Admissions Holistic Review of Socioeconomic Factors Fosters Diversity in a Doctor of Physical Therapy Program : Journal of Physical Therapy Education

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CASE REPORT

Admissions Holistic Review of Socioeconomic Factors Fosters Diversity in a Doctor of Physical Therapy Program

Coleman-Salgado, Bryan DPT

Author Information
Journal of Physical Therapy Education 35(3):p 182-194, September 2021. | DOI: 10.1097/JTE.0000000000000187
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Abstract

BACKGROUND AND PURPOSE

Health professions admissions decisions have significant implications for students, educational institutions, and the future health care workforce. For more than 20 years, graduate and professional programs have engaged in a reconsideration of the best admissions criteria to predict success in the discipline, as well as to address equity for underrepresented minority (URM) applicants wanting to enter the professions.1 The admissions practices of many health professions education programs have long sought to identify the attributes most important for successfully completing the rigorous academic and clinical expectations that can produce diverse and successful health care providers.2-5 As more health professions education programs seek ways to diversify their graduates' racial, ethnic, and socioeconomic status, holistic review processes are looking for innovative ways to best appraise and identify sociodemographic factors, experiences, and attributes that can produce a more culturally competent workforce and address health care inequities.6

Social determinants of health include both the social processes that distribute health care resources unequally in society and the social conditions that influence health.7,8 A seminal report on holistic admissions in medical schools notes that a “lack of diversity among health professionals may contribute to disparities in access to health care and services for minority populations.”9 In addition, members of racial and ethnic minorities tend to perceive their health care to be better quality when the allied health professional is of similar racial or ethnic background.10 Production of a more sociodemographically diverse and culturally competent health care workforce may substantially contribute toward attaining a broader goal of increased health care equity.

Admissions practices that holistically consider racial and socioeconomic factors can positively influence the proportion of URMs who may enter the health care professions.11,12 Analysis of simulated undergraduate admissions show that weighting of socioeconomic status increased acceptance rates of Black and Hispanic applicants, and reduced rates for White and Asian applicants.13 When race and ethnicity cannot be used in admissions decisions—whether due to legal, political, or institutional barriers—weighting of socioeconomic factors may partially serve to act as a proxy for race and ethnicity in achieving higher rates of URM acceptance.

Typical admissions practices in health care professional programs include assessment of academic metrics—such as grade point averages and standardized test scores—as well as using reference letters and interviews to try to assess individual attributes. Primary reliance on standardized academic metrics and test scores, however, decreases admissions rates of URMs to allied health professional programs.14 Many Doctor of Physical Therapy (DPT) programs in the United States use graduate record examination (GRE) general test scores in their admissions criteria, and in doing so may be systematically disadvantaging some racial and socioeconomic groups.15-17 Increased weighting of nonacademic factors in DPT program admissions may facilitate more diversity in the racial, ethnic, and socioeconomic status of the physical therapy profession.

In physical therapy education, there is widespread support for the use of holistic review in admissions and an equally widespread variation in practice. Different rationales and purposes for holistic review exist in physical therapist education, and holistic review practices vary widely.18 Some programs simply want to discover attributes in their applicants that measure characteristics beyond academic skills—be they communication skills, “people” skills, empathy, or leadership. Other programs attempt to align their holistic practices with the mission of the institution that are most relevant to addressing equity goals and/or health care workforce needs.19 Some DPT programs are in the early stages of trialing some combination of these holistic review practices.18

An American Council of Academic Physical Therapy (ACAPT) Diversity Task Force has recently published a definition of URM in the physical therapy profession. Markers indicative of URMs included race and ethnicity, educationally disadvantaged background, low socioeconomic status, and persons from geographically underrepresented and medically underserved areas.20 The Diversity Task Force noted that this was a broader definition of URMs than that which was commonly used because it goes beyond people who identify as racial and ethnic minorities to include members of other underrepresented populations. Wise et al20 speculate that using a more narrow definition of URMs (by only referring to members of racial and ethnic minorities) makes it more difficult to recruit students from the other 3 identified underrepresented populations. Socioeconomic status is one dimension of diversity that has been incorporated into the admissions considerations of many US medical schools using definitions standardized by the American Medical College Application Service (AMCAS).21 Weighting of applicants using socioeconomic status adjusted applicants' rankings sufficiently to reduce or eliminate disparities in URM student representation.22 Black and Hispanic medical students, for example, were 3 times more likely to come from low-income backgrounds and to have attended high-poverty schools.23 A recent study found that medical schools that had undergone the AMCAS holistic review training showed a significant increase in the percentage of First-Generation, African American and Hispanic accepted and matriculated applicants compared with before the training, and when compared with medical schools that had not done the training.24 A 2019 Pew Poll found that 73% of Americans say colleges and universities should not consider race or ethnicity when making decisions about student admissions.25 In the United States, 8 states prohibit race-based admissions policies, and in California, it has been illegal in public institutions since 1996. However, there are no legal barriers to using socioeconomic classifications, and one theory postulates that using measures of socioeconomic disadvantage (SED) can result in better inclusion practices because they are attentive to both economic and racial diversity.26

The ACAPT definition of URM purposely does not distinguish which racial identities are underrepresented, with a recognition that demographics in the profession and in the US population can change over time. In 2020, the ACAPT National Equity, Diversity, and Inclusion Commission identified underrepresented racial and ethnic groups as Black, Native American or Tribal Groups, Alaska Native, Native Hawaiian, and Latinx.27 The National Health Resources and Services Administration notes that all racial minority groups except Asians are underrepresented in Health Diagnosis and Treating occupations.28 Currently, United States Census Bureau data indicate that Asians, as a racial minority, are 5.9% of the US population.29 Approximately 12.9% of the physical therapy workforce in the United States are Asian American, and the Physical Therapist Centralized Application Service (PTCAS) reports that Asians make up approximately 9.5% of accepted applicants. Therefore, from a national perspective, Asians cannot currently be classified as an URM in the US physical therapy profession.30,31 However, aggregating people of Asian American identities into one demographic category obscures the cultural, historical, and socioeconomic differences among Asian American subgroups, some of which may be underrepresented in physical therapy as they are in medical schools.32

Being a First-Generation college student is the most common nonacademic background characteristic assessed by health care programs using holistic admissions review processes in the United States.7 In 2015, the PTCAS national application started asking applicants if they were the first generation to enroll in higher education, listing this as one of several environmentally disadvantaged status factors. The AMCAS definitions of parental education, however, support the use of defining “first-generation” in college degree attainment rather than mere enrollment as a measure of the socioeconomic status for medical school applicants.33 Major undergraduate institutions are now defining First-Generation as neither parent having a 4-year college degree, and that is the definition used in this study.

