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261© Springer Nature Switzerland AG 2021
L. H. Powell et al., Behavioral Clinical Trials for Chronic Diseases,
https://doi.org/10.1007/978-3-030-39330-4_11
Chapter 11
The Future ofBehavioral
Randomized Clinical
Trials
The chapter aims to predict the future of behavioral randomized trials in four key
areas. The emergence of a metascience for behavioral clinical trials will replace the
“one-size-ts all” approach to behavioral trial design with designs that feature a
progression of questions, a progression of methods, and the use of guidelines to
facilitate decision-making. Behavioral treatments will produce stronger effects with
the emergence of precision lifestyle medicine that targets precisely those most likely
to benet and tailors precisely to diverse persons, settings, and time, and with mul-
tilevel trials that simultaneously intervene on more than one level of ecologic risk.
Behavioral trials will be easier to implement using networks that collaborate on
multi-site behavioral trials, leveraging data routinely collected in the healthcare sys-
tem, and enhancing accessibility to trials using digital technology. The gap between
trial results and implementation in practice will be narrowed by strategic planning
for dissemination featuring outcomes in trials that are meaningful to clinicians and
third-party payers, commitment to rene treatments that have failed, and a push
toward inuencing clinical practice guidelines with Phase III efcacy trials.
“It is difcult to make predictions, especially about the future.”
Yogi Berra
Fundamental Point
Behavioral clinical trials will evolve in four areas in the future. They will be
more rigorous, guided by the emergence of a metascience for behavioral
trial methodology. They will benet from stronger treatment effects result-
ing from precision targeting and tailoring to diverse risk proles and from
intervening simultaneously on multiple levels of ecological risk. They will
be easier to implement using networks of investigators and drawing on big
data to simplify approaches to recruitment, assessment, and intervention.
They will be more relevant for improving healthcare delivery by strategic
planning for dissemination at all stages of behavioral treatment development.
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RANDOMIZED CLINICAL TRIALS
WILL NOT BEOUTDATED
Are clinical trials becoming outdated? This question has been raised repeatedly by
critics who have expressed a number of concerns. (1) Randomized trial data should
not be prioritized over alternative ways of knowing whether a treatment works, such
as observational studies, studies of mechanisms, uncontrolled case studies, and
clinical experience. (2) Methodologic aws in randomization procedures fail to
create equality across treatment arms. (3) Limited external validity results from
carefully selected target populations treated in articial settings. (4) Group designs
are unable to inform treatment response of an individual patient. (5) Priority is
placed on whether a treatment works at the expense of understanding how it
works [1].
Admittedly, clinical trials are not perfect. But they are widely accepted as the gold
standard by which to determine whether or not a behavioral treatment works. There
are several reasons for their primacy.
Randomized Clinical Trials Make theStrongest Causal
Inferences
The argument that randomized trials should not be prioritized over other ways of
knowing is a reection of the “nirvana fallacy” of assuming that because they are
imperfect, they are no better than other designs. This is an error in inference [1]. No
other design is as successful in minimizing the error of inferring that a treatment,
and not some factor related to that treatment, is responsible for benet. No other
design carries more weight in clinical practice guidelines, in third-party reimburse-
ment, and, ultimately, in maximizing patient care. Clinical trials are a “crucial linch-
pin for evidence-based practice” [1].
An excellent example of their potency is with the question of the optimum diet to
enhance health. Almost all nutritional variables are correlated with one another in
the large, complex system of dietary intake. If one nutritional variable is correlated
with an outcome, so too are many other nutritional variables. This problem of con-
founding is not solved by increasing the size of the dataset, now made possible by
the advent of “big data.” Nutritional variables will be intercorrelated similarly in
datasets that are both large and small. Statistical adjustment for the inuence of one
dietary component on health over another in an observational study is challenging,
if not impossible, due to this multicollinearity [2]. However, with a randomized
trial, these intercorrelated dietary variables can be disentangled by randomizing par-
ticipants to receive, or not receive, one single dietary component. This has often
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produced a dramatic difference in results from observational studies and clinical
trials. For example, observational studies made a strong case for the benet of
omega-3 sh oil on vascular events in patients with diabetes. But the ASCEND trial
found no such benet [3]. The messy problem of confounding between intake of
sh oil and the variety of dietary and socioeconomic factors that covary with it was
solved by shifting the choice of ingesting omega-3 sh oil from the patient to a ip
of a coin. No other way of knowing has such power in making a causal inference as
random assignment.
Randomized Clinical Trials Can Have Strong
Ecologic Validity
The argument that carefully controlled trials are limited because they are conducted
in articial settings which do not generalize to real-world contexts conates eco-
logical validity with internal validity. A treatment that is offered in a real-world
context with high ecological validity can be evaluated using a randomized design
with strong internal validity. An excellent example is a trial of blood pressure man-
agement that was conducted in black barbershops. Fifty-two black barbershops
were randomly assigned to a treatment in which pharmacists prescribed blood pres-
sure medication in the barbershop or to a comparator in which barbers provided
lifestyle advice and encouragement to visit the doctor [4]. Retention was 95% in
both arms and the trial showed a benet from the pharmacist treatment. This was a
randomized trial with strong internal validity that evaluated an ecologically valid
intervention conducted in a real-world setting. This example can be easily extended
to any pragmatic trial that uses a randomized design but brings the context closer to
clinical or community reality.
