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Does emotional intelligence influence success during medical school admissions and program matriculation?: a systematic review  
Christian Jaeger Cook, Chad E. Cook, Tiffany N. Hilton
J Educ Eval Health Prof. 2016;13:40.   Published online November 8, 2016
DOI: https://doi.org/10.3352/jeehp.2016.13.40
  • 32,647 View
  • 384 Download
  • 14 Web of Science
  • 17 Crossref
AbstractAbstract PDF
Purpose
It aimed at determining whether emotional intelligence is a predictor for success in a medical school program and whether the emotional intelligence construct correlated with other markers for admission into medical school. Methods: Three databases (PubMed, CINAHL, and ERIC) were searched up to and including July 2016, using relevant terms. Studies written in English were selected if they included emotional intelligence as a predictor for success in medical school, markers of success such as examination scores and grade point average and association with success defined through traditional medical school admission criteria and failures, and details about the sample. Data extraction included the study authors and year, population description, emotional intelligence I tool, outcome variables, and results. Associations between emotional intelligence scores and reported data were extracted and recorded. Results: Six manuscripts were included. Overall, study quality was high. Four of the manuscripts examined emotional intelligence as a predictor for success while in medical school. Three of these four studies supported a weak positive relationship between emotional intelligence scores and success during matriculation. Two of manuscripts examined the relationship of emotional intelligence to medical school admissions. There were no significant relevant correlations between emotional intelligence and medical school admission selection. Conclusion: Emotional intelligence was correlated with some, but not all, measures of success during medical school matriculation and none of the measures associated with medical school admissions. Variability in success measures across studies likely explains the variable findings.