In addition to socioeconomic and First-Generation status, the ACAPT Diversity Task Force cited English as a Second Language (ESL) as an example of an educational disadvantage in defining persons who identify as URMs.20 Language proficiency, familiarity with minority patients' sociocultural values, health beliefs, and lifestyles can be strengths that URMs bring to the profession. When these background strengths combine with an understanding of minority-specific health disparities and disproportionate disease burdens, physicians tend to practice in communities with higher densities of minority patients.34 Language and cultural barriers limit providers' ability to serve the needs of minority patients in ways that are culturally relevant. The valuing of second language fluency in admissions—especially when acquired as a first language—may therefore bring valuable cultural competence and diversity to the profession. Producing health care practitioners with language skills and cultural competence may lessen health inequities because the link between provider language competency and health inequities is well established.23,34

This report will 1) describe the holistic review practices in the DPT program at California State University, Sacramento (CSUS) for weighting SED and language skills; 2) report the frequencies of qualified applicants' and matriculants' language skills, SED status, race, and ethnicity; 3) analyze the relationships among and between language skills, SED scores, and racial identities; 4) analyze the relationships between language skills, SED scores, racial identities, and acceptance into the DPT program. The purpose of this study was to strengthen the evidence-based inclusion practices in our departmental admissions processes to increase URM enrollment. The purpose of disseminating the results of this study is to offer a model to DPT programs that are seeking to assess and utilize admissions practices to increase diversity of their admitted students as part of a larger effort to increase the racial, ethnic, and socioeconomic diversity of the physical therapy profession.

CASE DESCRIPTION

CSUS Holistic Admissions Practices

California State University, Sacramento is a federally designated Hispanic-Serving Institution (HSI) and Asian-American Native American Pacific Islander-Serving Institution (AANAPISI). Diversity and inclusion are among the University's explicit values. Since its inception in 1995, the CSUS DPT program has been dedicated to admissions policies that encourage access for nontraditional and underrepresented groups to the profession of physical therapy, and initially race-based admissions criterion were utilized. After race-based admissions consideration became illegal in California public institutions of higher education, SED variables became the predominant admissions factors used to attain the diversity goals of the program. Retrospective analysis of the relationship of SED background to underrepresented racial and ethnic groups was therefore one area of interest in this study.

Health professions holistic admissions practices that increase chances for admission for underrepresented applicants are often scrutinized with an underlying assumption that URM students would have higher rates of academic difficulty.35 An important challenge is to develop a systematic holistic admissions processes that address these concerns, are mission-based, evidence-informed, and applied equitably to all applicants. Previous studies by this author examined correlations between demographic factors, background characteristics, academic performance, and licensure exam success. The results were reassuring in that no significant correlations between sex, race/ethnicity, ESL or First-Generation status, and academic performance were found.36 In addition, we were able to establish GRE cutoff test scores to use as thresholds that predicted success rates on the National Physical Therapy Licensure Examination, and that also addressed the historical disadvantages that ESL applicants tended to have in passing licensure tests.37 The analytic GRE (aGRE) score (an academic metric) was subsequently eliminated as a weighted factor and changed to a minimum threshold score. In this way, the GRE scores were incorporated into the admissions criterion without making them a weighted factor, allowing more weight to be given for nonacademic factors in the admissions formula. Because the aGRE and quantitative GRE thresholds were determined based on evidence (about student success) rather than arbitrarily, faculty concerns about student success no longer conflicted with the diversity goals of the DPT program.

The background characteristics aspect of the holistic review process at CSUS considers 4 variables in the admissions rankings: 1) second language skills, 2) economic background, 3) educational background, and 4) environmental background. Because the holistic factors include valued second language skills as well as background characteristics, the variables are collectively referred to as Skills and Background Characteristics (SBCs). Socioeconomic status is a complex concept that is generally defined as access to social, financial, and cultural resources.38 The Association of American Medical Colleges has developed indicators for use in assessing the socioeconomic status of medical school applicants, which include educational and occupational categories.39 In the present study, SED was measured assessing disadvantages reported by applicants in their economic, educational, or environmental backgrounds. These efforts are aimed at increasing the diversity of our students and facilitating access to the profession for persons from demographic backgrounds who have not traditionally been accepted in proportional numbers into the physical therapy professional training programs. Terminology and definitions used in this study are summarized in Table 1.

Table 1. - Definition of Terms Used in This Study
Term Definition Used in This Study
Bilingual proficiency Being able to speak and comprehend a language in addition to English at an elementary or limited working level, often indicated by at least 2 y of college-level language courses
Bilingual fluency Being able to speak and comprehend a language in addition to English at a professional, full professional, or native speaker level
Economic disadvantage Having been raised in the lower strata of income and wealth as indicated by a relative lack of material resources and opportunities
Educational disadvantage Poor quality in K-12 educational background and/or any concomitant barriers to higher education access, including low levels of parental education, deficient or no higher education counseling in high school
Environmental disadvantage Having a background of residing in socially disadvantaged communities, including residing in a neighbourhood where there is concentrated poverty and/or the social disadvantages that often accompany poverty; also may include non–English speaking households or geographic location
First-generation The applicant reports that neither parent graduated from a 4-y college
Overrepresented racial groups Those persons self-identifying as White alone or Asian alonea
Second-language skills The extent to which an applicant has facility with a second language other than English, assessed at 2 levels: proficiency and fluency
Skills and background characteristics The cluster of variables that includes second language skills, economic, educational, and environmental background
Socioeconomic disadvantage The cluster of variables that include economic, educational, and environmental disadvantage(s)
Sociodemographic Characteristics of an applicant that includes both sociological (like education and income) and demographic (populations) characteristics (like race, gender, ethnicity, and language)
Underrepresented minority Persons of a race and ethnicity that is underrepresented in the physical therapy profession and/or persons from educationally disadvantaged background, low socioeconomic status, or from geographically underrepresented and medically underserved areas
Underrepresented racial minority Those persons self-identifying as Black/African American alone, Latinx, or American Indian alonea
aPersons of mixed (2 or more) racial identities or unknown are not included in this category.

