The DOI matches its Crossref record; 87 of the 88 references it cites were found in a registry or an index; 3 of the 50 sources its claims cite were checked for support.
Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research
Open accessAbstract
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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36 Not checked yet · 29 Own interpretation · 26 No basis given · 4 Own method · 1 Supported · 1 Supported so far
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“factorial designs (along with other approaches) are often used in the optimization stage of MOST to develop more potent interventions [65,67]”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
What the sources say
- Not checked yetcites [65] Chakraborty B, Collins LM, Strecher V, et al. Developing multicomponent interventions using fractional factorial designs. Stat Med. 2009; 28: 2687-2708. source
- Supportedcites [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. source
The Methods section (page not provided) uses a fractional factorial experiment in the phased approach’s screening phase to select intervention components, and describes a factorial experiment as one option in its refining phase. The Background (page not provided) describes screening and refining as steps intended to optimize multicomponent interventions. Together, these passages support the cited point that factorial designs are used in this optimization process, alongside other approaches. (LLM, conf=0.86)
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“in terms of second-stage treatment offerings, nonresponders are underrepresented in the data; this underrepresentation occurs by design.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Analysis associated with the embedded adaptive interventions aim
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In the paper
“the four AIs in Table 2 employ this intermediate tailoring variable as the sole tailoring variable.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Embedded adaptive interventions aim
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“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 %.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SAMPLE SIZE CONSIDERATIONS
What the sources say
- Not checked yetcites [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
hedgedn = 122- Asserted: passes — The authors put it forward as true.
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“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SAMPLE SIZE CONSIDERATIONS
hedgedn = 204- Asserted: passes — The authors put it forward as true.
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In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Analysis associated with the embedded adaptive interventions aim
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“Comparing the mean outcomes between the four AIs can be done using all of the data in one regression analysis.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Analysis associated with the embedded adaptive interventions aim
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In the paper
“The weights are inversely proportional to the probability of being offered a particular treatment sequence.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Analysis associated with the embedded adaptive interventions aim
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“Further, research suggests that it may be possible to identify such individuals early, i.e., during treatment [16].”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Abstract
What the sources say
- Not checked yetcites [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
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In the paper
“Data analyses associated with the aim to develop a more deeply-tailored AI are akin to, but go beyond, standard moderator analysis [69][70][71][72].”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Analysis associated with the embedded adaptive interventions aim
What the sources say
- Not checked yetcites [69][70][71]
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- Probably not a substantial claim. 34
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In the paper
“Different SMART designs are suitable for addressing different types of scientific questions [21,23].”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SAMPLE SIZE CONSIDERATIONS
What the sources say
- Supportedcites [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
The “Other Types of SMART Designs” section describes designs that differ in how intermediate outcomes and prior treatment determine re-randomization, and says investigators choose design features based on scientific evidence and ethical considerations. The “Sequential Multiple Assignment Randomized Trial” section identifies several kinds of research questions SMART data can address. Together, these passages support the paraphrase; page numbers are unavailable in our copy. (LLM, conf=0.90)
- Supportedcites [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
The “Comparison of SMART Studies” section says SMART designs vary in the primary research questions they are sized to address. It gives examples focused on first-stage options, second-stage options, and embedded adaptive interventions (page not supplied). (LLM, conf=0.93)
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In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Embedded adaptive interventions aim
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In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Analysis associated with the embedded adaptive interventions aim
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In the paper
“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)”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Embedded adaptive interventions aim
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In the paper
“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).”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SAMPLE SIZE CONSIDERATIONS
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In the paper
“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].”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Abstract
What the sources say
- Not checked yetcites [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 yetcites [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
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“Since the example SMART experimentally”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Embedded adaptive interventions aim
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In the paper
“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].”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Analysis associated with the embedded adaptive interventions aim
What the sources say
- Not checked yetcites [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.
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In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIALS
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In the paper
“For example, SMART has been used in oncology to develop medication algorithms to treat prostate cancer [36,52,53].”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIALS
What the sources say
- Not checked yetcites [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 yetcites [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 yetcites [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
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“Note that the AIs themselves do not involve randomization.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Embedded adaptive interventions aim
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Abstract
What the sources say
- Not checked yetcites [7,[10][11][12][13][14]
- Not checked yetcites [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
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Embedded adaptive interventions aim
plainconditional- Asserted: passes — The authors put it forward as true.
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In the paper
“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).”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > OVERVIEW OF DATA ANALYSES FOR THE COMMON SCIENTIFIC AIMS IN A SMART
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In the paper
“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”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > ADAPTIVE INTERVENTIONS
What the sources say
- Not checked yetcites [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
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > COMMON SCIENTIFIC AIMS IN A SMART
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In the paper
“Among these, the primary aim in a SMART is often one of the main effect aims or embedded AIs aim.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > COMMON SCIENTIFIC AIMS IN A SMART
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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).”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Analysis associated with the embedded adaptive interventions aim
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In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIALS
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In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIALS
What the sources say
- Not checked yetcites [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
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“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].”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Abstract
What the sources say
- Not checked yetcites [21][22][23]
plain- Asserted: passes — The authors put it forward as true.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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).”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > OVERVIEW OF DATA ANALYSES FOR THE COMMON SCIENTIFIC AIMS IN A SMART
plain- Asserted: passes — The authors put it forward as true.
