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Cited by 460Statistical Methods in Clinical TrialsAdvanced Causal Inference TechniquesHealth Policy Implementation Science

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

Open access
Almirall, Daniel, Nahum-Shani, Inbal, Sherwood, Nancy E., Murphy, Susan A.·2014·Translational Behavioral Medicine
DOI 10.1007/s13142-014-0265-0PMC PMC4167891
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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.

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Crossref · 10.1007/s13142-014-0265-0

Cites

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Claims the paper makes

0 of 50 cited sources checked · 0 supported · 0 flagged

  • Findingreasoning

    Nonresponders are underrepresented in the data by design for second-stage treatment offerings.

    “in terms of second-stage treatment offerings, nonresponders are underrepresented in the data; this underrepresentation occurs by design.”
    Quote in the paperSubstantial claim
  • Findingreasoning

    The four embedded AIs in Table 2 use response/nonresponse after initial IBT as their sole tailoring variable.

    “the four AIs in Table 2 employ this intermediate tailoring variable as the sole tailoring variable.”
    Quote in the paperSubstantial claim
  • Findingcitation

    For the first-stage main effect, under a within-person correlation of 0.50 and 10% dropout, N=122 (61 per arm) is required to detect d=0.5 with 85% power and 5% type-I error.

    “Therefore, assuming a within-person correlation of 0.50 in longitudinal weight, and a study drop-out rate of 10 %, a total sample size of at least N=122 (i.e., 61 in group A+B+C vs 61 in group D+E+F) would be needed in order to detect a medium effect size [58] (Cohen's d=0.5) with at least 85 % power and type-I error of 5 %.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [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. source

      Not checked in the free run.

  • Findingreasoning

    Assuming a nonresponse rate of 0.60 and other assumptions same, total N=204 (102 per initial group; 61 per second-stage group) is required.

    “Assuming a nonresponse rate of 0.60 to initial IBT, and keeping all other assumptions the same as above, would require a total sample size of at least N=204=122/0.6;that is, 204/2=102 in group A+B+C vs 102 in group D+E+F, which implies 102×0.6=61 in group B+E vs 61 in group C+F.”
    Quote in the paperNot a substantial claim
  • Study design and conductreasoning

    Weighted regression is used to account for nonresponder underrepresentation, assigning nonresponders weight 4 and responders weight 2.

    “To account for this imbalance (i.e., to account for the underrepresentation of nonresponders), weighted regression is employed, whereby nonresponders are assigned a weight of 4 and responders are assigned a weight of 2.”
    Quote in the paperSubstantial claim
  • May combine two claims. 20
  • Classified as probably not a substantial claim. 34

  • May combine two claims.

    Findingreasoning

    The four embedded AIs do not individualize initial IBT duration and do not use additional heterogeneity among nonresponders to choose between IBT+MR and ACT.

    “these four AIs do not (i) individualize initial IBT duration (first-stage treatment), and they (ii) do not take advantage of additional heterogeneity within the nonresponders to further individualize the choice of IBT+MR vs ACT.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning

    In a SMART, nonresponders are randomized twice and responders once, so nonresponders have a 1/4 chance and responders a 1/2 chance of following the offered treatment sequence.

    “by design-i.e., nonresponders are randomized twice whereas responders are randomized only once-nonresponders would have a 1/4 chance of following the sequence of treatments they were offered, whereas responders would have a 1/2 chance of following the sequence of treatments they were offered.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingreasoning

    In the example SMART, AI #1 and AI #4 are the two most distinct embedded adaptive interventions in terms of first-stage treatment duration and second-stage treatment (augment versus switch).

    “These two AIs, for example, represent the two most distinct AIs in this SMART in terms of first-stage treatment duration and second-stage treatment (i.e., an augment versus a switch)”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingreasoning

    A variation of the SMART in Fig. 2 concerns whether the decision to provide 5 versus 10 weeks of initial IBT occurs at baseline or after initial IBT but before 10 weeks.

    “An interesting variation of the SMART shown in Fig. 2 centers on whether the decision to provide 5 vs 10 weeks of initial IBT occurs at baseline or whether this decision occurs at some point after initial IBT (but prior to 10 weeks).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Individuals differ in how much they respond to or adhere to weight loss treatment, in their side effect profiles, and in how quickly they respond (between-persons heterogeneity).

