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Rationale: Psychedelic research continues to garner significant public and scientific interest with a growing number of clinical studies examining a wide range of conditions and disorders. However, expectancy effects and effective condition masking have been raised as critical limitations to the interpretability of the research. Objective: In this article, we review the many methodological challenges of conducting psychedelic clinical trials and provide recommendations for improving the rigor of future research. Results: We found that although some challenges are shared with psychotherapy and pharmacology trials more broadly, psychedelic clinical trials have to contend with several unique sources of potential bias. The subjective effects of a high-dose psychedelic are often so pronounced that it is difficult to mask participants to their treatment condition; the significant hype from positive media coverage on the clinical potential of psychedelics influences participants’ expectations for treatment benefit; and participant unmasking and treatment expectations can interact in such a way that makes psychedelic therapy highly susceptible to large placebo and nocebo effects. Specific recommendations to increase the success of masking procedures and reduce the influence of participant expectancies concern study development, participant recruitment and selection, incomplete disclosure of the study design, choice of active placebo condition, as well as the measurement of participant expectations and masking efficacy. Conclusion: Incorporating these design elements is intended to reduce the risk of bias in psychedelic clinical trials and thereby increase the ability to discern treatment-specific effects of psychedelic therapy
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Great Expectations: Recommendations for improving the methodological rigor of psychedelic clinical trials
Jacob S. Aday*, Boris D. Heifets**, Steven D. Pratscher, Ellen Bradley, Raymond Rosen, & Joshua D. Woolley
Author Note
List of Authors / Affiliations:
Jacob S. Aday, Ph.D. [*Corresponding author]
401 Parnassus Ave.
San Francisco, CA 94143
Department of Psychiatry and Behavioral Sciences
University of California, San Francisco
Boris D. Heifets, M.D., Ph.D. [**Co-first author]
Department of Anesthesiology, Perioperative and Pain Medicine
Stanford University
Steven D. Pratscher, Ph.D.
Department of Community Dentistry and Behavioral Science
Pain Research and Intervention Center of Excellence
University of Florida
Ellen Bradley, M.D.
Department of Psychiatry and Behavioral Sciences
University of California, San Francisco
San Francisco VA Medical Center
Raymond Rosen, Ph.D.
Department of Psychiatry and Behavioral Sciences
University of California, San Francisco
Joshua D. Woolley, M.D., Ph.D.
Department of Psychiatry and Behavioral Sciences
University of California, San Francisco
San Francisco VA Medical Center
Acknowledgements: We would like to thank members of the Translational Psychedelic Research (TrPR) Program
at University of California, San Francisco (UCSF) for providing comments on this manuscript.
Conflicts of Interest Statement: JDW was a paid consultant for Silo Pharma and Filament Health last in June 2021.
BDH is a paid consultant for Clairvoyant Therapeutics. None of the other co-authors have any conflicts of interest to
Rationale: Psychedelic research continues to garner significant public and scientific interest with a growing number
of clinical studies examining a wide range of conditions and disorders. However, expectancy effects and effective
condition masking have been raised as critical limitations to the interpretability of the research.
Objective: In this article, we review the many methodological challenges of conducting psychedelic clinical trials
and provide recommendations for improving the rigor of future research.
Results: Although some challenges are shared with psychotherapy and pharmacology trials more broadly,
psychedelic clinical trials have to contend with several unique sources of potential bias. The subjective effects of a
high-dose psychedelic are often so pronounced that it is difficult to mask participants to their treatment condition;
the significant hype from positive media coverage on the clinical potential of psychedelics influences participants’
expectations for treatment benefit; and participant unmasking and treatment expectations can interact in such a way
that makes psychedelic therapy highly susceptible to large placebo and nocebo effects. Specific recommendations to
increase the success of masking procedures and reduce the influence of participant expectancies are discussed in the
context of study development, participant recruitment and selection, incomplete disclosure of the study design,
choice of active placebo condition, as well as the measurement of participant expectations and masking efficacy.
Conclusion: Incorporating these design elements is intended to reduce the risk of bias in psychedelic clinical trials
and thereby increase the ability to discern treatment-specific effects of psychedelic therapy.
Keywords: Psychedelics, psychedelic therapy, clinical trials, treatment expectations, expectancies, placebo effect,
masking, recommendations
Recent high-profile clinical trials with psychedelic drugs have highlighted challenges related to rigorous
study design and condition masking that have simmered in both psychotherapy and pharmacology research for
decades (e.g., Başoğlu et al. 1997; Enck and Zipfel 2019). Interrelated methodological challenges regarding the
selection of appropriate control conditions, masking (also known as blinding
), and expectancy effects have clouded
our understanding of the source of clinical improvements in psychedelic studies and, in fact, across medicine.
Studies on psychedelic therapy are particularly challenging as they must address methodological issues inherent to
both psychotherapy and pharmacology research as well as issues that are distinctly problematic to the field, such as
“hype” and salient psychoactive effects that compromise masking. In this paper, we delineate how many of the
methodological limitations that have been raised as critiques of psychedelic science are common challenges across
psychotherapy and pharmacology research more broadly that are in need of addressing. This review allows us to
share lessons across disciplines and provide recommendations for improving future psychedelic and non-
psychedelic research. We conclude by highlighting that psychedelic studies should not be held to a different
standard than other forms of psychotherapy or pharmacology research, and that the fields can leverage important
lessons from one another by recognizing their shared limitations. To this end, we provide practical methodological
recommendations to measure and manage expectations as well as to enhance masking in psychedelic studies. These
recommendations can be deployed more broadly across clinical trials to improve the rigor and reproducibility of
future research.
Treatment-nonspecific effects
To begin, we review the various reasons for including control conditions in clinical studies and examine
what exactly is being controlled. In any clinical trial, changes in symptoms can be observed because of treatment-
specific or treatment-nonspecific effects (Turner et al. 1994). Treatment-specific effects are changes directly
attributable to the independent variable or intervention under study (e.g., drug dose or psychotherapeutic approach).
Treatment-nonspecific effects are changes not related to the specific treatment arm (i.e., common to being in any
clinical trial), as well as placebo and nocebo effects related to treatment expectations (Table 1). Including certain
In recent years, the term “masking” has been used in place of “blinding”; here, we have opted to use the term
“masking” but consider the terms synonymous.
control conditions allows the trialist to filter out contributions of treatment-nonspecific effects from treatment-
specific effects to attribute clinical improvements to the intervention under study (Fig 1a).
Fig. 1 Treatment non-specific effects in clinical trials. a) Hypothetical results of a clinical trial to delineate the
sources of treatment-specific and treatment-nonspecific effects. Including placebo and no treatment control
conditions allows trialists to identify treatment-specific effects (figure inspired by Wampold et al. 2016) b) In a clear
illustration of expectancy effects, Bingel et al. (2011) measured participants’ pain intensities before (i.e., Baseline)
and after receiving remifentanil while manipulating participant expectancies across three groups (e.g., No
expectancy, Positive expectancy, or Negative expectancy). They found that priming positive treatment expectancy
doubled the analgesic effect of remifentanil when compared to no expectancy. In contrast, inducing negative
treatment expectancies eliminated the analgesic effect. c) Gold et al. (2017) demonstrated that treatment effect sizes
vary as a function of the type control group utilized.
Key Terms
Confounding Variable
A factor other than variables under study that influences the dependent variable.
Hawthorne Effect
Changing one’s behavior as response to the interest, care, or attention received through
observation and assessment.
Regression to the
Tendency for extreme scores to return to average over time.
Symptom resolution independent of the study manipulation as a function of an
biological or psychosocial change.
Process Expectancies
Expectations regarding what will happen during the treatment.
Outcome Expectancies
Expectations regarding the outcome of the treatment.
Active Placebo
A control condition that closely resembles the presentation and side effects of the
experimental treatment without providing the therapeutic effects.
Masking Efficacy
Degree to which participants are unaware of their treatment arm assignment
Placebo Effect
Treatment-nonspecific improvement in symptoms attributable to contextual factors, such
participants’ positive expectations regarding the treatment.
Nocebo Effect
Treatment-nonspecific worsening of symptoms as a result of contextual factors, such as
negative expectations regarding the treatment.
Michael Pollan
Heightened positive expectations regarding the efficacy of psychedelics in recent years
stemming from Michael Pollan's book, How to Change Your Mind.
Table 1. Key terms and definitions
The natural history or spontaneous variation of any given disease under study may be the least controllable
source of treatment-nonspecific change that can confound clinical trial interpretation. Symptoms can change (e.g.,
spontaneous remission) independently of the study intervention as a function of an unidentified biological or
psychosocial change in the individual’s life. Additionally, in most clinical trials, participants are screened and
selected based on a minimum criteria of symptom severity, and many individuals may be especially motivated to
seek out research studies when their symptoms peak in severity (Whitney and Von Korff 1992). Subsequent
measurements using the same scale may show an apparent improvement. This "regression to the mean" rather than a
true treatment-specific effect may lead researchers to erroneously conclude a treatment is effective when participants
may have improved over time without any treatment (Hengartner 2020). Regression to the mean is a ubiquitous
statistical phenomenon that results whenever cases are selected for follow-up based on abnormally high or low
scores at baseline, demonstrated in observational studies and clinical trials, and across multiple diseases (Bland and
Altman 1994). Changes due to the natural course of the condition and regression to the mean are considered
theoretically distinct but in practice are difficult to disentangle.