The physical therapy program at CSUS has long considered bilingual skills to be a tangible asset in the practice of physical therapy because health care delivered by persons who are fluent in the language of the patient/clients are more effective in providing culturally competent health care services.34,35 Students with second language fluency have been afforded a slight advantage in admissions throughout the program's history. In California, 44% of the population speaks a language other than English, with 28.7% of Californians speaking Spanish and 9.9% speaking an Asian language.40 Admissions ranking points were given for second-language proficiency, and applicants who are fluent in a language other than English were given additional extra points.

To help determine SED, applicants were asked to describe background characteristics in a supplemental application. Indicators of disadvantage were suggested in the essay question prompts. Applicants were prompted that economic disadvantage, for example, could be indicated by a background of low income, such as history of receiving public assistance, eligibility for Pell Grants as an undergraduate, parental occupation at a lower socioeconomic level, near or below the federally defined poverty level, or having worked as a minor to support their family. Educational disadvantage could be indicated by factors such as being the first in the family to graduate from an institution of Higher Education, parents with little or no education beyond elementary or secondary school, no higher education counseling in high school, or graduation from a high school in the lowest 10th percentile in statewide testing. Environmental disadvantage could be based on applicant descriptions including, but not limited to, conditions of being from an underrepresented socioeconomic environment such as rural community that is medically underserved, being part of an immigrant family, residing on a Rancheria, reservation or in a migrant camp, or English was not the primary language spoken in the home.

Methods

Subjects

The CSUS Institutional Review Board approved this investigation. Two overlapping datasets were analyzed in this study. Admissions application data were collected on all matriculated students in the first 8 years of the CSUS DPT program, with the first 5 cohorts enrolling in 2012–2016, and the most recent 3 cohorts enrolling 2017–2019. After the first 5 years of DPT cohorts, the overall weighting of academic metrics decreased slightly from 58% to 55%. The remaining 45% weighting encompasses 2 types of holistic factors—the SBCs for background characteristics and assessment of individual attributes based on letters of recommendation and structured panel interview scores. Over the course of the 8 years, grade point averages weighting remained at 45% but GRE scores were eliminated beginning with the 2017 cohort, and the total SBC weighting was increased from 9.2% to 12%. Figure 1 illustrates the admissions weighting for the last 3 cohorts, wherein the nonacademic factors make up 45% of the admissions scoring.

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Figure 1.:
Admissions Weighting for the Most Recent 3 Cohorts (D06–08). GPA = grade point average; SBC = Skills and Background Characteristics; SED = socioeconomic disadvantage

All analyses were performed using SPSS version 25 for Windows (SPSS, Inc, Chicago, IL). In the first part of the study, the data analyzed included the matriculated students in the first 8 cohorts to be enrolled in the CSUS DPT program. In the second part of the study, we were able to analyze data on all qualified applicants (both accepted and not accepted) from the most recent 3 years of DPT applicant pools. The analyses included only those qualified applicants that remained in the applicant pools prior to the decision to accept the applicants or not. The SBC analysis did not include unqualified applicants or those who withdrew their applications prior to the notification of decision because we did not have a chance to accept or reject those applicants based on the weighted factors. For purposes of determining the effect of our SBC on the admissions decision, the data were analyzed on the remaining qualified applicants as to whether they were accepted or not, regardless of whether the accepted applicants matriculated or declined. Of these remaining 646 applicants, 155 were accepted and 491 were not accepted. By collecting and analyzing the data on all qualified applicants to the last 3 years of the DPT program, we are able to analyze the relationships between SBC scores, race/ethnicity, and acceptance into the DPT program. Retrospective data analyses explored the prevalence of association between the independent variables of gender, race, language skills, and the SED markers of economic, environmental, and educational disadvantage with acceptance into the CSUS DPT program (whether or not they matriculated). This analysis sought to determine if weighting of these holistic factors was disproportionately discriminating against, or favoring, any demographic or SES background groups. Figure 2 is the flowchart of all applicants for the most recent 3-year application cycles at the CSUS DPT program.

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Figure 2.:
Flowchart of Combined Applicant Pools for the Most Recent 3-Year Application Cycles to the CSUS Doctor of Physical Therapy Program

Socioeconomic disadvantage of all qualified applicants for the most recent 3 years were based on scoring of supplemental application essays. Each applicant had the opportunity to write a short essay describing why they believe they qualify for admissions points based on their language skills or SED. For consistency, one faculty reviewer was trained to read and score all essays about one socioeconomic category as either meeting the criteria or not. Applicants who were granted bilingual skills, economic, educational and/or environmental disadvantage were awarded points on an all or none basis for each variable. Beginning with the 2017 entering cohort, each of the 5 SBC variables was weighted at 2.4 percentage points. English as a Second Language status and First-Generation status were not scored or weighted as free-standing markers, but the data were extracted from the application essays and used in the analysis. Students' essays on the question about educational disadvantage were used to identify those applicants who were the first generation in their family to graduate from college. Student essays about second language skills identified those applicants for whom English was their second language.