Randomized Clinical Trials Are Essential toTranslational
Research
The argument that key patient subgroups are left out of clinical trials is not a problem
of the randomized design but a problem with a “one fell swoop” approach to science
that expects all questions to be answered in a single trial. Campbell has argued for
the primacy of internal validity as a prerequisite for external validity based upon the
premise that one cannot meaningfully generalize a nding unless it is a genuine nd-
ing [5]. A progressive program of translational research features a series of studies,
each of which provides more information about a treatment and who would benet
from it. When results converge from case studies, clinical experience, observational
studies, and studies of mechanisms, the case is strong for a denitive, conrmatory
clinical trial where the inference of causality will be the strongest.
Randomized Clinical Trials Will Not BeOutdated
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If the clinical trial shows benet for the population selected to maximize internal
validity, this opens the door to subsequent trials and other types of studies to accu-
mulate evidence on external validity. Campbell and Stanley argued that external
validity is accumulated over a series of studies. In their words:
“We learn about external validity only piece by piece through trial and error, typically
over multiple studies that contain different kinds of persons, settings, treatments, and
outcomes. Scientists do this by conducting a program of research.” (p.86) [5]
Randomized clinical trials are a crucial part of the translational research enterprise
that evolves through discovery, exploration, conrmation, and generalization, and
moves from novel laboratory ndings to the generation of robust evidence [6]. The
place of the randomized trial in translational research is in conrmation. There may
be other powerful ways to achieve randomization in the future. For example,
Mendelian randomization compares outcomes in individuals who do, and do not,
have gene variants linked to an exposure, such as physical activity. Because genes
are free of environmental inuences, randomly distributed, and thereby free of
residual confounding, comparisons of outcomes in those with and without the gene
provide a randomized natural experiment [7, 8]. There may be other ways to make
convincing causal attributions. For example, the impact of policy-level changes
using a time-lagged interrupted time series design which compares outcomes before
and after serial implementations of policy may be a powerful, fast, efcient, and
conclusive way to evaluate organizational change in a living healthcare system [9].
However, there is a general con-
sensus that the future is less about
abandoning randomized clinical
trials and more about nding
ways to improve them [10]. To
draw on Bob Dylan’s metaphor
(see box), the behavioral clinical
trial “wind is blowing” toward
increased methodological rigor,
stronger interventions, greater ease of implementation, and more relevant results.
BEHAVIORAL TRIALS WILL
BEMORE RIGOROUS
Behavioral randomized clinical trial design has been stuck in a single mold. Most
trials have been small and underpowered to detect improvements in clinically
important outcomes and characterized by a multiplicity of outcomes [11, 12].
Successes tend to be left standing without replication, and failures are seldom
rened and re-examined. Funders, publishers, societies, institutions, editors,
“You don’t need a weather man
to know which way the wind blows.”
Bob Dylan
Subterranean Homesick Blues,
1965
Nobel Prize in Literature, 2016
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reviewers, and authors all contribute to the cultural norms that support this status
quo and the dysfunctional incentive system that sustains it [13].
These observations have fostered some
soul-searching. This has translated
into an emerging metascience for
behavioral clinical trials that looks
beyond a critique of any individual
trial and focuses instead on the funda-
mental processes of science that under-
lie it. Metascience, the scientic study
of science itself [13], has been alive and well among the philosophers of science for
more than two centuries. It is now gaining momentum in the behavioral clinical trial
community [14–19].
Some of the highlights of the innovations that are emerging from the metascience
movement in behavioral clinical trial methodology are the following:
• The goals of behavioral and social science research have been challenged
to go beyond exploration and discovery and to be more applied and ori-
ented toward solving practical problems [20, 21].
• The psychological side of science has shown the ways in which investiga-
tors knowingly or unknowingly deceive themselves through the combina-
tion of apophenia (the tendency to see patterns in random data), conrmation
bias (the tendency to focus on evidence that is in line with expectations or
favored explanations), and hindsight bias (the tendency to see an event as
having been predictable only after it has occurred) [13].
• Progressive models for behavioral treatment development have been pro-
posed that encourage the use of a variety of designs as questions about a
treatment and the purpose of the study evolve [22].
• A systematic way to describe the nature of any behavioral intervention
now exists [23].
• Guidelines have been developed for: choosing an appropriate comparator
(Chapter 6: Choice of a Comparator); conducting pilot, feasibility, and
proof-of-concept studies (Chapter 3: Behavioral Treatment Development;
Chapter 7: Feasibility and Pilot Studies); framing research questions [24];
and reporting behavioral clinical trial results [25–28].
• The International Behavioural Trials Network (IBTN) (www.ibtnetwork.
org) has been formed to provide an international network aimed at foster-
ing methodological rigor in the development of interventions and in the
conduct of behavioral clinical trials [29, 30].
