Skip to main content
SpringerLink
Log in

Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research

  • Original Research
  • Published:
Translational Behavioral Medicine

Abstract

The management of many health disorders often entails a sequential, individualized approach whereby treatment is adapted and readapted over time in response to the specific needs and evolving status of the individual. Adaptive interventions provide one way to operationalize the strategies (e.g., continue, augment, switch, step-down) leading to individualized sequences of treatment. Often, a wide variety of critical questions must be answered when developing a high-quality adaptive intervention. Yet, there is often insufficient empirical evidence or theoretical basis to address these questions. The Sequential Multiple Assignment Randomized Trial (SMART)—a type of research design—was developed explicitly for the purpose of building optimal adaptive interventions by providing answers to such questions. Despite increasing popularity, SMARTs remain relatively new to intervention scientists. This manuscript provides an introduction to adaptive interventions and SMARTs. We discuss SMART design considerations, including common primary and secondary aims. For illustration, we discuss the development of an adaptive intervention for optimizing weight loss among adult individuals who are overweight.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig 1
Fig 2
Fig 3

Similar content being viewed by others

References

  1. Murphy SA, Lynch KG, Olsin D, et al. Developing adaptive treatment strategies in substance abuse research. Drug Alcohol Depend. 2007; 88(2): S24-S30.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Lavori PW, Dawson R. Adaptive treatment strategies in chronic disease. Annu Rev Med. 2008; 59: 443p-453p.

    Article  Google Scholar 

  3. Middleton KM, Patidar SM, Perri MG. The impact of extended care on the long-term maintenance of weight loss: a systematic review and meta-analysis. Obes Rev. 2012; 13(6): 509-517.

    Article  PubMed  Google Scholar 

  4. Butryn ML, Webb V, Wadden TA. Behavioral treatment of obesity. Psychiatric Clin North Am. 2011; 34(4): 841-859.

    Article  Google Scholar 

  5. Rock CL, Flatt SW, Sherwood NE, et al. Effect of a free prepared meal and incentivized weight loss program on weight loss and weight loss maintenance in obese and overweight women: a randomized controlled trial. JAMA. 2010; 304(16): 1803-1810.

    Article  PubMed  CAS  Google Scholar 

  6. Jeffrey RW, Drewnowski A, Epstein LH, et al. Long-term maintenance of weight loss: current status. Health Psychol. 2000; 19(1): 5-16.

    Article  Google Scholar 

  7. Tate DF, Jeffery RW, Sherwood NE, et al. Long-term weight losses associated with prescription of higher physical activity goals. Are higher levels of physical activity protective against weight regain? Am J Clin Nutr. 2007; 85(4): 954-959.

    PubMed  CAS  Google Scholar 

  8. Waleekhachonloet OA, Limwattananon C, Limwattananon S, et al. Group behavior therapy versus individual behavior therapy for healthy dieting and weight control management in overweight and obese women living in rural community. Obes Res Clin Pract. 2007; 1(4): 223-232.

    Article  PubMed  Google Scholar 

  9. Makris A, Foster GD. Dietary approaches to the treatment of obesity. Psychiatr Clin North Am. 2011; 34(4): 813-827.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Wing RR, Jeffery RW. Food provision as a strategy to promote weight loss. Obes Res. 2001; 9(4): 271S-275S.

    Article  PubMed  Google Scholar 

  11. The Diabetes Prevention Program (DPP): description of lifestyle intervention. Diabetes Care. 2002; 25(12): 2165–2171.

  12. Ryan DH, Espeland MA, Foster GD, et al. Look AHEAD (Action for Health in Diabetes): design and methods for a clinical trial of weight loss for the prevention of cardiovascular disease in type 2 diabetes. Control Clin Trials. 2003; 24(5): 610-628.

    Article  PubMed  Google Scholar 

  13. Jeffery RW, Wing RR, Sherwood NE, et al. Physical activity and weight loss: does prescribing higher physical activity goals improve outcome? Am J Clin Nutr. 2003; 78(4): 669-670.

