Background
Clinical trials remain the cornerstone of evidence-based health care. As of July 1,
2021, there were 382,313 clinical trials registered on ClinicalTrials.gov, an average
of 33,400 new registrations over each of the past 3 years, and 19,782 new registrations
for this year (2021) alone [1]. Even assuming modest sample sizes of 125 participants
for each of those new 19,782 trials in that one registry, these trials already require
more than 2.4 million participants this year, approximately 13,737 every day, and
hundreds of potential participants being approached or being followed up right now.
Despite the incredible volume of research activity and collective trial experience,
trials still routinely take longer (and cost more) than originally proposed, often
due to challenges with recruitment (including participants in a trial) and/or retention
(keeping participants in a trial) [2]. For example, only 56% of UK National Institute
for Health Research Health Technology Assessment funded trials recruited the number
of people they needed, and some suffered loss to follow-up of up to 77% [2]. Alongside
challenges of recruitment and retention, many other trial process-related deficiencies
produce trial results that are at best unreliable and at worst unusable leading to
research waste [3].
Amongst the existing evidence on how to improve the design and conduct of trials,
little attention has been given to the integral and multifactorial role of human behaviour
to trial success. Indeed, all of these trials depend on behaviours: they rely on people
(patients, clinicians, trial staff) performing actions (such as receiving or delivering
a trial intervention, attending a clinic, returning a questionnaire, or approaching
eligible participants) that they would not do otherwise. Clearly defining and specifying
behaviours is a key first step in clarifying behaviours in terms of who needs to do
what differently to/for whom and when. The AACTT behaviour specification framework
was developed for implementation research and proposes five domains (action, actor,
context, target, time) to describe and detail relevant behaviours [4]. The AACTT framework
can be used to specify the behaviours of individuals and to describe team and organisational
behaviour. Even considering a simple process such as developing AACTT specifications
for key trial activities (e.g. returning a questionnaire) could provide considerable
additional insight. There are many influences on participants, trial staff, and clinicians’
behaviours within clinical trials. These trial-related behaviours are widespread,
often contextually dependent and amenable to change. Indeed, failure to recognise
the behavioural influences (and change them where appropriate) could contribute to
the failure of the trial. Moreover, insofar as behaviours are at the heart of clinical
trial delivery, then behavioural science—the study of behaviour and behaviour change—can
provide critical, replicable, and generalisable insights for the clinical trials community.
The potential value of behavioural science to inform trial design, delivery, and reporting
Behavioural science is cross-disciplinary and has been considered as an umbrella term
that includes contributions from various disciplines (including psychology, economics,
sociology, political science, and anthropology). The field concerns how and why people
behave as they do. Behavioural science as applied to health seeks to use the theories,
methods, and knowledge from these disciplines to design more effective health care
interventions. Within this article, we have focussed primarily on contributions from
psychology but recognise that many of the other disciplines may have important contributions
for clinical trials. The application of behavioural science to complex problems in
health care has clearly been effective in changing both patient (e.g., smoking cessation)
and health care professional behaviour (e.g., following recommendations for acute
stroke care) as well as improving patient outcomes on both the short and long terms
[5, 6]. For decades, implementation science has informed how to improve the uptake
of trial results into practice, but lessons from the wider field of behavioural science
have only recently been applied to problems of trial design and delivery.
Clinical trials are complex and made up of multiple processes at various stages of
the trial lifecycle. These include, but are not limited to, question conception, trial
design, grant and protocol writing, planning trial delivery, recruitment, intervention
delivery, data collection, retention, analysis, dissemination of findings, and closedown.
Understanding the influences on trial processes as multiple behaviours (performed
by multiple actors), across the trial life cycle, has the potential for developing
more effective evidence-based strategies for improvement. For example, recruitment
can be further broken down to designing recruitment marketing materials (performed
by investigator teams), approaching all eligible participants (performed by trial
recruiters), signing of the consent form (performed by recruiters and participants),
etc. Once a trial process is broken down in this way, it becomes more amenable to
study and improvement with the tools of behavioural science. In what follows, we will
present detailed examples of how behavioural science has been applied to trial processes
in just this way.