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In weight loss research, the primary outcome is often weight loss, and secondary outcomes may include quality of life or cost-effectiveness outcomes.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > COMMON SCIENTIFIC AIMS IN A SMART
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In the paper
“A growing body of literature suggests that ACT may be useful for managing or losing weight [48][49][50].”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > ADAPTIVE INTERVENTIONS
What the sources say
- Not checked yetcites [48][49][50]
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In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Embedded adaptive interventions aim
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This examination would be part of the optimization aim analysis.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SAMPLE SIZE CONSIDERATIONS
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“AIs, which SMARTs aim to construct, are multicomponent interventions (e.g., different components may be provided at different time points to different individuals);”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Such analyses are often also used with RCT data to determine whether the identified moderators are also baseline tailoring variables.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > Analysis associated with the embedded adaptive interventions aim
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SAMPLE SIZE CONSIDERATIONS
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Indeed, the ideas in this manuscript extend readily to this type of application, and within or between any phases/sequences of care.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
In the paper
“Misconceptions about SMART also arise when the term “adaptive design” is used to describe SMARTs because the phrase is not sufficiently precise [81].”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
What the sources say
- Not checked yetcites [81] The Methodology Center. are adaptive interventions Bayesian? Available at http://methodology.psu.edu/eresources/ask/sp11 . Accessibility verified December 31, 2013.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“is a data analysis method useful for optimizing the AI while exploring candidate tailoring variables [22].”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > "Q-Learning
What the sources say
- Not checked yetcites [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.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > "Q-Learning
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“To avoid information bias, these measures would not be used to address the research aims.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SAMPLE SIZE CONSIDERATIONS
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“this is used to control potential bias due to chance imbalances in treatment groups on key prognostic factors.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“After these decisions were made, the investigators evaluated this adaptive intervention versus a standard behavioral weight loss intervention using a 2-arm RCT.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
What the sources say
- Not checked yetcites [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
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“SMART studies are used to develop “adaptive interventions”.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Q-Learning is essentially a generalization of moderated regression analysis to multiple stages of treatment.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > "Q-Learning
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“yet such stratification is particularly attractive when nonadherence in the first-stage (to IBT) may be prognostic of outcomes to the second-stage treatments.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SAMPLE SIZE CONSIDERATIONS
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“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”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
What the sources say
- Not checked yetcites [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
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > "Q-Learning
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“An alternative, potentially less conservative approach, is to calculate the sample size to contrast two (or more) embedded adaptive interventions by simulation experiment [78].”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SAMPLE SIZE CONSIDERATIONS
What the sources say
- Not checked yetcites [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
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“A common misconception is that SMARTs require prohibitively large sample sizes.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SAMPLE SIZE CONSIDERATIONS
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
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?””
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The adaptive intervention that a SMART design produces can be incorporated into clinical practice more naturally and seamlessly than the findings of a fixed-intervention study [53, 54, 62].”
From A Sequential Multiple Assignment Randomized Trial (SMART) study of medication and CBT sequencing in the treatment of pediatric anxiety disorders (2021) · cites this paper as [54]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“That analysis, however, does not correspond with our primary aims and hypotheses, which are tested as two main effects and their interaction, and which require a sample size considerably smaller than for a 6-way ANCOVA [54].”
From A Sequential Multiple Assignment Randomized Trial (SMART) study of medication and CBT sequencing in the treatment of pediatric anxiety disorders (2021) · cites this paper as [54]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“making them ideal for developing an adaptive intervention that optimizes outcomes based on patient treatment history [51–54].”
From A Sequential Multiple Assignment Randomized Trial (SMART) study of medication and CBT sequencing in the treatment of pediatric anxiety disorders (2021) · cites this paper as [54]
The cited source says what the claim attributes to it.
In the citing paper
“Findings of the sequential randomization aspect of the SMART design during treatment can inform clinician decisions about treatment sequencing based on the individual patient’s response to the intervention currently in use, further supporting personalized treatment [53, 54].”
From A Sequential Multiple Assignment Randomized Trial (SMART) study of medication and CBT sequencing in the treatment of pediatric anxiety disorders (2021) · cites this paper as [54]
The cited source says what the claim attributes to it.
In the citing paper
“SMART designs are commonly but incorrectly assumed to require prohibitively large sample sizes [54].”
From A Sequential Multiple Assignment Randomized Trial (SMART) study of medication and CBT sequencing in the treatment of pediatric anxiety disorders (2021) · cites this paper as [54]
In the citing paper
“The experimental approaches used for optimization include full or fractional factorial experiments 38, 39, the sequential multiple-assignment randomized trial (SMART), 40 and system identification techniques 41, 42.”
From Evaluating Digital Health Interventions (2016) · cites this paper as [42]
In the citing paper
“These methods are designed to optimize intervention components with regard to dose and sequencing and to test which intervention components can be used alone or in combination.”
From A Research Agenda for Advancing Non-pharmacological Management of Chronic Musculoskeletal Pain: Findings from a VHA State-of-the-art Conference (2018) · cites this paper as [33]
In the citing paper
“innovative trial designs 31 that allow rigorous, systematic ways of testing a combination of approaches within a single trial including the multiphase optimization strategy and the sequential multiple assignment randomized trial. 32,33”
From A Research Agenda for Advancing Non-pharmacological Management of Chronic Musculoskeletal Pain: Findings from a VHA State-of-the-art Conference (2018) · cites this paper as [33]
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.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > DISCUSSION
“This is a variation of the example SMART in Fig.3in which the decision to provide 5 vs 10 weeks of initial IBT occurs at the end of 5 weeks on IBT instead of at baseline.”
§ Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research > SAMPLE SIZE CONSIDERATIONS
“The design in Fig. 2 supposes that the decision of 5 vs 10 weeks occurs at baseline; and consistent with this consideration, all participants are randomized at baseline to 5 vs 10 weeks duration of IBT.”
