Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Frey's Scenario F simulation mentioned in account of the Democratic Party's tribulations

U-M Poverty Solutions funds nine projects

Dynarski says NY's Excelsior Scholarship Program could crowd out low-income and minority students

More News

Highlights

Workshops on EndNote, NIH reporting, and publication altmetrics, Jan 26 through Feb 7, ISR

2017 PAA Annual Meeting, April 27-29, Chicago

NIH funding opportunity: Etiology of Health Disparities and Health Advantages among Immigrant Populations (R01 and R21), open Jan 2017

Russell Sage 2017 Summer Institute in Computational Social Science, June 18-July 1. Application deadline Feb 17.

More Highlights

Next Brown Bag

Mon, Jan 23, 2017 at noon:
Decline of cash assistance and child well-being, Luke Shaefer

A Strategy for Optimizing and Evaluating Behavioral Interventions

Publication Abstract

Collins, L.M., Susan A. Murphy, V. Nair, and V. Strecher. 2005. "A Strategy for Optimizing and Evaluating Behavioral Interventions." Annals of Behavioral Medicine, 30(1): 66-73.

Background. This article suggests a multiphase optimization strategy (MOST) for achieving the dual goals of program optimization and program evaluation in the behavioral intervention field. Methods. MOST consists of the following three phases: (1) screening, in which randomized experimentation closely guided by theory is used to asses an array of program and/or delivery components and select the components that merit further investigation; (2) refining, in which interactions among the identified set of components and their interrelationships with covariates are investigated in detail, again via randomized experiments, and optimal dosage levels and combinations of components are identified; and (3) confirming, in which the resulting optimized intervention is evaluated by means of a standard randomized intervention trial. In order to make the best use of available resources, MOST relies on design and analysis tools that help maximize efficiency, such as fractional factorials. Results. A slightly modified version of an actual application of MOST to develop a smoking cessation intervention is used to develop and present the ideas. Conclusions. MOST has the potential to husband program development resources while increasing our understanding of the individual program and delivery components that make up interventions. Considerations, challenges, open questions, and other potential

Browse | Search : All Pubs | Next