• This book is essentially a metascience of behavioral randomized clinical
trial methodology that applies principles of scientic inquiry to the devel-
opment of behavioral treatments, and the design of behavioral clinical tri-
als, over the spectrum of translational research.
“Stakeholders of science must not
embrace the status quo, but instead
pursue self-examination continuously
for improvement and self-correction of
the scientic process itself.”
Munafò et al., 2017 [13]
Behavioral Trials Will BeMore Rigorous
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The future of behavioral clinical trials will be one of enhanced methodological rigor
shaped by these meta-scientic recommendations and guidelines. They will relieve
the investigator from relying upon a “one-size-ts-all” status quo and foster instead
a progressive approach characterized by an evolving understanding of a behavioral
treatment, evolving questions that need to be answered, and a close link between
evolving questions and evolving trial design. They will inspire pursuit of continuing
education, networking, and training opportunities in this new metascience for investi-
gators at all levels of their academic careers [13].
BEHAVIORAL TRIALS WILL
TEST STRONGER
INTERVENTIONS
Behavioral clinical trials often produce clinically insignicant effects on important
clinical endpoints. Stronger behavioral treatments are needed. Momentum is build-
ing in two areas that offer promise for enhancing strength: precision lifestyle medi-
cine and multilevel treatments.
Precision Lifestyle Medicine
Challenging the “one-size-ts-all” approach to behavioral treatment development,
precision lifestyle medicine seeks to target subgroups most likely to benet from a
behavioral treatment and tailor treatments to diverse persons, settings, and time
[31]. The vision is that a deeper understanding of the biological, psychological,
social, and environmental mechanisms that facilitate behavior change will make it
possible to design interventions that target those mechanisms precisely.
Target Subgroups Most Likely toBenet
Genetic Predisposition.
Medicine is personalized. The choice of a drug is
based upon a match between the characteristics of the patient and the evidence that
the drug will work for that patient. Precision medicine is an approach to treatment
and prevention that takes into account individual variability in genes, environment,
and lifestyle [32]. Its greatest success has been in the treatment of some types of
cancer where advances in genome sequencing and biotechnology have made it pos-
sible to match treatment to the genetic characteristics of a particular tumor [33].
This success has fostered an interest in precision prevention [34] which seeks to use
genetic markers of disease risk to personalize preventive interventions to reduce
that risk.
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At least two studies have posed a challenge to precision prevention. The rst focused
on the popular assumption that DNA is destiny and that lifestyle change is useless
for those whose genetic risk is very high, and unnecessary for those whose genetic
risk is very low. The study involved 55,685 participants who were assessed on 50
markers of genetic risk for coronary artery disease, and on healthy lifestyle, and
then followed for approximately 19 years for incident coronary events. Results
showed that a healthy lifestyle reduced risk within low, medium, and high tertiles of
genetic risk, with the strongest benets of lifestyle in those at highest genetic risk
[35]. Everyone benetted from healthy living, regardless of their genetic risk.
The second study was based upon the popular assumption that the optimum diet
should be targeted to one’s genetic weak link. This was a trial of 609 overweight or
obese adults who were assessed for a low-fat-responsive and a low-carbohydrate-
responsive genotype at baseline and then randomized to receive either a low-fat or
low- carbohydrate diet [36]. It was hypothesized that those with a low-fat-responsive
genotype would lose more weight when assigned to a low-fat diet and a parallel
effect would be found for carbohydrates. However, no enhanced benet for DNA
and diet concordance was observed on weight loss at 1 year. Individuals in all sub-
groups lost weight primarily because they improved overall diet quality. Everyone
benetted from a healthy diet, regardless of their genetic risk.
Thus, as far as healthy living goes, it appears that one size ts all. Healthy living
provides benets for all levels of genetic risk. This may be a robust nding given the
fact that lifestyle is a root cause of most chronic diseases. Alternatively, it may be
related to a limited understanding of the genetics of chronic diseases and metabolic
factors. This eld is exploding and more precise explorations into precision preven-
tion are likely in the future.
Motivation. Generalizability of the benets of a behavioral treatment to all
patients with a target disease is widely viewed as a criterion for judging that treat-
ment to be strong, persuasive, relevant, and exciting. But there are clearly sub-
groups of patients with a disease who prefer drug management, or no management
at all, over a commitment to change their lifestyle. Although this preference may
be shaped by physical and social environments which could themselves be inter-
vened upon, the need for individual agency and effort in many behavioral treat-
ments suggests a misalignment between those with low motivation and those
treatments. Persuading patients to enroll in a behavioral trial in pursuit of general-
izability undermines patient respect and exposes a lack of investigator humility to
accept that what is offered may not be what a patient wants. If they do end up in a
trial, these patients require excessive attention and effort to achieve adherence and
complete the trial. (See Chapter 8: Protection of Random Assignment.)
Precision lifestyle medicine reconsiders the target population for behavioral trials.
Rather than targeting all who have the disease, a more precise target would be all
who have the disease and are motivated to change their behavior. This shift is
Behavioral Trials Will Test Stronger Interventions
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