Sex and race data for all applicants was collected. Applicants self-identified for sex and ethnicity, choosing from the categories offered on the PTCAS application. For “sex or gender,” applicants had to select 1 of 2 binary categories for (either male or female). A nonbinary gender identity was not available on the applications analyzed in this study. For race/ethnicity, applicants were allowed to select more than one race/ethnicity. In this study, a “mixed race” category identified those applicants who marked 2 or more races. The category of “2 or more” races did not include “Hispanic” because it is designated as an ethnicity rather than a race. Hawaiian and Pacific Islander identities were grouped into the “Asian” category to allow comparisons across local, state, and national data sets that tend to conglomerate these categories.

To assess the impact of weighting socioeconomic factors on race, 2 ways of dichotomizing racial groups were utilized. One method dichotomized applicants as White alone and not White alone and was aimed at discerning if the SED factors influenced acceptance rates for applicants of color differently than for White alone applicants. With this method, those who claimed 2 or more race identities were categorized as mixed race, so that the total percentages did not exceed 100%. The second method sought to assess the impact on the non-White racial or ethnic groups that are currently underrepresented in physical therapy by dichotomizing into underrepresented racial minorities (URRMs) and overrepresented racial groups (ORGs) in the physical therapy profession. The ACAPT task force definition was applied so that those racial/ethnic groups that tended to have lower percentages of physical therapists relative to the percentages in the population were operatively defined as URRMs. The URRM grouping included Black/African American, Latinx, and American Indian applicants. Use of the term Latinx in this article is interchangeable with Latino or Hispanic and denotes individuals who self-identified as being of Latin American origin or descent living in the United States. The ORG included White alone and Asian alone applicants. Those who claimed 2 or more identities (mixed) or whose racial identities were unknown (either because they checked “other” or “declined to state”) were excluded from the URRM/ORG dichotomy. Establishing these definitions and coding of the data allowed analyses of the impacts on members of racial minorities (which includes Asian Americans) as well as on people who identify as URRMs. Although the demographic factors of sex and race/ethnicity were not weighted in the admissions decisions, they were included in the analysis to detect if either of these demographic factors were associated with acceptance into the program.

OUTCOMES

Analysis of the First 8 Doctor of Physical Therapy Cohorts

Descriptive Statistics of the 8 Doctor of Physical Therapy Cohorts

Descriptive data of the gender, and racial and ethnic makeup of the matriculants, and the background characteristics of language skills, SED factors, ESL, and First-Generation were analyzed. The frequency counts of language skills and SED background characteristics that were claimed and granted on the application of the 256 matriculated students in the 8 DPT cohorts are listed in Table 2. Nearly 3 in 10 claimed second language fluency, and more than 3 of 4 DPT students claimed proficiency in a second language. In total, 28 languages were spoken fluently by student in the 8 doctoral cohorts. Spanish was the most common non-English language, accounting for 26% of the non-English languages, and the Asian languages taken together accounted for approximately 44% of the non-English language fluency. For most of the applicants (75%) who were fluent in a second language, English was not their first language. Some applicants who were ESL reported that they are merely proficient, and some for whom English was their first language had acquired fluency in a second language by educating themselves or living in another country. Although ESL was also a factor in some student descriptions of environmental or educational disadvantage, for weighting purposes, only the current language ability of the applicant was considered in determining the language skills score. Nearly 1 in 3 DPT students were the first in their family to graduate from college, and 83% of those with educational disadvantage were First-Generation. Approximately 1 in 4 claimed ESL, and 91% of them were still fluent in a second language.

Table 2. - Frequencies of Language Skills and Sociodemographic Factors Among the First 8 Cohorts of CSUS DPT Matriculants (N = 256)
Skill, Demographic, or Background Characteristic Percent of Matriculants Claiming
Bilingual proficiency 77.0
Bilingual fluency 29.7
Economic disadvantage 25.8
Educational disadvantage 34.0
Environmental disadvantage 39.8
Sex or gender (male) 42.6
ESL 24.6
First generation 29.7
Abbreviations: DPT = Doctor of Physical Therapy; ESL = English as a second language.

The frequencies of the matriculants' self-identified race/ethnicity are listed in Table 3. Almost 40% of matriculants in the 8 cohorts claimed a race/ethnic identity other than White alone. Figure 3 illustrates the number of SBC factors granted to each matriculant dichotomized by White alone race compared with all other race/ethnicity identities. The trend lines indicate decreasing numbers of SBCs among White alone applicants and an increasing proportion of SED and language skills factors among those not identifying as White alone. The trend lines in Figure 4 reflect a similar pattern showing the extent of SED among URRM compared with ORG. Nearly two-thirds of URRM matriculants had 3 or more SBCs, whereas nearly half the ORG applicants had 1 or no SBC characteristics.

Table 3. - Racial/Ethnic Identities of CSUS Matriculated Students in First 8 Cohorts (N = 256)
Percentage of Matriculated Students (Number)
White alone 60.2 (154)
Asian/Pacific Islander/Hawaiiana 13.7 (35)
Latinx 10.5 (27)
Mixed (2+ races) 8.2 (21)
Declined to state 5.9 (15)
African American/Black 0.8 (2)
American Indian 0.4 (1)
Other 0.4 (1)
aOnly 1 student was Native Hawaiian, with no Pacific Islanders.

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Figure 3.:
Proportion of the Frequency of Language Skills and Socioeconomic Disadvantage (SED) Factors Granted on Applications of Doctor of Physical Therapy Program Matriculants Dichotomized by White Alone Race and All Others (N = 237)
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Figure 4.:
Proportion of the Frequency of Language Skills and Socioeconomic Disadvantage (SED) Factors Granted on the Applications of Doctor of Physical Therapy Program D01–08 Matriculants Dichotomized by Overrepresented Racial Groups (ORGs) and Underrepresented Racial Minorities (URRMs)

Tests of Association for Skills and Background Characteristics and Dichotomized Race and Underrepresented Racial Minorities

In statistical tests of association, total SBC scores were found to be statistically significantly associated with race/ethnicity when dichotomized into White alone and Not White alone (chi-squared statistic = 31.651 and P = .000). The individual variables of language skills, SED, and gender were individually cross-tabulated and tested for association with dichotomized race, and the results are listed in Table 4. All variables except Gender and bilingual proficiency were statistically associated with dichotomized race. For those factors that were statistically significantly associated with dichotomized race, a Cramer's V posttest was used to determine how strong the association was, and interpretations based on the study by Rea and Parker41 are listed in Table 4. Of students declaring a race, the non-White matriculants were twice as likely to be in the first generation to graduate from college, nearly 3 times as likely to be fluent in a second language, and 4.5 times as likely to have ESL compared with their White counterparts.