Participant behavior can also change simply as a consequence of the interest, care, or attention received as
part of a study. This well-established psychological phenomenon is known as the Hawthorne effect (Sedgwick and
Greenwood 2015). This effect is associated with outcomes as diverse as workplace productivity to cognitive
functioning and quality of life in dementia patients (McCarney et al. 2007). Notably, researchers and study
personnel, not just participants, can be susceptible to Hawthorne effects, thereby influencing clinical outcomes
(Sedgwick and Greenwood 2015). That is, those caring for participants in an experimental trial are under increased
scrutiny and observation as compared to those operating in an unobserved clinical setting, and this difference may
impact both quality and quantity of patient care. This bias can cause an overestimation of an experimental
treatment’s therapeutic effect due to clinical improvements from treatment-nonspecific factors. A distinct but related
issue is that the simple act of repeated observation and measurement of behaviors and symptoms can alter those
same behaviors and symptoms. Repeated pain assessments can increase pain chronicity (Ferrari and Russell 2010),
asking about illicit drug use can decrease use (D’Onofrio et al. 2012), and daily symptom assessments can worsen or
improve symptom severity in PTSD (Dewey et al. 2015; Pederson et al. 2014). Drawing extra attention to an issue
can lead to symptom amplification or may provide more opportunities to resolve it (Barsky and Klerman 1983). In
either case, it is clear that simply enrolling in a clinical trial can influence symptoms regardless of treatment
Taken together, issues related to the natural course of the disease, regression to the mean, and observation-
related changes highlight that there are many mechanisms by which symptoms may change in a clinical trial
irrespective of the treatment being tested. It is therefore important to include, at a minimum, control arms that do not
receive the treatment, as treatment-nonspecific factors confound experimental and control arms to a similar extent.
However, the simple inclusion of an untreated comparison group may not be enough to isolate treatment-specific
effects (Gold et al. 2017; Enck and Zipfel 2019). Participants often have expectations regarding the efficacy of the
treatment under study. If participants have knowledge about their treatment arm assignment (e.g., in an open-label
study), or gain knowledge through their subjective experience (e.g., having a psychedelic trip) or somatic symptoms,
their expectations about therapeutic efficacy can affect their clinical outcomes. This problem is common to most
psychotropic trials (e.g., selective serotonin reuptake inhibitors [SSRIs]; Hieronymus et al. 2018) and is particularly
salient for high-dose psychedelic trials in which subjective drug effects are especially pronounced. Without effective
condition masking, it is virtually impossible to maintain the independence of the main variable under study (i.e., the
treatment), as it is confounded by participant expectations. In addition to influencing participant outcomes, baseline
expectancies about a treatment’s therapeutic effects can also impact masking efficacy (i.e., whether participants are
aware of their treatment arm assignment), as those with noticeable improvements in symptoms often assume they
were assigned to the active treatment group (Sackett 2007). We now consider several specific expectations and how
they interact with masking and treatment outcomes.
Expectancies in psychotherapy and pharmacology research
Tambling (2012) differentiates between expectations about the process of treatment and expectations about
the outcome of treatment. In the case of psychotherapy, process expectations are expectations about what will
happen during therapy (e.g., patient’s thoughts about roles they and their therapist will assume, characteristics of
their therapist, and what sessions will entail). In pharmacological trials, process expectations can include
expectations about any acute drug effects, including psychoactive effects. Process expectancies may be particularly
pertinent with psychedelic drug trials as expectations about the acute effects of the drugs are shaped by hours of
psychotherapy, widespread representations in popular media, and a highly ritualized process of drug administration.
When these expectations are matched by experience, a study participant may be especially confident in unmasking
their treatment arm assignment.
Outcome expectations refer to whether the treatment is anticipated to reduce symptoms. In the case of
psychotherapy, studies suggest that outcome expectancies are stronger predictors of therapeutic effects than are
specific psychotherapy techniques (Horvath et al. 2011; Webb et al. 2010). Positive outcome expectations are
related to stronger alliance with the therapist, which is associated with better outcomes (Vîslă et al. 2018; Yoo et al.
2014). A recent, well-powered meta analysis (N = 12,722) compared patient outcome expectancies and clinical
outcomes across a variety of diagnoses and psychotherapy interventions, revealing that greater positive outcome
expectancy was consistently associated with better treatment results (Cohen’s d = 0.36; Constantino et al. 2018).
Outcome expectancies also have strong effects relative to the active effects of psychotropic drugs (Rutherford and
Roose 2013). In trials where patient-reported outcomes are the primary efficacy measures, the effects of outcome
expectancies are particularly strong (Atlas 2021). Fillingim and Price (2005) concluded that, in placebo analgesia
studies outcome expectancies accounted for up to 81% of variance in post-treatment pain ratings. Thus, across
clinical research contexts, participants’ outcome expectations about the specific treatment being administered
influence clinical outcomes.
Negative outcome expectations can also influence clinical outcomes. When individuals are aware that they
have been assigned to a treatment that they believe is unlikely to improve their symptoms, negative expectation
alone can worsen patient outcomes, which is known as the nocebo effect (Gold et al. 2017; Planès et al. 2016). This
effect was elegantly demonstrated in a study with remifentanil, an opioid analgesic, which found that priming
negative expectations about the treatment completely negated the analgesic effect of the drug (Bingel et al. 2011;
Fig. 1b). Furthermore, if a participant has positive expectations about the proposed experimental treatment but
comes to believe they have been assigned to a control condition, outcomes may worsen as a result of disappointment
or the belief that one will not improve without being assigned to the active treatment (Furukawa et al. 2014). Indeed,
those put on a waitlist control condition typically have worse outcomes than those assigned to active placebo, or
even no treatment, as they have less reason to expect an improvement in symptoms (Patterson et al. 2016). With
waitlist control designs, those in the control condition do not receive treatment until after a waiting period, where
they are compared with the active treatment group. However, participants are generally aware that they are in a
control condition during their waiting period and thus may not expect to see improvements, whereas the active
treatment group likely has the opposite expectation. Therefore, waitlist control designs may artificially inflate
intervention effect size estimates (Fig. 1c; Cunningham et al. 2013; Zhipei et al. 2014). Possibly illustrating this
effect, in a waitlist-control study of psilocybin for the treatment of major depressive disorder, waitlisted participants
reported higher anxiety scores at the end of the waitlist period compared to the beginning, enhancing the apparent
therapeutic effect of psilocybin (Davis et al. 2021). The crucial role of expectancies in treatment outcomes across
clinical contexts underscores the need for trial designs that control for expectation-related improvements, which we
elaborate on in the following sections.
Importantly, outcome expectancies are rarely measured in psychotherapy and pharmacology studies
(Doering et al. 2014). Constantino and colleagues (2010) noted that expectancies have often been thought of as
nuisances to clinical research and disregarded rather than being considered important ingredients of the therapeutic
process. Furthermore, the few studies that have included assessments of treatment expectations have used brief and
study-specific measures, meaning there is surprisingly little overlap between studies in how expectations are
quantified (Tambling 2012). Moreover, there is no manual or expert consensus for managing expectancies despite
the extensive evidence of the important role of expectancy in treatment responses (Zilcha-Mano et al. 2019).
Collectively, these findings highlight that challenges related to participant expectations are common across
psychotherapy and pharmacology research, and that, to date, there is no standard for addressing expectation-related
Psychedelic research and expectations
Briefly, the typical structure of a modern psychedelic therapy clinical trial involves an arduous screening
process, multiple preparation sessions, single or multiple drug dosing sessions, and integration sessions after drug
administration (Fig. 2). The preparation sessions are used for several purposes, including to build rapport between
the participant and the therapists or facilitators
, to inform the participant about common or possible psychedelic
drug experiences, to reassure the participant’s safety with dosing day procedures, and to assist with establishing the
patient’s intention(s) for their dosing session. The drug dosing session is highly structured with two therapists
accompanying the participant throughout the 68-hour session in a comfortable environment. During the dosing
session, participants often remain reclined on a couch with eyeshades and headphones for music and are encouraged
to focus on their inner experience throughout the drug session, exploring any content that arises with an open and
accepting mindset. In the days following drug dosing, the participant works with the same clinical team in
integration sessions to make meaning of their experiences and to incorporate any insights they may have had into
their life going forward. With these fundamental elements of psychedelic therapy, it is best considered a complex,
multicomponent intervention that includes aspects of both pharmacology and psychotherapy. Notably, throughout
the course of a psychedelic therapy trial, a participant’s process expectations and outcome expectations are subject
to change as they gather more information about possible drug effects, approach the sessions in a certain way (e.g.,
trust, let go, be open), and experience the actual drug effects. Hereafter, we refer to this package of procedures as
psychedelic therapy and acknowledge all of these aspects may determine treatment-specific effects.
Notably, there is significant debate about the proper terminology for the people who provide the preparation and
integration and who monitor participants during the dosing session. “Guide”, “sitter”, “facilitator”, “therapist”,
“monitor”, and other terms have been proposed and have their advocates and detractors. The intensity of these
debates highlights the truth of the old joke that “Scientists would rather use each other’s toothbrushes than use each
other’s terminology”. We use the term “facilitator” throughout this manuscript without taking a strong stance on
which term is the most correct.”
Fig. 2 Stages of Psychedelic Therapy. Psychedelic therapy typically involves preparation, dosing, and
integration sessions.
Participants’ expectations as well as intentions (i.e., what they desire from the psychedelic experience) are
thought to play a prominent role in the drugs’ acute and long-term effects (Olson et al. 2020). Some have even
termed psychedelics “placebo enhancers”, as they can enhance the perception of meaningfulness (Hartogsohn 2016,
2018) and induce a state of suggestibility (Carhart-Harris et al. 2015). It has been noted across popular culture that
psychedelic experiences are heavily influenced by one’s expectations, and some have gone as far as to claim “no
other class of drugs are more suggestible in their effects” (Pollan 2018). Hartogsohn (2021) noted that the
fundamental role of expectations in psychedelic drug effects may reconcile the paradoxical conceptions that have
been held about the drugsviews that are so varied, it at times sounds as though scientists are discussing completely
different drugs (e.g., they have been used to both treat mental illness and to model psychosis). Utilizing pre-dosing
expectations as well as the acute state of suggestibility induced by psychedelics in tandem may be an important
component of the therapeutic process with psychedelic therapy, but this combination can also be co-opted for
nefarious purposes. Historically, psychedelics have been used by cults as well as investigated for their alleged
potential in “mind control” by the US government during MK Ultra (Cusack 2020; Kogo 2003; Ledford 2021).