Citations

Citations to this article as recorded by  
  • Emotional intelligence weakly predicts academic success in medical programs: a multilevel meta-analysis and systematic review
    Ahmed M. Abdulla Alabbasi, Fatema A. Alabbasi, Aseel AlSaleh, Ahmed M. Alansari, Reginald P. Sequeira
    BMC Medical Education.2023;[Epub]     CrossRef
  • Emotional intelligence in undergraduate medical students: a scoping review
    Helga V. Toriello, J. M. Monica Van de Ridder, Patricia Brewer, Brian Mavis, Renoulte Allen, Cindy Arvidson, Iris Kovar-Gough, Elizabeth Novak, John O’Donnell, Janet Osuch, Brian Ulrich
    Advances in Health Sciences Education.2022; 27(1): 167.     CrossRef
  • Emotional Intelligence and Good Medical Practice: Is There a Relationship?
    Cameron Dott, George Mamarelis, Edward Karam, Kavyansh Bhan, Kash Akhtar
    Cureus.2022;[Epub]     CrossRef
  • Concept Analysis of Emotional Intelligence in Nursing
    Sun Yeob Choi
    Journal of Korean Academy of Fundamentals of Nursing.2021; 28(2): 263.     CrossRef
  • Medical Student Selection
    Ian Kratzke, Muneera R. Kapadia, Fumiko Egawa, Jennifer S. Beaty
    Surgical Clinics of North America.2021; 101(4): 635.     CrossRef
  • Traits and Attributes of a Successful Physical Therapy Resident: A Delphi Study
    Rebecca Shepard, Lauren Haines, Karen Abraham, A. J. Lievre
    Journal of Physical Therapy Education.2021; 35(4): 315.     CrossRef
  • Cross-Sectional Assessment of the Emotional Intelligence of Fourth-Year Veterinary Students and Veterinary House Officers in a Teaching Hospital
    Darcy B. Adin, Kenneth D. Royal, Christopher A. Adin
    Journal of Veterinary Medical Education.2020; 47(2): 193.     CrossRef
  • Predictors of success on the MCAT among post-baccalaureate pre-medicine students
    Rohini Ganjoo, Lisa Schwartz, Mackenzie Boss, Matthew McHarg, Yuliya Dobrydneva
    Heliyon.2020; 6(4): e03778.     CrossRef
  • More Than Their Test Scores: Redefining Success with Multiple Mini-Interviews
    Ann Blair Kennedy, Cindy Nessim Youssef Riyad, Laura H. Gunn, April Gant Brown, Kandyce Brooke Dunlap, Melissa Elizabeth Knutsen, Alicia Anne Dahl
    Medical Science Educator.2020; 30(3): 1049.     CrossRef
  • COVID-19: A Driver for Disruptive Innovation of the Emergency Medicine Residency Application Process
    Alexis Pelletier-Bui, Doug Franzen, Liza Smith, Laura Hopson, Lucienne Lutfy-Clayton, Kendra Parekh, Mark Olaf, Tom Morrissey, David Gordon, Erin McDonough, Benjamin Schnapp, Mary Ann Edens, Michael Kiemeney
    Western Journal of Emergency Medicine.2020;[Epub]     CrossRef
  • Reimagining Residency Selection: Part 3—A Practical Guide to Ranking Applicants in the Post-COVID-19 Era
    Jaime Jordan, Kevan Sternberg, Mary R.C. Haas, Shuhan He, Lalena M. Yarris, Teresa M. Chan, Nicole M. Deiorio
    Journal of Graduate Medical Education.2020; 12(6): 666.     CrossRef
  • Assessments of Non-academic Attributes in Applicants for Undergraduate Medical Education: an Overview of Advantages and Limitations
    Jochanan Benbassat
    Medical Science Educator.2019; 29(4): 1129.     CrossRef
  • The right kind of smart: emotional intelligence’s relationship to cognitive status in community-dwelling older adults
    Odelyah Saad, Leehu Zysberg, Jeremia Heinik, Ron Ben-Itzhak, Anna Zisberg
    International Psychogeriatrics.2019; 31(9): 1241.     CrossRef
  • The relationship between emotional intelligence, previous caring experience and successful completion of a pre‐registration nursing/midwifery degree
    Austyn Snowden, Rosie Stenhouse, Lorraine Duers, Sarah Marshall, Fiona Carver, Norrie Brown, Jenny Young
    Journal of Advanced Nursing.2018; 74(2): 433.     CrossRef
  • A novel tool for evaluating non-cognitive traits of doctor of physical therapy learners in the United States
    Marcus Roll, Lara Canham, Paul Salamh, Kyle Covington, Corey Simon, Chad Cook
    Journal of Educational Evaluation for Health Professions.2018; 15: 19.     CrossRef
  • 20th Pauline Cerasoli Lecture: The Sunk Cost Fallacy
    Chad Cook
    Journal of Physical Therapy Education.2017; 31(3): 10.     CrossRef
  • What is interesting in the issue 2016 of Journal of Educational Evaluation for Health Professions?
    Yera Hur
    Journal of Educational Evaluation for Health Professions.2016; 13: 46.     CrossRef
Selectivity of physiotherapist programs in the United States does not differ by institutional funding source or research activity level  
Sean P. Riley, Kyle Covington, Michel D. Landry, Christine McCallum, Chalee Engelhard, Chad E. Cook
J Educ Eval Health Prof. 2016;13:17.   Published online April 15, 2016
DOI: https://doi.org/10.3352/jeehp.2016.13.17
  • 26,768 View
  • 150 Download
  • 3 Web of Science
  • 4 Crossref
AbstractAbstract PDF
Purpose
This study aimed to compare selectivity characteristics among institution characteristics to determine differences by institutional funding source (public vs. private) or research activity level (research vs. non-research). Methods: This study included information provided by the Commission on Accreditation in Physical Therapy Education (CAPTE) and the Federation of State Boards of Physical Therapy. Data were extracted from all students who graduated in 2011 from accredited physical therapy programs in the United States. The public and private designations of the institutions were extracted directly from the classifications from the ‘CAPTE annual accreditation report,’ and high and low research activity was determined based on Carnegie classifications. The institutions were classified into four groups: public/research intensive, public/non-research intensive, private/research intensive, and private/non-research intensive. Descriptive and comparison analyses with post hoc testing were performed to determine whether there were statistically significant differences among the four groups. Results: Although there were statistically significant baseline grade point average differences among the four categorized groups, there were no significant differences in licensure pass rates or for any of the selectivity variables of interest. Conclusion: Selectivity characteristics did not differ by institutional funding source (public vs. private) or research activity level (research vs. non-research). This suggests that the concerns about reduced selectivity among physiotherapy programs, specifically the types that are experiencing the largest proliferation, appear less warranted.

Citations

Citations to this article as recorded by  
  • Predictors of research productivity among physical therapy programs in the United States: an observational study
    David M. Rowland, Amanda A. Murphy, Hannah R. Manik, Chris Y. Lane, Deborah L. Givens, Chad E. Cook, Alessandra Narciso Garcia
    BMC Medical Education.2020;[Epub]     CrossRef
  • Impact of funding allocation on physical therapist research productivity and DPT student graduates: an analysis using panel data
    Tara Dickson, P. Daniel Chen, Barrett Taylor
    Advances in Health Sciences Education.2019; 24(2): 269.     CrossRef
  • Predicting performance in health professions education programs from admissions information – Comparisons of other health professions with pharmacy
    Richard E. Wilcox, Kenneth A. Lawson
    Currents in Pharmacy Teaching and Learning.2018; 10(4): 529.     CrossRef
  • 20th Pauline Cerasoli Lecture: The Sunk Cost Fallacy
    Chad Cook
    Journal of Physical Therapy Education.2017; 31(3): 10.     CrossRef

JEEHP : Journal of Educational Evaluation for Health Professions