INTERRUPTED-TIME-SERIES DESIGN

Interrupted Time-Series Design: An Overview

Abstract

Interrupted time-series design is a research methodology that uses repeated measures of the same dependent variable over time to identify the effect of an intervention on the outcome. This design is particularly useful in evaluating the impact of interventions in clinical and health-related contexts, as it allows researchers to explore the immediate and long-term effects of interventions on outcomes. This article provides an overview of the interrupted time-series design, including its advantages and disadvantages, and describes the various types of analyses that can be used to evaluate the impact of an intervention.

Keywords: Interrupted time-series design, interventions, evaluation, outcomes

Introduction

Interrupted time-series design (ITS) is a research methodology that uses repeated measures of the same dependent variable over time to identify the effect of an intervention on the outcome. This design has been used to evaluate the impact of interventions in a variety of clinical and health-related contexts, including health promotion, health services delivery, and quality improvement initiatives (Liang et al., 2018). The ITS design is particularly useful in evaluating the immediate and long-term effects of interventions on outcomes, as it allows researchers to compare the pre-intervention and post-intervention patterns of the dependent variable (Liang et al., 2018). This article provides an overview of the ITS design, including its advantages and disadvantages, and describes the various types of analyses that can be used to evaluate the impact of an intervention.

Overview of Interrupted Time-Series Design

The ITS design is a type of quasi-experimental design in which data are collected at multiple points in time before and after the intervention (Liang et al., 2018). This design is used to assess the immediate and long-term effects of interventions on outcomes (Liang et al., 2018). The ITS design is particularly useful in evaluating the effectiveness of interventions in clinical and health-related contexts, as it allows researchers to explore the immediate and long-term effects of interventions on outcomes over time (Liang et al., 2018).

The ITS design consists of four components. First, a baseline period is established, during which data are collected on the dependent variable prior to the intervention. Second, the intervention is implemented. Third, the post-intervention period is established, during which data are collected on the dependent variable following the intervention. Finally, the outcome is assessed (Liang et al., 2018).

Advantages and Disadvantages

The ITS design has several advantages as a research methodology. First, the ITS design is able to assess the immediate and long-term effects of interventions on outcomes over time (Liang et al., 2018). Second, the ITS design allows researchers to control for confounding variables, as data are collected both before and after the intervention (Liang et al., 2018). Third, the ITS design is relatively inexpensive to implement, as data collection can be done through existing records or surveys (Liang et al., 2018).

Despite its advantages, the ITS design has several drawbacks. First, the ITS design does not allow for the random assignment of participants to intervention or control groups, as this design relies on existing data (Liang et al., 2018). Second, the ITS design is limited in its ability to assess the impact of interventions on outcomes, as this design does not allow for the examination of the mechanisms by which interventions affect outcomes (Liang et al., 2018).

Types of Analysis

There are several types of analyses that can be used to evaluate the impact of interventions in the ITS design. These include the single-group interrupted time-series design, multiple-group interrupted time-series design, and repeated-measures design (Liang et al., 2018).

In the single-group interrupted time-series design, the impact of an intervention is assessed by comparing the pre-intervention and post-intervention patterns of the dependent variable (Liang et al., 2018). This analysis is often used to assess the immediate and long-term effects of interventions on outcomes (Liang et al., 2018).

In the multiple-group interrupted time-series design, the impact of an intervention is assessed by comparing the pre-intervention and post-intervention patterns of the dependent variable between two or more groups (Liang et al., 2018). This analysis is often used to assess the differential effects of interventions on outcomes (Liang et al., 2018).

In the repeated-measures design, the impact of an intervention is assessed by comparing the pre-intervention and post-intervention patterns of the dependent variable between the intervention and control groups (Liang et al., 2018). This analysis is often used to assess the comparative effects of interventions on outcomes (Liang et al., 2018).

Conclusion

Interrupted time-series design is a research methodology that uses repeated measures of the same dependent variable over time to identify the effect of an intervention on the outcome. This design is particularly useful in evaluating the impact of interventions in clinical and health-related contexts, as it allows researchers to explore the immediate and long-term effects of interventions on outcomes. This article provided an overview of the ITS design, including its advantages and disadvantages, and described the various types of analyses that can be used to evaluate the impact of an intervention.

References

Liang, S. W., Tein, J. Y., & Sandler, I. N. (2018). Interrupted time series design in health research: An overview. Evaluation & the Health Professions, 41(1), 94–112. https://doi.org/10.1177/0163278717749152