    “In addition, not all individuals will respond or adhere to the weight loss treatment to the same degree, have the same side effect profile (e.g., in the case of weight loss medications), or respond within the same time-frame, to any given treatment or package of treatments (between-persons heterogeneity; [5,6].”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [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. source

      Not checked in the free run.

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

      Not checked in the free run.

  • May combine two claims.

    Premisereasoning

    The example SMART systematically varies two first-stage options against two second-stage options for nonresponders, producing four experimental groups that correspond to four embedded AIs.

    “Since the example SMART experimentally”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation

    After estimating mean outcome and standard error for each embedded AI, one can test hypotheses comparing two or more AIs or identify the AI with greatest estimated weight loss.

    “Once the mean outcome and standard error is estimated for each of the embedded AIs, it is possible to conduct a hypothesis test to compare any two (or more) of the embedded AIs, or identify the AI leading to the greatest estimated weight loss [63].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [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.

      Not checked in the free run.

  • May combine two claims.

    Interpretationcitation

    Although ACT may not produce superior average weight losses compared with more traditional interventions, it may be particularly effective for individuals with higher levels of negative affect, making it a suitable second-stage treatment option for nonresponders.

    “Although ACT may not produce superior weight losses on average compared to more traditional interventions, ACT may be particularly effective for certain types of individuals, specifically, those who experience higher levels of negative affect, and may, therefore, be a suitable second-stage treatment option for nonresponders.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    In oncology, SMART has been applied to create medication algorithms for prostate cancer.

    “For example, SMART has been used in oncology to develop medication algorithms to treat prostate cancer [36,52,53].”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [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. source

      Not checked in the free run.

    • cites [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. source

      Not checked in the free run.

    • cites [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. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisenone given

    The adaptive interventions embedded in a SMART do not themselves involve randomization.

    “Note that the AIs themselves do not involve randomization.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Even though IBT is generally successful, many individuals fail to achieve a clinically meaningful weight loss (e.g., ≥7% over 26 weeks) or reach their weight-loss targets.

    “Despite the general success of interventions such as IBT (and others [7,[10][11][12][13][14]), a significant number of individuals do not lose a clinically significant amount of weight (for example, ≥7 % weight loss in a 26week period (~6 months) [15]) or meet their targeted goals for weight loss.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [7,[10][11][12][13][14]

      Not checked in the free run.

    • cites [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. source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    Comparing AI #1 and AI #4 allows investigators to examine whether it is better to be stringent about achieving response during IBT and augment if nonresponsive, or to be less stringent and switch to an alternative if still nonresponsive.

    “That is, such a comparison permits investigators to examine whether it is better to be more stringent about achieving response during IBT and, if not responsive, augment IBT versus whether it is better to be less stringent about achieving response during IBT and, if still not responsive, give up on IBT and try an alternative.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    The second main effect analysis compares weight change between nonresponders randomized to augmented IBT+MR versus switch to ACT.

    “This analysis compares change in weight loss between all nonresponders randomly assigned to augmented IBT+MR (subgroups B+E) versus all nonresponders randomly assigned to switch to ACT (subgroups C + F).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    The 5-lb nonresponse cutoff comes from prior research and clinical experience indicating that a loss below 5 lbs by week 5 of behavioral therapy predicts inadequate longer-term weight loss (<5-10% of body weight at 26 weeks) and thus a need to change or augment treatment.

    “In this example, the 5 lbs cutoff is based on previous research [16], which is corroborated by clinical experience, suggesting that weight loss of less than 5 lbs during the first 5 weeks of behavioral therapy treatment is associated with longer-term insufficient weight loss (<5-10 % of body weight at the end of 26 weeks), thereby indicating a need for subsequent (changes or”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [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. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisereasoning

    The optimization aim is less confirmatory and more hypothesis generating, akin to identifying moderators in a standard RCT, and is rarely chosen as primary; investigators often choose it as a third aim.

    “The optimization aim is less confirmatory (more hypothesis generating)-it is akin to the aim of identifying moderators in a standard RCT.For this reason, the optimization aim is rarely chosen as primary; in a SMART, investigators often choose the optimization aim as a third aim.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisenone given

    In a SMART, the primary aim is often a main effect aim or an embedded adaptive interventions aim.

    “Among these, the primary aim in a SMART is often one of the main effect aims or embedded AIs aim.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Replication is necessary because responders to short initial IBT are consistent with AIs #1 and #2, and responders to long initial IBT are consistent with AIs #3 and #4.

