Evidence map›Paper›PMID 31941519›Full record

ArticleBMC medical education2020

Predicting professional school performance with a unique lens: are there other cognitive predictors?

Theresa A Davies, Madeline B Miller, Vincent A Moore, Elizabeth A Kaye

Open access · goldAbstract read
In one paragraph

Article in BMC medical education, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.8field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Theresa A DaviesDepartment of Medical Sciences & Education, Boston University School of Medicine, Boston, MA, USA. tdavies@bu.edu.ORCID http://orcid.org/0000-0001-6619-2648
Madeline B MillerGraduate Medical Sciences, Boston University School of Medicine, 72 East Concord Street, L317, Boston, MA, 02118, USA.
Vincent A MooreDepartment of Medical Sciences & Education, Boston University School of Medicine, Boston, MA, USA.
Elizabeth A KayeDepartment of Health Policy and Health Services Research, Henry M. Goldman Boston University School of Dental Medicine, Boston, MA, USA.
Boston University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe investigated the associations between admissions criteria and performance in four cohorts of pre-dental MS in Oral Health Sciences (OHS) program at Boston University Schools of Medicine and Dental Medicine. Previously we have reported that OHS serves as a successful pre-dental pipeline program for students from underrepresented groups.

methodsWe evaluated academic variables that further affect overall graduate GPA and grades in the first year dental school courses taken by OHS students at Boston University between 2012 and 2016 as part of the MS curriculum. Demographic data, region of residency, undergraduate grade point average, number of science and math credits, major of study, dental admissions test scores and undergraduate institution were collected. The competitiveness of the undergraduate institution was scored based on Barron's Profiles of American Colleges. OHS-GPA was assessed and individual grades in two first year dental school courses taken as part of the OHS curriculum were collected. Analysis of variance, the Chi-square test and Fisher's Exact test were utilized to assess associations between academic performance parameters, successful program completion and matriculation to dental school.

resultsResults indicate that undergraduate major, age and number of science course credits taken had no impact on MS performance in the Boston University MS in Oral Health Sciences program; however, students who took an undergraduate course in Physiology performed better than those who did not (p = 0.034). This was not the case with courses in Cell Biology and Biochemistry. Students with DAT scores over 20 academic average (p = 0.001), 18 total science average (p = 0.001) and 22 reading comprehension (p = 0.004) performed better in dental school courses taken in OHS.

conclusionWe report that strong test scores, attending a mid or highly rigorous undergraduate institution and completion of an undergraduate Physiology course are positive predictors. We hope these findings will guide admission's decisions and improve recruitment to, and future success of, graduate student's pursuit of professional school. Understanding alternative predictors of success may help to reduce the intrinsic bias among applicants from underrepresented groups and continue to look beyond the DATs (or MCATs) to decrease the gap between professionals from underrepresented groups and those they serve.

Indexed as

Academic PerformanceSchool Admission CriteriaAge FactorsAnalysis of VarianceAsianBiasBiochemistryBlack or African AmericanBostonCell BiologyChi-Square DistributionCohort StudiesComprehensionCurriculumEducation, DentalEducation, Dental, GraduateAcademic performanceAdmissions criteriaDATDentalMedicalPipelineUnderrepresented groups

Identifiers

PMID31941519
PMCPMC6961370
OpenAlexW3013833316

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.