Mild traumatic brain injury in a gymnast.

Primary care providers often are responsible for the initial evaluation and management plan of young patients with mild traumatic brain injury (mild TBI, also called concussion), and need to be familiar with new protocols and how to incorporate them into a patient's treatment plan. This article describes a patient who suffered a mild TBI and returned to sports too early, and discusses the appropriate protocols for managing concussion in children.

Predicting physician assistant students' professionalism by personality attributes.

PURPOSE: The purpose of this study is to determine whether personality characteristics, both positive and negative, predict the level of professionalism in physician assistant (PA) students. METHODS: Both the Millon College Counseling Inventory (MCCI) and a physician assistant professionalism scale (PA Professional Scale) were administered to 82 PA students in 5 multiple years at University of Detroit Mercy, a private-university PA program with an end point of a master's degree. Cluster analysis determined natural groupings of healthy and unhealthy personality characteristics, and the two personality clusters were compared to each of 15 professionalism parameters. Significant correlations were determined using a two-tailed Pearson correlation. RESULTS: The "healthy" personality clusters characterized by conscientiousness and outward directedness were significantly predictive for the professionalism attributes of taking full responsibility for self, volunteering for others, dressing professionally, punctuality, participating in class, ability to give and receive criticism, and seeking out new challenges. The "unhealthy" cluster was negatively correlated to taking full responsibility, volunteerism, trustworthiness, dressing professionally, being punctual, giving and receiving criticism, and taking on new challenges. CONCLUSION: Healthy personality characteristics do predict high levels of self-reported professionalism according to this study. Conversely, unhealthy personality characteristics will predict a low level of self-reported professionalism. Personality profiles can be incorporated into the admission process to select a higher percentage of candidates who value and emulate professionalism, producing better practitioners.

Admission variables as predictors of PANCE scores in physician assistant programs: a comparison study across universities.

PURPOSE: The purpose of this study was to create a model of cognitive and noncognitive measures that could estimate the probability of achieving a given level of performance on the Physician Assistant National Certifying Examination (PANCE). METHODS: A retrospective records review of admissions information used by six universities was conducted to discover which factor had the most impact on the dependent variable of the PANCE score. Multiple predictors were measured: undergraduate grade point average (uGPA), graduate GPA, prerequisite grades, Graduate Record Exam (GRE)-verbal, GRE-quantitative, GRE combined, interview scores, years of health care experience, age, gender, and first-year scores on the Physician Assistant Clinical Knowledge Rating and Assessment Tool (PACKRAT). While PACKRAT scores are not applicable to admission selection, they are a strong midpoint predictor of PANCE performance. Multiple regression analysis was used to develop prediction equations. Expectancy tables were developed to provide estimation of PANCE performance, given the various score ranges on each of the predictor variables. RESULTS: Four predictors made a significant contribution to the final regression equation: GPA, GRE-verbal, GRE-quantitative, and PACKRAT scores. The PACKRAT scores were consistently the best predictors of performance on the PANCE. Each of these four predictors can be plugged into predictability tables to estimate the probability of achieving various score intervals on the PANCE. CONCLUSION: A model of equations and predictors can be used to project how successful a physician assistant (PA) graduate will be on PANCE performance. Years of health care experience, grades on prerequisites, and demographics were not significant predictors across programs but did have significance in certain individual institutions. Future research should examine which specific noncognitive traits measured in interviews can add value to predictability.