Cited by 608Advanced Causal Inference TechniquesStatistical Methods in Clinical TrialsSubstance Abuse Treatment and Outcomes

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A Conceptual Framework for Adaptive Preventive Interventions

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Collins, Linda M., Murphy, Susan A., Bierman, Karen L.·2004·Prevention Science

DOI 10.1023/b:prev.0000037641.26017.00PMC PMC3544191

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Abstract

Recently, adaptive interventions have emerged as a new perspective on prevention and treatment. Adaptive interventions resemble clinical practice in that different dosages of certain prevention or treatment components are assigned to different individuals, and/or within individuals across time, with dosage varying in response to the intervention needs of individuals. To determine intervention need and thus assign dosage, adaptive interventions use prespecified decision rules based on each participant's values on key characteristics, called tailoring variables. In this paper, we offer a conceptual framework for adaptive interventions, discuss principles underlying the design and evaluation of such interventions, and review some areas where additional research is needed.

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Authors: Collins, L. M., Murphy, S. A., & Bierman, K. L.
Affiliations: Pennsylvania State University (US)
University of Michigan (US)
Corresponding author: Collins, Linda M.
ORCID: Collins, Linda M.
Murphy, Susan A.
Bierman, Karen L.
Venue: Prevention Science
Publisher: Springer Science and Business Media LLC
Published: 2004-09
Volume: 5
Issue: 3
Pages: 185-196
ISSN: 1389-4986 (ISSN-L)
1573-6695
DOI: 10.1023/b:prev.0000037641.26017.00
PMC: PMC3544191
OpenAlex: W2021206292
Semantic Scholar: 2dfd8040ec25b7b63e4bcff6e2c5671c91529c2e
Cited by: 608
References: 46
Citations by year: 2026: 19 · 2025: 18 · 2024: 19 · 2023: 34 · 2022: 27 · 2021: 27 · 2020: 23 · 2019: 33 · 2018: 30 · 2017: 33 · 2016: 38 · 2015: 30 · 2014: 42 · 2013: 37 · 2012: 34
FWCI: 19.93
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.springernature.com/gp/researchers/text-and-data-mining (tdm)
www.springernature.com/gp/researchers/text-and-data-mining (vor)
Locations: Prevention Science (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Deep Blue (University of Michigan) (submittedVersion)
Funders: National Institute of Mental Health (R01MH050953)
National Institute on Drug Abuse (K02DA015674, P50-DA-10075, P50DA010075, K02-DA15674)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
Keywords: adaptive interventions, preventive interventions, decision rules, intervention dosage, personalized prevention, intervention design, intervention evaluation, conceptual framework
MeSH terms: Child, Child Behavior Disorders, Clinical Competence, Decision Support Techniques, Forecasting, Home Care Services, Humans, Judgment, Parent-Child Relations, Parents, Patient Care Planning, Patient Participation, Primary Prevention, Research Design, Risk Factors, Time Factors, Reproducibility of Results, Confounding Factors, Epidemiologic, Outcome Assessment, Health Care, Risk Assessment, Conduct Disorder, Needs Assessment

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A Conceptual Framework for Adaptive Preventive Interventions

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