FACTORS RELATED TO MEDICAL SCHOOL APPLICATION AND ACCEPTANCE IN MINORITY SUMMER ENRICHMENT PROGRAM STUDENTS

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1 FACTORS RELATED TO MEDICAL SCHOOL APPLICATION AND ACCEPTANCE IN MINORITY SUMMER ENRICHMENT PROGRAM STUDENTS Valory N. Pavilk, MEd, Billy B. Rankin, Carlos Vallbona, MD, Robert J. Michael P. Tristan, MD, MPH Houston, Texas Bacon, MD, and Baylor College of Medicine has conducted a summer enrichment program for minority/ disadvantaged premedical students since Follow-up data on medical school application and acceptance for participants from 1980 through 1984 were analyzed in relation to selected preprogram variables-cumulative college grade point average, total Scholastic Aptitude Test score, competitiveness of undergraduate college, sex, and ethnicity. Results of univariate and multivariate analyses indicated that: 1) females were significantly less likely to apply to medical school than males, 2) females had significantly lower mean MCAT scores (5.9 vs 7.2) even though their preprogram academic performance was comparable to that of the males, and 3) after controlling for MCAT scores, none of the preprogram variables were significant in predicting medical school acceptance. These findings suggest the need for research to explain the discrepancy between From the Baylor College of Medicine and the University of Texas Health Science Center, Houston and the University of Texas Medical Branch, Galveston, Texas. Supported in part by Health Careers Opportunity Grant #D18 MB00084, US Department of Health and Human Services. Requests for reprints should be addressed to Mrs Valory N. Pavlik, Department of Community Medicine, Baylor College of Medicine, Texas Medical Center, Houston, TX male and female MCAT performance and frequency of medical school application in summer program participants. The findings also have implications for the type of counseling provided to female participants in summer enrichment programs. (J Nati Med Assoc ;83: ) Key words * enrichment program * sex * ethnicity * grade point average Beginning in the late 1960s, numerous medical schools established summer enrichment programs designed to enhance the preparedness of underrepresented minorities for medical school.1-9 While the programs differed in details of length and content, they generally contained an academic component, some clinical or laboratory experience, and personal counseling. Detailed evaluation of the outcome of these programs can provide valuable information to help current program directors refine their methods and identify recruitment techniques and curriculum content that may be more effective in encouraging greater minority representation in medicine. This article presents an analysis of the relationship between selected academic and demographic variables and career outcome of participants in the Baylor Summer Program for Premedical Minority/ Disadvantaged Students during the 1980 through 1984 program years. 628 JOURNAL OF THE NATIONAL MEDICAL ASSOCIATION, VOL. 83, NO. 7

2 PROGRAM DESCRIPTION Since its establishment in 1969 until 1985, the Baylor Summer Program was structured as an 8-week academic enrichment experience. The program also provided exposure to the clinical and research environments of an academic medical center, as well as personal and group counseling regarding the medical school application process, adjustment to the medical school environment, and sources of financial aid. Details of the participant selection criteria and process and long-term program outcome have been reported previously.8 In briet through 1984, the program gave preference to rising sophomores and juniors whose academic record indicated the need to improve their grades and standardized test-taking ability in order to ensure their competitiveness as medical school applicants. Thus, applicants with a college grade point average (GPA) of more than 3.5 and combined Scholastic Aptitude Test (SAT) scores of more than 1100 were not admitted because they were not considered to need the intensive premedical sciences curriculum offered by the program. The goals of the program were to increase the size of the minority applicant pool and to increase the competitiveness of program participants for medical school admission. Thus, the program has been evaluated in terms of the numbers of participants applying to and being accepted to medical school. Of the 378 students who participated in the program through 1984, 68% eventually applied to medical school, and 73% of those who applied were accepted to a US medical school. In 1985, in keeping with Health Career Opportunity Grant program guidelines for priority funding, Baylor removed the academic enrichment component from the summer program