There is even concern about psychedelics’ potential for changing beliefs (e.g., political or metaphysical; de Wit et al.
2021; Pace and Devenot 2021; Timmermann et al. 2021) and memories, though that is beyond the scope of this
review. Therefore, it may be ethical to include an enhanced informed consent process about possible belief changes
induced by psychedelic therapy prior to enrolling participants into a clinical trial (Smith and Sisti 2021).
Although pre-dosing expectations have long been thought to be integral to the effects of psychedelics
(Eisner 1997; Leary et al. 1963), very few studies have actually measured them. A recent “microdosing” (i.e., sub-
hallucinogenic dosing) study found that positive expectations regarding psychedelics at baseline predicted
subsequent increases in wellbeing irrespective of whether a participant received a psychedelic or an inert placebo
(Kaertner et al. 2021). Similarly, a large-scale, placebo-controlled study of microdosing found that participants
experienced comparable improvements in mood and cognition in the drug and placebo conditions (Szigeti et al.
2021). Another microdosing study found that after controlling for baseline expectancies, there was no difference
between psilocybin and placebo on measures of awe (van Elk et al. 2021). However, to the best of our knowledge,
only a single “macrodosing” (i.e., full hallucinogenic dosing) trial has recorded pre-treatment expectancies. An
open-label ayahuasca study found that participants endorsing an expectancy of favorable change in neuroticism,
extraversion, and conscientiousness in response to ayahuasca showed a greater decrease in neuroticism and greater
increases in extraversion and conscientiousness following ayahuasca administration compared to participants with
lower expectancies receiving the same treatment (Weiss et al. 2021). A recent systematic review found those with a
recreational intention with psychedelics tended to have less challenging experiences when they used a psychedelic
(Aday et al. 2021; Haijen et al. 2018), again suggesting that what one desires and expects to experience with a
psychedelic influences the drug’s effects. Thus, the few studies that have measured expectations and intentions to
date support the prevalent assumption that pre-dosing expectations interact with psychedelic drug effects and
outcomes. Whether these same considerations apply to other drug classes (e.g., such as psychostimulants) is
unknown, further emphasizing the need to measure and report therapeutic expectations in a systematic way across
areas of clinical research.
High-dose psychedelic trials may also be particularly susceptible to a type of bias termed “hype” or the
“Michael Pollan Effect'' (Carpenter 2020; Table 1). Some have argued that psychedelic therapy marks the most
important innovation in psychiatry since the introduction of SSRIs, or possibly ever, and it is not uncommon to hear
claims about the potential for psychedelics to “change the world” from industry leaders and enthusiasts (Dupuis
2021). This pervasive messaging may lead to amplified positive expectations compared with many other types of
clinical interventions and perhaps motivates participants to “not let the movement down” by failing to clinically
improve. This notion was illustrated in a recent ayahuasca study (Aday 2021), where one of the participants asked us
(JSA) if they should stop participating in the study because they did not have a mystical experience and did not want
to “ruin the research”. In our experience recruiting for psychedelic studies, many potential participants explicitly
express a sense of pride and excitement in participating in a psychedelic trial as well as strong confidence in the
benefit of psychedelics to their mental wellbeing. These motivations for participation and heightened positive
expectations coupled with the functional unmasking that often occurs make identification of a treatment-specific
effect in high-dose psychedelic trials particularly challenging and highlights the need for study designs that properly
mask participants to conditions (Burke and Blumberger 2021).
Certain aspects of the study personnel, environmental context, and measures included in psychedelic drug
trials may contribute to enhanced expectations as well. For example, the use of two therapists at a time and rituals
like placing a fresh rose in the room on dosing day may serve to amplify positive expectations and signal that the
experience is of particular significance (Gukasyan and Nayak 2021). Additionally, outcome expectancies of
psychotherapists have been shown to have a marked effect on treatment engagement and clinical outcomes across
therapeutic approaches (Doering et al. 2014; Leake and King 1972), suggesting this may be a treatment-nonspecific
factor relevant to psychedelic studies as well. Lastly, the specific measures used in psychedelic trials can influence
participant expectations; one study volunteer noted “I long to see some of the stuff hinted at in the questionnaire” in
reference to questions they encountered on the Mystical Experience Questionnaire (MEQ; MacLean et al. 2012;
Pollan 2018). Thus, in addition to preexisting attitudes about psychedelics, certain expectations may be engendered
by characteristics of the trial.
Modern era clinical research design elements
Next, we will describe many of the study designs and methods that have been attempted to manage these
issues across psychotherapy and pharmacology trials to-date. Open-label study designs, in which both the patient
and study personnel are aware of what specific treatment is administered, most closely resemble how psychotherapy
and psychotropic drugs are administered in real-world, non-research settings. Although high in ecological validity,
this type of design does not control for most of the confounding nonspecific factors that can affect clinical outcomes
(e.g., Hawthorne effect, spontaneous variation of symptoms, regression to the mean).
Some treatment-nonspecific factors, such as regression to the mean, can be controlled if sufficient data are
available at both the individual and group level, as a precise mathematical formula can be developed to predict the
actual regression effect in a given experimental setting (Barnett et al. 2004). These authors have identified specific
experimental strategies to mitigate or manage expected regression to the mean effects in a clinical trial. First, they
recommend selecting cases based on multiple baseline observations. Requiring that eligible subjects have stable test
scores over two or more baseline assessments will predictably reduce, although not necessarily eliminate, regression
to the mean. Second, the authors suggest correcting for regression to the mean effects in the analyses by using either
ANCOVA modeling or application of a correction formula. Of note, neither of these strategies have been
systematically applied in studies of psychedelic therapy. Third, investigators may consider a waitlist control
condition, although we refer the reader to limitations to this approach noted previously.
The double-blind randomized controlled trial (RCT) is considered the gold standard design for identifying a
true treatment-specific effect, under conditions where neither investigator nor participant know their treatment
allocation. An RCT entails randomly assigning participants to treatment or control conditions and withholding
knowledge of treatment arm assignment from participants and study personnel (i.e., masking). Effectively executing
this design controls for expectancies as it is unknown which treatment each participant received, and therefore
treatment-nonspecific factors can be ruled out as the source of treatment arm outcome differences. Treatment arm
masking in RCTs is best achieved with active placebo comparators, in which the control condition is structurally
equivalent and closely resembles the presentation and side effects of the experimental treatment without providing
the therapeutic effects (Doering et al. 2014). Inert but identical looking pills that lack the side effects of the
treatment condition (i.e., inactive placebos) are often used but may be easy for participants to detect, and subsequent
nocebo effects may confound analyses.
There has been considerable debate that continues today about what constitutes a proper “inert” placebo for
psychotherapy in the same sense as an “inert” placebo in pharmacology, as some have argued that “there is no such
thing as inert psychotherapy” (Rosenthal and Frank 1956; Wampold et al. 2016). In the context of psychedelic trials,
to date, the psychotherapy component has been held constant across the treatment and control conditions, making
this issue less relevant for the field for now. However, as researchers delineate the nuances of what specific forms of
psychotherapy are most synergistic with psychedelics, this potential confound will become an increasingly
important issue to address (Horton et al. 2021). A related challenge with psychedelic studies is that unmasking may
lead to differences in how the psychotherapy component is administered and received, given that the context of the
therapy shifts once the participant and/or therapist becomes aware of the treatment arm assignment. Therefore,
improved masking procedures must be implemented into psychedelic science for the field to meet the assumptions
of the current gold standard clinical trial design.
Crossover RCT designs have been used in many pharmacological studies as an efficient way to account for
treatment-nonspecific confounds because participants act as their own control. In a crossover design, participants are
randomly assigned to a sequence of treatments where they receive both the experimental and placebo treatments but
at different timepoints (i.e., placebo then experimental treatment or vice versa). A major weakness of crossover
designs, however, is the potential for carryover effects (i.e., the therapeutic benefits could ‘carryover’ after the first
treatment and misrepresent the true effect of the second treatment). Carryover effects are especially concerning in
psychedelic trials because the effects of psychedelic therapy in some cases have been shown to be durable for over a
year (Griffiths et al., 2008; Johnson et al., 2017; see Aday et al. 2020b for review). Thus, even a 12-month washout
period is unlikely to achieve a return to pre-treatment levels on the variable of interest, which biases within-person
analyses and threatens the validity of conclusions that can be drawn. Moreover, masking is likely to be compromised
in crossover designs that involve a psychoactive drug (Wilsey et al. 2016). For example, almost all participants
accurately identified their treatment condition in a crossover study that used psilocybin and niacin as a placebo
control (Grob et al. 2011). Thus, simple crossover designs may be more confounded than a parallel (between-
subjects) RCT design for psychedelic trials.