    Google Scholar 

  14. Levy RL, Jeffery RW, Langer SL, et al. Maintenance-tailored therapy vs. standard behavior therapy for 30-month maintenance of weight loss. Prev Med. 2010; 51(6): 457-459.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Knowler WC, Barrett-Connor E, Fowler SE, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002; 346: 393-403.

    Article  PubMed  CAS  Google Scholar 

  16. Nackers LM, Ross KM, Perri MG. The association between rate of initial weight loss and long-term success in obesity treatment: does slow and steady win the race? Int J Behav Med. 2010; 17(3): 161-167.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Murphy SA, Bingham D. Screening experiments for developing dynamic treatment regimes. J Am Stat Assoc. 2009; 184: 391-408.

    Article  Google Scholar 

  18. Lavori PW, Dawson R. A design for testing clinical strategies: biased adaptive within-subject randomization. J R Statist Soc A. 2000; 163: 29-38.

    Article  Google Scholar 

  19. Lavori PW, Dawson R. Dynamic treatment regimes: practical design considerations. Clin Trials. 2004; 1: 9-20.

    Article  PubMed  Google Scholar 

  20. Murphy SA. An experimental design for the development of adaptive treatment strategies. Stat Med. 2005; 24: 1455-1481.

    Article  PubMed  CAS  Google Scholar 

  21. Nahum-Shani I, Qian M, Almirall D, et al. Experimental design and primary data analysis methods for comparing adaptive interventions. Psychol Methods. 2012; 17(4): 457-477.

    Article  PubMed  Google Scholar 

  22. Nahum-Shani I, Qian M, Almirall D, et al. Q-Learning: a data analysis method for constructing adaptive interventions. Psychol Methods. 2013; 2012; 17(4): 478–94.

  23. Lei H, Nahum-Shani I, Lynch K, et al. A “SMART” design for building individualized treatment sequences. Annu Rev Clin Psychol. 2012; 8: 21-48.

    Article  PubMed  CAS  Google Scholar 

  24. Voils CI, Chang Y, Crandell J, et al. Informing the dosing of interventions in randomized trials. Contemp Clin Trials. 2012; 33: 1225-1230.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Murphy SA. Optimal dynamic treatment regimes. J R Stat Soc Series B. 2003; 65: 331-355.

    Article  Google Scholar 

  26. van der Laan MJ, Petersen ML. History-adjusted marginal structural models and statically-optimal dynamic treatment regimes. UC Berkeley Division of Biostatistics Working Paper Series. 2004; 158. http://www.bepress.com/ucbbiostat/paper158.

  27. Wahed AS, Tsiatis AA. Optimal estimator for the survival distribution and related quantities for treatment policies in two-stage randomization designs in clinical trials. Biometrics. 2004; 60: 124-133.

    Article  PubMed  Google Scholar 

  28. Hernán MA, Lanoy E, Costagliola D, et al. Comparison of dynamic treatment regimes via inverse probability weighting. Basic Clin Pharmacol Toxicol. 2006; 98: 237-242.

    Article  PubMed  Google Scholar 

  29. Moodie EEM, Richardson TS, Stephens DA. Demystifying optimal dynamic treatment regimes. Biometrics. 2007; 63: 447-455.

    Article  PubMed  CAS  Google Scholar 

  30. Bembon O, van der Laan MJ. Analyzing sequentially randomized trials based on causal effect models for realistic individualized treatment rules. Stat Med. 2008; 27(19): 3689-3716.

    Article  Google Scholar 

  31. Murphy SA, Almirall D. Dynamic treatment regimens. In: Kattan MW, ed. Encyclopedia of Medical Decision Making. Thousand Oaks: Sage Publications; 2009.

    Google Scholar 

  32. Chakraborty B, Murphy SA, Strecher V. Inference for non-regular parameters in optimal dynamic treatment regimes. Stat Methods Med Res. 2010; 19(3): 317-343.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Orellana L, Rotnitzky A, Robins JM. Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part I: Main Content. Int J Biostat. 2010; 6(2): Article No. 8.

  34. Orellana L, Rotnitzky A, Robins JM. Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, part ii: proofs of results. Int J Biostat. 2010;6(2):Article No. 9.