activities. Baylor now offers a medical school familiarization experience heavily devoted to clinical exposure, interviewing skills development, and personal counseling regarding the medical school application process. METHODS The present study was conducted to identify preprogram variables that are important in determining career outcome of program participants. Career outcome, in this context, was considered to be the step of applying to medical school and success in gaining acceptance to medical school. The study is limited to 116 participants in the 1980 through 1984 program years for whom complete follow-up data were available at the time of analysis. Participants from previous years were not included because of the possibility that social and economic trends or other unknown variables might alter the relationship between the predictor and outcome variables. The period from 1980 through 1984 was considered to be relatively uniform in terms of sociocultural, economic, and other factors. Students from more recent program years have not been included because insufficient time has elapsed between program participation and the medical school application and acceptance process. Sources of data for the analysis were those used for routine tracking of program participants. The following academic and demographic baseline variables were extracted from the participants' program application forms: * sex, * ethnicity, * number of college hours completed at the time of program application, * total SAT scores (ie, verbal plus quantitative), and * college attended. College attended was then rated for academic competitiveness using Barron's Profiles of Undergraduate Schools.'0 The Barron's rating is on a scale of 1 to 6, with 1 being least competitive and 6 being most competitive. Follow-up or outcome variables considered were: * MCAT score on the first sitting of the exam, * application to medical school, and * acceptance to medical school. Data sources for these variables were periodic mail surveys of program participants, and the Association of American Medical Colleges' (AAMC) routine listings of MCAT scores and individuals accepted to US medical schools each year. The mail survey was used primarily to obtain information on application to medical school. Premed advisors of nonrespondents to the mail surveys were contacted to supply missing data on application to medical school. In the 10% of cases for which data on medical school application could not be ascertained from the participant or the premed advisor, a participant was considered not to have applied to medical school if no MCAT score could be found in the AAMC listings from the time of program participation until the analysis was conducted. In this way, information on medical school application was obtained for all 116 participants in the sample. After data coding and entry, descriptive statistics were calculated for the study variables. A univariate analysis of the association between baseline variables JOURNAL OF THE NATIONAL MEDICAL ASSOCIATION, VOL. 83, NO

3 TABLE 1. RELATIONSHIP BETWEEN DEMOGRAPHIC VARIABLE AND APPLICATION TO MEDICAL SCHOOL Applicants to Medical School by Sex* Males Females Total (n=59) (n=57) (n=116) 45 (76%) 28 (49%) 73 (63%) Applicants to Medical School by Ethnicityt Mexican American Black American Indian Total (n=66) (n=48) (n=2) (n= 116) 44 (67%) 29 (60%) 0 (0%) 73 (63%) *x2 = 8.03, P<.01. tx2 = 3.92, not significant. and outcome variables was then carried out using the chi-square test in the case of dichotomous variables and analysis of variance for differences between groups on continuous variables. Discriminant analysis was used to explore the multivariate relationship between baseline variables identified as significant in univariate analysis and the dichotomous outcome variables, application to medical school, and acceptance to medical school. All analyses were carried out with the Statistical Package for the Social Sciences (SPSS) program for personal computers. RESULTS Of the 116 program participants studied, 51% were male and 49% were female. The ethnic breakdown was 57% black, 41% Mexican American, and 2% Native American. The average overall GPA as reported on the program application form was 3.20 ±.41, and the average combined SAT score was 975 ± 132. Participants had completed an average of 38±21 college hours at the time of program application. As shown in Tables 1 and 2, sex and overall college GPA were significantly different for students who applied to medical school compared to those who did not. Ethnicity, college competitiveness rating, and combined SAT scores were not significantly different for the two groups. The academic and demographic variables were then subjected to a discriminant analysis procedure to