Results from a psychometric assessment of a new tool for measuring evidence-based decision making in public health organizations. (February 2017)

• Record Type: Journal Article
• Authors: Stamatakis, Katherine A.; Ferreira Hino, Adriano Akira; Allen, Peg; McQueen, Amy; Jacob, Rebekah R.; Baker, Elizabeth A.; Brownson, Ross C.
• Is Part Of: Evaluation and program planning. Volume 60(2017)
• Page Start: 17
• Page End: 23
• Publication Date: 2017-02
• Subjects: EBDM evidence-based decision making -- EBI evidence-based interventions -- SHD state health department -- EFA exploratory factor analysis -- CFA confirmatory factor analysis -- SEM structural equation model -- D&I dissemination and implementation -- EIDM evidence-informed decision making -- KTE knowledge translation and exchange; Evidence-based decision making -- Public health -- Measurement -- Confirmatory factor analysis; Health planning -- Periodicals; Medical care -- Evaluation -- Periodicals; 362.1068
• DOI: 10.1016/j.evalprogplan.2016.08.002
• Languages: English
• ISSNs: 0149-7189

Abstract

Highlights: A set of items was developed to measure evidence-based decision making (EBDM). Confirmatory factor analysis suggested a set of five latent constructs. The EBDM measurement tool may be used to evaluate needed public health supports. Abstract: Background: In order to better understand how to improve evidence-based decision making (EBDM) in state health departments, measurement tools are needed to evaluate changes in EBDM. The purpose of this study was to test the psychometric properties of a new measurement tool to assess EBDM in public health practice settings. Methods: A questionnaire was developed, pilot-tested and refined in an iterative process with the input of public health practitioners with the aim of identifying a set of specific measures representing different components of EBDM. Data were collected in a national survey of state health department chronic disease practitioners. The final dataset (n = 879) for psychometric testing was comprised of 19 EBDM items that were first examined using exploratory factor analysis, and then confirmatory factor analysis. Results: The final model from confirmatory factor analysis includes five latent factors representing components of EBDM: capacity for evaluation, expectations and incentives for EBDM, access to evidence and resources for EBDM, participatory decision making, and leadership support and commitment. Conclusions: This study addresses the need for empirically tested and theory-aligned measures that may be used to assess the extent to which EBDM is currently implemented, and further, to gauge the success of strategies to improve EBDM, in public health settings. This EBDM measurement tool may help identify needed supports for enhanced capacity and implementation of effective strategies.