  35. Cain LE, Robins JM, Lanoy E, Logan R, Costagliola D, Hernán MA. When to start treatment? A systematic approach to the comparison of dynamic regimes using observational data. Int J Biostat. 2010; 6(2): Article No. 18.

  36. Wang L, Rotnitzky A, Lin X, et al. Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer. J Am Stat Assoc. 2012; 107(498): 493-508.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Laber E, Lizotte D, Qian M, Pelham W, and Murphy SA. Statistical inference in dynamic treatment regimes. Unpublished.

  38. Almirall D, Compton SN, Rynn MA, et al. SMARTer discontinuation trials: with application to the treatment of anxious youth. J Child Adolesc Psychopharmacol. 2012; 22(5): 364-374.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Dawson R, Lavori PW. Placebo-free designs for evaluating new mental health treatments: the use of adaptive treatment strategies. Stat Med. 2004; 23(21): 3249-3262.

    Article  PubMed  Google Scholar 

  40. Wilson GT, Vitousek KM, Loeb KL. Stepped care treatment for eating disorders. J Consult Clin Psychol. 2000; 68(4): 564-572.

    Article  PubMed  CAS  Google Scholar 

  41. Carels RA, Darby L, Cacciapaglia HM, et al. Applying a stepped-care approach to the treatment of obesity. J Psychosom Res. 2005; 59(6): 375-383.

    Article  PubMed  Google Scholar 

  42. Carels RA, Young KM, Coit CB, et al. The failure of therapist assistance and stepped-care to improve weight loss outcomes. Obesity. 2008; 16(6): 1460-1462.

    Article  PubMed  Google Scholar 

  43. Carels RA, Wott CB, Young KM, et al. Successful weight loss with self-help. J Behav Med. 2009; 32(6): 503-509.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Jakicic JM, Tate DF, Lang W, et al. Effect of a stepped-care intervention approach on weight loss in adults. JAMA. 2012; 307(24): 2617-2626.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  45. McKellar J, Austin J, Moos R. Building the first step: a review of low-intensity interventions for stepped care. Add Sci Clin Pract. 2012; 7(1): 26.

    Article  Google Scholar 

  46. Strecher VJ, Shiffman S, West R. Randomized controlled trial of a web-based computer-tailored smoking cessation program as a supplement to nicotine patch therapy. Addiction. 2005; 100(5): 682-688.

    Article  PubMed  Google Scholar 

  47. Hayes SC, Luoma J, Bond F, et al. Acceptance and commitment therapy: model, processes, and outcomes. Behav Res Ther. 2006; 44(1): 1-25.

    Article  PubMed  Google Scholar 

  48. Lillis J, Hayes SC, Bunting K, et al. Teaching acceptance and mindfulness to improve the lives of the obese: a preliminary test of a theoretical model. Ann Behav Med. 2009; 37: 58-69.

    Article  PubMed  Google Scholar 

  49. Lillis J, Hayes SC, Levin ME. Binge eating and weight control: the role of experiential avoidance. Behav Modif. 2011; 35(3): 252-264.

    Article  PubMed  Google Scholar 

  50. De Zwaan M, Mitchell J, Seim HC, et al. Eating related and general psychopathology in obese females with binge-eating disorder. Int J Eat Disord. 1994; 15: 43-52.

    Article  PubMed  Google Scholar 

  51. Forman EM, Butryn ML, Juarascio AS, et al. The mind your health project: a randomized controlled trial of an innovative behavioral treatment for obesity. Obesity. 2013; 21(6): 1119-1126.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  52. Thall P, Logothetis C, Pagliaro L, et al. Adaptive therapy for androgen-independent prostate cancer: a randomized selection trial of four regimens. J Natl Cancer Inst. 2007; 99(21): 1613-1622.

    Article  PubMed  CAS  Google Scholar 

  53. Almirall D, Lizotte D, Murphy SA. SMART design issues and the consideration of opposing outcomes. J Am Stat Assoc. 2012; 107(498): 509-512.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Lieberman JA, Stroup TS, McEvoy JP, et al. Effectiveness of antipsychotic drugs in patients with chronic schizophrenia. N Engl J Med. 2005; 353: 1209-1223.

