Competence and confidence in rural and remote nursing practice: A structural equation modelling analysis of national data.

Aims And Objectives: To empirically test a conceptual model of confidence and competence in rural and remote nursing practice.

Background: The levels of competence and confidence of nurses practising in rural settings have been highlighted as essential to the quality of health outcomes for rural peoples. However, there is limited research exploring these constructs in the context of rural/remote nursing practice.

Design: Structural equation modelling was used to verify the conceptual model with data from the cross-sectional pan-Canadian Nursing Practice in Rural and Remote Canada II Survey. The STROBE guidelines for cross-sectional research were followed in the design/reporting of this analysis. The sample consisted of 2,065 registered nurses and nurse practitioners who were working in direct rural/remote nursing practice.

Results: The maximum likelihood ratio χ  = 0.0822, df = 2, p = 0.959 indicated model fit, with final model estimates explaining 53% of the variance in work confidence and 17% of the variance in work competence. The model also accounted for 40% of the variance in work engagement, 39% of the variance in burnout and 15% of the variance in perceived stress. The complexity of competence and confidence in rural nursing practice was evident, being influenced by nursing experience in rural settings, rural work environment characteristics, community factors and indicators of professional well-being.

Conclusions: The factors influencing nurses' competence and confidence in rural/remote nursing practice are more complex than previously understood. Our model, created and tested using structural equation modelling, merits further research, to extend our understanding of how nurses can be prepared and supported for practice in rural and remote settings.

Relevance To Clinical Practice: This study highlights the importance of supporting new nurses' exposure to rural nursing experiences, reducing professional isolation and improving decision-making support for those who are working at a greater distance from colleagues and/or those with fewer opportunities for interprofessional collaboration.