Work

Adaptive Interventions and SMART Designs

Year: 2015

Type: article

Abstract: Heterogeneity between and within people necessitates the need for sequential personalized interventions to optimize individual outcomes. Personalized or adaptive interventions (AIs) are relevant for diseases and maladaptive behavioral trajectories when one intervention is not curative and success of a subsequent intervention may depend on individual characteristics or response. AIs may be applied to medical settings and to investigate best prevention, education, and community-based practices. AIs can begin with low-cost or low-burden interventions and followed with intensified or alternative interventions for those who need it most. AIs that guide practice over the course of a disease, program, or school year can be investigated through sequential multiple assignment randomized trials (SMARTs). To promote the use of SMARTs, we provide a hypothetical SMART in a Head Start program to address child behavior problems. We describe the advantages and limitations of SMARTs, particularly as they may be applied to the field of evaluation.

Source: American Journal of Evaluation

DOI: 10.1177/1098214015617013

Authors: Kelley M. Kidwell, Luke W. Hyde

Institutions: University of Michigan, Institute for Social Research

Language: English

Topic: Advanced Causal Inference Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institute of Mental Health, National Institute on Drug Abuse