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“Despite the general success of interventions such as IBT (and others [7, 10–14]), 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.”
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“ACT is a psychotherapeutic approach focusing on acceptance and mindfulness strategies for promoting health behavior change [47].”
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“Data analyses associated with the aim to develop a more deeply-tailored AI are akin to, but go beyond, standard moderator analysis [69–72].”
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Cited by
Sorted by citations
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Hollis, C., Falconer, C. J., Martin, J. L., Whittington, C., Stockton, S., Glazebrook, C., & Davies, E. B. (2017) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12663 · Cited by 846
Skivington, K., Matthews, L., Simpson, S. A., Craig, P., Baird, J., Blazeby, J. M., Boyd, K., Craig, N. J., French, D., McIntosh, E., et al. (2021) · Health Technology Assessment · doi:10.3310/hta25570 · Cited by 585
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“answers within a shorter time frame than the conventional 5-year clinical trial when testing a delivery mode that will become obsolete before the end of the trial.(88) • Finally, we need to capitalize on the currently available technologies that permit collection and transmission of data in real time to better learn a…”
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Prescribable mHealth apps identified from an overview of systematic reviews
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“62 As our overview showed, the effect of apps as health interventions might be marginal, and such small bene fi ts can only be reliably detected by rigorous testing.”
BackgroundDesigning and undertaking randomised implementation trials: guide for researchers
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Self-citationPrecision Health: The Role of the Social and Behavioral Sciences in Advancing the Vision
Hekler, E. B., Tiro, J. A., Hunter, C. M., & Nebeker, C. (2020) · Annals of Behavioral Medicine · doi:10.1093/abm/kaaa018 · Cited by 154
Moller, A. C., Merchant, G., Conroy, D. E., West, R., Hekler, E., Kugler, K. C., & Michie, S. (2017) · Journal of Behavioral Medicine · doi:10.1007/s10865-016-9818-7 · Cited by 151
“A further complexity arises when interventions are ‘adaptive’ in that they change over time and potentially in continuous fashion according to feedback from the user (Almirall et al., 2014; Lagoa et al., 2014).”
BackgroundTutorial for Using Control Systems Engineering to Optimize Adaptive Mobile Health Interventions
Hekler, E. B., Rivera, D. E., Martín, C. A., Phatak, S. S., Freigoun, M. T., Korinek, E. V., Klasnja, P., Adams, M. A., & Buman, M. P. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.8622 · Cited by 141
“To accomplish the goal of meeting and maintaining clinically meaningful targets, many have argued for adaptive mHealth interventions that are individualized and vary the intervention based on an individual’s evolving needs [9-18].”
BackgroundTranslational Behavioral Medicine
Spring, B. J., Pfammatter, A. F., Hoffman, S. A., & Warnick, J. L. (2017) · Springer eBooks · doi:10.1007/978-1-4614-6439-6_221-2 · Cited by 134
Davis, M. M., Freeman, M., Shannon, J., Coronado, G. D., Stange, K. C., Guise, J., Wheeler, S. B., & Buckley, D. (2018) · BMC Cancer · doi:10.1186/s12885-017-3813-4 · Cited by 126
“community, and population settings; to use SMART designs to test stepped-implementation support in response to baseline setting capacity and intervention responsiveness over time; and to implement “layered” interventions which may first build clinic capacity and visit-based workflows prior to implementing population o…”
MethodPham, Q., Graham, G., Carrion, C., Morita, P. P., Seto, E., Stinson, J. N., & Cafazzo, J. A. (2019) · JMIR mHealth and uHealth · doi:10.2196/11941 · Cited by 131
“Future evaluations assessing the relationship between engagement and clinical outcomes should consider alternative trial designs with multiple randomizations to ensure that findings are not biased by confounding [76-78].”
BackgroundInnovations in the Use of Interactive Technology to Support Weight Management
Spruijt‐Metz, D., Wen, C. K. F., O’Reilly, G. A., Li, M., Lee, S., Emken, B. A., Mitra, U., Annavaram, M., Ragusa, G., & Narayanan, S. (2015) · Current Obesity Reports · doi:10.1007/s13679-015-0183-6 · Cited by 110
Theoretical Advancements in mHealth: A Systematic Review of Mobile Apps
Chib, A., & Lin, S. H. (2018) · Journal of Health Communication · doi:10.1080/10810730.2018.1544676 · Cited by 107
Rollo, M. E., Aguiar, E. J., Williams, R. L., Wynne, K., Kriss, M., Callister, R., & Collins, C. E. (2016) · Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy · doi:10.2147/dmso.s95247 · Cited by 107
“Compared to randomized controlled trials that aim to evaluate the effect of an existing intervention, SMART designs aim to optimize the intervention arm.(86) The use of these study designs to Table 1 Advantages and disadvantages of eHealth technologies”
MethodJones, B. E., Ying, J., Stevens, V., Haroldsen, C., He, T., Nevers, M., Christensen, M. A., Nelson, R. E., Stoddard, G. J., Sauer, B. C., et al. (2020) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2019.7495 · Cited by 122
Korinek, E. V., Phatak, S. S., Martín, C. A., Freigoun, M. T., Rivera, D. E., Adams, M. A., Klasnja, P., Buman, M. P., & Hekler, E. B. (2017) · Journal of Behavioral Medicine · doi:10.1007/s10865-017-9878-3 · Cited by 97
Crank, J. E., Sandbank, M., Dunham, K., Crowley, S., Bottema‐Beutel, K., Feldman, J., & Woynaroski, T. G. (2021) · Autism Research · doi:10.1002/aur.2471 · Cited by 115
Managing temptation in obesity treatment: A neurobehavioral model of intervention strategies
Appelhans, B. M., French, S. A., Pagoto, S., & Sherwood, N. E. (2015) · Appetite · doi:10.1016/j.appet.2015.09.035 · Cited by 108
Self-citationBonten, T. N., Rauwerdink, A., Wyatt, J. C., Kasteleyn, M. J., Witkamp, L., Riper, H. M., van Gemert‐Pijnen, J. E. W. C., Cresswell, K. M., Sheikh, A., Schijven, M. P., et al. (2020) · Journal of Medical Internet Research · doi:10.2196/17774 · Cited by 90
“SMART United States 2014 Almirall et al [76]”
Biagianti, B., Quraishi, S. H., & Schlosser, D. A. (2018) · Psychiatric Services · doi:10.1176/appi.ps.201700283 · Cited by 90
“methods and designs—including sequential, multiple assignment, randomized trial (SMART) methods that focus on multiple assessments on an individual level (69,70) or steppedwedge research designs (71,72)—may be more useful in determining and comparing the efficacy of DIs and their components.”