    Article  PubMed  CAS  Google Scholar 

  55. The Methodology Center. Projects using SMART. Available at http://methodology.psu.edu/ra/adap-treat-strat/projects. Accessibility verified December 31, 2013.

  56. Wing RR, Jeffery RW, Burton LR, et al. Food provision vs structured meal plans in the behavioral treatment of obesity. Int J Obes Relat Metab Disord. 1996; 20(1): 56-62.

    PubMed  CAS  Google Scholar 

  57. Heymsfield SB, van Mierlo CA, van der Knaap HC, et al. Weight management using a meal replacement strategy: meta and pooling analysis from six studies. Int J Obes Relat Metab Disord. 2003; 27(5): 537-549.

    Article  PubMed  CAS  Google Scholar 

  58. Forman EM, Hoffman KL, McGrath KB, et al. A comparison of acceptance- and control-based strategies for coping with food cravings: an analog study. Behav Res Ther. 2007; 45(10): 2372-2386.

    Article  PubMed  Google Scholar 

  59. Lillis J, Hayes SC, Bunting K, et al. Teaching acceptance and mindfulness to improve the lives of the obese: a preliminary test of a theoretical model. Ann Behav Med. 2009; 37(1): 58-69.

    Article  PubMed  Google Scholar 

  60. Forman EM, Butryn M, Hoffman KL, et al. An open trial of an acceptance-based behavioral treatment for weight loss. Cogn Behav Pract. 2009; 16: 223-235.

    Article  Google Scholar 

  61. Juarascio A, Shaw J, Forman E, et al. Acceptance and commitment therapy as a novel treatment for eating disorders: an initial test of efficacy and mediation. Behav Modif. 2013; 37(4): 459-489.

    Article  PubMed  Google Scholar 

  62. Forman EM, Hoffman KL, Juarascio AS, et al. Comparison of acceptance-based and standard cognitive-based coping strategies for craving sweets in overweight and obese women. Eat Behav. 2013; 14(1): 64-68.

    Article  PubMed  Google Scholar 

  63. Oetting AI, Levy JA, Weiss RD, et al. Statistical Methodology for a SMART Design in the development of adaptive treatment strategies. In: Shrout PE, Keyes KM, Ornstein K, eds. Causality and Psychopathology: Finding the Determinants of Disorders and their Cures. Arlington: American Psychiatric Publishing, Inc; 2011: 179-205.

    Google Scholar 

  64. Verbeke G, Molenberghs G. Linear Mixed Models for Longitudinal Data. New York: Springer; 2001.

    Google Scholar 

  65. Chakraborty B, Collins LM, Strecher V, et al. Developing multicomponent interventions using fractional factorial designs. Stat Med. 2009; 28: 2687-2708.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Collins LM, Baker TB, Mermelstein RJ, et al. The multiphase optimization strategy for engineering effective tobacco use interventions. Ann Behav Med. 2011; 41: 208-226.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Collins LM, Chakraborty B, Murphy SA, et al. Comparison of a phased experimental approach and a single randomized clinical trial for developing multicomponent behavioral interventions. Clin Trials. 2009; 6(1): 5-15.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Robins JM, Orellana L, Rotnitzky A. Estimation and extrapolation in optimal treatment and testing strategies. Stat Med. 2008; 27: 4678-4721.

    Article  PubMed  Google Scholar 

  69. Kraemer H, Stice E, Kazdin A, et al. How do risk factors work together? Mediators, moderators, and independent, overlapping, and proxy risk factors. Am J Psychiatry. 2001; 158(6): 848-856.

    Article  PubMed  CAS  Google Scholar 

  70. Kraemer H, Wilson G, Fairburn C. Mediators and moderators of treatment effects in randomized clinical trials. Arch Gen Psychiatry. 2002; 59: 877-883.

