Influence of Contextual Environment and Community-Based Dental Education on Practice Plans of Graduating Seniors

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1 Milieu in Dental School and Practice Influence of Contextual Environment and Community-Based Dental Education on Practice Plans of Graduating Seniors Pamela L. Davidson, Ph.D.; Daisy C. Carreon, M.P.H.; Sebastian E. Baumeister, Ph.D.; Terry T. Nakazono, M.A.; John J. Gutierrez, B.A.; Abdelmonem A. Afifi, Ph.D.; Ronald M. Andersen, Ph.D. Abstract: This study investigated senior dental students plans to provide care to underserved racial/ethnic minority populations. Three sets of determinants were analyzed: contextual environment, community-based dental education (CBDE), and student characteristics. We analyzed data from the ADEA Survey of Dental School Seniors and administrative data sources to construct contextual variables. Multivariable results show three contextual variables predicted practice plans: greater numbers of federally qualified health centers, higher percentages of underrepresented minorities, and attending a California Pipeline dental school. Regarding CBDE predictors, it was alarming to find seniors who viewed the cultural competency curriculum as inadequate and perceived themselves as less prepared to provide oral health care to diverse populations were also those most likely to serve minority patients. Significant student characteristics included racial/ethnic minority, female gender, older age, lower parent s income, and socially conscious orientation. The study provides evidence that contextual environment, CBDE, and student characteristics were significantly associated with plans to care for underserved patients. Findings suggest if the Pipeline initiative is successful in stimulating reform in U.S. dental schools, future students will develop greater awareness regarding critical access problems and the competencies required to effectively care for diverse populations. In the long term, addressing the problem of dental care access will require the creation of policy, financial, and structural interventions to motivate providers to care for the underserved. Dr. Davidson is Associate Professor, Department of Health Services, School of Public Health, University of California, Los Angeles, and Project Director and Co-Investigator for the National Evaluation Team; Ms. Carreon is Research Associate, Department of Health Services, School of Public Health, University of California, Los Angeles; Dr. Baumeister is Research Epidemiologist, Institute of Epidemiology and Social Medicine, University of Greifswald, Germany; Mr. Nakazono is Programmer Analyst, Department of Health Services, School of Public Health, University of California, Los Angeles; Mr. Gutierrez is Project Manager, Department of Health Services, School of Public Health, University of California, Los Angeles; Dr. Afifi is Professor, Department of Biostatistics, School of Public Health, University of California, Los Angeles; and Dr. Andersen is Principal Investigator of the National Evaluation Team and Professor Emeritus, Department of Health Services, School of Public Health, University of California, Los Angeles. Direct correspondence and requests for reprints to Dr. Pamela L. Davidson, University of California, Los Angeles, Department of Health Services, CHS , 650 C.E. Young Drive South, Campus Box , Los Angeles, CA ; phone; fax; Davidson@ucla.edu. Key words: dental practice intention, dental education, access to dental care Submitted for publication 7/31/06; accepted 11/7/06 The nation s dental care safety net is inadequate to serve the population in need, and access problems are likely to intensify. 1,2 Access barriers are created on several fronts not the least of which are the following: 1) so few underrepresented minorities enter dentistry; 2) a general apathy regarding societal responsibility to care for underserved populations among dental schools, faculties, and the students they historically recruit; 3) little or no government reimbursement to provide care to low-income, uninsured populations; and 4) sizeable educational debt incurred by dental school seniors, which immediately accrues interest upon graduation. Minority representation in the dental and other health professions remains a concern. 3-5 The shortage of dentists is particularly critical in African American and Hispanic communities. 6-8 This study analyzed dental school senior students plans to provide care to underserved racial/ ethnic minority populations. The Robert Wood Johnson Foundation (RWJF) and The California Endowment (TCE) funded the Pipeline, Profession, and Practice: Community-Based Dental Education program to address the critical shortage of oral March 2007 Journal of Dental Education 403

2 health care services for underserved and disadvantaged populations by changing dental education in the United States. RWJF funded competitive grants proposed by eleven of the fifty-six accredited U.S. dental schools, and one year later, TCE funded four additional dental schools in California to design and implement a Pipeline program. Additionally, TCE required all five of California s dental schools to develop a regional recruitment program for underrepresented minorities and a collaborative statewide health policy effort to sustain the Pipeline initiative after funding ends. The three Pipeline objectives are: 1) increase recruitment and retention of underrepresented minority and low-income students; 2) revise didactic and clinical curricula to support community-based educational programs; and 3) establish communitybased clinical education programs that provide dental students and residents with sixty days of experience in a patient care environment. 