We have repeatedly noted the importance of adequate masking in double-blind RCTs, and emphasize that it
is impossible to know if the double-blind or masking was achieved without testing masking efficacy. Surprisingly,
however, masking efficacy typically goes unmeasured or unreported in psychotherapy and pharmacology trials
(Doering et al. 2014). Many researchers report their studies as being “double-blind” without testing such claims
(Başoğlu et al. 1997). A systematic review on methods of masking in randomized controlled trials with
pharmacologic treatments concluded that reporting of condition masking is generally ‘quite poor’, and based on
trials that have tested the success of masked methods, a high proportion of studies are effectively unmasked
(Boutron et al. 2006; Rabkin et al. 1986). This corroborates a recent systematic review of studies published in top
psychiatry journals in 2017 and 2018, which found that only 59% of the trial reports included adequate reporting of
masking outcomes (Juul et al. 2020), as well as a meta-analysis that indicated a large majority of antidepressant
RCTs do not assess masking efficacy, and when measured, masking often fails (Scott et al. 2022). Similarly, a
comprehensive literature search found that masking was not maintained in 20/23 “double-blind” studies examining
psychotropic drugs (Fisher and Greenberg 1993). The authors noted improvements in patient symptomology and
side effects from the active drug were the major cause of unmasking. Long-term masking can be difficult, if not
impossible, to achieve with highly efficacious treatments because it is clear to the patient that they experienced an
improvement in symptoms (Muthukumaraswamy et al. 2021). Thus, many argue that end-of-trial assessments for
masking cannot be done with validity, as they cannot disentangle masking from guesses based on efficacy (Mataix-
Cols and Anderson 2021; Sackett 2007). Although, it should be noted some researchers argue that it is not
considered unmasking at the end of the trial if people guess their condition based on efficacy (Katz 2021).
Masking attempts in psychedelic studies
Multiple approaches have been attempted to address these methodological challenges specifically as they
relate to psychedelic trials. First, active placebos have been used in an attempt to mask participants and therapists to
treatment conditions, albeit generally unsuccessfully. This difficulty was infamously demonstrated in the “Good
Friday Experiment”, where divinity school students were assigned to receive psilocybin or niacin, a B vitamin with
mild physiological effects, in a group setting at a chapel (Pahnke et al. 1963). Despite some initial confusion because
of niacin’s fast-acting effects on vasodilation and general relaxation, before long, it became clear which participants
had been assigned to which condition, as those in the psilocybin group had intense subjective reactions and often
spiritual experiences, whereas the niacin group “twiddled their thumbs” while watching on (Prideaux 2021). By the
end of the day, all participants correctly ascertained whether they were in the treatment or control group (Doblin
1991). Despite the clear masking failure, after more than 50 years, many researchers today still use niacin as the
active placebo in clinical trials with psychedelics, perhaps for a lack of better alternatives (Grob et al. 2011; Ross et
al. 2016; Siegel et al. 2021). Nevertheless, participants are now dosed individually rather than in a group to reduce
potential unmasking from witnessing others’ experiences. Modern psilocybin trials have also employed
methylphenidate (Griffiths et al. 2006) and dextromethorphan (DXM; Carbonaro et al. 2018) as active placebos;
although, the success of masking was typically less than 25% or unreported in these studies (Bershad et al. 2019;
Carbonaro et al. 2018; Griffiths et al. 2006). Uthaug et al (2021) tested an innovative strategy at masking by
mimicking the aesthetic and somatic features of the psychedelic brew, ayahuasca. The investigators used a mixture
of coco powder, vitamins (unspecified), turmeric powder, quinoa, traces of coffee, and potato flour, as a placebo to
mimic the texture as well as gastrointestinal side effects of the drug. Despite effectively masking the profound
effects of ayahuasca in several experienced users, a majority of participants were still able to accurately identify
their treatment assignment (Uthaug et al. 2021). A review of ongoing clinical trials revealed that researchers are
currently experimenting with a number of other potential control conditions in psychedelic studies, including
mannitol, lactose, ketamine, microcrystalline cellulose, and nicotinamide (Siegel et al. 2021), but the effectiveness
of these attempts remains to be seen.
Low doses of psychedelics have also been tried as a potential control condition to improve participant
masking (Griffiths et al. 2016). One study combined a low dose of psilocybin with incomplete disclosure (see
below) such that participants and study staff were unaware of the number of treatment arms in the study.
Specifically, participants were informed that they could receive anywhere from 0.5 mg to 30 mg of psilocybin in the
trial when in fact they could only receive 0.5 mg if they were in the control condition or 25 mg if they were in the
treatment condition (Griffiths et al. 2016). An advantage of including the low dose of psilocybin is that all
participants are truthfully told they will receive psilocybin, which presumably helps balance treatment expectations
across both conditions. However, participants and therapists are still at risk for unmasking with this design because
it is typically easy to ascertain whether the participant has an intense psychedelic experience or not. Schenberg
(2021) also noted that this design may be limited by ethical considerations, given that 3,4-methylenedioxy
methamphetamine (MDMA) research has shown that low dose control conditions can be stressful and trying for
patients, leading to dropouts and dissatisfaction (Oehen et al. 2013), and anecdotal lore in the underground
psychedelic therapy community suggests that medium doses of psychedelics can agitate people without allowing
them to “breakthrough” (JDW, personal communication, 2021). On the other hand, low doses of classic
psychedelics (i.e., microdosing) have been purported to be therapeutic (Fadiman 2011; Kuypers et al. 2019), which
could also confound study results; although, the therapeutic benefit of single microdoses seems unlikely to be
durable or significant. Thus, including a low dose psychedelic as part of an active control condition is a promising
starting point.
Incomplete disclosure of certain aspects of the study design is a strategy that has been employed to
enhance masking success and balance treatment expectations among conditions. For example, some studies
incompletely disclose the number of treatment arms to participants in an attempt to obscure the study design and
reduce the participants’ confidence in their treatment group allocation (Bershad et al. 2019; Carbonaro et al. 2018;
Griffiths et al. 2006; Reissig et al. 2012). Another compelling approach (in healthy subjects) involves consenting
participants to possibly receiving one of several substances in order to reduce their certainty of treatment allocation.
For example, in some experiments, participants consent to receive MDMA, methamphetamine, tetrahydrocannabinol
(THC), benzodiazepine, and/or placebo (Bedi et al. 2010; Bershad et al. 2019), but in fact only receive one or two of
these drugs in any particular study. Although this design is possible to implement in psychedelic studies of healthy
individuals who are not seeking a treatment, there are limitations to this approach, including reduced generalizability
because a large proportion of the population may not be comfortable with receiving any one of the listed substances.
Moreover, this design has not proven to be particularly effective to-date, as participants accurately identify the
experimental condition (e.g., MDMA and psilocybin) ~7085% of the time (Bershad et al. 2019; Carbonaro et al.
2018). Thus, even with these more rigorous approaches, adequate masking remains a challenge. Taken together,
there is a pressing need for methodological innovations that adequately address the problem of masking in
psychedelic studies.
Muthukumaraswamy et al. (2021) made several recommendations for addressing masking in psychedelic
clinical trials. The authors suggested that active placebos may need to be combined with alternative trial designs
(e.g., dose-response parallel groups design) as well as some vagueness about the acute effects of psychedelics when
consenting participants. Dose-response parallel-groups designs compare the full dose of the active treatment drug
with a low dose; the advantages and disadvantages of such an approach are discussed previously. Vagueness
regarding the acute effects of psychedelics has tradeoffs as well: although it may improve masking, there are clear
ethical concerns as participants need to be able to give fully informed consent (Smith and Sisti 2021). This
consideration is especially true with psychedelic studies, as psychedelic experiences have been described as “life
changing” and have the potential to affect one’s social relationships (Ross et al. 2016), spirituality (Griffiths et al.
2006), and worldview (Timmermann et al. 2021). Another recommendation provided was the 2 × 2 balanced
placebo design (Rohsenow and Marlatt 1981), or 2 × 2 factorial design, in which the intervention factor (psychedelic
drug, placebo) and instructional set provided to each participant (receiving psychedelic drug, receiving placebo) are
systematically crossed with each other. This design offers a potentially rigorous experimental means for separating
pharmacological effects of the drug from participant expectations, but is most suitable for mechanistic studies of
acute drug effects, rather than clinical trials examining treatment efficacy. To date, there are no published reports of
this design being used in psychedelic drug research, possibly because of its high costs (Schenberg 2021). Although
researchers have begun to address the methodological challenges associated with masking, treatment expectations,
and their combined impact that can bias study results, there is a need to advance the rigor of future research. We
build upon this work in the next section by elaborating on recommendations for improving psychedelic clinical
Novel recommendations to improve future research
Experimental confounds related to expectancies and placebo effects in psychedelic studies largely stem
from inadequate masking. Therefore, our recommendations are primarily focused on how to improve masking in
psychedelic trials through a combination of procedures intended to decrease participants’ confidence in their
assigned treatment arm (Fig 3). As our review of others’ pioneering work makes clear, adequate masking involves
critical decision points at every step in the lifecycle of a clinical study. Our suggestions follow suit, noting elements
for consideration in study development and design, participant recruitment and selection, outcomes and endpoints,
study procedures, and analysis plans. It should be noted that masking is not an all-or-nothing phenomenon;
incorporating a portion of these suggestions can incrementally reduce participants’ confidence in their treatment arm
assignment and attenuate the influence of treatment-nonspecific factors in interpretations of clinical trials.
Fig. 3 Recommendations for Improving Methodology in Psychedelic Trials. Overview of our recommendations
for improving experimental methodology in future clinical trials with psychedelics
Study development and design
The choice of a control condition, the number of study arms, and overall design should be determined by
the specific purpose of the study (Freedland, 2020; Gold et al., 2017). For example, although an open-label study
design does not mask participants or control for treatment-nonspecific factors, it may be appropriate when the
purpose of the study is to examine safety, feasibility, or proof-of-concept. If the purpose is to examine treatment
efficacy, inactive control conditions (e.g., treatment-as-usual, waitlist controls) should be included at the minimum
to control for some treatment-nonspecific factors, such as natural history or regression to the mean. A stronger study
design to test for efficacy would include an active control condition, such as an active placebo that mimics some of
the acute effects of a psychedelic. Including both an active and inactive control condition (i.e., 3-arm design) is a
promising way to disentangle placebo effects (Fillingim and Price 2005; Smith et al. 2020; Vase and Wartolowska
2019), because 3-arm trial designs allow for comparisons between both the treatment and the active placebo
conditions with the inactive control condition to delineate treatment-specific effects from placebo effects (see Fig.
