant/Associate Workforce: Examining the Profession's Growth and Trends in Demographic Composition. J Med Regul. 2024;110(1):7\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStanford F. The importance of diversity and inclusion in the healthcare workforce. J Natl Med Assoc. 2020;112(3):247\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBradley-Guidry C, Burwell N, Dorough R, Bester V, Kayingo G, Suzuki S. An assessment of physician assistant student diversity in the United States: a snapshot for the healthcare workforce. BMC Med Ed. 2022;22(680):1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGomez L, Bernet P. Diversity improves performance and outcomes. J Natl Med Assoc. 2019;111(4):383\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVanderMeulen S, Snyder J, Kohlhepp W, Mustone Alexander J, Straker H, Bowser J, et al. Pipeline to the physician assistant profession: a look to the future. J Physician Assist Educ. 2022;33:e1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePhysician Assistant Education Association. Program Report 36. PAEA Research. 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNajmabadi S, Valentin V, Rolls J, Showstark M, Elrod L, Barry C, et al. Non-native English-speaking applicants and the likelihood of physiican assistant program matriculation. Med Educ Online. 2024;29:1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShowstark M, Bessette M, Barry C, Najmabadi S, Rolls J, Hamilton C, et al. PA applicant US citizenship status and likelihood of program matriculation. BMC Med Ed. 2022;22(887):1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBecome a PA. American Academy of Physician Associates; [Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.aapa.org/career-central/become-a-pa/\u003c/span\u003e\u003cspan address=\"https://www.aapa.org/career-central/become-a-pa/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed February 24, 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMace K, Rogers K, Brown S. The Current State of Prerequisite Coursework in Health Professions Education: Function, Assumptions, and Best Practices for a Path Forward. J Allied Health. 2024;53(3):E157\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilcox R, Lawson K. Predicting performance in health professions education programs from admissions information - comparisons of other professions with pharmacy. Curr Pharm Teach Learn. 2018;10:529\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWolden M, Hill B, Voorhees S. Predicting success for student physical therapists on the national physical therapy examination: systematic review and meta-analysis. Phys Ther. 2020;100(1):73\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollecting Race and Ethnicity Data from Students. and Staff Using the New Categories: National Center for Education Statistics. Accessed January 6, 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChestnut R, Anderson G, Buncher O, Dietrich M, Rosenberg J, Ross L. Are prerequisite courses barriers to pharmacy admission or the keys to student success. Am J Pharm Educ. 2022;86(10):1059\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAckerman-Barger K, London M, Yi A, Wilson M, Fine J, Kayingo G. Understanding early admission processes: implications for physician assistant workforce diversity and healthcare equity. J Physician Assist Educ. 2022;33(2):119\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCuenca J, Ganser K, Luck M, Smith N, McCall T. Diversity in the physician assistant pipeline: experiences and barriers in admissions and PA school. J Physician Assist Educ. 2022;33(3):171\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuo Q, Erikson C, Chitwood R, Yuen C. Does community college attendance affect matriculation to a physician assistant program? A pathway to increase diversity in the health professions. Acad Med. 2022;91(1):121\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePhysician Assistant Education Association. Program Report 18. PAEA Research. 2001.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"admission processes, under-represented minorities","lastPublishedDoi":"10.21203/rs.3.rs-6098505/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6098505/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eAcademic programs seeking to increase diversity must consider the potential that prerequisite requirements disproportionately burden individuals from diverse backgrounds. To assess this within one physician assistant program, demographics were compared between those who completed their prerequisites and those who did not. Our aim was to identify any relationship between whether applicants had completed prerequisite coursework at time of application and the applicants’ race/ethnicity, gender, and first-generation status.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe conducted a retrospective review of de-identified applicants over 4 consecutive admissions cycles at one physician assistant program in the Northeast. Applicants self-reported their race/ethnicity, first-generation status, and gender. Prerequisite status for the 6 required content areas was assessed by the program. A series of logistic regression models were fit, predicting the influence of each of the demographic variables on the likelihood of prerequisites being complete.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eCompared to White students, Black students were less likely to have completed prerequisites. Male applicants, along with applicants who did not report their gender, were less likely than female applicants to have prerequisites completed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThese findings suggest prerequisite requirements may present a barrier for Black applicants, that is not experienced by those who are White. Findings also suggest a barrier for male applicants, and applicants who don’t report their gender, that is not experienced by females. While this data is specific to one physician assistant program, other programs and disciplines may consider similar data in their applicant pools in an exploration of strategies to support under-represented applicants to academic programs in health disciplines.\u003c/p\u003e","manuscriptTitle":"Associations between Prerequisite Course Completion and Race/Ethnicity, Gender, and First-Generation Status: A Single-Institution Report of the Physician Assistant Program ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-10 08:57:43","doi":"10.21203/rs.3.rs-6098505/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"698c1492-bdb5-4676-8d2f-7dc34c49fbd1","owner":[],"postedDate":"March 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-14T09:38:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-10 08:57:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6098505","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6098505","identity":"rs-6098505","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}