9,10 This study examines student characteristics (e.g., race/ethnicity), community-based dental education (e.g., curriculum and clinical rotations), and contextual environment (e.g., number of federally qualified health centers in the county) on a longer-term outcome, the practice plans of senior dental students. Data were analyzed from the 2003 American Dental Education Association (ADEA) Survey of Dental School Seniors and a set of contextual variables. To our knowledge, this study is the first to include individual and contextual-level variables to investigate plans to provide care to underserved minority patients upon graduation; no other studies were found in the literature combining these levels of data. From a methodological perspective this study advances the use of contextual variables in dental education and dental health services research and provides detailed information on constructing contextual variables. The study examines baseline measures before the Pipeline program was implemented in academic year Future evaluation research will analyze data collected in the 2007 ADEA survey, when foundation funding culminates, to examine the impact of the Pipeline program on practice plans of graduating seniors. Literature Review Articles were identified from medical and health services research journals using PUBMED database and the following keywords: plans upon graduation, early and long-term career decisions, practice decisions, preferences, motivations, and interests. Research has emphasized different aspects of practice plans, such as practice location, practice arrangement (solo versus group practice), 4,15-17 and postdoctoral education and specialization. 18,19 Six studies specifically investigated factors influencing plans to provide care to underserved and minority populations. 4,20-24 Several researchers focused on the personal characteristics of students or dentists, such as gender and race/ethnicity; 4,15-18,24 only a few explored variables that influence the individual, i.e., educational program and economic factors. 12,21,22 The following sections summarize findings from the research literature on determinants of practice plans including student characteristics, community-based dental education, and contextual variables. Student Characteristics In part, the Pipeline initiative was promulgated on the belief that workforce diversity may help to alleviate disparities in oral health care for low-income and underserved populations. Minority providers may be more culturally sensitive to their minority patients needs. Our review yielded only a few studies examining the relationship between race/ethnicity and plans to provide care for minority patients. One study showed African Americans compared to whites were more likely to establish practices in underserved communities, provide care to uninsured and Medicaid beneficiaries, and continue service after participation in the National Health Service Corps. 4,15,21 In studying the supply of dentists in California, Hayes-Bautista et al. 5 found Latino dentists comprised 4.6 percent of the total dental supply in Although Latinos comprise about a third of the state s population, only one out of every twenty dentists was Latino. Our search yielded no literature on practice plans of American Indians. Clearly, more research is needed to understand recruitment of underrepresented minorities to dentistry and implications for practice upon graduation. The root problem for the underrepresented minority groups (African American, American Indian, and Hispanic) appears to be that so few apply for and are accepted into dental school. A report issued by ADEA found underrepresented minorities comprised 12.4 percent of the applicant pool and 11.6 percent of first-year enrollees in Asian/ Pacific Islanders and whites comprised 69.7 percent of applicants and 404 Journal of Dental Education Volume 71, Number 3

3 71.1 percent of first-year enrollees (see Table 3 in Weaver et al. for more detailed information). 26 Other student characteristics, such as gender and age, have been found to influence dental students preferences for type and specialty of practice. 15,19,27,28 For instance, males have consistently rated the solo owner practice arrangement more favorably than females ,29 Age significantly influences the decision to enter into an academic career, with younger individuals finding income of an academic dentist to be a deterrent. 19 However, the search yielded no studies indicating gender or age was associated with providing care to the underserved. Our search yielded few studies showing the relationship between attitudes and beliefs and practice plans. Medical students when compared to dental students were found to demonstrate greater altruism and a sense of intellectual challenge as motivating factors in career choice; dental students demonstrated more commitment to personal and financial gain. 18 In studying attitudes of family physicians, Eliason et al. 24 found an association between universalism values (i.e., motivation to enhance and protect all people) and the number of indigent patients served. Li et al. 23 found primary care providers who had a strong sense of service to humanity were more satisfied with their work. Some believe inequities are compounded in dentistry more than medicine due to tensions within the dental profession between the moral values traditionally identified with the health professions and the commercial values of practice achieved through entrepreneurial self-interest. 30 In summary, although the literature is limited, research suggests certain student characteristics (race/ethnicity, attitudes, and beliefs) do predict practice plans. Community-Based Dental Education In a descriptive study, Smith et al. 20 found a positive relationship between curricular emphasis on treating patients from diverse backgrounds and student and alumni intentions to care for these patients in their practices. Findings from another study showed greater time spent in rotations was a significant predictor of perceived ability to provide care to diverse groups. 31 In a third study, Mofidi et al. 21 found 46 percent of alumni who participated in the National Health Service Corps continued to provide care to underserved groups. In contrast, DeCastro et al. 22 found no significant differences in alumni attitudes towards practicing in underserved areas or accepting Medicaid patients between a communityoriented dental education program and a traditional program. Although results are somewhat equivocal, the literature does suggest some correlation between preparation in the academic programs (didactic and clinical rotations) and the extent to which care is provided to underserved patients in future practice. Contextual Environment Contextual variables represent the social, economic, structural, and public policy environment influencing access to care. 32,33 As noted, much of the literature on practice plans focuses on the characteristics of the decision maker (student or dentist) and a few on the educational program. Our search yielded only one study testing the effects of contextual variables on plans to provide care to underserved patients. Beazoglou et al. 12 found size of population, per capita disposable income, and cost of operating a dental practice were significantly associated with number of practicing