Special educators serve a diverse population of students with unique strengths and needs, and adaptive interventions that account for individual differences before and during the intervention are an important tool to moving the field toward more individualized practices. The purpose of this article is to detail the conceptualization and application of tailoring the sequential multiple assignment randomized trial (SMART) design approach to developing and evaluating deeply tailored adaptive interventions through the application of secondary analyses to account for individual differences at multiple time points. This conceptual paper provides an overview beyond the basic SMART design components by describing the tactics, design options, and analyses currently available to further refine a SMART study into a more personalized intervention to account for individual differences at multiple points throughout the intervention and individual response to treatment.
AlmirallD.KasariC.McCaffreyD. F.Nahum-ShaniI. (2018). Developing optimized adaptive interventions in education. Journal of Research on Educational Effectiveness, 11(1), 27–34. https://doi.org/10.1080/19345747.2017.1407136
2.
AlmirallD.Nahum-ShaniI.SherwoodN. E.MurphyS. A. (2014). Introduction to SMART designs for the development of adaptive interventions: With application to weight loss research. Translational Behavioral Medicine, 4(3), 260–274. https://doi.org/10.1007/s13142-014-0265-0
3.
ArtmanW. J.Nahum-ShaniI.WuT.MckayJ. R.ErtefaieA. (2020). Power analysis in a SMART design: Sample size estimation for determining the best embedded dynamic treatment regime. Biostatistics, 21(3), 432–448. https://doi.org/10.1093/biostatistics/kxy064
4.
ChambersD. A.NortonW. E. (2016). The adaptome: Advancing the science of intervention adaptation. American Journal of Preventive Medicine, 51(4), S124–S131. https://doi.org/10.1016/j.amepre.2016.05.011
5.
ChowJ. C. (2020). Commentary–Classroom motivation and learning disabilities: Consensus points and recommendations. Learning Disabilities: A Multidisciplinary Journal, 25(2), 54–60.
6.
ChowJ. C.HamptonL. H. (2019). Sequential multiple-assignment randomized trial: Developing and evaluating adaptive interventions in special education.se. Remedial and Special Education, 40(5), 267–276. https://doi.org/10.1177/0741932518759422
7.
CollinsL. M.Nahum-ShaniI.AlmirallD. (2014). Optimization of behavioral dynamic treatment regimens based on the sequential, multiple assignment, randomized trial (SMART). Clinical Trials (London, England), 11(4), 426–434. https://doi.org/10.1177/1740774514536795
8.
DziakJ. J.Nahum-ShaniI.CollinsL. M. (2012). Multilevel factorial experiments for developing behavioral interventions: Power, sample size, and resource considerations. Psychological Methods, 17(2), 153–175. https://doi.org/10.1037/a0026972
9.
EngelmannS. (2008). Corrective reading: Comprehension. A. SRA/McGraw-Hill.
10.
FuchsD.FuchsL. S. (2019). On the importance of moderator analysis in intervention research: An introduction to the special issue. Exceptional Children, 85(2), 126–128. https://doi.org/10.1177/0014402918811924
11.
Gunlicks-StoesselM.MufsonL. (2011). Early patterns of symptom change signal remission with interpersonal psychotherapy for depressed adolescents. Depression and Anxiety, 28(7), 525–531. https://doi.org/10.1002/da.20849
12.
HardemanW.HoughtonJ.LaneK.JonesA.NaughtonF. (2019). A systematic review of just-in-time adaptive interventions (JITAIs) to promote physical activity. International Journal of Behavioral Nutrition and Physical Activity, 16(1), Article 31. https://doi.org/10.1186/s12966-019-0792-7
13.
Institute of Education Sciences. (2020). Special Education Research Request for Applications. FY 2021; CDFA Number: 84.324A.
14.
KasariC.KaiserA. P.GoodsK.NietfeldJ.MathyP.LandaR.MurphyS.AlmirallD. (2014). Communication interventions for minimally verbal children with autism: A sequential multiple assignment randomized trial. Journal of the American Academy of Child & Adolescent Psychiatry, 53(6), 635–646. http://doi.org/10.1016/j.jaac.2014.01.019
15.