1a). There are also alternative study designs that may be especially useful because of psychedelic trials’
vulnerability to large placebo effects. Sequential parallel designs with a placebo run-in period can reduce the size of
placebo effects by excluding “placebo responders” from the subsequent treatment phase (Campbell et al. 2019;
Dworkin et al., 2010; Ivanova 2016; Tamura and Huang 2007). This alternative design can be implemented in
psychedelic trials by giving all participants an active placebo in the first phase and then randomly assigning only the
participants who did not respond to the initial treatment (i.e., placebo nonresponders) to the psychedelic or placebo
in the second phase. This placebo run-in period creates a subgroup for analysis that increases the sensitivity to detect
a treatment-specific effect (Dworkin et al., 2010; Ivanova et al., 2016); however, a recent systematic review
challenges the notion that this design actually reduces the measured placebo response (Scott et al. 2021).
We also recommend designing studies with a single psychedelic administration when possible, given our
current understanding regarding the efficacy of psychedelic therapy. There are compelling reasons to believe that
multiple psychedelic dosing sessions may have therapeutic advantages (Bouso et al. 2013; Leger and Unterwald
2021; Mithoefer et al. 2019), and this treatment model is very likely to be adopted in clinical practice if these
therapies become FDA-approved. On the other hand, the current controversies surrounding psychedelic therapy are
focused on whether there is any drug-specific benefit of the complex therapeutic intervention. The answer to this
basic question is very likely to inform regulatory decisions, cost-effectiveness models, and coverage by insurers, and
is dependent on adequately masked trials. To that end, studies with only a single dosing session are likely to be
superior in supporting adequate masking compared to studies with multiple dosing sessions. That is, once
participants have experienced the subjective effects of a substance, they are more likely to identify that substance if
it is readministered or recognize that a different substance has been given, compromising the conclusions that can be
drawn from the trial (Wilsey et al. 2016). Therefore, we recommend between-subjects designs with a single dosing
session when evaluating treatment efficacy.
Several trials have included an open-label crossover component, wherein patients assigned to the inactive
control arm are offered the opportunity to receive open-label psychedelic-assisted therapy after completing the final
post-treatment assessment (Wolfson et al. 2020). Some have argued that this design feature is ethically mandatory in
order to provide the patient with the best possible chance of therapeutic response. We disagree with the idea that the
standard of care, or optimal care, involves offering unregulated and unapproved psychedelic therapy, particularly
when the goal of these trials is to establish the efficacy of these same interventions. We recommend incorporating
well-established strategies to minimize harm to participants that may arise if an experimental therapy is either
harmful, or conversely highly effective, rendering placebo treatment unethical. “Stopping rules” are predefined time
points where an interim analysis for efficacy can be performed to identify these situations and minimize harm.
Alternatively, adaptive randomization based on outcome (see below) can achieve a similar goal while maintaining
statistical power (Dragalin 2011)
. We also emphasize the importance of including robust psychotherapeutic support
in any treatment arm when dealing with high-risk populations selected for treatment-resistance, both to maximize
patient safety and monitoring and to better assess drug-specific enhancement of psychotherapy as discussed
Participant recruitment and selection
We recommend recruiting psychedelic-naive participants when possible for clinical trials. Masking an
individual’s treatment condition is much more feasible if they have no prior experience with that substance and are
less certain about what effects to expect (i.e., process expectations; Tambling 2012; Wilsey et al. 2016). On that
basis, participants should be naive to the active placebo as well. Ostensibly, psychedelic-naive individuals would
have less confidence as to whether they received the treatment or active placebo, particularly if the active placebo
had hallucinogenic effects. Carbonaro et al. (2018) demonstrated that experienced hallucinogen users are highly
accurate at differentiating between whether they received psilocybin or DXM, but those without prior hallucinogen
use may be easier to convince, especially if this strategy is combined with others recommendations given here (e.g.,
incomplete disclosure of study design, between-subjects designs with a single drug administration). It should be
noted, however, that a challenge with this design is that several psychoactive substances (e.g., cannabis, opioids) are
known to elicit different subjective and behavioral responses in drug-naive individuals compared to those with past
experience (Solowij et al. 2019). This appears to be the case with psychedelics too, as demonstrated by a negative
relationship between number of previous psychedelic uses and the intensity of acute effects (Aday et al. 2021).
Thus, the phenomenological experience and intensity of drug effects may differ in first time users, which could limit
generalizability. If recruiting only psychedelic-naive participants is not feasible given the increasing number of
recreational users (Yockey et al. 2020), then imposing clear exclusion criteria, such as restrictions on number of
lifetime uses or use within the past 12 months, should be incorporated.
Outcomes, assessments, and endpoints
These strategies are complementary to existing mechanisms for patients to try unapproved therapies, instituted as
the Right to Try Act in the United States, as well as expanded access clinical programs (Holbein et al. 2015).
The choice of outcomes, assessments, and endpoints can have a large impact on the evaluation of treatment
benefit and overall methodological rigor of psychedelic clinical trials. The primary endpoint for a trial should be
well-defined, reliable, and represent a clinically meaningful outcome of how a patient feels, functions, or survives
(e.g., Fleming and Powers 2012; US FDA 2009). Outcome measures should be consistent with expert
recommendations or consensus statements for a given disease or condition under study when available (e.g., Deyo et
al. 2014), and the minimal clinically important difference in the primary outcome measure that represents a
treatment benefit should be set a priori (e.g., Dworkin et al. 2008, 2009). There are unresolved questions regarding
the long-term efficacy of psychedelic assisted therapy. Lasting, clinically significant improvements following
psychedelic therapy, regardless of any placebo group difference, are likely more important to patients, providers,
and stakeholders than an acute improvement that is not maintained. However, given the current level of evidence
and controversy regarding the drug-specific efficacy of the treatment, we emphasize the primary importance of
rigorous, well-controlled trials is to define clear evidence of benefit that outlasts the acute drug effect. The specific
timing of outcomes will depend heavily on the indication under consideration. Although long-term follow-ups
provide a more complete understanding of treatment effects, especially in trials on chronic conditions, they are still
susceptible to placebo effects and selection bias affecting trials from the outset. For example, a well-designed,
masked RCT showed that arthroscopic knee surgery was never better than placebo surgery across two years of
assessments (Moseley et al. 2002).
We recommend using multiple methods of measurement to comprehensively examine the effects of
psychedelic therapy in clinical trials. Patient reported outcomes (PROs) assess the status of a patient’s health
condition (e.g., disease symptoms, functioning) directly from the patient, and are commonly used as endpoints in
clinical trials (Mercieca-Bebber et al. 2017; US FDA 2009). Including valid, reliable, and clinically informative
PRO measures are valuable because they capture patient-centered perceptions of meaningful change and have
downstream influence on clinical decision making, drug labeling claims, and health policy (Calvert et al. 2018;
Doward et al. 2010). Clinician-administered assessments or observer reports can also be useful in psychedelic trials
as they avoid potential self-report biases of PROs; however, these types of assessments are also vulnerable to
methodological issues, such as low interrater reliability and rater bias (Kobak et al. 2007). Therefore, when feasible,
trials should also include objective and reliable measures, such as biomarkers and/or behavioral tasks that reflect
component processes related to the index pathology. Two categories of biomarkers recognized by the FDA (Smith et
al. 2017; US FDA 2020) that may be particularly relevant for psychedelic clinical trials are predictive biomarkers
and surrogate endpoints. Predictive biomarkers indicate whether certain participants respond differentially to the
treatment or placebo and can be used to stratify randomization on variables of interest that may maximize the
efficiency of a trial and minimize the risk of exposing additional patients to an unproven treatment (Strimbu and
Tavel 2010). Surrogate endpoint biomarkers include accurate and well-validated lab measures or physical signs that
reliably predict or stand-in for a clinically meaningful endpoint (e.g., biomarkers of abstinence; Johnson et al. 2014;
Fleming and Powers 2012). Not all diseases or health conditions have biomarkers that predict treatment benefit or
represent clinical endpoints, but when available, inclusion of these types of biomarkers may lead to more efficient
trials with less bias (Fleming and Powers 2012). Because psychedelic clinical trials are particularly expensive, one
must weigh the tradeoffs between trial costs and participant burden with the addition of biomarkers, long-term
follow-ups, and lengthy assessments.
Study procedures: Managing and measuring treatment expectations
Several pragmatic steps can be taken at the beginning stages of a study to manage participants’ expectation
bias. We do not currently have sufficient data to claim that psychedelic therapy is an effective treatment; therefore,
investigators should emphasize the uncertainty regarding the treatment efficacy, rather than insinuating that the
treatment will improve participants’ symptoms (Erpelding et al. 2020; Evans et al. 2021; Gewandter et al. 2020;
Smith et al. 2020). This communication on the uncertainty of treatment efficacy should be consistent across
recruitment materials, initial contact with potential participants, consent forms, and in any interactions with
participants. Moreover, in trials comparing psychedelic therapy to a placebo, drug effects should be explained
neutrally (Smart et al. 1966). For example, participants can truthfully be informed about possible drug effects while
also noting that there is significant variability between peoplesome people have strong reactions to a psychedelic
while others have very mild reactions (Griffiths et al. 2016). Similarly, in studies in which both treatment arms
receive psychotherapy, the investigator can honestly describe psychotherapy as an effective treatment whether or not
it is paired with a psychedelic. To ensure this clinical equipoise and manage participants’ expectations, all study
staff should be masked to treatment arm assignment and trained to present the study and arms of the trial neutrally.