Table 4. - Tests of Association for Language Skills, and Socioeconomic Status With Dichotomized Racial/Ethnic Identity in the First 8 Cohorts of the Doctor of Physical Therapy Program (N = 243)
Demographic, Skill, or Background Characteristic Not “White” Aloneb (%) White Aloneb (%) Chi-Squared Statistic Statistical Significance (P-value) Cramer's V Posttest Strength of Association
Gender (male) 47.7 39.5 1.524 .225
Bilingual proficiency 86.0 73.2 5.266 .024
Bilingual fluency 51.2 17.2 30.995 .000a .357 Moderate
Economic disadvantage 38.4 18.5 11.579 .001a .218 Moderate
Educational disadvantage 47.7 27.4 10.109 .002a .204 Moderate
Environmental disadvantage 55.8 32.5 12.527 .001a .227 Moderate
English as a second language 51.2 11.5 46.075 .000a .435 Relatively strong
First generation to graduate college 45.3 21.7 14.841 .000a .247 Moderate
aStatistically significant at the alpha = .01 level.
bSixteen applicants who declined to state or claimed “Other” race/ethnicity were excluded.

In statistical tests of association, total SBC scores were also found to be statistically significantly associated with members of URRMs (chi-squared statistic = 12.361 and P = .030). The individual SBC variables were individually cross-tabulated and tested for association with URRM, and the results are listed in Table 5. While all the SBC variables were higher in URRM compared with ORGs, only Bilingual Proficiency, ESL, and First-Generation were statistically significantly higher at the alpha = .01 level, with Educational Disadvantage approaching significance (P = .014). The Cramer's V posttests reveal that the strength of association was moderate for ESL and First-Generation. Matriculants who were URRM were more than twice as likely to be in the first generation to graduate from college and to have ESL compared with their ORG counterparts.

Table 5. - Tests of Association for Language Skills, and Sociodemographics With Dichotomized URRM Versus ORG in the First 8 Matriculated Cohorts of Doctor of Physical Therapy Program (N = 218)
Demographic, Skill, or Background Characteristic URRMa % Claiming ORGb % Claiming Chi-Squared Statistic Statistical Significance (P-value) Cramer's V Posttest Strength of Association
Gender (male) 58.6 40.2 3.483 .062
Bilingual proficiency 96.6 73.5 7.426 .006 .185 Weak
Bilingual fluency 44.8 25.4 4.710 .030
Economic disadvantage 34.5 24.3 1.355 .244
Educational disadvantage 55.2 31.7 6.076 .014 .167
Environmental disadvantage 58.6 38.6 4.147 .042
English as a second language 48.3 22.2 8.940 .003 .203 Moderate
First generation to graduate college 55.2 27.0 9.384 .002 .207 Moderate
P-values in bold are statistically significant at the alpha = .01 level.
aUnderrepresented racial minorities (URRMs; Latinx, Black/African American and American Indian alone).
bOverrepresented racial groups (ORGs; White alone and Asian alone).

Correlations Among the Skills and Background Characteristics Variables

The correlations between the SBC weighted variables that were significantly associated with dichotomized race are shown in Table 6. While all the scored variables were significantly associated with each other at the P < .01 level, most of the correlations were weak, except for moderate correlations between environmental disadvantage and educational disadvantage, and between educational disadvantage and economic disadvantage. The variables not counted in the admissions weighting show some notable correlations: ESL was strongly correlated with bilingual fluency (.760) and moderately correlated with environmental disadvantage. First-Generation was very strongly correlated to educational disadvantage (.833) and was also moderately correlated with environmental disadvantage.

Table 6. - Correlations Between the Variables That Were Significantly Associated With Dichotomized Race/Ethnicity in the First 8 Doctor of Physical Therapy Cohorts (N = 256)
Economic Disadvantage Educational Disadvantage Environmental Disadvantage ESL First Generation
Bilingual fluency Correlation coefficient .223 .202 .309 .760 .233
Sig. (2-tailed) .000 .001 .000 .000 .000
Economic disadvantage Correlation coefficient 1 .407 .396 .244 .399
Sig. (2-tailed) .000 .000 .000 .000
Educational disadvantage Correlation coefficient 1 .562 .298 .833
Sig. (2-tailed) .000 .000 .000
Environmental disadvantage Correlation coefficient 1 .443 .536
Sig. (2-tailed) .000 .000
ESL Correlation coefficient 1 .323
Sig. (2-tailed) .000
Abbreviation: ESL = English as a second language.
Correlation is an effect size and the strength of the correlation can be described using the following guide: .00 = none; .1–.29 “weak”; .30–.59 “moderate”; .60–.74 “strong”; .75–.99 “very strong; 1.0 = perfect.

Analysis of the Most Recent 3-Year Applicant Pools

Acceptance Rates and Skills and Background Characteristics

Table 7 reports the frequencies of language skills, socioeconomic status, race, and gender of the matriculants in the most recent 3 DPT cohorts. Acceptance into the program was found to be significantly associated with total SBC scores for the last 3 years of applicant pools (chi-square statistic = 26.096, P = .000). As with the full 8 cohorts, the higher the number of SBC variables granted, the more likely that an applicant was admitted. A moderate strength of association between Total SBC scores and acceptance into the DPT program was found (Cramer's V = .201).

