The value of interrupted time-series experiments for community intervention research

Abstract

Greater use of interrupted time-series experiments is advocated for community intervention research. Time-series designs enable the development of knowledge about the effects of community interventions and policies in circumstances in which randomized controlled trials are too expensive, premature, or simply impractical. The multiple baseline time-series design typically involves two or more communities that are repeatedly assessed, with the intervention introduced into one community at a time. It is particularly well suited to initial evaluations of community interventions and the refinement of those interventions. This paper describes the main features of multiple baseline designs and related repeated-measures time-series experiments, discusses the threats to internal validity in multiple baseline designs, and outlines techniques for statistical analyses of time-series data. Examples are given of the use of multiple baseline designs in evaluating community interventions and policy changes.

Fig. 1

Measurement variability in two hypothetical interrupted time series. The first shows a highly variable series and the second a relatively stable series.

Fig. 2

The effects of Michigan’s implementation of mandatory automobile safety seat on injuries to motor vehicle occupants 0 to 3 years of age.

Fig. 3

The proportion of tobacco outlets in each of four communities that were willing to sell to those under 18 before and after the implementation of a reward and reminder program.