In addition to managing expectations, it is important to measure participants’ treatment expectations. We
and others (e.g., Muthukumaraswamy et al. 2021) recommend use of established measures of expectancy, such as
the Stanford Expectations of Treatment Scale (Younger et al. 2012), which is a valid and reliable measure of
participants' positive and negative treatment expectancies. The scale includes six items that can easily be adapted
across research contexts to identify differences in expectancies between treatment groups as well as relationships
between treatment expectancies and outcomes. The Credibility and Expectancy Questionnaire (Devilly and
Borkovec 2000) can also be used to measure the degree to which a participant thinks and feels the treatment will
improve their symptoms or functioning. Furthermore, several face-valid questions, such as “how helpful do you
believe the treatment will be for improving your [primary symptom]?”, have been used successfully to measure
treatment expectations in previous research (e.g., Sherman et al. 2010). Another option is to conduct semi-structured
interviews, possibly during participant preparation and integration sessions, and use qualitative analyses to assess
participants’ positive and negative treatment expectations (e.g., Eaves et al. 2015). Because of the aforementioned
issues with unmasking following a psychedelic session, and the interaction between masking and expectations, it
may be useful to measure treatment expectations after the drug dosing session in addition to at baseline. Arguably,
expectations at baseline may be predictive of subjective effects during the psychedelic session, and expectations at
post-session may be predictive of changes in clinical outcomes. This speculation remains to be tested, but it is
worthwhile to systematically evaluate the natural dynamics of expectations during psychedelic trials and examine
whether expectations change after the dosing session.
Study procedures: Incomplete disclosure
We have reviewed studies where incomplete disclosure has been used to reduce participants’ certainty
regarding their treatment assignment (Bershad et al. 2019; Carbonaro et al. 2018; Griffiths et al. 2006; Reissig et al.
2012). In designing a trial, it is critically important to distinguish “incomplete disclosure” from “deception”. Most
institutional review boards have internally defined these respective procedures; however, “deception” is generally
agreed to mean that the investigators provide false information to a participant whereas “incomplete disclosure”
indicates that the subject is not fully informed about the purpose or design of the study. These strategies are
controversialthe ethics of omitting important information about a study and misleading participants is an area of
ongoing debate (Miller et al. 2005; Roulet et al. 2017). Implementing any deceptive practice requires thorough
scientific justification and authorization by institutional review boards. Empirical evidence in healthy adults
suggests that research participants may not be adversely affected by deception (Mundt et al. 2017); however, in the
context of clinical trials in which therapeutic alliance is critical for patient safety and treatment efficacy, deception
may be particularly ill-advised. If it is considered ethically appropriate, though, withholding information from
participants as well as study staff about the number of study arms and the exact doses administered may be
particularly effective for enhancing masking success. Providing a vague, incomplete description of the study
structure and a range of possible dosages may be best suited for standard, two-armed RCT designs (and avoids the
need to use an alternative study design that requires a significantly larger sample size for adequate statistical power).
Without the cues of knowing that it is only possible to receive the experimental treatment or placebo (e.g., a high
dose or an ultra-low dose of a psychedelic), it may be difficult for both a participant and staff to develop a firm
belief about the participant’s treatment condition. Similarly, listing the side effects of all of the potential study drugs
togetherinstead of listing effects specific to each substance—may be an ancillary strategy to reduce participants’
confidence in their treatment arm assignment while still fully informing them of all the drug effects they may be
exposed to (Boutron et al. 2006). In a recent study with 5-MeO-DMT, researchers withheld the identity of the study
drug but informed participants that they would be receiving a tryptamine psychedelic (Reckweg et al., 2021); this
may be a useful method for managing expectations in cases where participants could have distinct expectations
regarding specific psychedelic substances. A related recommendation to improve methodological rigor in the field is
for researchers to report what drug effects participants were informed about prior to the study.
Incomplete disclosure to participants and study personnel regarding key elements of a study’s design may
help to meet a central objective of masking: establishing “a state of ambivalence” about treatment allocation to
minimize the impact of beliefs on study outcomes (Mathieu et al. 2014). Ensuring that study staff receive the same
information as participants and remain unaware of the true design throughout the study is critical, as feedback from
observers is known to influence participants’ clinical outcomes (Colagiuri and Boakes 2010; Hróbjartsson et al.
2012). It is important to acknowledge that undertaking this effortconcealing fundamentals of study design from
staff as well as participantsis challenging from a practical standpoint, requiring careful management of access to
information about the study (e.g., a “cone of silence”). Using incomplete disclosure or deception also necessitates
appropriate debriefing protocols, as well as development of masking assessments that avoid revealing the true study
design. Most assessment tools in the clinical trial literature measure perceived treatment assignment as nominal data
and implicitly indicate study design (i.e., “Do you think you received the active treatment or placebo?”). Probing
participants’ and staff members’ beliefs using ordinal/parametric scales may not only allow investigators to maintain
uncertainty about the design, but also has the advantage of increasing statistical power (Laferton et al. 2017).
Study procedures: Active placebo
Use of an active placebo has a clear rationale for psychopharmacology studies. However, as reviewed
above, efforts to mask the unique subjective effects of psychedelics have had limited success. Our choices are
largely constrained by a limited understanding of how psychedelics produce therapeutic benefits. For example, a
drug that mimics psychedelic effects but provides no therapeutic benefit could potentially be an excellent active
placebo. However, the internal contradiction in this strategy becomes apparent if, as several researchers argue
(Yaden and Griffiths 2020), the subjective effects produced by psychedelics (particularly mystical states) themselves
drive therapeutic benefit. Although intuitive, this hypothesis is nonetheless unproven and a thorough evaluation is
beyond the scope of this review; we instead refer the reader to an excellent summary of arguments for and against
this idea (Olson 2020; Yaden and Griffiths 2020). We anticipate that future research will clarify whether mystical
states induced by means other than psychedelics such as hypnosis (Lynn and Evans 2017), holotropic breathwork
(Puente 2014), meditation (Russ and Elliott 2017), virtual reality (Glowacki et al. 2020), or non-psychedelic
psychoactive drugs (Earleywine et al. 2021) are sufficient for therapeutic effects observed in psychedelic therapy
trials, such as smoking cessation and symptomatic relief from depression in appropriate target populations.
A deeper understanding of the neural systems and neurochemistry required for psychedelics’ therapeutic
effects may lead to highly effective comparators for use in clinical trials. A recent clinical study investigating the
antidepressant mechanism of ketamine illustrates that the acute subjective effects of a psychedelic-class drug may be
separable from its therapeutic effects. Williams et al. (2018, 2019) found that a high dose of an opioid antagonist,
naltrexone, effectively blocked ketamine’s antidepressant and anti-suicidal effects but had a minimal impact on
ratings of ketamine-induced dissociation. This small study was met with some controversy (Heifets et al. 2019;
Marton et al. 2019; Yoon et al. 2019), and requires replication in a larger independent sample. Also, notably, the
authors did not formally assess masking efficacy in the respective treatment conditions. Nonetheless, these findings
suggest a powerful active placebo comparator for future studies of ketamine, and potentially other psychedelics.
Similarly, for classical psychedelics like psilocybin, pharmacological agents may be discovered that interrupt
neuroplastic processes triggered by psilocybin, but do not interfere with its acute psychedelic effects. Another highly
innovative approach in development (NCT04842045) pairs psilocybin with an amnestic drug (midazolam, a
benzodiazepine). This study is focused on safety. The broader hypothesis, yet to be tested, is that psychedelic and
mystical states evoked in participants who do not form memories of the experience are not therapeutic, likely
because participants’ amnesia prevents subsequent therapeutic integration of the psychedelic experience. An
alternate outcome may be that participants do experience therapeutic benefit, but are effectively masked to their
assigned treatment condition by virtue of midazolam-induced amnesia. In this case, a near-perfectly controlled,
masked study design is achieved, with an easily interpretable finding for psilocybin’s efficacy, uncomplicated by
differential placebo or nocebo effects in patients receiving midazolam alone versus midazolam plus psilocybin. We
eagerly anticipate results from this pioneering line of inquiry, and note several challenges. In addition to the ethical
considerations of using amnestic agents in psychiatric populations, there are technical considerations that may
confound this approach, including uncertainty as to whether midazolam retains its amnestic property when paired
with a psychedelic, whether amnestic doses of midazolam produce a degree of sedation that precludes entry into a
mystical state, or whether midazolam directly blocks therapeutic psychological or neural mechanisms induced by
psychedelic medications.
Psychedelic therapy may be an uninterruptible whole, requiring the drug, psychedelic experience, and
associated psychotherapy to achieve any therapeutic benefits (Sessa 2014). In this case, which should be assumed
true until proven otherwise, there is still a pragmatic need to identify pharmacological and somatic placebo
treatments that adequately mask psychedelic effects. Although we have no evidentiary basis to recommend specific
active placebos beyond those that have been attempted, substances with hallucinatory effects (e.g., ketamine, DXM,
and high doses of tetrahydrocannabinol) may be compelling options, especially when combined with drug-naive
participants. We strongly support studies specifically devoted to developing and testing active placebos for use in
therapeutic clinical trials. The need to develop active placebos for participants with past psychedelic use is
particularly important given the likely decrease in psychedelic-naive participants that can be recruited for clinical
therapeutic studies in the coming years.
Design of an active placebo ought to be considered in concert with other study design elements described
above, with the overarching goal of reducing a prospective study participant’s certainty of their treatment condition.
For example, if testing psilocybin’s efficacy for major depressive disorder, investigators may combine active
placebo and incomplete disclosure to balance expectancy effects across treatment arms. For simplicity, the study
could be designed as a two-arm comparison of high dose psilocybin versus ultra-low (ineffective) dose psilocybin
plus an active placebo. During the informed consent process, participants would truthfully be informed that they will
receive a range of psilocybin doses and may also receive an active placebo, with full disclosure that the purpose of
the active placebo is to reduce their certainty of treatment assignment. The number of study arms (two, in fact) and
the likelihood that their assigned psilocybin dose would be effectively non-therapeutic would not be disclosed.
