Physician assistant job satisfaction
a narrative review of empirical researchPhysician assistant job satisfaction
a narrative review of empirical researchSamenvatting
PURPOSE: To examine physician assistant (PA) job satisfaction and identify factors predicting job satisfaction and identify areas of needed research. With a global PA movement underway and a half-century in development, the empirical basis for informing employers of approaches to improve job satisfaction has not received a careful review. METHODS: A narrative review of empirical research was undertaken to inform stakeholders about PA employment with a goal of improved management. The a priori criteria included published studies that asked PAs about job satisfaction. Articles addressing PA job satisfaction, written in English, were reviewed and categorized according to the Job Characteristics Model. RESULTS: Of 68 publications reviewed, 29 met criteria and were categorized in a Job Characteristics Model. Most studies report a high degree of job satisfaction when autonomy, income, patient responsibility, physician support, and career advancement opportunities are surveyed. Age, sex, specialty, and occupational background are needed to understand the effect on job satisfaction. Quality of studies varies widely. CONCLUSIONS: Employers may want to examine their relationships with PAs periodically. The factors of job satisfaction may assist policymakers and health administrators in creating welcoming professional employment environments. The main limitation: no study comprehensively evaluated all the antecedents of job satisfaction. PAs seem to experience job satisfaction supported by low attrition rates and competitive wages. Contributing factors are autonomy, experienced responsibility, pay, and supportive supervising physician. A number of intrinsic rewards derived from the performance of the job within the social environment, along with extrinsic rewards, may contribute to overall job satisfaction. PA job satisfaction research is underdeveloped; investigations should include longitudinal studies, cohort analyses, and economic determinants.