When is a trial needed?
It can be difficult to determine when the evidence is strong enough to support the
widespread implementation of an intervention or when further RCTs may be required.
A study by Cuthbertson and colleagues sought to identify why the ICU community had
not widely adopted the use of selective decontamination (SDD) of the digestive tract
in ICU patients given the substantial evidence supporting the effectiveness of SDD
from 12 meta-analyses of 36 RCTs [7]. Using a Delphi survey based on the Theoretical
Domains Framework (TDF), the team were able to assess the factors affecting the clinical
behaviour and the appetite for a further RCT [7]. In brief, the TDF is a comprehensive
framework that proposes 14 theoretical domains that may influence behaviour (e.g.
knowledge, behavioural regulation, emotion) [8]. Priority domains can be determined
with regard to facilitators or barriers to performing the behaviour, which are then
targeted when developing behavioural interventions [9]. The Delphi study concluded
that the behaviours (in this case actively delivering SDD to ICU patients) would not
be more widely implemented without further supportive evidence given the concern regarding
the lack of appropriate/relevant outcomes in the existing trial contexts. This work
directly informed the successful funding of an international trial of SDD in ICU patients
with hospital mortality (primary) and antibiotic usage/resistance (secondary) as outcome
measures. This approach of analysing the profile of behavioural responses to determine
whether further (or indeed preliminary) trials are needed could be adapted for many
clinical questions as one of the first steps in designing an RCT.
Is a trial feasible?
There are many ways that assessments of trial feasibility can be conducted. One of
the benefits of assessing trial feasibility using a behavioural science approach is
that it offers detailed identification of barriers and potential facilitators to performing
key behaviours, which, in turn, drive the development of highly tailored, specific
solutions with real potential to overcome feasibility challenges. To inform a future
large-scale evaluation of a prehospital trauma intervention, ongoing work by Gillies
et al. is developing a detailed behaviour specification and ‘diagnosis’ to identify
the key challenges and opportunities for improving the feasibility and ultimate success
of the future trial [10]. Specifically, interviewing health care professionals who
are currently (or potentially would be) delivering the intervention will allow an
understanding of behavioural challenges in intervention delivery and will provide
evidence to help future strategies succeed for the future randomisation of participants.
Understanding the broad challenges for potential trial participants is also an important
barrier to overcome when recruiting to a trial. Some studies have used surveys informed
by behavioural theory, such as the health belief model (a model that assumes people’s
subjective health considerations determine health-related behaviour), to investigate
why patients choose to participate in trials [11, 12]. Brehaut and colleagues have
taken this a step further by developing a theory-guided TDF survey to identify the
challenges and opportunities to trial participation amongst potential participants,
rather than amongst those who have participated [13]. The use of tailored surveys
(which could be informed by the Brehaut approach) can be applied pretrial to determine
what the main barriers to trial recruitment are likely to be and to facilitate recruitment
strategies to address these barriers.
Do trial teams involve patients and public partners?
There are many motivators for involving patients and/or the public as research partners,
not least of all to ensure the research is relevant for those it seeks to serve. The
involvement of the patient and public partners in trials is now commonplace, but the
extent and depth of that involvement vary significantly. A recent study by Goulao
et al. surveyed trial teams to investigate the behavioural determinants of involving
patient partners in numerical aspects of trials using a TDF-based survey [14]. The
survey highlighted several domains that act as barriers (knowledge; skills and beliefs
about capabilities; resources; reinforcement) which could be targeted with behaviourally
specified interventions to improve current practice. This approach could be extended
to the involvement of other stakeholders in the trial design and delivery process.
What are the challenges to trial recruitment?
