A structural regression analysis of trauma-informed climate factors, organizational commitment, and burnout among behavioral healthcare providers in a large public hospital.

07:00 EST 3rd December 2019 | BioPortfolio

Summary of "A structural regression analysis of trauma-informed climate factors, organizational commitment, and burnout among behavioral healthcare providers in a large public hospital."

As an approach to organizational change, trauma-informed care is contextualized within the broader organizational literature by examining the associations between organizational conditions (i.e., psychological experiences of choice and collaboration in the work environment) with precursors to organizational effectiveness (i.e., affective commitment and burnout). The study occurred within a large public hospital's behavioral health department located in the Western New York region (N = 197). Structural regression analyses were conducted, and the primary findings, while nuanced, include support for choice and collaboration's prediction of employee commitment and burnout. Organizational interventions that improve worker's experiences of choice and collaboration may result in increased commitment, reduced burnout, and possibly improved effectiveness. Future research should employ longitudinal designs to further examine the condition-performance relationship and include direct measures of clinical effectiveness.


Journal Details

This article was published in the following journal.

Name: Journal of community psychology
ISSN: 1520-6629


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Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable.

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