Dental school application timing: implications for full admission consideration and improving diversity of dental students

J Dent Educ. 2014 Apr;78(4):575-9.


The national underrepresentation of minorities in dental schools and the dental profession is a significant concern. Despite efforts over previous years, the number of practicing dentists from underrepresented minority (URM) groups has increased very little. Many dental schools have adopted a holistic admissions review process that uses noncognitive factors in an effort to increase diversity. However, application timing also significantly impacts the success of candidates. This study examined whether URM students' applying late in the application cycle contributes to their lower enrollment. This study attempted to fill a void in the dental admissions knowledge base by examining whether the timing of dental school applications in a rolling admissions system with a set number of interview spots favors those who apply early. De-identified applications (N=1,673) from one U.S. dental school in 2011 were examined. A binary logistic regression analysis revealed that URM applicants were significantly more likely to apply later in the admission cycle than non-URM applicants by a factor of 63 percent (p=0.001), increasing the competiveness for fewer remaining spots. These results suggest the need for pre-admission interventions and for future research to understand and address barriers that impact application timing.

Keywords: dental education; dental school admissions; holistic admissions; rolling admissions; underrepresented minorities.

Publication types

  • Comparative Study

MeSH terms

  • Cultural Diversity*
  • Educational Status
  • Ethnicity / statistics & numerical data
  • Humans
  • Interviews as Topic
  • Kentucky
  • Minority Groups / statistics & numerical data
  • Parents / education
  • Personnel Selection
  • Residence Characteristics
  • School Admission Criteria*
  • Schools, Dental*
  • Students, Dental* / statistics & numerical data
  • Time Factors
  • White People / statistics & numerical data