How leaky is the health career pipeline? Minority student achievement in college gateway courses.
OBJECTIVE
To determine whether underrepresented minority (URM) students receive lower grades than do non-URM students in college prehealth gateway courses; the extent to which lower grade performance might be explained by the differences in precollege academic achievement; and whether URM students are less likely than non-URM students to persist in completing at least four gateway courses.


METHODS
Administrative data were obtained from six California colleges on 15,000 college students who matriculated in the 1999-2000 or 2000-2001 academic years and enrolled in at least one college course required for application to medical or dental school ("gateway" courses). Students were compared across ethnic groups in gateway course grade performance and persistence in completing at least four gateway courses, using regression methods to control for students' college admission test scores and caliber of high school attended.


RESULTS
URM students received significantly lower grades on average in gateway courses than did white students. This gap persisted after adjusting for measures of prior academic performance. However, URM students were nearly as likely as white students to persist in completing at least four gateway courses. After accounting for the lower grades of URM students in their initial classes, URM students were more likely than white students to complete four or more gateway courses.


CONCLUSIONS
URM students experienced academic challenges, but many persist in their prehealth courses despite these challenges. Interventions at the college level to support URM student performance in gateway courses are particularly important for increasing the diversity of medical and dental schools.
Alexander
Charles
C
School of Dentistry, University of California, Los Angeles, Los Angeles, California, USA. calexander@college.ucla.edu
Chen
Eric
E
Grumbach
Kevin
K
D002140:California; D002321:Career Choice; D018864:Cultural Diversity; D016208:Databases, Factual; D004504:Education, Medical, Undergraduate / Q000706:statistics & numerical data / Q000639:trends; D004516:Education, Premedical / Q000706:statistics & numerical data / Q000639:trends*; D004521:Educational Measurement; D005260:Female; D006281:Health Occupations / Q000193:education; D006801:Humans; D008297:Male; D008913:Minority Groups / Q000193:education* / Q000706:statistics & numerical data; D020380:Needs Assessment; D011237:Predictive Value of Tests; D012570:School Admission Criteria / Q000706:statistics & numerical data / Q000639:trends*; D012575:Schools, Dental; D012577:Schools, Medical; D013332:Student Dropouts / Q000706:statistics & numerical data*; D014495:Universities; D055815:Young Adult