Table 7. - Frequencies of Language Skills, Race and Gender for the 3 Most Recent Matriculated Doctor of Physical Therapy Cohorts (N = 96)
Skill or Background Characteristic Percent of Matriculants Claiming
Bilingual proficiency 60.4
Bilingual fluency 45.8
Economic disadvantage 30.2
Educational disadvantage 28.1
Environmental disadvantage 32.3
Sex or gender (male) 47.9
ESL 25.0
First generation 24.0
“White” alone 52.1
URRM alone 15.6
Abbreviations: ESL = English as a second language; URRM = underrepresented racial minority (Latinx, Black/African American alone, American Indian alone).

Table 8 reports the results of the chi-square tests of association between acceptance into the program and each SBC factor and for dichotomized race status. Neither bilingual proficiency, White alone race, nor being an URRM were statistically significantly different between those accepted into the program and those not accepted. Bilingual fluency, Educational, and Environmental Disadvantage are weakly associated with acceptance into the program, and Economic Disadvantage shows a moderate positive association with acceptance.

Table 8. - Tests of Association Between Skills and Background Characteristics Factors, White Alone Race, and Underrepresented Minorities and Acceptance Into the Program of all Qualified Applicants for the 3 Most Recent Doctor of Physical Therapy Application Cycles (N = 646)
Characteristic of Applicants D06–08 All Qualified Applicants (N = 646), n (%) Percent Not Accepted (N = 491) Percent Accepted (N = 155) Chi-Squared Statistic Sig. (P-value) Odds Ratio Cramer's V (Strength of Association)
Bilingual proficiency 298 (46.1) 44.0 52.9 3.765 .052
Bilingual fluency 241 (37.3) 34.2 47.1 8.357 .004a 1.71 .114 (weak)
Economic disadvantage 86 (13.3) 9.2 26.5 30.506 .000a 3.57 .217 (moderate)
Educational disadvantage 135 (20.9) 18.5 28.4 6.919 .009a 1.74 .103 (weak)
Environmental disadvantage 127 (19.7) 16.9 28.4 9.835 .002a 1.95 .123 (weak)
Race: “White” alone 310 (47.9) 46.4 52.9 1.974 .160
Underrepresented racial minoritiesb 94 (14.6) 79.8 20.2 .443 .506
aStatistically significant at the alpha <.05 level.
bUnderrepresented racial minorities are drawn from N = 569 because mixed (2 or more) and unknown (declined to state and other) were excluded from the category.

Acceptance Rates of Racial and Ethnic Groups

No overall statistically significant association between self-claimed racial or ethnicity identity and acceptance rate for the 3-year qualified applicant pool was found (chi-square statistic = 8.949, P = .256). Table 9 indicates the percent of applicant pool, frequency and acceptance rates for each self-identified race and ethnic category of qualified applicants for the 3-year period. The graph in Figure 5 illustrates the racial and ethnic profiles of the qualified applicant pool and of those accepted at CSUS in the most recent 3-year period. The average acceptance rate was 24% for all applicants, with Asian/Pacific Islanders having the lowest acceptance rate (17.6%), and applicants of mixed race having the highest acceptance rates (37%).

Table 9. - Racial and Ethnic Identities Frequency and Acceptance Rates for the Qualified Applicants That Did Not Withdraw Prior to Admissions Decision (N = 646)
Number Percent of Applicants Accepted Not Accepted Acceptance Rate (%)
American Indian alone 3 0.5 1 2 33.3
African American/Black alone 11 1.7 2 9 18.2
Asian/Pacific Islander alone 165 25.5 29 136 17.6
Latino 80 12.4 16 64 20.0
Mixed (2 or more) races 41 6.3 15 26 36.6
White alone 310 48.0 82 228 26.5
Declined to state/other 36 5.6 10 26 27.8
Total 646 100 155 491 24.0

F5
Figure 5.:
Percent of Applicants' Race and Ethnic Identities in Qualified Applicant Pool and Among Those Accepted in the Most Recent 3 Cohorts at CSUS (N = 646). AA = African American; DTS = Declined to State

Acceptance Rates of Persons from Underrepresented Racial Minorities Compared With Overrepresented Racial Groups

Tests of association between acceptance and whether the applicants were in an URRM were analyzed for all qualified applicants in the most recent 3-year period (N = 569). Although 23.4% (111/475) of ORGs are accepted, and URRMs are accepted at a 20.2% rate (19/94), there is no statistically significant association (chi-square = .443, P = .506) with acceptance into the program between ORGs (Whites and Asians) and members of URRMs (African American/Black, Latinx and American Indian). The data in Table 10 indicate that URRM have statistically significantly higher prevalence of economic, educational, and environmental disadvantage with more than double the prevalence of educational and environmental disadvantage among URRMs.

Table 10. - Tests of Association for the D06–08 all Qualified Applicants Dichotomized Between URRM and ORG (N = 569)
Demographic, Skill, or Background Characteristic URRM (%) ORG (%) Chi-Squared Statistic Statistical Significance (P-value) Cramer's V Posttest Strength of Association
Bilingual proficiency 54.3 46.1 2.090 .148
Bilingual fluency 41.5 35.6 1.182 .277
Economic disadvantage 22.3 11.8 7.466 .006a .085 Negligible
Educational disadvantage 38.3 18.7 17.516 .000a .175 Weak
Environmental disadvantage 36.2 16.6 18.823 .000a .182 Weak
Abbreviations: ORG = overrepresented racial group (White alone and Asian alone); URRM = underrepresented racial minority (Latinx, Black/African American alone and American Indian alone).
aStatistically significant at the alpha = .01 level.

To investigate a hypothesis that Asian American applicants, as an overrepresented group, may be gaining advantage because of the inclusion of language skills in CSUS's DPT program admissions, the prevalence of second language skills among Asian alone applicants was compared with URRM applicants. Among all applicants (N = 319), there was no significant difference in the percent who claimed bilingual proficiency or fluency between Asians and URRMs (Fluency: chi-square = 1.207, P = .272; Proficiency: chi-square = .093, P = .761). When Asian alone applicants were compared with Black alone applicants, there was also no advantage. Among all applicants who were Black alone or Asian alone (N = 291), there was no statistically significant difference between Black alone and Asian alone in the percentages claiming second language fluency (P = .104) or proficiency (P = .056).