    “responders to initial short duration IBT (subgroup A; see Table 2 and Fig. 2) are consistent with AIs # 1 (A+B) and # 2 (A+C); and, similarly, responders to initial long duration IBT (subgroup D) are consistent with AIs # 3 (D+E) and # 4 (D+F).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Across behavioral and clinical sciences, many SMART designs have been conducted or are underway to build adaptive interventions.

    “Across a wide-range of the behavioral and clinical sciences, a wide variety of SMART designs has been conducted, or is currently being conducted, to build adaptive interventions.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Lei et al. describe the rationale and scientific questions of four SMART studies in autism, ADHD, and substance use disorders.

    “Lei et al. [23] describe the rationale and scientific questions addressed by four different SMART studies either recently completed or underway in autism, attention-deficit/hyperactivity disorder (ADHD), and for various substance use disorders.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [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. source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    SMART was developed explicitly to build empirically supported adaptive interventions and is meant to complement theoretical models and expert clinical consensus.

    “Developed explicitly for the purpose of building empirically supported adaptive interventions, they are meant to complement the use of theoretical models and expert clinical consensus for developing optimal adaptive interventions [21][22][23].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [21][22][23]

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  • May combine two claims.

    Interpretationreasoning

    The first main effect analysis is a single-factor analysis with two levels (short versus long initial IBT duration) and is identical to a two-arm longitudinal RCT analysis.

    “This is a single factor (initial IBT duration) analysis where the factor has two levels (short vs long duration).This analysis is identical to the analysis used to analyze data arising from a two-arm, longitudinal randomized clinical trial (RCT).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisenone given

    Weight loss is commonly the primary outcome in weight-loss studies, while quality of life and cost-effectiveness are often secondary outcomes.

    “In weight loss research, the primary outcome is often weight loss, and secondary outcomes may include quality of life or cost-effectiveness outcomes.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    An expanding literature indicates that ACT might help with weight management or weight loss.

    “A growing body of literature suggests that ACT may be useful for managing or losing weight [48][49][50].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [48][49][50]

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  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationreasoning

    The ranking operationalization seeks to identify the best-performing AI, unlike the first operationalization, which compares two or more AIs with a statistical hypothesis test.

    “Since this operationalization of the aim seeks to identify the best performing AI, it differs from the first operationalization, which aims to compare two (or more) AIs using a statistical hypothesis test.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Premisenone given

    High heterogeneity in treatment response is often present for chronic disorders, for conditions without widely effective treatment, or for conditions with effective treatments that are burdensome, costly, or have side effects.

    “This is often the case for many chronic disorders, conditions for which there is no widely effective treatment, or conditions for which there are widely effective treatments but they are burdensome, costly, or carry side effects.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    This examination would be part of the optimization aim analysis.

    “This examination would be part of the optimization aim analysis.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisereasoning

    Adaptive interventions, the target of SMART construction, are multicomponent interventions.

    “AIs, which SMARTs aim to construct, are multicomponent interventions (e.g., different components may be provided at different time points to different individuals);”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisenone given

    Moderator analyses with RCT data are often used to determine whether identified moderators are also baseline tailoring variables.

    “Such analyses are often also used with RCT data to determine whether the identified moderators are also baseline tailoring variables.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisenone given

    Two types of aims often serve as primary aims in a SMART: main effect aims and the embedded AIs aim.

    “Above, we have identified two types of aims that often serve as primary aims in a SMART: main effect aims and the embedded AIs aim.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationnone given

    The ideas in the manuscript extend readily to adaptive interventions spanning acute and maintenance phases or any phases/sequences of care.

    “Indeed, the ideas in this manuscript extend readily to this type of application, and within or between any phases/sequences of care.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Misconceptions about SMART arise when the term 'adaptive design' is used to describe SMARTs because the phrase is not sufficiently precise.

    “Misconceptions about SMART also arise when the term “adaptive design” is used to describe SMARTs because the phrase is not sufficiently precise [81].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [81] The Methodology Center. are adaptive interventions Bayesian? Available at http://methodology.psu.edu/eresources/ask/sp11 . Accessibility verified December 31, 2013.

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Q-Learning is a data analysis method useful for optimizing an AI while exploring candidate tailoring variables.

    “is a data analysis method useful for optimizing the AI while exploring candidate tailoring variables [22].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [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.

