scholarly journals Adaptive intervention designs in pediatric psychology: The promise of sequential multiple assignment randomized trials of pediatric interventions.

2017 ◽  
Vol 5 (2) ◽  
pp. 170-179 ◽  
Author(s):  
Amy E. Noser ◽  
Christopher C. Cushing ◽  
Meghan E. McGrady ◽  
Christina M. Amaro ◽  
Lindsay P. Huffhines
Keyword(s):  
Randomized Trials ◽  
Pediatric Psychology ◽  
Adaptive Intervention ◽  
Multiple Assignment ◽  
Pediatric Interventions

Sequential Multiple-Assignment Randomized Trials: Developing and Evaluating Adaptive Interventions in Special Education

2018 ◽  
Vol 40 (5) ◽  
pp. 267-276 ◽  
Author(s):  
Jason C. Chow ◽  
Lauren H. Hampton
Keyword(s):  
Special Education ◽  
Individual Differences ◽  
Educational Outcomes ◽  
Randomized Trials ◽  
Sufficient Evidence ◽  
Adaptive Intervention ◽  
Meaningful Information ◽  
Adaptive Interventions ◽  
Multiple Assignment ◽  
Individual Variables

Interventions often require multiple decisions to improve outcomes for every student. Whether the decision to implement a practice, tailor an existing protocol, or change approaches, these decisions should be based on individual variables and outcomes via a sequence of treatment. To develop adaptive interventions that have sufficient evidence to support decisions, components, and sequences, they must be evaluated as they operate. The sequential multiple-assignment randomized trial is a design that experimentally assesses the efficacy of the decisions, components, and sequence of an adaptive intervention. The purpose of this article is to provide an overview of this novel methodology and describe how this design can provide meaningful information about components and sequence based on individual differences and response to maximize educational outcomes in special education.

scholarly journals Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations

2017 ◽  
Vol 26 (4) ◽  
pp. 1572-1589 ◽  
Author(s):  
Timothy NeCamp ◽  
Amy Kilbourne ◽  
Daniel Almirall
Keyword(s):  
Randomized Trial ◽  
Randomized Trials ◽  
Treatment Regimens ◽  
Patient Level ◽  
Multiple Assignment ◽  
Dynamic Treatment ◽  
The Mean ◽  
Cluster Randomized ◽  
The Individual ◽  
Cluster Level

Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.

BestFIT Sequential Multiple Assignment Randomized Trial Results: A SMART Approach to Developing Individualized Weight Loss Treatment Sequences

2021 ◽  
Author(s):  
Nancy E Sherwood ◽  
A Lauren Crain ◽  
Elisabeth M Seburg ◽  
Meghan L Butryn ◽  
Evan M Forman ◽  
...  
Keyword(s):  
Weight Loss ◽  
Randomized Trial ◽  
Controlled Trial ◽  
Response Assessment ◽  
Optimal Time ◽  
Behavioral Weight Loss ◽  
Weight Loss Treatment ◽  
Adaptive Intervention ◽  
Weight Losses ◽  
Multiple Assignment

Abstract Background State-of-the-art behavioral weight loss treatment (SBT) can lead to clinically meaningful weight loss, but only 30–60% achieve this goal. Developing adaptive interventions that change based on individual progress could increase the number of people who benefit. Purpose Conduct a Sequential Multiple Assignment Randomized Trial (SMART) to determine the optimal time to identify SBT suboptimal responders and whether it is better to switch to portion-controlled meals (PCM) or acceptance-based treatment (ABT). Method The BestFIT trial enrolled 468 adults with obesity who started SBT and were randomized to treatment response assessment at Session 3 (Early TRA) or 7 (Late TRA). Suboptimal responders were re-randomized to PCM or ABT. Responders continued SBT. Primary outcomes were weight change at 6 and 18 months. Results PCM participants lost more weight at 6 months (−18.4 lbs, 95% CI −20.5, −16.2) than ABT participants (−15.7 lbs, 95% CI: −18.0, −13.4), but this difference was not statistically significant (−2.7 lbs, 95% CI: −5.8, 0.5, p = .09). PCM and ABT participant 18 month weight loss did not differ. Early and Late TRA participants had similar weight losses (p = .96), however, Early TRA PCM participants lost more weight than Late TRA PCM participants (p = .03). Conclusions Results suggest adaptive intervention sequences that warrant further research (e.g., identify suboptimal responders at Session 3, use PCMs as second-stage treatment). Utilizing the SMART methodology to develop an adaptive weight loss intervention that would outperform gold standard SBT in a randomized controlled trial is an important next step, but may require additional optimization work. Clinical Trial information ClinicalTrials.gov identifier; NCT02368002

scholarly journals Noninferiority and equivalence tests in sequential, multiple assignment, randomized trials (SMARTs).

2020 ◽  
Vol 25 (2) ◽  
pp. 182-205 ◽  
Author(s):  
Palash Ghosh ◽  
Inbal Nahum-Shani ◽  
Bonnie Spring ◽  
Bibhas Chakraborty
Keyword(s):  
Randomized Trials ◽  
Equivalence Tests ◽  
Multiple Assignment
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