The weighting of the SBC factors increased from 9.2% weighting of the SBC factors to 12% weighting beginning with the 2017 cohort. An analysis of the impact on URRM applicants from this increased weighting of SBC showed a corresponding increase in the percentage of accepted URRM applicants from 11.0% to 17.1%. This increase did not, however, represent a statistically significant change in the prevalence of URRMs in the cohorts after the increase (chi-square = 1.620, P = .203).

DISCUSSION AND CONCLUSION

Frequency Counts of Matriculants' Language Skills, Socioeconomic Disadvantage, Race, and Ethnicity

The matriculated students in the first 8 years of the CSUS DPT program demonstrate more First-Generation and ESL diversity than the national averages reported by PTCAS of accepted applicants. The CSUS program's matriculation of 30% of students who are first generation to graduate from college is significantly higher than the PTCAS accepted applicant pool of 13.3% claiming to be first generation to enroll in college—well over twice the national average of First-Generation accepted applicants. The comparison, however, may not be equivalent, given that fewer applicants' are likely to have previous generations graduate from college than merely enroll in college. In addition, first generation to graduate from college status is increasingly an indirect marker of family income because whether you graduate from college is largely determined by your parents' income. In the United States, over half of children born into the top income brackets will earn a bachelor's degree by age 25, but for the bottom quartile that number is a mere 9%.42 This relationship may account for the moderate level of association between Economic Disadvantage and First-Generation status and may also indirectly contribute to the relatively high rate of First-Generation matriculants at CSUS. Each institution that is interested in First Generation as a marker of diversity must decide which definition is most appropriate for their DPT program.

English as a Second Language was claimed by more than 1 in 4 DPT students at CSUS, and the PTCAS data reports 1.6% of accepted applicants claim that “English is not my primary language.” Although different interpretations of what is meant by “primary language” may skew a comparison of these data, enrollment of people claiming ESL at a rate nearly 16 times the national average was likely due to the long-standing policy of awarding of admissions points for second language fluency in the CSUS DPT program. Regardless of the comparison to national averages, with 46% of CSUS DPT matriculants being fluent in a second language, our DPT graduates' language skills are an excellent match with the 44% of Californians who speak a language other than English. The weighting of SED factors may have contributed to the notably higher rates of ESL and First-Generation students among those enrolled at the CSUS DPT program.

Race and ethnicity proportions at CSUS also differ from the national averages as reported by PTCAS. At CSUS, the non-White acceptance rate was 39.8%. The data available from PTCAS for the same years reports that 28.8% of accepted applicants were not White. The acceptance of non-White applicants at CSUS' DPT program was 31% higher than the average of the DPT programs using PTCAS. At 60.2% matriculated White alone students, the CSUS program is a close match with the 60.4% of the US population that is White alone according to the US Census Bureau.43 The proportion of matriculants claiming 2 or more races was markedly higher (by 165%) than the national average, possibly a reflection of the fact that the county in which the program is located has one of the highest mixed-race populations in the state, and was more than 2.5 times the mixed race percentage of the US population.43 These differences may reflect differences in applicant pools as well as the variation of local and regional demographics from national data.

Although First-Generation and ESL were not admissions factors in themselves, they were found to be strongly correlated with at least 1 other SED indicator. First-Generation was very strongly correlated with Educational Disadvantage and reflected a moderate association with dichotomized race. Unsurprisingly, ESL was very strongly correlated with second-language fluency and demonstrated a relatively strong association with dichotomized race. These data suggest that ESL and, to a lesser extent, First-Generation status are significantly more common in non-White applicants. Because the CSUS DPT program values second-language fluency, these results showing that non-White students are nearly 3 times as likely to be fluent in a second language means that weighting of language fluency skills not only may increase cultural competencies that enhance health care efficacy in minority populations but also may increase the non-White racial diversity of the student body.

Relationships Among and Between Language Skills, Socioeconomic Disadvantage Scores, and Racial Identity

Gender and bilingual proficiency were not associated with race, although the data show that male matriculants at CSUS are more than 20% higher among non-White students than among White students, and 46% higher for URRMs. The finding of a statistically significant association between total SBC scores and dichotomized race (White alone vs all others) and between URRM and ORG suggests that when all variables are included, even a relatively small weighting of these socioeconomic and language skills in admissions can play a dual role in improving both language and racial diversity. The clear and direct association shown in Figure 4 between SBCs and URRMs confirms that SED and second language fluency can be scored factors that increase acceptance rates for applicants from URRMs. Furthermore, the data in Table 4 revealed a substantial association of SED factors with non-White race. Notably, second-language fluency and all 3 measures of SED were shown to have a moderately strong association, and therefore may have some utility in increasing the proportion of non-White applicants' acceptance.

The correlations between the weighted admissions factors of bilingual fluency, economic, educational, and environmental disadvantage are generally weak or moderate, suggesting that they do not robustly measure the same things. Educational disadvantage has a moderate correlation with both economic and environmental disadvantage, and both correlation coefficients are higher than for First-Generation alone. This suggests that allowing applicants to describe educational disadvantage beyond First-Generation status incorporated environmental (e.g., rural) and economic (e.g., low income) disadvantages that correlate with an educational disadvantage. Each SED variable makes a unique, although partially overlapping, contribution that favors URM diversity in the applicant pool. The inclusion of all 3 SED variables also reflects the ACAPT URM definition and affirms that these factors should be considered as part of a holistic admissions process that is aimed at increasing URM diversity.