KidwellK. M.SeewaldN. J.TranQ.KasariC.AlmirallD. (2017). Design and analysis considerations for comparing dynamic treatment regimens with binary outcomes from sequential multiple assignment randomized trials. Journal of Applied Statistics, 45(9), 1628–1651. https://doi.org/10.1080/02664763.2017.1386773
16.
MajeikaC. E.BruhnA. L.SterrettB. I.McDanielS. (2020). Reengineering Tier 2 interventions for responsive decision making: An adaptive intervention process. Journal of Applied School Psychology, 36(2), 111–132. https://doi.org/10.1080/15377903.2020.1714855
17.
Nahum-ShaniI.AlmirallD. (2019). An introduction to adaptive interventions and SMART designs in education (NCSER 2020-001). National Center for Special Education Research.
18.
Nahum-ShaniI.ErtefaieA.LuX.LynchK. G.McKayJ. R.OslinD. W.AlmirallD. (2017). A SMART data analysis method for constructing adaptive treatment strategies for substance use disorders. Addiction, 112(5), 901–909. https://doi.org/10.1111/add.13743
19.
Nahum-ShaniI.HeklerE. B.Spruijt-MetzD. (2015). Building health behavior models to guide the development of just-in-time adaptive interventions: A pragmatic framework. Health Psychology, 34(S), Article 1209. https://doi.org/10.1037/hea0000306
20.
Nahum-ShaniI.QianM.AlmirallD.PelhamW. E.GnagyB.FabianoG.WaxmonskyJ.YuJ.MurphyS. (2012a). Experimental designed and primary data analysis Methods for comparing adaptive interventions. Psychological Methods, 17(4), 457–477. https://doi.org/10.1037/a0029372
21.
Nahum-ShaniI.QianM.AlmirallD.PelhamW. E.GnagyB.FabianoG.WaxmonskyJ.YuJ.MurphyS. (2012b). Q-learning: A data analysis method for constructing adaptive interventions. Psychological Methods, 17(4), 478–494. https://doi.org/10.1037/a0029373
22.
OettingAlena I.LevyJ. A. (2007). Statistical methodology for a SMART design in the development of adaptive treatment strategies. Causality and Psychopathology. https://doi.org/10.1093/oso/9780199754649.003.0013
23.
OgbagaberS. B.KarpJ.WahedA. S. (2016). Design of sequentially randomized trials for testing adaptive treatment strategies. Statistics in Medicine, 35(6), 840–858. https://doi.org/10.1002/sim.674
24.
PelhamW. E.Jr.FabianoG. A.WaxmonskyJ. G.GreinerA. R.GnagyE. M.PelhamW. E.IIICoxeS.VerleyJ.BhatiaI.HartK. (2016). Treatment sequencing for childhood ADHD: A multiple-randomization study of adaptive medication and behavioral interventions. Journal of Clinical Child & Adolescent Psychology, 45(4), 396–415. https://doi.org/10.1080/15374416.2015.1105138
25.
SeewaldN. J.KidwellK. M.Nahum-ShaniI.WuT.McKayJ. R.AlmirallD. (2020). Sample size considerations for comparing dynamic treatment regimens in a sequential multiple-assignment randomized trial with a continuous longitudinal outcome. Statistical Methods in Medical Research, 29(7), 1891–1912. https://doi.org/10.1177/0962280219877520
26.
SnowR. E. (1991). Aptitude-treatment interaction as a framework for research on individual differences in psychotherapy. Journal of Consulting and Clinical Psychology, 59(2), 205–216. https://doi.org/10.1037/0022-006X.59.2.205
StrainP. S. (2018). Personal thoughts on early childhood special education research: An historical perspective, threats to relevance, and call to action. Journal of Early Intervention, 40(2), 107–116. https://doi.org/10.1177/1053815117750411
29.
WangM.LamY. (2017). Evidence-based practice in special education and cultural adaptations: Challenges and implications for research. Research and Practice for Persons with Severe Disabilities, 42(1), 53–61. https://doi.org/10.1177/1540796916685872
