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Improving Student Outcomes with an Adaptable Molecular Cloning Course-Based Undergraduate Research Experience
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Predictors of Success in a Graduate, Entry-Level Professional Program: From Admissions to Graduation.

Gregory F Spadoni1,2,3,4,5, Sarah Wojkowski1,2,3,4,5, Jenna Smith-Turchyn1,2,3,4,5

  • 1Gregory F. Spadoni is the associate professor in the School of Rehabilitation Science at the McMaster University and is the faculty fellow in the McMaster Program for Education Research, Innovation, and Theory (MERIT) in the Faculty of Health Sciences at the McMaster University. Institute for Applied Health Sciences, Room 433, 1400 Main Street West, Hamilton, ON L8S 1C7, Canada ( spadongf@mcmaster.ca ). Please address all correspondence to Gregory F. Spadoni.

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PubMed
Summary
This summary is machine-generated.

Higher multiple mini-interview (MMI) scores predict fewer academic concerns in physiotherapy programs. Early admission offers are linked to increased risk, highlighting the need to refine admissions processes for student success.

Keywords:
Academic performanceAcademic trainingHealth educationSchool admission criteria

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Area of Science:

  • Health Professions Education
  • Physiotherapy Admissions
  • Academic Success Prediction

Background:

  • Admission to Canadian health professional programs (HPPs) is highly competitive.
  • Predicting academic success using admissions data is crucial for HPPs.
  • Limited research exists on admissions criteria predicting physiotherapy student performance in Canada.

Purpose of the Study:

  • To evaluate if admissions package factors predict academic concerns in a Canadian physiotherapy program.
  • To identify specific admissions metrics associated with student academic performance.

Main Methods:

  • Retrospective, nonconcurrent cohort study of 256 physiotherapy students (2016-2019 admissions).
  • Analysis of admissions metrics (e.g., GPA, interview scores) and program data.
  • Calculation of odds ratios (ORs) to assess the relationship between admissions data and academic concerns (P < .05).

Main Results:

  • Higher multiple mini-interview (MMI) scores were associated with a lower incidence of academic concerns (OR = 0.52).
  • Grade point average (GPA) did not significantly predict academic concerns when combined with MMI or virtual MMI (VMMI).
  • Admissions round offer was a significant predictor, with later offers increasing the risk of concerns (OR = 2.48).

Conclusions:

  • Physiotherapy programs can refine admissions processes by considering interview performance and offer rounds.
  • The study highlights the utility of admissions data in identifying candidates at higher risk for academic concerns.
  • Ensuring optimal candidate selection enhances the likelihood of student success in demanding HPPs.