Relationships Between Skills and Background Characteristics Scores, Race, and Acceptance into the Doctor of Physical Therapy Program

Among all the tested variables, economic disadvantage showed the strongest association with acceptance to the CSUS DPT program. The odds of an applicant with economic disadvantage being accepted are more than 3.5 times the odds of being accepted if the applicant did not have economic disadvantage. Educational and environmental disadvantage showed statistically significantly, albeit weak association with acceptance into the program. Although all SED variables had mild levels of correlation with one another, economic disadvantage exerted more influence on acceptance than either environmental or educational disadvantage. This may be attributed to an intersection between economic disadvantages and both environmental and educational factors. The trend suggested by these data make it imperative that we refine and develop best practices for measuring SED. Incorporating the AAMC's classification of economic disadvantage based on parental occupation, for example, may bolster the DPT program's efficacy in assessing this variable.

Because socioeconomic factors (3 of the 4 ACAPT markers of URM) were significantly higher among URRM than among ORGs in the applicant pool, the weighting of all these factors is going to give some advantage to URRM in the application process and likely to engender greater URM proportions among the accepted applicants. At the same time, language skills do not seem to be significantly higher among URRMs, so that language capacity is not giving an advantage to URRMs over ORGs in the application process. For Black alone applicants, the advantages of the SED factors are not diminished by inclusion of the language skills factors vis-à-vis Asian alone applicants—the overrepresented group that is most prevalent among matriculants having a second language fluency skill.

While the white/non-white dichotomy can assess impact of using SBC factors for all applicants of color, the URRM/ORG dichotomy indicates more specifically the impact of admissions practices on Latinx, Black, and American Indian applicants. The relatively lower acceptance rates for Latinx and Asian and Pacific Islander applicants are especially concerning to the program because it is part of an HSI and AANAPISI institution. The lowest acceptance rate of any racial group is among Asian Americans, with Black applicants close behind. However, the matriculation rate of Asian Americans remained high because of the large proportion of applicants who identified in the single demographic of Asian American. In contrast, the numbers of Black applicants were dismally low, and their similarly low acceptance rate resulted in extremely low matriculation rates. Increasing from no matriculated Black students in the first 5 cohorts to 2 in the next 3 cohorts (when SBC weighting increased by 30%) may possibly indicate a trend, yet even such a positive “trend” suggests that there may be significant room for increasing the weighting of the SED factors before meaningful improvements in acceptance rates for Black applicants are apparent.

While the weighting of SED at the relatively small weighting of 12% seems to give a boost to URMs, the acceptance rate data show that this level of weighting is not sufficient to completely offset the challenges for people who identify as URRMs. The increase of accepted URRM applicants from 11% to 17% in the wake of the 2.8 percentage point increase in weighting the SBC factors has encouraged the DPT program to consider incrementally increasing the weighting of the SBC factors—particularly the SED variables—perhaps to 15% or 18%. These changes should be undertaken with an assessment of their impact on applicants of all backgrounds, and in tandem with ongoing investigations of the other holistic admissions factors for bias. The data showing lower acceptance rates among non-White applicants may be confounded by biases (either positive or negative) in the other admissions criterion. Interview and letters of recommendation score disparities, for example, will need to be investigated to root out possible areas of implicit bias that may be suppressing acceptance of URMs. Further reductions in weighting academic measures may also be indicated. Other US DPT programs are urged to integrate into their holistic admissions process those factors that may serve to offset the disadvantages that URMs may have in gaining acceptance into the physical therapy profession.

Study Limitations

The study had limitations inherent in sampling a single, public DPT program that is in a state that prohibits any weighting of race or ethnicity in higher education admissions. Physical therapist education programs should critically assess the applicability of this DPT program's definitions, scoring and weighting of those factors that might best redress URM applicants' disadvantages. Even though efforts were made to maximize reliability in scoring the SED essays, the graders may have been biased in a way that amplified or reduced certain SED claims by applicants.

The necessity to group applicants into racial categories to develop comparable data to other research data has some significant limitations. Grouping Pacific Islanders, Native Hawaiians, and all people of Asian descent into one demographic is a particular oversimplification of Asian Americans' diverse backgrounds and experiences. The disaggregation of data on Asian American subgroups was beyond the scope of this study, yet may well reveal important differences in acceptance rates among different Asian subgroups. In addition, using a unique “mixed race” category for persons of 2 or more racial groups rather than counting them as members of both races tended to undercount the numbers of non-White applicants.

The definition of “First-Generation” used in this study limits the ability to compare our data to that used by PTCAS and some researchers of undergraduate demographics because there is significant variation in how “First-Generation” is defined. For example, “First-Generation” can refer to those who are the first in their family to attend college, first in their family to graduate from college, first in their family to earn a Bachelor's Degree, or to be the first generation (older siblings may have graduated/attended to college before them) to attend or graduate from college.

CONCLUSION

The ACAPT has offered guidance about a definition of “diversity” in a contemporary context that includes SED and racial and ethnic groups. In this case study, each of the SED factors informed the holistic admissions process and contributed to diversifying the accepted applicants. The results demonstrated that a holistic admissions process that considers SED and language skills can enhance the socioeconomic and racial diversity of physical therapist student cohorts, particularly for members of URRMs. Programs are urged to consider using similar methodologies to develop evidence-based admissions policies that integrate academic rigor and reflect the sociodemographics of their unique applicant pool. Applicant selection criteria and desired outcomes will necessarily vary as to the definitions of student diversity, and by regional considerations in the economic, racial/ethnic makeup, and extent of non-English languages spoken in the populations served. No single program's inclusion practices, however, can eliminate the inequities in admissions to programs in physical therapy. Best practices for assessing socioeconomic and educational challenges need to be further developed and validated across multiple DPT programs to increase racial, ethnic, and socioeconomic diversity in the profession as a whole. Such collaborative research could contribute to best practices for the entire DPT pipeline—outreach and recruitment, admissions practices, retention and mentoring practices—that are aimed at improving the racial, ethnic, and socioeconomic diversity of the physical therapy profession. This improved diversity, in turn, may contribute toward an ultimate goal of attaining equity in health care access.

Funding

Nil.

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Keywords:

Holistic admissions; Diversity; Underrepresented minorities; Socioeconomic disadvantage

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