dentists in 140 Connecticut townships. The study examined distribution of dentists in the state, but did not analyze the influence of individual characteristics or academic program on the decision-making process; only contextual variables were analyzed in this study. Materials and Methods The following sources of data were used to investigate senior dental students plans to provide care to underserved racial/ethnic minority populations. From the ADEA Annual Survey of Dental School Seniors, questionnaire items were identified that best represent student characteristics and components of community-based dental education using a conceptual and analytical model to guide variable selection (Figure 1). The ADEA survey administers an annual questionnaire to graduating seniors in accredited dental schools. The survey collects information about social and demographic characteristics, educational financing, indebtedness, adequacy of time in predoctoral instruction, preparedness for practice, and practice and postdoctoral plans. 25 Additionally, starting in 2003 the survey began collecting information related to the Pipeline initiative and community-based dental education, e.g., recruitment, curriculum, and extramural clinical rotations. Each school uses its own survey distribution and collection system. Surveys are returned annually to March 2007 Journal of Dental Education 405

4 Contextual Environment Policy Population Delivery System Dental School Pipeline Status at Dental Schools National Pipeline California Pipeline Non-Pipeline (n=10) (n=5) (n=38) Community-Based Dental Education RECRUITMENT Factors affecting decision to pursue dentistry career CBDE CURRICULA Time devoted to cultural competency Preparedness for providing care to diverse groups EXTRAMURAL CLINICAL ROTATIONS Influence of practice location (positive or negative) # Weeks in extramural rotations Student Characteristics Demographic Race/Ethnicity Gender Age Marital Socioeconomic Parent s income Father s education Education Expenses & Debt Participation in loan repayment Debt upon graduation Attitudes & Beliefs Socially conscious Cultural awareness Service orientation Entrepreneur Plans to Care for Underserved Minority Patients Figure 1. Measurement model for predicting plans to care for underserved minority patients ADEA for reporting and analysis. Additionally, a set of constructed contextual variables came from administrative data sources measuring policy, population, dental care delivery system, and dental school environment. (See Table 1 for a detailed list of data sources and references used to construct contextual variables.) Figure 1 presents a measurement model for predicting plans to care for underserved minority patients. The model posits contextual environment, community-based dental education (CBDE), and student characteristics influence practice plans of graduating seniors. The variables selected to measure the various constructs, along with their definitions and distributions, are provided on Table 1. The dependent variable for students practice plans was measured using the following ADEA questionnaire item: When you enter practice, about 406 Journal of Dental Education Volume 71, Number 3

5 what percent of your patients do you expect will be from underserved racial/ethnic minority populations? The variable included five response categories (or cut points): 0 percent (n=177, 4.8 percent), 1-10 percent (n=1460, 39.5 percent), percent (n=1246, 33.7 percent), percent (n=291, 7.9 percent), and greater than 50 percent (n=234, 6.3). We combined the percent and greater than 50 percent categories for the analysis (n=525, 14.2 percent). A practice plans intervening variable was included and constructed into a categorical measure indicating primary activity immediately upon graduation: 1) private practice (49.9 percent), 2) community clinic or government service (9.9 percent), and 3) postdoctoral or academic appointment (40.2 percent). Independent variables in the measurement model are discussed in the sections below: contextual environment, CBDE, and student characteristics (Figure 1). The contextual environment included policy, population, dental care delivery system, and dental school characteristics (Table 1). Federal, state, and local health policies influence dental care financing and the percent of the population with public insurance. Racial/ethnic representation in the state legislature can influence resources for medical and dental education and the availability of services for vulnerable populations. Two state policy variables were measured: percent underrepresented minorities in the state legislature (mean=16.8, range percent because the study includes Puerto Rico); and adult Medicaid dental coverage: no benefits (15 percent), emergency only (18.2 percent), partial coverage (39.4 percent), and full coverage (27.3 percent). Contextual variables can be used to measure population characteristics and their collective effect on access. For example, when large numbers of low-income, racial/ethnic minority groups and/or uninsured persons reside in a geographic area, access barriers are magnified for individuals competing for limited services and resources. 32 When dental students have the opportunity to train in communitybased settings, potentially they will become more aware of access barriers and better trained to respond to population oral health needs. Two county-level population variables were measured: percent underrepresented minorities (ranging from 4.6 to 98.3 percent because the study includes Puerto Rico); and percent population with income less than 200 percent of the federal poverty level (ranging from 15.8 percent to 63.6 percent). Three contextual variables measured the dental care delivery system: 1) practicing dentists per 10,000 population for each state and District of Columbia (ranging from 3.9 to 12.6); 2) number of federally qualified health centers (FQHCs) in the county providing dental care (ranging from 0-10); and 3) number of federally qualified health centers (FQHCs) in the county per 100,000 low-income residents (ranging from 0 to 81.7). The final set of contextual variables measured dental school environment (Table 1). Data collected by the American Dental Association (ADA) were used to show university ownership (public or private). Two variables were constructed from dental school mission statements: commitment to recruiting diverse students and providing health care to underserved populations. Two school-level variables were measured: percent underrepresented