Recruitment to clinical trials has been identified as the top methodological priority
by UK Clinical Trials Units directors, evidencing its importance to many in the community
[15]. Understanding the main challenges relating specifically to trial recruitment
has been the focus of much research, but still very few high-quality, generalisable
solutions exist [16]. A number of studies have applied behavioural science to understand
the problems of trial recruitment. This has included conducting behavioural theory-informed
qualitative interviews to understand the potential challenges to recruitment to early
phase trials from the perspectives of clinicians and patients [17–20]. Findings from
these studies were then used to refine the design and conduct of future trials. In
addition to early phase trials, an exploratory TDF-based approach is currently being
used to understand the challenges faced by health care professionals when recruiting
pregnant women into clinical trials. The findings of the interviews will be used to
develop, and subsequently test, a behaviour change intervention targeting professionals
to improve the recruitment of pregnant women [21]. A similar approach has been used
to develop an implementation intervention to address low recruitment to cancer clinical
trials amongst rural and minority community urology practices [22]. This implementation
intervention, termed ‘learn/inform/recruit’ was deemed appealing and acceptable by
stakeholders [22]. The theory of planned behaviour (which proposes a model based on
three variables: attitudes, subjective norms, and perceived behavioural control, which
work together to predict the intention to perform a behaviour) has also been used
to explore trial recruitment [23, 24]. TPB was used as a guiding framework to assess
an intervention aimed at supporting patients in making fully informed decisions about
lung cancer trials, highlighting that the application of this approach can be used
with a range of theoretical approaches [23]. Using theoretical frameworks in this
way is helpful for the individual trials as it enables more direct identification
of possible strategies/techniques tailored to address the construct/factors more readily.
A further advantage is this approach also allows the opportunity to combine data across
studies and consider the meta-level findings of relevance across (possibly similar
phased) trials.
Whilst many of the examples to date have been based on the TDF, a range of other behavioural
theories and frameworks have been applied to problems of trial recruitment and retention.
A recent mapping review identified 31 studies that used a range of theories/frameworks
including the TDF, the theory of planned behaviour, social cognitive theory (describes
the influence of the actions of others, experiences, and environmental contexts on
an individual’s health behaviour), and others [Coffey et al. manuscript under review
[25, 26]]. Establishing whether there are ‘best fit’ theories and frameworks for different
trial problems is an important consideration for future work in this area.
How is the trial intervention delivered?
Process evaluations have long been embedded in randomised evaluations of clinical
interventions to understand various aspects of delivery [27]. Many of these have included
behavioural theories that have underpinned the behaviour change interventions being
evaluated or indeed used theories (from a wide range of fields) to understand the
mechanisms of change or barriers to implementation. However, less well addressed in
this literature is the application of behavioural science to unpack the behaviours
and behaviour change required for the delivery of clinical interventions within trials.
Two recent studies have aimed to do just that. The first was with health care professionals
delivering a trial of individualised temperature-reduced haemodialysis to explore
the behaviours involved in adjusting the temperature on a dialysis machine [28]. The
second was using a theory-based approach in data analysis gathered from both health
care professionals and patients to explore trial experience and beliefs and experiences
of the intervention, which in this case is catheter wash out policies [29].
What are the challenges to trial retention?
Similar to work on recruitment, a number of studies are now emerging that have conducted
qualitative interviews informed by behavioural frameworks to understand trial retention
behaviours such as postal questionnaire return and follow-up clinic attendance [30,
31]. Findings from the interview studies were then used to develop participant-centred,
theory-informed interventions to promote trial retention that have been codesigned
with stakeholders and will be tested in randomised evaluations [32].
The Cochrane reviews on interventions to improve recruitment to and retention in clinical
trials have found very little evidence of effect [16, 33]. The reviews largely include
interventions that were not designed as behaviour change interventions (BCIs) with
only a minority (< 5%) conceptualised as BCIs, yet the implicit aim of the majority
is to change participants’ recruitment or retention behaviour. For example, intervention
categories in both reviews include incentives and rewards (which target the theoretical
behavioural domain of reinforcement), reminders and prompts (target theoretical domain
of memory, attention and decision-making, environment context, and resources), and
improvements to information (target theoretical domain, knowledge). Yet, the design
and delivery of these interventions do not include the explicit inclusion of behaviour
change input, nor are these interventions informed by the bodies of knowledge in the
behavioural sciences. Deconstructing interventions into their behaviour change techniques
(BCT, defined as the smallest ‘active ingredient’ of an intervention that can be used
alone or in combination) has the potential to identify possible ‘active ingredients’
which could be enhanced in future replications of evaluations or implementation [34].
