3087.0: Monday, October 22, 2001 - 2:55 PM

Abstract #31740

Strength of Tobacco Control: Escaping the black box of program evaluation

Pamela I. Clark, PhD1, Frances A. Stillman, EdD2, Warren J. Strauss, ScM3, William Trochim4, and Carol L. Schmitt, MA1. (1) Battelle Centers for Public Health Research and Evaluation, 6115 Falls Road, Second Floor, Baltimore, MD 21209, (410) 372-2750, clarkp@battelle.org, (2) Institute for Global Tobacco Control, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Room W 6027, baltimore, MD 21205, (3) Statistics and Data Analysis Systems, Battelle Memorial Institute, 505 King Ave, Columbus, OH 43201-2693, (4) Policy Analyses and Management, Cornell University, 132MVR Hall, Ithaca, NY 14853

ASSIST prescribed complex, interrelated interventions in multiple domains of influence, a complexity typical of modern programmatic interventions. Previous efforts to evaluate complex interventions have utilized clinical trials models, often failing to account for the degree of fidelity with which interventions are implemented, diffusion of the intervention to control groups, and limited sample sizes. Measurement of Strength of Tobacco Control (SoTC) constructs used an evaluation mechanism that went beyond a clinical trials model.

SoTC utilized a conceptual framework with three latent variables: resources, capacity, and efforts. The objective was to combine information obtained from two surveys to form an overall measure of SoTC that summarized the complexities of those three constructs, provided a relative ranking of state tobacco control efforts, and served as an indirect measure for program effects at the state level. At levels of hierarchy below the three constructs existed other latent domains, with each relating to survey items. The hierarchical relationship of the data provided a road map for combining variables to describe SoTC. To best approximate the value of each latent variable, we combined the survey data using principal components analysis. A significant amount of variability was explained by the pathways in the conceptual model and fit the data well based on the overall model chi-square test and goodness-of-fit statistic. This process has historic significance by its success in defining the complex construct of tobacco control, and its value as a benchmark for state-level programs at a pivotal point in the history of tobacco control.

Learning Objectives: See abstract for details

Keywords: Tobacco Control, Evaluation

Presenting author's disclosure statement:
Organization/institution whose products or services will be discussed: None
I have a significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.
Relationship: Federal Government contractor

The 129th Annual Meeting of APHA