Health system workforce’s performance capacity towards integrated leading, managing and governing practices: with special reference to the application of factor analysis and ordinal logistic regression

Abstract AbstractObserving over-led and under-managed, over-managed and under-governed, and even out of these health organizations remains a common phenomenon in low and middle-income countries. The current study looks at the health system workforce’s performance capacity towards integrated leading, managing, and governing practices and its predictors in Ethiopia. Eight hundred thirteen health facility employees completed a multi-item questionnaire. The data were fitted to factor analysis and ordinal logistic regression models. The factor analysis was employed to develop a scientifically reliable and empirically scalable measurement model. The model was assembled from items rated, factors extracted and error variances observed. Besides, the health system workforce’s performance capacity was computed and labeled. Moreover, the ordinal logistic regression was conducted to identify predictors of the performance capacity. The outputs of factor analysis provided a four-factor measurement model. This model had acceptable estimates, composite reliability, and average variance extracted. Eighty-four percent of the participants had reported low (41.3%) and moderate (42.7%) performance capacity towards integrated leading, managing, and governing practices. Sex and responsibility were among significantly associated predictors. Empowering the health system workforce towards integrated leading, managing and governing practices using a scientifically reliable and empirically scalable model is important, particularly in resource-limited settings. In this regard, the policies and strategies should give due attention to females and service owners. The current results could provide a foundation for training and future research.