Duncan et al. demonstrated the potential value of this approach with preliminary work
identifying BCTs within interventions shown to improve retention [35]. The findings
identified that BCTs were used amongst the interventions but not labelled as such
(notably incentives and prompts—both behavioural strategies) and that several implicit
BCTs were applied in both intervention and control strategies. The need to explicitly
incorporate BCTs during the design of interventions to target recruitment and retention
behaviours (and others relevant for trial conduct) is key. A small number of studies
have developed behaviour change interventions for trial retention by incorporating
BCTs into covering letters of questionnaires, newsletters, and also use of trial stickers
on envelopes (to act as prompts) [36]. Preliminary evaluations of these behaviourally
focussed trial process interventions are showing promise, but replication and further
research to include patient input and assessment are required to maximise their potential
[33, 36]. Creating a shift in the conceptualisation of recruitment and retention interventions
to be considered (during design and delivery) as behaviour change interventions may
provide more potential for more focused assessment of effectiveness and may enhance
replicability.
It is important to highlight that the examples provided here are not an exhaustive
list but are exemplars from key trial life cycle stages that serve to show where existing
empirical studies have demonstrated the potential for a behavioural approach to address
trial process problems (see Fig. 1). In particular, the challenges that many trials
have faced during the COVID-19 pandemic (such as the move to remote delivery of recruitment,
interventions, and follow-up) also provide a wealth of opportunities to apply behavioural
approaches to generate evidence-informed solutions from the perspective of trial teams,
regulators, and trial participants. A varied range of other trial process problems
could also benefit from this approach including (but not limited to) choosing outcomes,
participants’ experience, and sharing of trial results with trial participants. In
addition, several behavioural approaches such as multiphase optimisation strategies
(MOST), intervention mapping, and ‘nudging’ (a recent focus in the behavioural economics
literature) could also warrant investigation in the future [37–39].
Fig. 1
Trial lifecycle highlighting example trial processes and potential application of
the behavioural science approach
Core considerations for applying behavioural approaches to trials
It is of greater importance than ever to ensure that any strategies or approaches
used in trials are sensitive to the different needs of diverse trial populations.
For example, the majority of interventions targeting trial recruitment and retention
to date have been developed by and tested in largely White populations [16, 33]. A
recent mapping review of the published studies that used behavioural strategies to
understand or develop solutions to problems of trial recruitment and/or retention
identified that 35% of studies (n = 11) were set within underserved populations (Coffey
et al., manuscript submitted [25]). This may suggest the potential for behavioural
approaches to begin to address some aspects of inclusion of underserved communities
in trials, ensuring that future research considers equitable participation for all
[40]. However, the systemic structural and institutional challenges of ensuring opportunities
and access to research are available for all and will also require work that may extend
beyond a behavioural framework.
Similarly, much of the work in this space is being conducted in developed countries,
but there are now projects being developed which also plan to use a behavioural science
approach in trials in low- and middle-income countries. One such study is focussing
on the behaviours of postal questionnaire return and follow-up clinic attendance after
surgery in a number of LMICs (e.g. India, South Africa, Philippines). This project
will apply the capabilities, opportunity, and motivation behaviour system (COM-B)
to provide a behavioural diagnosis and identify intervention functions that then help
to assess the relevance of existing interventions to modify target behaviours and
as such ‘treat’ the problems [41].
It is also worth considering not just how behavioural science can maximise learning
opportunities at key stages of trial design and delivery, but also its potential value
across different phases of trials and trials of various intervention types, e.g. clinical
trials of investigational medicinal products (CTIMPs) and non-CTIMPS. For example,
we know that the motivations of participants to participate first in human studies
are largely different to the motivations of those who participate in later stage pragmatic
effectiveness trials and are often linked to risk [42, 43]. It may also be that these
approaches could be more or less acceptable for trials in particular clinical contexts
(e.g. emergency care) or populations (e.g. children or adults who lack capacity).
