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Eval Program Plann. 2017 Feb;60:17-23. doi: 10.1016/j.evalprogplan.2016.08.002. Epub 2016 Aug 12.

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

Author information

1
Department of Epidemiology, College for Public Health & Social Justice, Saint Louis University, 3545 Lafayette Avenue, St. Louis, MO 63130, United States. Electronic address: kstamata@slu.edu.
2
Department of Physical Education, School of Health and Biosciences, Pontifícia Universidade Católica do Paraná, Curitiba, PR, Brazil. Electronic address: akira.hino@pucpr.br.
3
Prevention Research Center in St. Louis, Brown School, Washington University in St. Louis, One Brookings Drive, St. Louis, MO 63130, United States. Electronic address: pegallen@wustl.edu.
4
Health Communications Research Laboratory, Washington University in St. Louis, 700 Rosedale Avenue, St. Louis, MO 63112, United States. Electronic address: amcqueen@dom.wustl.edu.
5
Prevention Research Center in St. Louis, Brown School, Washington University in St. Louis, One Brookings Drive, St. Louis, MO 63130, United States. Electronic address: rebekahjacob@wustl.edu.
6
Department of Behavioral Science and Health Education, College for Public Health and Social Justice, Saint Louis University, 3545 Lafayette Ave., St Louis, MO 63130, United States. Electronic address: bakerpa@slu.edu.
7
Prevention Research Center in St. Louis, Brown School, Washington University in St. Louis, One Brookings Drive, St. Louis, MO 63130, United States. Electronic address: rbrownson@brownschool.wustl.edu.

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.

KEYWORDS:

Confirmatory factor analysis; Evidence-based decision making; Measurement; Public health

[Indexed for MEDLINE]
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