minority (URM) dental students (years 1-5); and average total educational cost for first-year students. The final contextual variable measured the dental school s aggregate cultural and social environment using average values at the school level from the following ADEA questionnaire item: The cultural and social environment of your school promotes acceptance and respect of students and patients of different races, ethnicities, and cultures, measuring level of agreement using a four-point Likert scale. Additionally, the measurement model (Figure 1) included a critical program evaluation measure showing Pipeline program status among the accredited dental schools: 1) National Pipeline schools funded by the Robert Wood Johnson Foundation; 2) California Pipeline schools funded by The California Endowment; and 3) non-pipeline dental schools. The University of California, San Francisco (UCSF) was funded by both foundations. However, we included UCSF in the California Pipeline category because all schools in the state of California received Pipeline program funding and are engaged in collaborative statewide recruitment and health policy initiatives. In addition to contextual environment, we investigated a set of community-based dental education (CBDE) variables hypothesized to influence practice plans (Figure 1). Specifically, we examined variables representing 1) recruitment of underrepresented minority students, 2) CBDE curricula, and 3) extramural clinical rotations. Recruitment measures tested included Importance of the following factors in influencing the decision to pursue dentistry as a career : a) high school or college counselor, b) recruitment by a dental school, c) pre- or post-baccalaureate dental career program, and d) awareness March 2007 Journal of Dental Education 407

6 Table 1. Description and distribution of independent and dependent variables Domain and Definition Geographic % or Mean Range* Indicator Unit of (Standard Observation Deviation) Contextual Environment Policy % URM in State This state level variable reflects the percent of African State 16.8 (18.2) Legislature 1 American and Latino senate and house members in the legislature. The numerator is the number of African American and Latino persons and the denominator is the total number of legislative seats. Adult Medicaid States were categorized according to Medicaid dental State No benefits=15.1% Dental Benefits 2 coverage provided to adults, 21+ years in The Emergency only= constructed variable reflects the level of dental benefits 18.2% provided: 0 for no benefits, 1 for emergency-only, Partial coverage= 2 for partial/limited coverage to adults, and 3 for 39.4% full coverage. Full coverage=27.3% Population Characteristics % URM Census data were used to construct a variable County 33.1 (20.0) population 3 reflecting the percent of the total population in the dental school s county that was URM (AA, Hispanic, AI/AN). The numerator is the total number of URM persons in the county. The denominator is the total population in the same county. % Federal Poverty The numerator includes those with low-income County 31.6 (8.5) Level <200% 3 (less than 200% federal poverty level, FPL) in the county. The denominator includes the total county population. Delivery System Dentists to The variable measures the supply of professionally County 6.0 (1.5) Population Ratio 4 active dentists per 10,000 population in The numerator includes dentists who indicated or were assigned an active occupation code as either primary or secondary occupation. These occupation categories include: active practitioners, dental school faculty or staff, armed forces, government employed dentists at the federal, state, or local levels, interns and residents, and other health or dental organizational staff members. The denominator reflects the estimated 2001 U.S. population (thousands) for the states and outlying areas from Census Bureau. # of FQHCs 5 The variable represents a simple count of the number County 2.4 (2.4) 0-10 of FQHCs in the county providing dental care. FQHCs /100kFPL The numerator is the number of FQHCs in the county. County 2.8 (11.9) <200% 5 The denominator is the number of low-income persons per 100,000 with income less than 200% of the federal poverty level. Dental School Pipeline Status 6 A categorical variable was constructed to reflect School National=19.2% school status related to the dental Pipeline program. California=9.6% This school level intervention variable reflects three Non-Pipeline=71.2% dental school categories: National (n=10), California (n=5), and non-pipeline (n=40). Ownership 7 The variable was constructed from the ADA 2002/03 School Public=65.4% Survey of Predoctoral Dental Education, Group 1, Private=34.6% Question #9: What type of support does your dental school receive: (a) public-dental school is state supported, (b) private-dental school is privately supported and receives no state aid, (c) private-state related-privately supported dental school receives a per capita enrollment subsidy from the state. The categorical variable was coded to reflect school status as (1) public or (2) private institution. 408 Journal of Dental Education Volume 71, Number 3

7 Table 1. Description and distribution of independent and dependent variables (continued) Domain and Definition Geographic % or Mean Range* Indicator Unit of (Standard Observation Deviation) Mission Statement: The School of Dentistry s (SOD) mission statement School Commitment=21.6% --- Commitment to indicates a commitment to recruiting diverse students. recruit URM 8 This school level variable is coded 0 if the SOD does not state a specific commitment to recruiting diverse students. The variable is coded 1 if the SOD directly states a commitment to recruiting diverse students. Mission Statement: The School of Dentistry s (SOD) mission statement School Commitment=19.6% --- Commitment to indicates a commitment to providing oral health care provide care to to underserved populations. This school level variable URM 8 is coded 0 if the SOD does not state a specific commitment to provide care to the underserved. The variable is coded 1 if the SOD directly states a commitment to provide care to the underserved. % URM in ADA 2002/03 Survey of Predoctoral Dental Education, School 12.8 (18.5) dental school 7 Group 2, Question #2: Schools were asked to report enrollment figures by race/ethnicity, gender, and academic year. The numerator represents the total number of URM students (AA, Hispanic, AI/AN). The denominator is the total number