explore whether linear combinations of preprogram variables are useful in predicting program outcome.i1 The combination of variables that resulted in the best prediction equation was sex, preprogram college GPA, and SAT scores. The summary statistics reinforce the significance of participants' gender in predicting which ones were more likely to apply to medical school (Table 3). Likewise, the contribution of GPA found on the univariate analysis was confirmed as an independent predictor of medical school application. The reduction in Wilks' lambda, which represents the ratio or within groups variability to total variability, resulting from inclusion of the SAT score was relatively small and not statistically significant on a univariate basis (P=.16). During the exploratory discriminant analysis, it was found that college competitiveness rating was closely correlated with SAT score. Therefore, the college competitiveness rating did not aid in the prediction of medical school application and actually suppressed the contribution of the SAT score when both were included in the analysis. The classification results-a test of how successful a particular derived discriminant function is in classifying cases-for the three variables in Table 3 was almost 77%. A breakdown of the female applicants by ethnicity indicated that Mexican-American females were somewhat less likely to apply than black females (X2 = 2.53, P=.11, with Yates' continuity correction), whereas application rates for black and Mexican-American males were comparable. Of the 73 participants who applied to medical school, 54 (74%) were accepted. Sex and ethnicity were not significantly different between the accepted versus the not accepted groups when analyzed in a univariate fashion. However, in a discriminant equation containing the baseline variables-sex, ethnicity, SAT, GPA, and college rating-the first three variables were found to be significantly associated with medical school acceptance.12 However, when the mean MCAT score (ie, the sum of the individual subscores divided by six) was included in the prediction equations, this variable became the only variable predictive of medical school acceptance (Table 4). In view of these findings, the four available academic variables, GPA, SAT, MCAT, and college competitiveness were compared for males and females, and for Mexican Americans versus blacks. There was no significant difference between the two ethnic groups on any of these variables. However, as shown in Table 5, the MCAT scores of females were significantly lower than those of males. The difference is quite large and surprising in view of the similarity between the groups on the other three academic variables. In the sample of participants in the 1980 through 1984 program years, there was an uneven sex by ethnicity breakdown. Therefore, the discrepancy in MCAT performance of females accounts for the ability of sex and 630 JOURNAL OF THE NATIONAL MEDICAL ASSOCIATION, VOL. 83, NO. 7

4 TABLE 2. PREPROGRAM ACADEMIC VARIABLES AND APPLICATION TO MEDICAL SCHOOL Applied to Medical School Did Not Apply to Medical School (n=73) (n=43) Preprogram GPA 3.31± ±.48* Combined SAT score 1002± ±1 49t College competitiveness rating 2.81 ± ±1.42t *P<.01, two-tailed t test. tnot significant. TABLE 3. SUMMARY OF DISCRIMINANT ANALYSIS OF VARIABLES PREDICTIVE OF MEDICAL SCHOOL APPLICATION* Standardized Discriminant Step Variable Entered Wilks' Lambda Significance Function Coefficient 1 Sex GPA SAT Variables not contributing to further reduction in Wilks' lambda: ethnicity. Percent of cases correctly classified with resulting discriminant function: 76.6%. *Candidate variables for stepwise selection: sex, ethnicity, preprogram GPA, combined SAT score. TABLE 4. SUMMARY OF DISCRIMINANT ANALYSIS OF FACTORS PREDICTIVE OF MEDICAL SCHOOL ACCEPTANCE* Step Variable Entered Wilks' Lambda Significance Standardized Discriminant Function Coefficient 1 Mean MCAT Variables not contributing to further reduction in Wilks' Lambda: sex, combined SAT score, college competitiveness rating. Percent of cases correctly classified through resulting discriminant function: 78.3%. *Candidate variables for stepwise selection: sex, combined SAT score, mean MCAT, college competitiveness rating. ethnicity to predict medical school acceptance in this sample when information on MCAT scores is not included in a prediction equation. DISCUSSION The most striking finding of this study was the difference in rates of application to medical school for women who had participated in the program compared to men. While women have not yet reached equal representation among medical school enrollees, one would expect that the female participants in the Baylor Summer Program were equally motivated to go on to medical