    Article  PubMed  Google Scholar 

  71. Kraemer H, Frank E, Kupfer D. Moderators of treatment outcomes. JAMA. 2006; 296(10): 1286-1288.

    Article  PubMed  CAS  Google Scholar 

  72. MacKinnon DP, Luecken LJ. How and for whom? Mediation and moderation in health psychology. Health Psychol. 2008; 27(2): S99.

    Article  PubMed  PubMed Central  Google Scholar 

  73. PROC QLEARN [Software] (2012). The Methodology Center, Penn State University. Available at http://methodology.psu.edu/downloads/procqlearn. Accessibility verified December 31, 2013.

  74. Ertefaie A, Almirall D, Huang L, Dziak JJ, Wagner AT, Murphy SA. SAS PROC QLEARN user’s guide. University Park: The Methodology Center, Penn State University.

  75. Piantadosi S. Clinical Trials: A Methodologic Perspective. 2nd ed. Hoboken: Wiley; 2005.

    Book  Google Scholar 

  76. Cohen J. Statistical Power Analysis For The Behavioral Sciences. 2nd ed. Hillsdale: Erlbaum; 1988.

    Google Scholar 

  77. The Methodology Center. Projects using SMART sample size calculator for continuous outcomes. Available at http://methodology.psu.edu/downloads. Accessibility verified December 31, 2013.

  78. Buyze J, Rompaye BV, Goetghebeur E. Designing a sequentially randomized study with adherence enhancing interventions for diabetic patients. Stat Med. 2010; 29: 1114-1126.

    PubMed  Google Scholar 

  79. Svetkey LP, Stevens VJ, Brantley PJ, et al. Comparison of strategies for sustaining weight loss: the weight loss maintenance randomized controlled trial. JAMA. 2008; 299: 1139-1148.

    Article  PubMed  CAS  Google Scholar 

  80. Almirall D, Compton SN, Gunlicks-Stoessel M, et al. Preparing for a sequential multiple assignment randomized trial for developing an adaptive treatment strategy: designing a SMART pilot study. Stat Med. 2012; 31(17): 1887-1902.

    Article  PubMed  PubMed Central  Google Scholar 

  81. The Methodology Center. are adaptive interventions Bayesian? Available at http://methodology.psu.edu/eresources/ask/sp11. Accessibility verified December 31, 2013.

  82. Berry SM, Carlin BP, Lee JJ, et al. Bayesian adaptive methods for clinical trials. Boca Raton: CRC Press; 2011.

    Google Scholar 

Download references

Acknowledgments

The development of this article was funded by the following grants from the National Institutes of Health: P50DA010075 (Murphy, Almirall), R03MH09795401 (Almirall), RC4MH092722 (Almirall), P30DK092924 (Sherwood), and P30DK050456 (Sherwood).

Author information

Authors and Affiliations

  1. 214NU Institute for Social Research, University of Michigan, 426 Thompson Street, Ann Arbor, MI, 48104-2321, USA

    Daniel Almirall & Inbal Nahum-Shani

  2. HealthPartners Institute for Education and Research, Minneapolis, USA

    Nancy E. Sherwood

  3. Department of Statistics and Institute for Social Research, University of Michigan, Ann Arbor, USA

    Susan A. Murphy

Authors
  1. Daniel Almirall
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Inbal Nahum-Shani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nancy E. Sherwood
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Susan A. Murphy
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Daniel Almirall.

Additional information

Implications

Practice: Adaptive interventions provide clinical practitioners with a guide to the type of sequential, individualized decision-making that is necessary for the care or management of many health disorders.

Research: Behavioral interventions researchers who are interested in empirically developing high-quality adaptive interventions should consider Sequential Multiple Assignment Randomized Trials (SMART) as part of their methodological toolbox.

Policy: For more efficient use of health research resources, funding agencies should support the use of SMART for developing and discovering adaptive interventions prior to their evaluation in a randomized clinical trial.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Almirall, D., Nahum-Shani, I., Sherwood, N.E. et al. Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research. Behav. Med. Pract. Policy Res. 4, 260–274 (2014). https://doi.org/10.1007/s13142-014-0265-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13142-014-0265-0

KEYWORDS

Search

Navigation