of dental students. Total educational ADA 2002/03 Survey of Predoctoral Dental Education, School $26,666 (12,292) $9597-$67,034 cost for first year 7 Group 2, Question #10a: What is the average cost of the following to the undergraduate dental student for the current academic year? The cost includes tuition, mandatory general fees, and other educational costs reported by the schools. School cultural The variable was constructed by averaging responses School 3.2 (0.2) and social of students completing the ADEA Survey of Dental environment 9 School Seniors (Q44c): Please indicate if you agree or disagree with each of the following statements: The cultural and social environment of your school promotes the acceptance and respect of students and patients of different races, ethnicities, and cultures [4-point scale, strongly disagree (1) to strongly agree (4)]. Community-Based Dental Education Recruitment Importance of This variable was constructed from the ADEA Survey Student 1.6 (1.1) 1-5 high school or of Dental School Seniors, Question 11a [5-point scale, college counselor low (1) to high (5)]. in decision to pursue dentistry as a career 9 Importance of This variable was constructed from the ADEA Survey Student 1.7 (1.1) 1-5 recruitment by of Dental School Seniors, Question 11e [5-point scale, a dental school low (1) to high (5)]. in decision to pursue dentistry as a career 9 Importance of This variable was constructed from the ADEA Survey Student 2.0 (1.3) 1-5 pre- or post-bac of Dental School Seniors, Question 11f [5-point scale, dental career low (1) to high (5)]. program in decision to pursue dentistry as a career 9 (continued) March 2007 Journal of Dental Education 409

8 Table 1. Description and distribution of independent and dependent variables (continued) Domain and Definition Geographic % or Mean Range* Indicator Unit of (Standard Observation Deviation) Importance of This variable was constructed from the ADEA Survey Student 2.9 (1.4) 1-5 workforce supply of Dental School Seniors, Question 11j [5-point scale, and demand low (1) to high (5)]. trends in dentistry in decision to pursue dentistry as a career 9 Time devoted This variable was constructed from the ADEA Survey Student Inadequate=25.1% 1-3 to cultural of Dental School Seniors, Question 32u: Do you Appropriate=68.5% competency 9 believe time devoted to instruction in cultural Excessive=6.4% competency was excessive, appropriate, or inadequate? [3-point scale, excessive (3), appropriate (2),inadequate (1)]. Preparedness This variable was constructed from the ADEA Survey Student 3.4 (0.96) 1-5 to provide oral of Dental School Seniors, Question 33w: Please health care for indicate your personal assessment of preparedness racial, ethnic for oral health care for racial, ethnic, and culturally and culturally diverse groups. [5-point scale, not well enough diverse groups 9 prepared (1) to well prepared (5)]. Extramural This variable was constructed from the ADEA Survey Student 2.2 (1.1) 1-5 clinical of Dental School Seniors, Question 42: Did your experiences extramural clinical experiences influence your practice influence location plans? [5-point scale, not at all (1) to very practice location much (5)]. plans 9 Extramural This variable was constructed from the ADEA Survey Student 3.8 (1.0) 1-5 clinical rotation of Dental School Seniors, Question 43: Were your positive or extramural clinical rotations positive or negative negative experiences in your dental education? [5-point scale, experience 9 very positive l (1) to very negative(5)]. Weeks of This variable was constructed from the ADEA Survey Student 6.6 (10.1) 0-54 extramural of Dental School Seniors, Question 34: Enter... clinical the number of required weeks you expect to spend rotation 9 over your last year in dental school providing (not just observing) dental care at extramural clinics/ practice settings. Primary activity This variable was constructed from the ADEA Survey Student Private practice= --- upon graduation 9 of Dental School Seniors, Question 24: Immediately 49.9% upon graduation from dental school do you intend Comm clin/govt your primary activity to be. The constructed variable services=9.9% reflects 3 categories, private practice, community Academic/ clinic/govt services, and dental school/academic/ postdoc=40.2% postdoc. Student Characteristics Gender 9 This variable was constructed from the ADEA Survey Student Female=40.7% --- of Dental School Seniors, Question 1 (male and female) Male =59.3% Age 9 This variable was constructed from the ADEA Survey Student 28.1 (3.5) of Dental School Seniors, Question 3: Age at time of graduation from dental school. Race/Ethnicity 9 This variable was constructed from the ADEA Survey Student URM =10.0% --- of Dental School Seniors, Question 2. African- Asian/PI =26.3% Americans, Hispanics, and Native Americans were White =63.7% combined into the URM group and Asian/ Pacific Islanders and whites were kept separate. Marital Status 9 This variable was constructed from the ADEA Survey Student married =43.4% --- of Dental School Seniors, Question 4 (married and not married =56.6% not married). 410 Journal of Dental Education Volume 71, Number 3

9 Table 1. Description and distribution of independent and dependent variables (continued) Domain and Definition Geographic % or Mean Range* Indicator Unit of (Standard Observation Deviation) Parents annual This variable was constructed from the ADEA Survey Student <=$30,000=14.7% --- household of Dental School Seniors, Question 6: Estimate your $30,001-$50,000= income 9 parents combined annual income before taxes. 