Estimating intervention effects of prevention programs: accounting for noncompliance

Prev Sci. 2008 Dec;9(4):288-98. doi: 10.1007/s11121-008-0104-y. Epub 2008 Oct 9.


Individuals not fully complying with their assigned treatments is a common problem encountered in randomized evaluations of behavioral interventions. Treatment group members rarely attend all sessions or do all "required" activities; control group members sometimes find ways to participate in aspects of the intervention. As a result, there is often interest in estimating both the effect of being assigned to participate in the intervention, as well as the impact of actually participating and doing all of the required activities. Methods known broadly as "complier average causal effects" (CACE) or "instrumental variables" (IV) methods have been developed to estimate this latter effect, but they are more commonly applied in medical and treatment research. Since the use of these statistical techniques in prevention trials has been less widespread, many prevention scientists may not be familiar with the underlying assumptions and limitations of CACE and IV approaches. This paper provides an introduction to these methods, described in the context of randomized controlled trials of two preventive interventions: one for perinatal depression among at-risk women and the other for aggressive disruptive behavior in children. Through these case studies, the underlying assumptions and limitations of these methods are highlighted.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Child
  • Child Behavior
  • Depression, Postpartum / prevention & control
  • Female
  • Health Promotion / statistics & numerical data*
  • Humans
  • Male
  • Models, Psychological*
  • Patient Compliance / statistics & numerical data*
  • Pregnancy
  • Randomized Controlled Trials as Topic*
  • Social Adjustment