Considerations of risk, whether in relation to the stage of evaluation or the interventions
under investigation, also raise another important consideration.
There will of course be some core challenges for trial teams in applying a behavioural
approach to trials. Some of these may relate to trial teams lacking confidence or
knowledge in how to apply particular theories or frameworks. The best option would
likely be to include behavioural scientists as part of the trial team but failing
that, tools that make this approach accessible and implementable will be key. A good
starting point exists amongst key papers for health behaviour change, in particular,
some worked examples of how to apply the AACTT framework [4], a step-by-step guide
to using the TDF [9], a guide for constructing questionnaire informed by the TPB [44],
and a core textbook on the behaviour change wheel which covers COM-B interventions
and includes lots of practical examples of application albeit in a different context
[45].
The ethics of behaviour change interventions requires further exploration. Will certain
behavioural approaches, and therefore particular behaviour changes interventions,
be more ethical in some trials over others? For instance, the use of ‘nudges’ in informed
consent has been criticised on ethical grounds [46]. But should behaviour change interventions
be conceptualised as nudges, and outside of the consent process, what is their impact
on the autonomy of trial participants? Where are the limits to when behaviour change
interventions become more or less acceptable, practically and philosophically, in
the context of trial-related behaviours?
One ethical advantage to framing trial processes as complex behaviours is that, by
unpacking the various behaviours, actors, and influences involved in any process,
it becomes clear how trial success is a social phenomenon—that is, trial funders,
investigators, recruiters, and patients all need to act in particular ways at particular
times in order for the trial to achieve its scientific and social aims. For example,
the model of the recruitment process that we described above includes behaviours,
and therefore potential interventions, that would target investigators, recruiters,
or patients. By contrast, the existing literature on nudges in trials has tended to
focus almost exclusively on interventions that would target patient behaviour—who
are often going to be the most vulnerable stakeholders. Whilst focusing on patient
behaviour is certainly important, by widening the behavioural lens, so to speak, the
model we advocate opens up possibilities to study and improve trial behavioural with
a more holistic, and potentially more equitable, approach.
Lastly, it will be important to ensure that behavioural interventions or approaches
seeking to address trial problems are evaluated using robust approaches such as Studies
Within A Trial (SWATs), or other appropriate study designs, to determine the effectiveness
and mechanisms of effect and to identify potential behavioural confounders in trial
conduct [47]. Ensuring interventions and processes for evaluation are detailed and
pre-specified in publicly available protocols will help to encourage replication by
other teams across a range of trials.
The added value of behavioural approaches to trial design and conduct
There is considerable potential for the behavioural approach to trials in that it
offers significant flexibility. For example, this approach can be applied before a
trial is started, can be implemented with multiple methods, and is theory-informed.
A further added value component of developing the methodology around behavioural optimisation
and operational strategies for clinical trials will be the greater potential for sharing
resources and learning across data sets. The potential for aggregation of diagnostic
behavioural data across trial types, collected using the same tools, to explore the
over-arching challenges and opportunities facing clinical trials has huge potential.
Further enhancing the potential for learning across trials and the application of
transferable solutions should be a focus going forward. Current research to determine
the best practices for sharing qualitative data in clinical trials will demonstrably
help move this agenda forwards [48].
Conclusions
Trialists are implicitly using behavioural approaches already. Fully engaging with
the science may help to make more explicit decisions for what behavioural strategies
to include and why at each stage of a trial. This explicit operationalisation of a
behavioural approach would enable the greater potential for generalisability and shared
accumulation of evidence to ensure that the funding, and the time and effort trial
teams and trial participants contribute are maximised. Ultimately, accelerating the
availability of new therapies to better the health of the population. Adopting a behavioural
approach to address problems of trial design and conduct has been shown to be an effective,
reproducible, transparent, and generalisable approach. As this is an emerging field,
however, thoughtful consideration and empirical work to establish the most suitable
approaches to a range of trial problems and contexts, whilst developing implementable
methodology supported by appropriate resources, is a key next step.