school and equally likely to apply as the men. The fact that the women obtained lower mean MCAT scores does not entirely account for the difference in application rates because the group of nonapplicants included many who did not take the MCAT. Thus, social and cultural pressures must be considered as possible deterrents to a career in medicine. Although the difference was not statistically significant in our sample, there was evidence that Mexican-American females were less likely to apply than black females, a finding that has also been reported by Baratz et al.'3 The difference in MCAT performance of males and females was also a disturbing finding, particularly in view of the equivalence of males and females on preprogram academic variables. This difference in MCAT performance between males and females has also been reported by Dawson-Sanders et al and by Baratz et al.12'13 The reasons behind the emergence of this gender difference in test performance must be studied further in view of the importance of the MCAT for medical school acceptance. The results of the discriminant analysis to predict medical school acceptance confirm the overwhelming importance of the MCAT score for participants' JOURNAL OF THE NATIONAL MEDICAL ASSOCIATION, VOL. 83, NO

5 TABLE 5. COMPARISON OF ACADEMIC VARIABLES IN MALE AND FEMALE PARTICIPANTS Males Females (n=59) (n=57) Preprogram GPA 3.23 ± ±.41* Combined SAT 992 ± ± 138* score Mean MCAT 7.20 ± ± 2.04t *Not significant. tp=.006, two-tailed t test. chances of being accepted to medical school. The wisdom of relying so heavily on this particular measure of ability has been widely debated, but for the moment, it appears that efforts to increase minority representation in medicine may be most efficient if focused on improving students' ability to achieve competitive scores on this measure.14 SUMMARY Current medical school admissions policies make it possible to predict which participants in summer enrichment programs are likely to apply to and be accepted to medical school on the basis of the three preprogram variables: sex, preprogram college GPA, and SAT scores. These variables are in turn related to MCAT test performance, which is the strongest predictor of medical school acceptance. However, the prediction equations developed for the sample in this study indicate that there is considerable unexplained variance in outcome not attributable to the variables considered, and there is a need to identify measurable, nonacademic variables that add to the accuracy of prediction models. Nonacademic predictors of medical school application among summer enrichment program participants may include certain personality traits (eg, need for achievement) or attitudes toward professional careers. Summer program directors must give careful thought to appropriate counseling of female participants in an effort to prevent attrition from this qualified, motivated pool of potential medical school applicants. Literature Cited 1. Johnson CW. Meharry's special medical and research programs. J Natl Med Assoc. 1973;65: Ortiz G, Kendler KS. The New York Medical College Summer Program: remedial education for medical school admission. J Med Educ. 1974;49: Epps AC. The Howard-Tulane challenge: a medical education reinforcement and enrichment program. J Natl Med Assoc. 1975;67: Levine HG, Williams LB, Bruhn JG. Six years of experience with a summer program for minority students. J Med Educ. 1976;51: Weymouth RJ, Wergin JF Pilot programs for minority students: one school's experience. J Med Educ. 1976;51: Beck P, Githens JH, Clinckscales D, et al. Recruitment and retention program for minority and disadvantaged students. J Med Educ. 1978;53: Clemendor AA, Moore ON. A premedical summer program for disadvantaged students. J Med Educ. 1979;53: Tristan MP, Pavlik VN, Rankin BB, et al. Review of a program for disadvantaged students. Texas Med. 1981;77: Pisano JC, Epps AC. The impact of a medical-schoolbased summer program on the acceptance of minority undergraduate students into health professions schools. J Natl Med Assoc. 1983;75: Barron's Educational Series Inc, College Division. Profiles of American Colleges. Vol. 1. Woodbury, NY: Barron's Educational Series; Norusis MJ. Spss/Pc + Advanced Statistics. Chicago, III: SPSS Inc; 1986:B1-B Dawson-Sanders B, Paiva RE, Doolen DR. Using ACT scores and grade-point averages to predict students' MCAT scores. J Med Educ. 1986;61: Baratz JC, Fikien MS, King B, Rosenbaum P. Who Is Going to Medical School? Princeton, NJ: Educational Testing Service, Robert Wood Johnson Foundation. Special Report- The Foundation's Minority Medical Training Programs. Robert Wood Johnson Foundation; Special Report Number One. 632 JOURNAL OF THE NATIONAL MEDICAL ASSOCIATION, VOL. 83, NO. 7