MethodFuture Directions in Symptom Cluster Research
Miaskowski, C. A. (2016) · Seminars in Oncology Nursing · doi:10.1016/j.soncn.2016.08.006 · Cited by 92
Getting “SMART” about implementing multi-tiered systems of support to promote school mental health
August, G. J., Piehler, T. F., & Miller, F. G. (2018) · Journal of School Psychology · doi:10.1016/j.jsp.2017.10.001 · Cited by 87
Chen, E. Y., Cacioppo, J. T., Fettich, K. C., Gallop, R., McCloskey, M. S., Olino, T. M., & Zeffiro, T. A. (2016) · Psychological Medicine · doi:10.1017/s0033291716002543 · Cited by 88
“Future studies are needed that use a sequential multiple assignment randomized trial design (Almirall et al. 2014), allowing randomization of early strong and early weak responders to both more and less intensive arms.”
BackgroundAdaptive Interventions in Child and Adolescent Mental Health
Almirall, D., & Chronis-Tuscano, A. M. (2016) · Journal of Clinical Child & Adolescent Psychology · doi:10.1080/15374416.2016.1152555 · Cited by 89
“A SMART is a multistage randomized trial design, which is used explicitly for the purpose of developing a high-quality adaptive intervention (Almirall et al., 2014; Chakraborty, 2011; Nahum-Shani et al., 2012a, 2012b).”
MethodSelf-citationRiley, W. T., Serrano, K. J., Nilsen, W., & Atienza, A. A. (2015) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2015.03.024 · Cited by 76
eHealth to Enhance Treatment Adherence Among Youth Living with HIV
Mulawa, M. I., LeGrand, S., & Hightow‐Weidman, L. (2018) · Current HIV/AIDS Reports · doi:10.1007/s11904-018-0407-y · Cited by 70
Almirall, D., DiStefano, C., Chang, Y., Shire, S. Y., Kaiser, A. P., Xi, L., Nahum-Shani, I. B., Landa, R. J., Mathy, P., & Kasari, C. L. (2016) · Journal of Clinical Child & Adolescent Psychology · doi:10.1080/15374416.2016.1138407 · Cited by 79
“This SMART had three twostage adaptive interventions embedded within it, by design (Almirall, Compton, Rynn, Walkup, & Murphy, 2012; Almirall et al., 2014; Nahum-Shani et al., 2012).”
MethodSelf-citationGrilo, C. M., White, M. A., Masheb, R. M., Ivezaj, V., MORGAN, P. T., & Gueorguieva, R. V. (2020) · American Psychologist · doi:10.1037/amp0000534 · Cited by 79
Kaizer, A. M., Belli, H. M., Ma, Z., Nicklawsky, A., Roberts, S. C., Wild, J. L., Wogu, A. F., Xiao, M., & Sabo, R. T. (2023) · Journal of Clinical and Translational Science · doi:10.1017/cts.2023.537 · Cited by 81
“The SMART design therefore not only helps to build optimal dynamic treatment regimens, but also permits researchers to identify characteristics of patients for whom particular treatment regimens may be most effective [95,96].”
Hightow‐Weidman, L., & Bauermeister, J. A. (2020) · mHealth · doi:10.21037/mhealth.2019.10.01 · Cited by 64
“What might have been done if this information was evaluated in “real-time”? In its next iteration, AllyQuest will be evaluated within a Sequential Multiple Assignment Randomized Trial (SMART) (26,27).”