13.2% The constructed variable reflects 3 categories, $50,001+= 72.1% <$30,000; $30,000-$50,000; and >$50,000. Debt upon This variable was constructed from the ADEA Survey Student $118,748 ($73,004) 0-$350,000 graduation 9 of Dental School Seniors, Question 20: Estimate your total educational debt upon graduation from dental school. Participation in This variable was constructed from the ADEA Survey Student Yes=9.3% --- loan repayment of Dental School Seniors, Question 13: To what No=90.7% program 9 extent did you participate in your dental school s retention programs such as receiving tutoring or counselling? Father s This variable was constructed from the ADEA Survey Student Less than college --- educational of Dental School Seniors, Question 7: Select the =21.8% attainment 9 highest level of education for your father. The At least some constructed variable reflects 2 categories, less than college=78.2% college and at least some college. Cultural sensitivity This variable was constructed from the ADEA Survey Student 9.8 (2.0) 3-12 scale 9 of Dental School Seniors, Questions 44a, 44b, 44c: You are prepared to accept and respect patients of different races, ethnicities, and cultures ; You are prepared to integrate knowledge regarding cultural differences into treatment planning and care delivery ; The cultural and social environment of your school promotes acceptance and respect of students and patients of different races, ethnicities, and cultures. [4-point scale, strongly agree (1) to strongly disagree (4)]. Service This variable was constructed from the ADEA Survey Student 9.9 (2.7) 2-15 orientation of Dental School Seniors, Question 10: For each of scale 9 the following reasons indicate its importance to you in selecting dentistry as a career. Three of the nine reasons for selecting dentistry as a career were used: service to others, service to my own race or ethnic group, and opportunity to serve vulnerable and low-income populations. Entrepreneurial This variable was constructed from the ADEA Survey Student 8.5 (1.6) 2-10 scale 9 of Dental School Seniors, Question 10: For each of the following reasons indicate its importance to you in selecting dentistry as a career. Two of the nine reasons for selecting dentistry as a career were used: opportunity for self-employment and high income potential. Socially conscious This variable was constructed from the ADEA Survey Student 11.8 (2.4) 1-16 scale 9 of Dental School Seniors, Questions 44f, 44g, 44h, 44i: access to care is a societal good and right, access to oral health care is a major problem in the United States, assuring and providing care to all segments of society is an ethical and professional obligation, and everyone is entitled to receive basic oral health care regardless of his or her ability to pay [4-point scale, strongly agree (1) to strongly disagree (4)]. *For individual level measures, the range reflects the variation among the schools. 1 National Conference of State Legislatures, At: Accessed: April Schneider D, Schneider K. Medicaid dental care for adults: a vanishing act? National Oral Health Conference, April 28, United States Census Bureau. Summary data file for the United States. Washington, DC: U.S. Government Printing Office, American Dental Association Survey Center. Distribution of dentists in the U.S. by region and state, Chicago: American Dental Association, Health Resources and Services Administration s Bureau of Primary Health Care s Uniform Data System, American Dental Education Association. Survey of dental school seniors. Washington, DC: American Dental Education Association, American Dental Association. Survey of predoctoral dental education, Chicago: American Dental Association, The School of Dentistry s websites were visited in July 2004 for the 56 U.S. accredited dental schools to obtain mission statements. When necessary, a phone call was made to the admissions office requesting a copy of the mission statement if it was not available on the website. 9 American Dental Education Association. Survey of dental school seniors, Washington, DC: American Dental Education Association, March 2007 Journal of Dental Education 411

10 of workforce supply and demand trends in dentistry, using a five-point Likert scale ranging from 1 (low) to 5 (high). Two curricular measures were selected for the study: 1) adequacy of time devoted to your instruction in cultural competency was measured using three response categories: inadequate (25.1 percent), appropriate (68.5 percent), and excessive (6.4 percent); and 2) level of preparedness for providing oral health care for racial, ethnic, and culturally diverse groups was measured using a five-point Likert scale ranging from not well enough prepared to well prepared (mean=3.4, s.d.=0.96). Extramural clinical rotation measures included the following: 1) extramural clinical experiences influenced your practice location plans, using a five-point Likert scale ranging from not at all to very much; 2) were your extramural clinical rotations positive or negative experiences in your dental education? using a five-point scale ranging from very negative to very positive; and 3) number of weeks providing dental care at extramural clinics, providing an open-ended space for seniors to indicate a response. Student characteristics were categorized as demographic, socioeconomic, educational expenses and debt, and attitudes and beliefs regarding dental practice and access (Table 1). Student characteristics included gender, age, race/ethnicity, marital status, parents annual household income (as a proxy for student resources), father s educational attainment, participation in a loan repayment program, and debt upon graduation. For the race/ethnicity variable, African Americans, Hispanics, and American Indians were combined into an underrepresented minority group (10 percent), and Asian/Pacific Islanders (26.3 percent) and whites (63.7 percent) were kept separate. Parents income was divided into three categories: 1) less than $30,000 (14.7 percent); 2) $30,001-$50,000 (13.2 percent); and 3) greater than $50,000 (72.1 percent). Since the Pipeline program is targeting lowincome students, we chose relatively lower income thresholds to examine differences among the lowest income families. According to the U.S. Department of Health and Human Services 2003 HHS Poverty Guidelines, the 200 percent Federal Poverty Level income threshold for a family of three was roughly $30,000; we categorized $30,001-$50,000 as a moderate income level; the >$50,001 comprised the rest of the sample. Four scales were constructed from the ADEA questionnaire to measure attitudes and beliefs: service orientation, social consciousness, entrepreneurial scale, and cultural awareness. Thind et al. 31 developed the service orientation scale from three of nine reasons for selecting dentistry as a career (service to others, service to my own race or ethnic group, and opportunity to serve vulnerable and low-income populations) and the socially conscious scale from questions related to access (access to care is a societal good and right; access to oral health care is a major problem in the United States; assuring and providing care to all segments of society is an ethical and professional obligation; and everyone is entitled to receive basic oral health care regardless of his or her ability to pay). The entrepreneurial scale was developed from two items (opportunity for self-employment and high income potential) by Baumeister et al. 34 