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    The third Q-Learning step examines candidate baseline tailoring variables of first-stage treatment while accounting for a future optimal decision.

    “The purpose of this final regression is to examine candidate baseline tailoring variables (e.g., emotional/binge eating or level of severity at baseline) of first-stage treatment while taking into account the fact that a future optimal decision has been made.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    To avoid information bias, measures used to determine response or nonresponse should not be used to address research aims.

    “To avoid information bias, these measures would not be used to address the research aims.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    In the Fig. 3 variation, the 5- versus 10-week decision occurs at week 5, which allows more opportunity to develop a more deeply tailored AI.

    “On the other hand, since in the latter design the decision concerning 5 vs 10 weeks of initial IBT occurs at week 5, this permits greater opportunity for developing a more deeply-tailored AI.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    Stratified random allocation is used to control potential bias from chance imbalances in treatment groups on key prognostic factors.

    “this is used to control potential bias due to chance imbalances in treatment groups on key prognostic factors.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Once those choices were made, the investigators compared the adaptive intervention with a standard behavioral weight-loss intervention in a two-arm RCT.

    “After these decisions were made, the investigators evaluated this adaptive intervention versus a standard behavioral weight loss intervention using a 2-arm RCT.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [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. source

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Premisenone given

    A SMART's main purpose is to build a high-quality adaptive intervention from data, while an RCT's main purpose is to test an already-developed intervention against a control.

    “Whereas the overarching aim of a SMART is to construct a high-quality adaptive intervention based on data, the overarching aim of an RCT is to evaluate an already-developed intervention versus a suitable control.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisenone given

    SMART studies are used to develop adaptive interventions.

    “SMART studies are used to develop “adaptive interventions”.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    An RCT is useful when investigators already have the theoretical basis and empirical evidence needed to construct the best/optimal adaptive intervention and wish to test its effectiveness against a control.

    “That is, an RCT is highly useful when investigators already have the theoretical basis and empirical evidence necessary for constructing the best/optimal adaptive intervention, and they wish to test the effectiveness of this already-developed AI by comparing it to a suitable control.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Different SMART designs are suitable for addressing different types of scientific questions.

    “Different SMART designs are suitable for addressing different types of scientific questions [21,23].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [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. source

      Not checked in the free run.

    • cites [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. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisenone given

    Q-Learning generalizes moderated regression analysis to multiple stages of treatment.

    “Q-Learning is essentially a generalization of moderated regression analysis to multiple stages of treatment.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    Stratifying the second-stage randomization on intermediate outcomes is particularly attractive when first-stage nonadherence may predict second-stage treatment outcomes.

    “yet such stratification is particularly attractive when nonadherence in the first-stage (to IBT) may be prognostic of outcomes to the second-stage treatments.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    A 6-way ANCOVA comparing subgroups A-F may require large sample sizes but does not correspond to any primary aim described.

    “Such an analysis may, indeed, require large sample sizes; however, as we have discussed, such an analysis does not correspond to any of the primary aims described above.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Before the Jakicic study, the team chose the number and timing of decision stages, the single tailoring variable (weight loss), the treatment options, and the rules connecting weight loss to treatments at each step.

    “In developing this AI prior to study, decisions were made (i) about the total number of decision stages, including when and how often they would occur (i.e., there was a step every 3 months over 18 months), (ii) to use one tailoring variable (i.e., weight loss), (iii) about the treatment options (i.e., group sessions, behavioral lessons, 1 vs 2 sessions of telephone counseling, individual sessions”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [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. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given

    The first-stage treatment decision (5 versus 10 weeks) may also serve as a tailoring variable for the second-stage decision between IBT+MR and ACT.

    “Note that the first-stage treatment decision (5 vs 10 weeks initial treatment duration) may also serve as a tailoring variable for the decision to augment with IBT+MR vs switch to ACT.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation

    An alternative less conservative approach is to calculate sample size to contrast two or more embedded AIs by simulation.

    “An alternative, potentially less conservative approach, is to calculate the sample size to contrast two (or more) embedded adaptive interventions by simulation experiment [78].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [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. source

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    Up-front randomization allows stratified allocation only on baseline prognostic factors, while real-time randomization can use a wider range of prognostic factors.

    “the former approach only allows stratified random allocation based on baseline prognostic factors, whereas in the latter approach randomizations can make use of a wider variety of prognostic factors.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisereasoning

    A common misconception is that SMARTs require prohibitively large sample sizes.

