ABSTRACT
Employers of 2007-2009 graduates from Iowa State University College of Veterinary Medicine were asked to respond to a survey regarding their overall satisfaction with their new employees as well as their new employees' preparation in several technical and non-technical skill areas. Seventy-five responses contained complete data and were used in the analysis. Four technical skill areas (data collection, data interpretation, planning, and taking action) and five non-technical skill areas (interpersonal skills, ability to deal with legal issues, business skills, making referrals, and problem solving) were identified. All of the skill area subscales listed above had appropriate reliability (Cronbach's alpha>0.70) and were positively and significantly correlated with overall employer satisfaction. Results of two simultaneous regression analyses indicated that of the four technical skill areas, taking action is the most salient predictor of employer satisfaction. Of the five non-technical skill areas, interpersonal skills, business skills, making referrals, and problem solving were the most important skills in predicting employer satisfaction. Hierarchical regression analysis revealed that all technical skills explained 25% of the variation in employer satisfaction; non-technical skills explained an additional 42% of the variation in employer satisfaction.
Subject(s)
Attitude of Health Personnel , Clinical Competence , Students, Health Occupations , Veterinarians/psychology , Animals , Educational Measurement/methods , Employment , Female , Hospitals, Animal , Humans , Iowa , Job Satisfaction , Male , Professional-Patient Relations , Regression Analysis , Schools, Veterinary , Surveys and Questionnaires , Veterinarians/standardsABSTRACT
OBJECTIVE: To determine relationships among several common measures of performance prior to and during veterinary school (ie, Graduate Record Examination [GRE] scores, undergraduate grade point average [UGPA], Qualifying Examination [QE] scores, overall grade point average during veterinary school [VGPA], and scores for the North American Veterinary Licensing Examination [NAVLE]). DESIGN: Longitudinal retrospective study. SAMPLE POPULATION: 192 students from the Iowa State University College of Veterinary Medicine and 152 students from the University of Minnesota College of Veterinary Medicine. PROCEDURES: Student UGPA, VGPA, and GRE score data were gathered during the normal admissions and academic processes. The QE was administered as a low-stakes examination at both institutions for the purposes of curricular assessment. Scores on the NAVLE were provided with student permission by the National Board of Veterinary Medical Examiners. Path analysis was used to explore hypothesized relationships among variables. RESULTS: GRE scores and UGPA predicted NAVLE scores indirectly through QE scores and VGPA, whereas QE scores and VGPA directly predicted NAVLE scores. The resulting models explained 58% to 62% of the variance in NAVLE scores, with QE score being the strongest predictor. CONCLUSIONS AND CLINICAL RELEVANCE: Results indicated that for veterinary school students, GRE scores, UGPA, VGPA, and QE scores could be used to predict scores on the NAVLE. This suggests that these measures could prove useful to veterinary schools when admitting students or preparing them for the NAVLE.