MethodInfluentialGuastaferro, K., & Collins, L. M. (2019) · American Journal of Public Health · doi:10.2105/ajph.2018.304874 · Cited by 70
Multilevel Interventions Targeting Obesity: Research Recommendations for Vulnerable Populations
Stevens, J., PRATT, C. A., Boyington, J., Nelson, C. R., Truesdale, K. P., Ward, D. S., Lytle, L. A., Sherwood, N. E., Robinson, T. N., Moore, S. M., et al. (2016) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2016.09.011 · Cited by 74
Self-citationFortney, J. C., Bauer, A. M., Cerimele, J. M., Pyne, J. M., Pfeiffer, P., Heagerty, P. J., Hawrilenko, M., Zielinski, M. J., Kaysen, D. L., Bowen, D. J., et al. (2021) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2021.2318 · Cited by 74
Nelson, K. M., Perry, N. S., Horvath, K. J., & Smith, L. R. (2020) · Translational Behavioral Medicine · doi:10.1093/tbm/ibaa007 · Cited by 61
Fowler, L. A., Grammer, A. C., Staiano, A. E., Fitzsimmons‐Craft, E. E., Chen, L., Yaeger, L., & Wilfley, D. E. (2021) · International Journal of Obesity · doi:10.1038/s41366-021-00765-x · Cited by 63
Paediatric migraine: evidence-based management and future directions
Orr, S. L., Kabbouche, M. A., O’Brien, H. L., Kacperski, J. E., Powers, S. W., & Hershey, A. D. (2018) · Nature Reviews Neurology · doi:10.1038/s41582-018-0042-7 · Cited by 68
Translational Behavioral Medicine
Spring, B. J., Pfammatter, A. F., Hoffman, S. A., & Warnick, J. L. (2020) · Springer eBooks · doi:10.1007/978-3-030-39903-0_221 · Cited by 66
Bierman, A. S., Wang, J., O’Malley, P. G., & Moss, D. (2021) · Health Services Research · doi:10.1111/1475-6773.13863 · Cited by 65
Gönül, S., Namlı, T., Huisman, S. D., Ertürkmen, G. B. L., Toroslu, İ. H., & Coşar, A. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy160 · Cited by 58
“Gustafson et al. 19 present self-management modules, 1 of which tracks GPS data and warns people with (prior) alcohol addiction when they approach a previously identified high-risk location.”
BackgroundMethodBrown, A. W., Aslibekyan, S. W., Bier, D. M., da Silva, R. F., Hoover, A. W., Klurfeld, D. M., Loken, E., Mayo‐Wilson, E., Menachemi, N., Pavela, G., et al. (2021) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2021.1985427 · Cited by 63
“Stepped-wedge cluster randomized designs (Hemming et al. 2015); within-cohort randomized trials (also called Trials within Cohorts) (Kim, Flory, and Relton 2018); Randomization to Randomization (R2R) (George et al. 2018); packet-randomized experiments (Pavela et al. 2015); multiphase optimization strategy trials (MOST…”
BackgroundIntensive Interventions for Students With Emotional and Behavioral Disorders
Maggin, D. M., Wehby, J. H., Farmer, T. W., & Brooks, D. S. (2016) · Journal of Emotional and Behavioral Disorders · doi:10.1177/1063426616661498 · Cited by 61
Lin, P., Grambow, S. C., Intille, S. S., Gallis, J. A., Lazenka, T., Bosworth, H. B., Voils, C. I., Bennett, G. G., Batch, B. C., Allen, J., et al. (2018) · JMIR mhealth and uhealth · doi:10.2196/10471 · Cited by 53
“The fact that engagement dropped substantially early suggests that a more effective intervention that automatically adapts to behavior and self-measured engagement, such as using just-in-time adaptive design, may be needed [35,36].”
BackgroundBecker, W. C., DeBar, L. L., Heapy, A. A., Higgins, D., Krein, S. L., Lisi, A., Makris, U. E., & Allen, K. D. (2018) · Journal of General Internal Medicine · doi:10.1007/s11606-018-4345-6 · Cited by 59
Militello, L. K., Melnyk, B. M., Hekler, E. B., Small, L., & Jacobson, D. (2016) · JMIR mhealth and uhealth · doi:10.2196/mhealth.4398 · Cited by 51
“Highly adaptive sequential multiple assignment randomized trials (SMART) have been used to inform the best sequencing of treatments when individuals are not responding, and the best time to transition from more to less intensive or maintenance therapy [50-53].”
MethodEvolutionary considerations on social status, eating behavior, and obesity
Caldwell, A. E., & Sayer, R. D. (2018) · Appetite · doi:10.1016/j.appet.2018.07.028 · Cited by 54
Cognitive dysfunction is a risk factor for overeating and obesity.
Gunstad, J., Sanborn, V. E., & Hawkins, M. A. W. (2020) · American Psychologist · doi:10.1037/amp0000585 · Cited by 57
Research Agenda of the Oncology Nursing Society: 2019–2022
Ah, D. M. V., Brown, C. G., Brown, S., Bryant, A. L., Davies, M. J., Dodd, M. J., Ferrell, B., Hammer, M. J., Knobf, M. T., Knoop, T., et al. (2019) · Oncology nursing forum · doi:10.1188/19.onf.654-669 · Cited by 67
“The main goal for a SMART design is to construct an adaptive intervention based on data, whereas the main goal of an RCT is to evaluate an already developed intervention versus a comparator condition (Almirall et al., 2014).”
Sucala, M. L., Ezeanochie, N., Cole-Lewis, H. J., & Turgiss, J. L. (2019) · Translational Behavioral Medicine · doi:10.1093/tbm/ibz109 · Cited by 49
“The “one size fits all” approach fails to accommodate the complexities of health behavior across diverse populations and we need interventions that can offer a personalized approach—one that is able to provide context-specific, relevant, personalized tools at the moment when the individual needs it to make healthier c…”
BackgroundDowns, D. S., Savage, J. S., Rivera, D. E., Pauley, A. M., Leonard, K. S., Hohman, E. E., Guo, P., McNitt, K. M., Stetter, C., & Kunselman, A. (2021) · Journal of Behavioral Medicine · doi:10.1007/s10865-021-00227-9 · Cited by 51
“, 2018) and adaptive interventions (Almirall et al., 2014), and produced a dynamical, mathematical model of energy balance (Dong et al.”
