Measuring and predicting academic generalists' work satisfaction: Implications for retaining faculty

Purpose. To develop a measure that could be used to identify interventions to improve the work satisfaction of academic generalists. Methods. To field-test the measure, the authors surveyed the generalist faculty at the University of Texas Southwestern Medical Center at Dallas. Ninety-four (80%) of the faculty responded. The measure's reliability was established using Cronbach's alpha, and its validity was established with the Pearson correlation coefficient using a previously validated global work- satisfaction measure. Using ten work-satisfaction dimensions and selected faculty characteristics, the authors performed univariate and stepwise multiple regression analyses to predict the generalist faculty's global work satisfaction and intentions of leaving their positions. Results. Work- satisfaction dimension predictors were autonomy in the workplace, professional status, teaching activities, clinical resources and activities, professional relationships, institutional governance, compensation, and professional advancement. Faculty characteristic predictors were gender, age, race or ethnicity, and living with children. Conclusion. The measure includes eight valid and reliable work-satisfaction dimensions that predict global work satisfaction or intentions to leave. Others may want to use this measure, along with the four faculty-characteristic predictors, as a management tool for improving academic generalists' work satisfaction and, ultimately, their performances and retention.