Deepening Empirical Understandings of Nurse Work Well-Being: Using Mixed Methods Including Path Analysis to Create Contextualized Outcome Models.

Abstract

Background: This 2022-2023 study across nine countries builds on a 2019-2021 ten-country study exploring nurse work well-being (WWB) and its associated outcomes. WWB, as assessed using the Profile of Caring (PoC) survey, is conceptualized as a multifactorial construct encompassing caring for self, caring of manager, clarity of role/system, and job satisfaction.

Aims: To explore relationships between WWB and staff outcomes by evaluating the PoC construct validity within an international nursing population in the post-pandemic context.

Methods: Nursing staff (n = 2546) from 128 facilities participated. Mixed methods, including thematic analysis, descriptive statistics, regression analyses, and path analysis, were employed to develop a WWB outcome model. Reliability was assessed with Cronbach's alpha, and construct validity was assessed through exploratory factor analysis.

Results: The final model had good model fit, explaining 76% of nurse WWB. Feeling rewarded for work well done, total direct effect had a positive relationship with job satisfaction (β = 0.415, p = < 0.001) and a negative effect on intent to leave (β = -0.242, p = 0.003). Job satisfaction total direct effect negatively related to intent to leave (β = -0.584, p = < 0.001). Relationship direction, strength, and significance varied by country. Caring of manager explained one-third of WWB. Job satisfaction subscales explained intent to leave (25.2%). The PoC showed high reliability (Cronbach's alpha ≥ 0.80), and robust construct validity was confirmed through exploratory factor analysis (KMO = 0.950, factor loadings ≥ 0.40).

Linking evidence to action: Conclusions suggest that understanding job satisfaction and intent to leave predictors is complex, requiring complex models to globally and contextually explain nurse WWB outcomes.