The cultural awareness scale was constructed from questions related to preparedness to accept and respect patients of different races, ethnicities, and cultures; preparedness to integrate knowledge regarding cultural differences into treatment planning and care delivery; and the cultural and social environment of your school promotes acceptance and respect of students and patients of different races, ethnicities, and cultures. In summary, the model posits that student characteristics, community-based dental education, and contextual variables influence practice plans of dental school seniors. The dependent variable is ordinal and thus requires a multivariable model appropriate for ordered data. The ordered logit model is typically applied in this situation; however, this model relaxes the restrictive proportional odds assumption (also called the parallel regression assumption), 35 which requires that the effects of the covariates in the log-odds of observing a score on a dependent variable are invariant to the cut point (or four categories) of the dependent variable. To evaluate the proportional odds assumption for the multivariable model, we performed a Brant test, 36 which indicates the assumption did not hold for some covariates. Consequently, we used a generalized ordered logit model, 37,38 which relaxes the proportional odds assumption. The generalized ordered logit model allows the effects of explanatory variables to change in addition to allowing for different intercepts. Variables that do not fulfill the proportional odds assumption can have varying effects on the dependent variable. (For more information on the generalized ordered logit model, refer to Long and Freese, Agresti, and McCullagh and Nelder 35,39,40 ) We used the Wald χ 2 test for assessing equality of odds ratios obtained from the generalized ordered logit model. 412 Journal of Dental Education Volume 71, Number 3

11 Data analyses took into account lack of independence in student reports from dental schools. This was necessary as students from the same schools are likely to have correlated measures due to shared environments resulting in intracluster correlation. Analyses that assume independence of the observations will generally underestimate the true variance and lead to test statistics with inflated Type I errors. 41 Bivariate statistics were calculated with the SVY procedures in the Stata software package. These procedures were developed to analyze data from complex sampling structures including clustered samples, 42 The generalized ordered logit models were fitted using Rogers s generalization of the robust variance estimation procedure developed by Huber. 43,44 Zero-order correlations among the covariates and collinearity diagnostics (i.e., a variance inflation factor <3) were examined as a check for multicollinearity. Results Fifty-two of the fifty-four accredited dental schools had graduating seniors in 2003 and returned ADEA surveys, resulting in an overall student response rate of 83.2 percent in This response rate is based on the total number of seniors who completed the survey from the fifty-two schools returning surveys divided by the total number of seniors graduating from the fifty-four schools (refer to Weaver et al. 25 for detailed information). For the fifty-two schools included in the 2003 ADEA survey, we conducted a bias analysis to compare differences in race/ethnicity using the ADA statistics for dental senior students. As a cautionary note, we found some discrepancies in the total number of seniors reported by ADEA and the ADA, and some individuals failed to report race/ethnicity, so these findings are limited. Nevertheless, among the estimated 543 nonresponders, results showed slightly higher nonresponses among African Americans (ADA 6.3 percent versus ADEA 3.7 percent) and Hispanics (ADA 6.8 percent versus ADEA 5.3 percent) in the ADEA survey. Additionally, more ADEA respondents reported themselves as American Indian dental seniors than reported in the ADA, but the number and percentages of American Indian students nationally were extremely low (<1 percent in the 2003 ADEA survey). Table 1 describes candidate independent variables organized by construct specified in the measurement model (Figure 1) along with definitions and distributions. All candidate independent variables were tested in preliminary stepwise regression analysis (data not shown). Variables were tested in conceptually cohesive blocks as shown in Figure 1 to identify significant predictors for the final model and to resolve multicollinearity concerns. Independent variables were trimmed from the final model if they did not reach significance (p<.20) or substituted due to collinearity concerns. For example, percent URM in the dental school had a variance inflation factor >3. This collinearity disappeared after removing percent URM in state legislature. Contextual variables were then added from distal to more proximal to the dependent variable: contextual environment, communitybased dental education, and individual student-level variables. The regression model reported on Table 2 shows only variables remaining significant in the final multivariable analysis. Table 2 reports results using a generalized ordered logit model, which relaxes the proportional odds assumption. The far right column identifies the five variables reaching significance on the Brant test of proportional odds assumption: number of FQHCs in the county, preparedness for providing oral health care, URM, service orientation scale, and primary activity upon graduation (column 3). The effect of these variables is unequally distributed at each cut point of the dependent variable (0 percent; 1-10 percent; percent), and an odds ratio is reported for each cut point. Additionally, we interpreted the results below. The overall Wald test was significant for all five variables, indicating each was significant in the multivariable model (data not shown). For variables not significant on the Brant test, the effect of the predictors on the dependent variable at each cut point was equally distributed and reporting a single odds ratio was sufficient (as shown in Table 2, column 2). Three URM variables were tested in the model: percent URM in the county, percent URM in the dental school, and a variable representing individual URM students (reported under student characteristics below). Percent URM in the school was no longer significant when the student level URM variable was entered. However, the variable measuring percent URM in the county where the dental school was located remained a significant predictor. Seniors from dental schools in counties with greater percentages of underrepresented minorities were two times as likely to care for underserved patients upon graduation (OR=2.09, p<0.05). The next predictor, number of federally qualified health centers (FQHCs) in the county, March 2007 Journal of Dental Education 413