BackgroundWalsh, J. C., & Groarke, J. M. (2019) · European Psychologist · doi:10.1027/1016-9040/a000351 · Cited by 51
Harvey, G., Rycroft‐Malone, J., Seers, K., Wilson, P. M., Cassidy, C. E., Embrett, M. G., Hu, J., Pearson, M., Semenic, S. E., Zhao, J., et al. (2023) · Frontiers in Health Services · doi:10.3389/frhs.2023.1162762 · Cited by 64
“This is particularly the case for experimental studies that are purposefully designed to neutralise context throughout the research process, although more recent developments such as the adaptive trial design offer greater flexibility to account for contextual factors (54).”
BackgroundMobile Health Interventions for Substance Use Disorders
Businelle, M. S., Perski, O., Hébert, E. T., & Kendzor, D. E. (2024) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-080822-042337 · Cited by 51
Kim, Y., Gray, N., Jones, A., Scher, S., & Kozlowska, K. (2021) · Seminars in Pediatric Neurology · doi:10.1016/j.spen.2021.100947 · Cited by 56
Batterham, M. J., Tapsell, L. C., & Charlton, K. E. (2015) · Obesity Research & Clinical Practice · doi:10.1016/j.orcp.2015.05.005 · Cited by 46
Nahum-Shani, I. B., Ertefaie, A., Lu, X., Lynch, K. G., McKay, J. R., Oslin, D. W., & Almirall, D. (2016) · Addiction · doi:10.1111/add.13743 · Cited by 49
Self-citationNahum-Shani, I. B., Almirall, D., Yap, J. R. T., McKay, J. R., Lynch, K. G., Freiheit, E., & Dziak, J. J. (2019) · Psychological Methods · doi:10.1037/met0000219 · Cited by 50
“These models suggest that a treatment that demonstrates short-term gains (e.g., weight loss) for an individual may not lead to gain in the long-term even if the individual remains on the same treatment over time (Almirall et al., 2014).”
BackgroundSelf-citationUnick, J. L., Pellegrini, C. A., Demos, K. E., & Dorfman, L. (2017) · Current Diabetes Reports · doi:10.1007/s11892-017-0904-1 · Cited by 43
Hsu, T. C., Whelan, P., Gandrup, J., Armitage, C. J., Cordingley, L., & McBeth, J. (2024) · British Journal of Health Psychology · doi:10.1111/bjhp.12766 · Cited by 57
“…is a multi-stage randomized trial design that systematically evaluates different intervention sequences to establish decision rules—whether, how, when and based on what criteria to modify intervention elements such as type and dosage (e.g., duration, frequency or amount) (Almirall et al., 2014).”
Moderators of Outcome for Youth Anxiety Treatments: Current Findings and Future Directions
Norris, L. A., & Kendall, P. C. (2021) · Journal of Clinical Child & Adolescent Psychology · doi:10.1080/15374416.2020.1833337 · Cited by 46
“Novel study designs also merit consideration, particularly adaptive treatment methods like the sequential multiple assignment randomized trial (SMART; Almirall et al., 2014).”
MethodXi, L., Nahum-Shani, I. B., Kasari, C. L., Lynch, K. G., Oslin, D. W., Pelham, W. E., Fabiano, G. A., & Almirall, D. (2015) · Statistics in Medicine · doi:10.1002/sim.6819 · Cited by 47
“Also known as adaptive treatment strategies [6–10], treatment policies [11–13], or adaptive interventions [14], dynamic treatment regimes aim to provide treatments when patients need them; to do this, DTRs adapt the type or dosage of treatments to patients’ changing needs.”
BackgroundSelf-citationSMARTer Approach to Personalizing Intervention for Children With Autism Spectrum Disorder
Kasari, C., Sturm, A., & Shih, W. (2018) · Journal of Speech, Language, and Hearing Research · doi:10.1044/2018_jslhr-l-rsaut-18-0029 · Cited by 46
“For example, it is common to think that the data arising from a SMART is analyzed as a comparison of all the subgroups (Almirall et al., 2014) and such an analysis may, indeed, need large sample sizes.”
BackgroundMethodRoss, K. M., Eastman, A., & Wing, R. R. (2019) · Obesity · doi:10.1002/oby.22400 · Cited by 43
“Future research should investigate whether more proximal intervention tailoring may further improve outcomes; for example, using an adaptive treatment design (32,33), a study could investigate whether providing an additional and/or tailored inter-”
BackgroundThe BestFIT trial: A SMART approach to developing individualized weight loss treatments
Sherwood, N. E., Butryn, M. L., Forman, E. M., Almirall, D., Seburg, E. M., Crain, A. L., Kunin‐Batson, A., Hayes, M. G., Levy, R. L., & Jeffery, R. W. (2016) · Contemporary Clinical Trials · doi:10.1016/j.cct.2016.01.011 · Cited by 44
“treatment is adapted over time based on an individual's evolving status and specific needs [7,8].”