    “A common misconception is that SMARTs require prohibitively large sample sizes.”
    Quote in the paperNot a substantial claim
49 of 49

  • The paper relies on this without support.

    Meal replacements are effective for weight loss partly because they remove the need to decide what food to prepare and the time and effort to prepare it, and they provide a clear method for portion control and reduced energy intake.

    “MR is effective for weight loss, in part, because it alleviates the need for decision-making regarding what food(s) to prepare as well as the time and effort needed to prepare the food.It provides a clear and unambiguous method for obtaining portion control and accompanying reduction in energy intake.”

  • The paper relies on this without support.

    Meal replacements and trained ACT psychotherapists are costly or limited in availability.

    “Due to the cost of meal replacements (MR) and the cost and availability of trained ACT psychotherapists”

  • The paper relies on this without support.

    ACT requires a time commitment from the individual that may be burdensome.

    “Furthermore, ACT requires a time commitment on the part of the individual, which may be burdensome.”

  • The paper relies on this without support.

    A subset of people may do well enough over time with IBT by itself.

    “These perspectives are important since some proportion of individuals might benefit adequately in the longterm from IBT alone.”

  • The paper relies on this without support.

    Creating a high-quality adaptive intervention usually demands answers to many critical questions, yet empirical evidence or theoretical grounding for those answers is frequently lacking.

    “Often, a wide variety of critical questions must be answered when developing a highquality adaptive intervention.Yet, there is often insufficient empirical evidence or theoretical basis to address these questions.”

  • The paper relies on this without support.

    Many behavioral intervention scientists are still unfamiliar with SMARTs.

    “Despite their increasing popularity due to their real-world clinical appeal, and their fit in research aimed at developing high-quality adaptive interventions, SMARTs remain relatively new to many behavioral intervention scientists.”

  • The paper relies on this without support.

    Most healthy dieting and weight-loss programs include IBT.

    “IBT is incorporated in most healthy dieting and weight loss interventions.”

  • The paper relies on this without support.

    Many investigators lack sufficient empirical evidence or theoretical basis to form a high-quality adaptive intervention.

    “in many other cases investigators have insufficient empirical evidence or theoretical basis to form a high-quality adaptive intervention.”

  • The paper relies on this without support.

    Investigators often face important open questions about optimal adaptive intervention design, such as the best first-stage treatment.

    “investigators often confront important open questions such as “What is the best first-stage treatment?””
9 of 9

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Figure 3 caption identifies itself as the baseline-randomization design

    Minor

    The caption calls Figure 3 a variation of the design in Figure 3, with the duration decision moved from baseline to week 5. The body instead identifies Figure 2 as the baseline-randomization design and Figure 3 as its variation.

1 of 1

Cites

Flagged first, then by citations

1 of the 88 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. 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. · DOI · Paper page

Cited by

Sorted by citations

Related

Authors
Almirall, D., Nahum-Shani, I., Sherwood, N. E., & Murphy, S. A.
Affiliations
  • University of Michigan (US)
  • HealthPartners (US)
Corresponding author
Almirall, Daniel
ORCID
Venue
Translational Behavioral Medicine
Publisher
Oxford University Press (OUP)
Published
2014-05-06
Volume
4
Issue
3
Pages
260-274
ISSN
  • 1613-9860 (ISSN-L)
  • 1869-6716
DOI
10.1007/s13142-014-0265-0
PMC
PMC4167891
OpenAlex
W1986546901
Cited by
453
References
88
Citations by year
2026: 35 · 2025: 50 · 2024: 49 · 2023: 37 · 2022: 49 · 2021: 44 · 2020: 45 · 2019: 47 · 2018: 26 · 2017: 27 · 2016: 30 · 2015: 11 · 2014: 2
FWCI
24.67
Type
journal article
Language
en
Open access
Locations
  • Translational Behavioral Medicine (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institutes of Health
  • National Institute of Mental Health (RC4MH092722, R03MH097954)
  • National Institute on Drug Abuse (P50DA010075)
  • National Institute of Diabetes and Digestive and Kidney Diseases (P30DK050456, P30DK092924)
  • National Institute of Biomedical Imaging and Bioengineering (U54EB020404)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
Keywords
adaptive interventions, sequential multiple assignment randomized trial, smart design, weight loss, overweight adults, personalized treatment, intervention development

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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