12 was significant on the Brant test, which means it did not fulfill the proportional odds assumption and therefore had varying effects on each cut point of the dependent variable (column 3). Here the effect was only significant for the lowest cut point of the dependent variable (0% OR=0.92, p<.001). Attending a dental school with lower numbers of FQHCs in the county was associated with a decreased likelihood of providing care to minority patients. A final Table 2. Variables predicting plans to care for underserved minority patients upon graduation Predictors Contextual Environment OR 95%-CI Percent underrepresented minorities 2.09* in the county Brant Test of Parallel Regression Assumption for Independent Variables+ Number of FQHCs in the county 0.92*** P= % % % Pipeline status (non-pipeline reference) 1.33** Cal Pipeline National Pipeline Percent URM in school Mission statement includes serving diverse 1.17 populations Community-Based Dental Education Time devoted to cultural competency 0.80** Preparedness for providing oral health care to racial, ethnic, and culturally diverse groups 1.36*** 0% % % Extramural clinical experiences influence 1.07* practice location plans Extramural clinical experience (positive or 1.12** negative) Student Characteristics Gender (female reference) 0.59** Age group (<29 years) 1.25* variable measured Pipeline school status. Compared to non-pipeline schools, California seniors reported greater likelihood (OR=1.33, p<.01) of providing care to minority patients upon graduation (all five of the California schools are funded for a dental Pipeline program). Turning to community-based dental education variables, the strongest predictors were time devoted to cultural competency and preparedness for providing oral health care to P=0.002 (continued) racial, ethnic, and culturally diverse populations. Seniors who felt time devoted to cultural competency was inadequate had an increased likelihood of caring for underserved patients (OR=0.80, p<0.01). Preparedness for providing care to diverse groups was significant on the Brant test. Only one category of the dependent variable was significant (0% OR=1.36, p<.001) although data show a clear trend in the analysis. Individuals who perceive themselves as less prepared were more likely to provide care to minority patients upon graduation. More indepth analysis revealed URM and Asian/PIs rated themselves as less prepared to care for racial, ethnic, and culturally diverse groups than white dental school seniors (chi square=19.0, p<.0001). However, parental income categories were not significantly different in regard to perceived preparedness (data not shown). Additionally, two predictors measuring the extramural clinical rotation experience showed a weak association with the practice plans dependent variable. Students who reported the extramural clinical experience influenced practice location plans and extramural experience was positive had a greater likelihood of serving minority patients upon graduation. A final set of multivariable predictors indicated several student characteristics were associ- 414 Journal of Dental Education Volume 71, Number 3

13 ated with providing care to minority patients: URM and Asian/PI race/ethnicity (compared to whites), female gender, older age, lower parents income, social consciousness, service orientation, and entrepreneurial attitudes (Table 2). Two variables were significant on the Brant test: URM race/ethnicity and service orientation scale. Overall, the strongest predictor in the multivariable model showed URM seniors had a significantly greater likelihood of serving minority patients upon graduation (1-10% OR=2.43, p<0.001; 11-24% OR=2.97, p<0.001) compared to their white counterparts. URM dental school seniors were up to three times as likely to care for underserved minority patients upon graduation. An intervening variable included in the model controlled for practice setting upon graduation: 1) private practice, 2) community clinic/government service, or 3) dental school/academic/postdoctoral residency. In terms of providing care to minority patients, individuals who were pursuing postdoctoral training or entering academic settings were not significantly different from those going into private practice. Not surprisingly, seniors planning to practice in community clinic or government settings had a significantly greater likelihood of serving minority patients. Discussion In this study, a comprehensive model was used to analyze contextual environment, community-based dental education, and student characteristics influencing practice plans of graduating seniors. Specifically, we examined variables significantly associated with plans to care for underserved minority patients. This baseline study analyzes 2003 ADEA data collected before the Pipeline, Profession, and Practice: Com- Table 2. Variables predicting plans to care for underserved minority patients upon graduation (continued) Predictors munity-based Dental Education program, sponsored by the Robert Wood Johnson Foundation and The California Endowment, was implemented in fifteen dental schools. A follow-up impact assessment will be conducted as part of the national evaluation study. We will analyze 2007 ADEA senior survey data and contextual variables to examine the impact of the Pipeline program on plans to care for underserved minority patients five years later. URM (white reference) 0.59 P< % % 2.43*** 11.24% *** Asian/PI 1.79*** Married (not married) Parents income (>$50K) <$30 K 1.34* $30-50 K Service Orientation Scale 0% 1.74*** 1-10% % 1.47*** *** Entrepreneurial Scale 0.72*** Socially Conscious Scale 1.26*** P=0.016 Primary activity (private practice) Community clinic/govt. service % % 1.81*** 11-24% *** P=0.001 Academic/Postdoc Wald χ 2 [P-value] *** Brant Test of Parallel Regression Assumption for Independent Variables+ 1 Generalized ordered logistic regression models were used. +P-value <0.05 did not fulfill the proportional odds assumption (based on the Brant test) and had three parameter estimates as indicated in the predictor column. *p<.05; **p<.01; ***p<.001 March 2007 Journal of Dental Education 415