BackgroundSelf-citationBosco, A., Paulauskaite, L., Hall, I., Crabtree, J. W., Soni, S., Biswas, A. B., Cooper, V., Poppe, M., King, M., Strydom, A., et al. (2019) · PLoS ONE · doi:10.1371/journal.pone.0221507 · Cited by 44
PIPELINEs: Creating Comparable Clinical Knowledge Efficiently by Linking Trial Platforms
Trusheim, M. R., Shrier, A., Antonijevic, Z., Beckman, R., Campbell, R. K., Chen, C., Flaherty, K., Loewy, J. W., Lacombe, D., Madhavan, S., et al. (2016) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.514 · Cited by 45
Missing data in primary care research: importance, implications and approaches
Marino, M., Lucas, J., Latour, E. J., & Heintzman, J. D. (2020) · Family Practice · doi:10.1093/fampra/cmaa134 · Cited by 47
“Generally, these include: (1) identifying target populations underserved by interventions that may have incentives to remain in the study; (2) under appropriate research questions, utilizing patient-centered (10) and adaptive interventions (11) to meet the specific needs of different clinics, their patients and avoid…”
BackgroundA Decade in Review: A Systematic Review of Virtual Reality Interventions for Emotional Disorders
Rowland, D. P., Casey, L. M., Ganapathy, A., Cassimatis, M., & Clough, B. A. (2021) · Psychosocial Intervention · doi:10.5093/pi2021a8 · Cited by 44
“Research designs such as sequential multiple assignment randomized trials (Almirall et al., 2014) or multiphase optimisation strategy trials (Collins et al., 2007) have the capacity to bridge the digital divide and keep pace with ongoing technological iterations and updates required by many third…”
BackgroundEster, M., Eisele, M., Wurz, A. J., McDonough, M. H., McNeely, M. L., & Culos-Reed, S. N. (2021) · JMIR Cancer · doi:10.2196/28852 · Cited by 43
Almirall, D., Nahum-Shani, I. B., Wang, L., & Kasari, C. L. (2018) · Statistics for social and behavioral sciences · doi:10.1007/978-3-319-91776-4_4 · Cited by 45
Self-citationHrynyschyn, R., Prediger, C., Stock, C., & Helmer, S. M. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19095221 · Cited by 46
“Alternative study designs or adaptive study designs describe a procedure in which different decisions are made regarding measurement, dosage, and time that affect the intervention [16,17].”
BackgroundCórdova, D., Muñoz-Velázquez, J., Lua, F. M., Fessler, K. B., Warner, S. C., Delva, J., Adelman, N., Fernandez, A. R., & Bauermeister, J. A. (2020) · JMIR mhealth and uhealth · doi:10.2196/16251 · Cited by 41
“Furthermore, given the multilevel approach of S4E, a sequential multiple assignment randomized trial (SMART) may lead to an optimally efficacious preventive strategy through the optimization of dose based on response (or lack thereof) to the intervention [59-62].”
Yu, F., Salisbury, D., & Mathiason, M. A. (2021) · Journal of Sport and Health Science · doi:10.1016/j.jshs.2020.05.007 · Cited by 40
“Inter-individual difference refers to the fact that not all individuals will respond to the same treatment to the same degree within the same timeframe or will have the same side-effect profiles.(20) The effect of inter-individual differences or individual heterogeneity in treatment responses has been well established…”
BackgroundMethodAn Exploratory Review of the Associations between Adverse Experiences and Autism
Dodds, R. L. (2020) · Journal of Aggression Maltreatment & Trauma · doi:10.1080/10926771.2020.1783736 · Cited by 44
“Longitudinal and experimental research to test the efficacy of individual and family therapies utilizing SMART designs that adapt to the needs of the participant (Almirall et al., 2014) should be conducted to provide clear guidance to practitioners.”
BackgroundA Systematic Review of Technology-Assisted HIV Testing Interventions
Horvath, K. J., Walker, T., Mireles, L., et al. (2020) · Current HIV/AIDS Reports · doi:10.1007/s11904-020-00506-1 · Cited by 42
“In a research setting, this may be done through sequential multiple assignment randomization trial (SMART) designs [45], while in community settings this may be accomplished by providing a menu of testing services (e.g., regular text messages for regular testers and technology-assisted peer…”
Valuing the Diversity of Research Methods to Advance Nutrition Science
Mattes, R. D., Rowe, S. B., Ohlhorst, S. D., Brown, A. W., Hoffman, D. J., Liska, D. J., Feskens, E. J. M., Dhillon, J., Tucker, K. L., Epstein, L. H., et al. (2022) · Advances in Nutrition · doi:10.1093/advances/nmac043 · Cited by 48
Bade, B. C., Faiz, S. A., Ha, D. M., Tan, M., Barton‐Burke, M., Cheville, A. L., Escalante, C. P., Gozal, D., Granger, C. L., Presley, C. J., et al. (2023) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.202210-1963st · Cited by 46
“For instance, as physical activity programs often provide multifaceted interventions, studies may use the SMART or MOST design to evaluate the impact of different program components and at different times along the lung cancer continuum (139, 140).”
BackgroundKidwell, K., Seewald, N. J., Tran, Q., Kasari, C. L., & Almirall, D. (2017) · Journal of Applied Statistics · doi:10.1080/02664763.2017.1386773 · Cited by 37
Self-citationKwaśnicka, D., Keller, J., Perski, O., Potthoff, S., ten Hoor, G. A., Ainsworth, B., Crutzen, R., Dohle, S., van Dongen, A., Heino, M. T. J., et al. (2022) · Health Psychology Review · doi:10.1080/17437199.2022.2046482 · Cited by 42
“…(Kahan et al., 2020), Micro-Randomised Trials (MRTs) (Dimairo et al., 2020), N-of-1 trials (Kwasnicka et al., 2019; Vohra et al., 2015), Sequential Multiple Assignment Randomised Trials (SMARTs) (Almirall et al., 2014; Collins et al., 2007), and Rapid Optimisation Methods (Morton et al., 2021).”