Furthermore, informed consent could include information that subthreshold (but not ultra-low) psilocybin may have
therapeutic value; although, again, it would not be disclosed that no participants would be assigned to a subthreshold
dose group. In this case, the specific goal of an active placebo might be to mimic aspects of a high dose psilocybin
dose, which could be achieved with DXM or perhaps a combination of a benzodiazepine and a mild stimulant.
Taken together, participants would be informed of all the possible treatment conditions, and may be reasonably
uncertain as to whether they received a high therapeutic dose of psilocybin versus an ultra low dose plus active
Analysis: Assessing and reporting outcomes related to trial design
The set of treatment-nonspecific effects, collectively termed “the placebo effect”, and effective masking are
key considerations for designing an interpretable study involving psychoactive drugs. Anticipating the placebo
effect, measuring the contribution of expectancies, assessing the effectiveness of masking, and systematically
reporting these data will set standards and lead to iterative improvements in trial design. These factors ought to be
considered at every step in the lifecycle of a clinical study. We specifically recommend: calculating statistical power
based on known placebo effect sizes; obtaining repeat baseline measures of the primary outcome(s); measuring
expectancies and masking success; and analyzing primary outcomes using expectancy and perceived (rather than
actual) treatment arm as covariates.
Estimating the size of the placebo effect informs statistical power calculations, which, if resources are
limited, may impact the feasible number of treatment arms. A common method of estimating the size of the placebo
effect in a trial is to compare outcomes in the placebo arm to a ‘no treatment’ arm (Hróbjartsson and Gøtzsche 2010;
Wampold et al. 2016). However, given the previously discussed ‘hype’ around psychedelics, participants randomly
assigned to the ‘no treatment’ arm would likely experience disappointment and nocebo effects from their knowledge
of not being in the active treatment. An alternative method of partitioning the placebo effect from the treatment
effect may be to compare against a ‘placebo benchmark’ (Jones et al. 2021). Jones and colleagues found that the
effect size of the placebo effect was uniform across different treatment approaches for depression (pooled Hedge’s g
= 1.05). In areas where the size of the placebo effect has been well-established, researchers may be able to compare
their anticipated effect size against a criterion. Investigators can also take simple steps to minimize some
components of the placebo effect, such as regression to the mean. We recommend that investigators perform repeat
baseline assessment of their outcome of interest and only enroll participants with stable response characteristics.
This procedure may be more cost-effective than including an untreated control condition to estimate regression to
the mean.
We strongly recommend measuring the factors that make up the placebo effect. Prior to conducting any
study procedures (e.g., preparation sessions), participants' treatment expectations should be measured as described
above. Measuring masking efficacy is similarly important and should be appropriately timed. In many cases, the
clinical benefits of psychedelics may be rapid (Majić et al. 2015; Murphy-Beiner et al. 2020). We recommend
measuring participant- and therapist-perceived treatment allocation, certainty of treatment allocation, and the reason
for their guess both immediately after the psychedelic dosing session(s) and at the end of the study.
Including two measurement occasions may help determine whether participants and therapists guessed the treatment
allocation based on the subjective effects during the treatment session or from changes in clinical symptoms over
time (Katz, 2021; Kolahi et al., 2009). We agree with Katz (2021) that accurate guesses of treatment allocation due
to treatment efficacy should not be considered unmasking. To further redress the influence of masking, we suggest
using clinical assessors who are unaware of the study design and participant treatment allocation to collect all
relevant measures. Clinical assessors should also be asked about perceived participant treatment allocation at the end
of the study (Katz 2021). We again emphasize that investigators should create protocols and adherence plans for all
relevant study staff to maximize the chances that masking is maintained throughout the study.
Participant expectations and functional unmasking may be unavoidable sources of bias that impact internal
validity and the inferences that can be drawn from study results (Higgins et al., 2011; Kolahi et al., 2009). However,
modern adaptive trial designs can help investigators at least achieve an even distribution of these biases across
conditions. A thorough discussion of adaptive designs is beyond the scope of this review, and we refer the reader to
two useful summaries, including draft guidance from the FDA on adaptive trial design for industry (FDA 2019;
Pallman et al. 2018). In short, investigators may consider using expectancy and participant-assessed treatment
conditions to create balanced randomization blocks (i.e., covariate-adapative treatment assignment) just as other
clinical trials stratify recruitment on the prevalence of comorbidities, sex, and other factors that may differentially
impact treatment outcomes. For small exploratory trials, it may not be possible to balance on multiple pre-treatment
variables; therefore, the decision to balance recruitment on treatment outcome expectations must be weighed against
other recruitment priorities.
A major benefit of measuring expectancies and masking efficacy is that these factors can be used as
covariates in the analysis of primary study outcomes, and the specific effects of expectancy and treatment arm guess
on outcome can be evaluated. In the previously discussed microdosing study by van Elk and colleagues (2021),
researchers initially found that microdoses of psilocybin led to greater ratings of awe than placebo; however, after
adding baseline expectations as a covariate to the analyses, the difference between conditions was non-significant. In
a study that employs an effective active placebo, outcomes can be analyzed according to the drug that participants
think they received compared to the drug they actually received. In a study measuring pleasantness of affective
touch, Bershad et al. (2019) found a significant effect of MDMA compared to an active placebo, methamphetamine.
A substantial number of participants who received methamphetamine believed they had received MDMA (38.9%).
Analyzing outcomes using a participant’s guess as a covariate showed no effect in this latter group. This comparison
strongly reinforced the authors’ conclusion that the effect of MDMA on affective touch was drug-specific and not a
product of participants’ expectations.
Beyond the scope of RCTs
One notion to consider is embracing expectancy and placebo effects. The important role of expectancies in
psychedelic therapy blurs the line between treatment-specific and treatment-nonspecific effects, and raises the
broader question: rather than eliminating treatment-nonspecific effects, should trialists be looking for ways to
optimize and synergize them with treatment interventions to enhance clinical outcomes (Colloca and Barsky 2020;
Enck et al. 2013)? Although no formalized manual exists on how to boost expectancy in psychotherapy, inducing
positive expectations has been shown to enhance the effectiveness of a variety of health interventions (Bingel et al.
2011; Flowers et al. 2018; Kaptchuk et al. 2020), a strategy which could seemingly be tailored toand be
particularly synergistic withpsychedelic treatments as well. As discussed previously, placebo and drug-specific
effects are likely to be interactive rather than additive (Kube and Reif 2017). Thus, it may be the case that the
“therapeutic window” opened by psychedelics is an emergent property of a complex system comprising
expectations, drug effects, setting, and therapeutic alliance. It may be impossible to isolate an individual component
of this complex package in an RCT. Critically, this does not condemn psychedelic therapy as being no more
effective than placebo, but means that the current gold standard clinical trial design may not be sensitive to detecting
the therapeutic effect of an individual treatment element.
A potential solution to this dilemma may be to shift focus from efficacy trials and the use of explanatory or
confirmatory RCT designs towards pragmatic clinical trial designs (PCTs), that have an alternative goal of assessing
treatment effectiveness. Whereas internal validity (i.e., objective comparison of drug vs placebo in tightly controlled
settings with homogenous groups) is the major objective of an explanatory or confirmatory trial, external validity
and the generalizability of treatment effectiveness is the primary focus of a well-designed PCT. Consequently, PCTs
offer potential “real world” tests of clinical effectiveness and the generalizability of outcome data, rather than
isolation of the active ingredient for change. To achieve these goals, PCTs typically include one or more alternative
therapies to the treatment under study, rather than active or inactive placebos, and participants are normally recruited
from a broad “real life” clinical population, with few exclusions or restrictions on participation. Although pragmatic
trials are normally conducted in the fourth, post-marketing phase of drug development, Carhart-Harris et al. (2021)
have argued cogently for the potential benefits of pragmatic designs being used earlier to broadly assess clinical
effectiveness of current psychedelic treatments, either as an alternative or complement to the much narrower focus
of current RCTs.
Lastly, a closely related approach to consider when testing the effectiveness of psychedelic therapy is to
evaluate large-scale population data using so-called “natural experiments”. Natural experiments provide an
alternative to RCTs by taking advantage of circumstances whereby naturally occurring events can be linked to
variables of interest (Thapar and Rutter 2019). This type of design is necessary when randomly assigning individuals
to masked conditions is not possible because of ethical or logistical constraints, such as when studying maltreatment
or child neglect (Rutter 2007). If the challenges related to expectations and masking with psychedelics preclude
rigorous RCTs, natural experiments may be another method of evaluating the treatment’s effects. With the recent
legalization of psilocybin therapy in Oregon as well as successful decriminalization movements across the US (Aday
et al. 2020a; Marks and Cohen 2021), it is possible that objective indices related to mental health (e.g., suicide rates,
emergency room visits for psychiatric issues) could precipitously decrease at the population level if psychedelics are
indeed an effective treatment for a variety of psychiatric conditions. Although it is unclear what the initial
accessibility of these treatments will be to individuals in states such as Oregon (Williams and Labate 2020), if
positive trends in mental health are observed at the population level after introduction of legal psychedelic therapy,
the role of expectations may be considered immaterial to the broader benefits to society.
Accurate detection of treatment-specific effects in clinical trials is an intrinsically complex task across
areas of research as study personnel and participant expectations interact dynamically with masking and therapeutic
outcomes. Psychedelic studies are particularly challenging as they must address additional confounds related to
“hype” and salient psychoactive effects that hinder treatment arm masking to an extensive degree. On one hand, to
characterize clinical efficacy and safety, it is an essential challenge for the field to separate pharmacological effects
from multiple, interactive socio-psychological influences in psychedelic medicine. Innovative, disruptive
experimental designs may be needed to this end. On the other hand, at a practical level, it is important from a public
health standpoint to identify methods of optimizing psychedelic treatment outcomes, perhaps by utilizing
expectancies. These results could potentially guide clinical decision-making.
