A review of bridging courses in Doctor of Pharmacy programs
Abstract
Objectives Bridging courses in Doctor of Pharmacy program can serve various purposes including but not limited to closing the knowledge gaps, reinforcing and refreshing foundational scientific material, mimicking the activities students will do in classroom, protecting in-class time, fostering self-directed learning, and ensuring all students have similar baseline knowledge that can forecast academic performance. This review attempts to summarize the content, delivery and assessment methods used in bridging programs offered in Doctor of Pharmacy programs described thus far in the literature. Findings A detailed literature search of various educational resources was conducted using bridging programs in Doctor of Pharmacy program and related terms. Mathematics was found to be a common content in a typical bridging program. Assessment of prior knowledge of math in students using tests such as quantitative component of Pharmacy College Admission Test (PCAT), math pretest, Basic Math Skills Test (BMST), Fogerty Math Confidence Scale, Test of logical thinking (TOLT), Assessment and Learning in Knowledge Spaces (ALEKS) etc. are discussed. Summary This review intends to summarize the wide variety of options that are available as far as the content, delivery and assessment of bridging programs offered in a Doctor of Pharmacy program. The choice of bridging modality should align with the nature and content emphasis of a particular university/college curriculum.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Reported outcomes of pre-matriculation programs have been mixed due to variations in program structure, timing, duration, delivery methods, curriculum depth, and topics.
“While these programs aim to increase confidence, retention, and academic performance, reported outcomes have been mixed due to variations in program structure, timing, duration, delivery methods, curriculum depth, and topics [15].”
From A Descriptive Website Review of Publicized PharmD Pre-Matriculation Programs (2026) · cites this paper as [15]
Cites
Klausner, E. A., Rowe, E. L., Hamilton, B. S., & Mark, K. S. (2019) · American Journal of Pharmaceutical Education · doi:10.5688/ajpe7021 · Cited by 20 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
A Descriptive Website Review of Publicized PharmD Pre-Matriculation Programs
Bessard, C. C., Oliver, K. B., Yu, F., & Fujiwara, R. (2026) · Pharmacy · doi:10.3390/pharmacy14060131
- Authors
- Joshi, M. D., & Uchizono, J. A.
- Affiliations
- Midwestern University (US)
- University of the Pacific (US)
- Corresponding author
- Joshi, Medha D.
- Venue
- Currents in Pharmacy Teaching and Learning
- Publisher
- Elsevier BV
- Published
- 2025-10
- Volume
- 17
- Issue
- 10
- Pages
- 102417
- ISSN
- 1877-1297 (ISSN-L)
- OpenAlex
- W4411437350
- Cited by
- 2
- References
- 1
- Citations by year
- 2026: 2
- FWCI
- 0.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Currents in Pharmacy Teaching and Learning (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › Mathematics Education and Programs
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacy and Medical Practices
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Medical Education and Admissions
- Keywords
- bridging courses, Doctor of Pharmacy programs, pharmacy education, prior knowledge assessment, mathematical ability, Test of Logical Thinking, ALEKS, self-directed learning, knowledge gaps
- MeSH terms
- Curriculum, Education, Pharmacy, Education, Pharmacy, Graduate, Educational Measurement, Humans
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review