BackgroundGaps and priorities in advancing methods for health behaviour change research
Byrne, M. (2019) · Health Psychology Review · doi:10.1080/17437199.2019.1707106 · Cited by 32
Lakka, T. A., Aittola, K., Järvelä‐Reijonen, E., Tilles‐Tirkkonen, T., Männikkö, R., Lintu, N., Karhunen, L. J., Kolehmainen, M., Harjumaa, M., Mattila, E., et al. (2022) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2022.100527 · Cited by 44
“26 In further developments of the BitHabit app, we will utilize the possibility to better adapt the digital intervention based on participants’ personal needs and preferences, utilizing the knowledge of over 1 ¢ 0 million daily habit selections reported by the participants within the first six…”
MethodEmbedding implementation science in the research pipeline
Zullig, L. L., Drake, C., Check, D. K., Brunkert, T., Deschodt, M., Olson, M. S., & Geest, S. D. (2023) · Translational Behavioral Medicine · doi:10.1093/tbm/ibad050 · Cited by 40
Fortney, J. C., Heagerty, P. J., Bauer, A. M., Cerimele, J. M., Kaysen, D. L., Pfeiffer, P. N., Zielinski, M. J., Pyne, J. M., Bowen, D., Russo, J. E., et al. (2019) · Contemporary Clinical Trials · doi:10.1016/j.cct.2019.105873 · Cited by 47
Geng, E., Mody, A., & Powell, B. J. (2023) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-051920-124515 · Cited by 38
Mansfield, E., Boyes, A. W., Bryant, J., & Sanson‐Fisher, R. (2017) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.4642 · Cited by 38
“This approach would have particular utility in the case of adaptive intervention strategies, whereby the intervention is adapted and readapted sequentially in response to the needs of the individual (Almirall et al., 2014).”
BackgroundBridging Innovation and Equity: Advancing Public Health Through Just-in-Time Adaptive Interventions
Zainal, N. H., Liu, X., Leong, U., Yan, X., & Chakraborty, B. (2024) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-071723-103909 · Cited by 42
Lochman, J. E., Dishion, T. J., Boxmeyer, C. L., Powell, N. P., & Lixin Qu, A. (2017) · Research on Child and Adolescent Psychopathology · doi:10.1007/s10802-016-0252-7 · Cited by 38
Breaux, R., Baweja, R. K., Eadeh, H., Shroff, D. M., Cash, A. R., Swanson, C. S., Knehans, A. C., & Waxmonsky, J. G. (2022) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2022.05.012 · Cited by 40
McDonald, S., Vieira, R., Godfrey, A., O’Brien, N., White, M. J., & Sniehotta, F. F. (2017) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-017-0623-7 · Cited by 43
Grilo, C. M., White, M. A., Ivezaj, V., & Gueorguieva, R. V. (2020) · Obesity · doi:10.1002/oby.22975 · Cited by 37
“Grilo and colleagues (15) recently reported acute outcomes from an adaptive Sequential Multiple Assignment Randomized Trial (SMART) (16,17) that evaluated an innovative treatment model for patients with BED with coexisting obesity.”
BackgroundDaniels, S. R., PRATT, C. A., Hollister, E. B., Labarthe, D. R., Cohen, D. A., Walker, J. R., Beech, B. M., Balagopal, P., Beebe, D. W., Gillman, M. W., et al. (2019) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2019.01.042 · Cited by 36
Self-citationMechanisms of Change in Exposure Therapy for Anxiety and Related Disorders: A Research Agenda
Benito, K., Pittig, A., Abramowitz, J. S., Arch, J. J., Chavira, D. A., de Kleine, R. A., Nadai, A. S. D., Hermans, D., Hofmann, S. G., Hoyer, J., et al. (2024) · Clinical Psychological Science · doi:10.1177/21677026241240727 · Cited by 37
“SMARTs test adaptive interventions via multiple randomization points based on time and/or tailoring factors (Almirall et al., 2014).”
Machine Learning and Health Science Research: Tutorial
Cho, H., She, J., de Marchi, D., El-Zaatari, H., Barnes, E. L., Kahkoska, A. R., Kosorok, M. R., & Virkud, A. (2023) · Journal of Medical Internet Research · doi:10.2196/50890 · Cited by 39
“For example, researchers can plan adaptive intervention programs for weight loss where later interventions are adjusted depending on responses to the previous treatment [83].”
Use of Mental Health Apps by Patients With Breast Cancer in the United States: Pilot Pre-Post Study
Chow, P. I., Showalter, S. L., Gerber, M. S., Kennedy, E. M., Brenin, D. R., Mohr, D. C., Lattie, E. G., Gupta, A., Ocker, G., & Cohn, W. F. (2020) · JMIR Cancer · doi:10.2196/16476 · Cited by 33
Karp, J. F., Zhang, J., Wahed, A. S., Anderson, S., Dew, M. A., Fitzgerald, G. K., Weiner, D. K., Albert, S. M., Gildengers, A. G., Butters, M. A., et al. (2019) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2019.03.011 · Cited by 34
“It is possible that patients may need to practice the techniques learned in CBT and PT longer than 8 weeks to benefit from the acquired psychological skills and physical gains (40).”
BackgroundInterpreting Randomized Controlled Trials
Msaouel, P., Lee, J., & Thall, P. F. (2023) · Cancers · doi:10.3390/cancers15194674 · Cited by 38
“On the other hand, a problem with composite outcomes such as PFS time is that death without recurrence or disease recurrence prior to death carries the same implication regarding the treatment effect.”
Metadata
- Authors
- Almirall, D., Nahum-Shani, I., Sherwood, N. E., & Murphy, S. A.
- Affiliations
- University of Michigan (US)
- HealthPartners (US)
- Corresponding author
- Almirall, Daniel
- 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
- 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
- bronze
- doi.org
- 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.
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