Empirical Assessment of Well-Being: The Stanford Model of Occupational Well-Being

幸福感的实证评估:斯坦福职业幸福感模型

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Abstract

PURPOSE: The Stanford Model of Occupational Well-Being (Stanford Model) hypothesizes that occupational well-being is driven by 3 reciprocally related domains: workplace efficiency, culture of wellness, and individual factors. The current analysis assesses the key elements of this model with cross-sectional empirical data. METHOD: In fall 2020 and spring 2022, well-being surveys were distributed to all Stanford School of Medicine clinical faculty working at 50% or more of full-time equivalent. A total of 1,909 clinical faculty were invited to complete the 2020 survey and 2,251 to complete the 2022 survey. The survey assessed burnout and professional fulfillment, along with 9 hypothesized determinants, as occupational well-being outcome indicators. Exploratory factor analysis was used to determine whether these determinants grouped well into the 3 domains described by the model. Domain scores were created based on factor analysis groupings of the scores for the determinants in each domain. RESULTS: Of 1,909 clinical faculty invited to complete the 2020 survey, 1,479 (78%) participated. Of the 2,251 clinical faculty invited in 2022, 1,552 (69%) participated. The associations of the 3 domain scores with burnout and professional fulfillment were moderate for workplace efficiency ( r = 0.42-0.49; P < .001) and large for culture of wellness ( r = 0.51-0.63; P < .001) and individual factors ( r = 0.52-0.72; P < .001). Domain scores accounted for 45% and 50% of the variance in professional fulfillment and 56% and 58% of variance in burnout in 2020 and 2022 data, respectively. CONCLUSIONS: These results provide empirical evidence to support a widely adopted conceptual model of occupational well-being, including categorization of the hypothesized determinants of well-being into 3 domains, correlations among the domains, and association of the domain scores with burnout and professional fulfillment. Further research is needed to test causal relationships hypothesized by the model.

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