Traditional placebo masking with inert comparators is insufficient for high-dose psychedelic studies, and
this review highlights that this issue often extends to psychotherapy and pharmacology research more broadly. Here,
recommendations are presented for improving the methodological rigor of future psychedelic studies that addresses
issues related to expectations and participant masking. Specifically, we provide guidelines on study design (e.g.,
incomplete disclosure of treatment arms, neutral explanation of drug effects), participant recruitment and selection
(e.g., include psychedelic- and active placebo-naive participants), outcomes and endpoints (e.g., include biomarkers
and behavioral measures), control conditions (e.g., use active comparators), and analyses (e.g., test masking
efficacy, control for pre-treatment expectations, compare against placebo benchmark). Although these
recommendations are tailored to psychedelic studies, they can be incorporated into psychotherapy and
pharmacology research more broadly to increase precision in identifying treatment-specific effects. Doing so may
improve methodological rigor and identification of effective interventions across areas of medicine.
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Background: Mindfulness protocols, though beneficial for a range of indications, often involve long-term commitment and may not be accessible for those naturally low in trait mindfulness (e.g. attention-/ anxiety-related disorders). It remains unclear which ‘dose’ of mindfulness is necessary to produce beneficial effects, and broadly, how drugs such as nootropics and psychedelics may interact with mindfulness meditation. / Aims: The aims of this thesis are (1) to explore what dose of mindfulness is necessary to enhance state mindfulness (among other outcomes) and whether a drug can modulate, or add to the effects of a mindfulness strategy, (2) to explore how psychedelics may affect a meditation experience, and (3) to examine what role changes in mindfulness play in regards to beneficial psychological health outcomes shown after ceremonial psychedelic use. / Methods: A mixture of methodologies were applied to answer the above questions. Specifically, single-session mindfulness literature was systematically reviewed, and a double-placebo controlled study was designed and conducted to explore the potential for pharmacological enhancement of a single mindfulness strategy. A thematic analysis was conducted to explore user accounts of combined psychedelic and meditation experiences. Finally, linear multilevel models and longitudinal mediation models were used to explore the associations between changes in mindfulness capacity and psychological health over the course of a naturalistic ayahuasca study. / Results: Single-session mindfulness studies are capable of producing a variety of beneficial effects, and adjunctive modafinil appears to enhance some effects of behavioural strategies as well as participant engagement in subsequent practice. Psychedelics may also prove to be useful counterparts to meditations, and conversely, while psychedelics appear to enhance mindfulness, meditation practice can assist also in the navigation of, and potentially enhance effects of the psychedelic process.
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Recent media advocacy for the nascent psychedelic medicine industry has emphasized the potential for psychedelics to improve society, pointing to research studies that have linked psychedelics to increased environmental concern and liberal politics. However, research supporting the hypothesis that psychedelics induce a shift in political beliefs must address the many historical and contemporary cases of psychedelic users who remained authoritarian in their views after taking psychedelics or became radicalized after extensive experience with them. We propose that the common anecdotal accounts of psychedelics precipitating radical shifts in political or religious beliefs result from the contextual factors of set and setting, and have no particular directional basis on the axes of conservatism-liberalism or authoritarianism-egalitarianism. Instead, we argue that any experience which challenges a person's fundamental worldview—including a psychedelic experience—can precipitate shifts in any direction of political belief. We suggest that the historical record supports the concept of psychedelics as “politically pluripotent,” non-specific amplifiers of the political set and setting. Contrary to recent assertions, we show that conservative, hierarchy-based ideologies are able to assimilate psychedelic experiences of interconnection, as expressed by thought leaders like Jordan Peterson, corporadelic actors, and members of several neo-Nazi organizations.
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5-Methoxy-N,N-Dimethyltryptamine (5-MeO-DMT) is a tryptamine with ultra-rapid onset and short duration of psychedelic effects. Prospective studies for other tryptamines have suggested beneficial effects on mental health outcomes. In preparation for a study in patients with depression, the present study GH001-HV-101 aimed to assess the impact of four different dose levels of a novel vaporized 5-MeO-DMT formulation (GH001) administered via inhalation as single doses of 2 ( N = 4), 6 ( N = 6), 12 ( N = 4) and 18 mg ( N = 4), and in an individualized dose escalation regimen ( N = 4) on the safety, tolerability, and the dose-related psychoactive effects in healthy volunteers ( N = 22). The psychedelic experience was assessed with a novel Peak Experience Scale (PES), the Mystical Experience Questionnaire (MEQ), the Ego Dissolution Inventory (EDI), the Challenging Experience Questionnaire (CEQ), and the 5-Dimensional Altered States of Consciousness Questionnaire (5D-ASC). Further aims were to assess the impact of 5-MeO-DMT on cognitive functioning, mood, and well-being. Higher doses of 5-MeO-DMT produced significant increments in the intensity of the psychedelic experience ratings as compared to the lowest 2 mg dose on all questionnaires, except the CEQ. Prominent effects were observed following single doses of 6, 12, and 18 mg on PES and MEQ ratings, while maximal effects on PES, MEQ, EDI, and 5D-ASC ratings were observed following individualized dose escalation of 5-MeO-DMT. Measures of cognition, mood, and well-being were not affected by 5-MeO-DMT. Vital signs at 1 and 3 h after administration were not affected and adverse events were generally mild and resolved spontaneously. Individualized dose escalation of 5-MeO-DMT may be preferable over single dose administration for clinical applications that aim to maximize the experience to elicit a strong therapeutic response.
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Importance The placebo effect in depression clinical trials is a substantial factor associated with failure to establish efficacy of novel and repurposed treatments. However, the magnitude of the placebo effect and whether it differs across treatment modalities in treatment-resistant depression (TRD) is unclear. Objective To examine the magnitude of the placebo effect in patients with TRD across different treatment modalities and its possible moderators. Data Sources Searches were conducted on MEDLINE, Web of Science, and PsychInfo from inception to June 21, 2021. Study Selection Randomized clinical trials (RCTs) were included if they recruited patients with TRD and randomized them to a placebo or sham arm and a pharmacotherapy, brain stimulation, or psychotherapy arm. Data Extraction and Synthesis Independent reviewers used standard forms for data extraction and quality assessment. Random-effects analyses and standard pairwise meta-analyses were performed. Main Outcomes and Measures The primary outcome was the Hedges g value for the reported depression scales. Secondary outcomes included moderators assessed via meta-regression and response and remission rates. Heterogeneity was assessed with the I² test, and publication bias was evaluated using the Egger test and a funnel plot. Cochrane Risk of Bias Tool was used to estimate risks. Results Fifty RCTs were included involving various types of placebo or sham interventions with a total of 3228 participants (mean [SD] age, 45.8 [6.0] years; 1769 [54.8%] female). The pooled placebo effect size for all modalities was large (g = 1.05; 95% CI, 0.91-1.1); the placebo effect size in RCTs of specific treatment modalities did not significantly differ. Similarly, response and remission rates associated with placebo were comparable across modalities. Heterogeneity was large. Three variables were associated with a larger placebo effect size: open-label prospective treatment before double-blind placebo randomization (β = 0.35; 95% CI, 0.11 to 0.59; P = .004), later year of publication (β = 0.03; 95% CI, 0.003 to 0.05; P = .03), and industry-sponsored trials (β = 0.34; 95% CI, 0.09 to 0.58; P = .007). The number of failed interventions was associated with the probability a smaller placebo effect size (β = −0.12; 95% CI, −0.23 to −0.01, P = .03). The Egger test result was not significant for small studies’ effects. Conclusions and Relevance This analysis may provide a benchmark for past and future clinical RCTs that recruit patients with TRD standardizing an expected placebo effect size.
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Pain is a fundamental experience that promotes survival. In humans, pain stands at the intersection of multiple health crises: chronic pain, the opioid epidemic, and health disparities. The study of placebo analgesia highlights how social, cognitive, and affective processes can directly shape pain, and identifies potential paths for mitigating these crises. This review examines recent progress in the study of placebo analgesia through affective science. It focuses on how placebo effects are shaped by expectations, affect, and the social context surrounding treatment, and discusses neurobiological mechanisms of placebo, highlighting unanswered questions and implications for health. Collaborations between clinicians and social and affective scientists can address outstanding questions and leverage placebo to reduce pain and improve human health.
Successful blinding in double-blind RCTs is crucial for minimizing bias, however studies rarely report information about blinding. Among RCTs for depression, the rates of testing and success of blinding is unknown. We conducted a systematic review and meta-analysis of the rates of testing, predictors, and success of blinding in RCTs of antidepressants for depression. Following systematic search, further information about blinding assessment was requested from corresponding authors of the included studies. We reported the frequency of blinding assessment across all RCTs, and conducted logistic regression analyses to assess predictors of blinding reporting. Participant and/or investigator guesses about treatment allocation were used to calculate Bang's Blinding Index (BI). The BI between RCT arms was compared using meta-analysis. Across the 295 included trials, only 4.7% of studies assessed blinding. Pharmaceutical company sponsorship predicted blinding assessment; unsponsored trials were more likely to assess blinding. Meta-analysis suggested that blinding was unsuccessful among participants and investigators. Results suggest that blinding is rarely assessed, and often fails, among RCTs of antidepressants. This is concerning considering controversy around the efficacy of antidepressant medication. Blinding should be routinely assessed and reported in RCTs of antidepressants, and trial outcomes should be considered in light of blinding success or failure.
Importance Single-blind placebo run-in (PRI) periods are common in randomized clinical trials (RCTs) of treatment for depression. They aim to increase sensitivity to detect drug effects; however, the association of PRI periods with study outcomes remains unclear. This is concerning given the costs of PRI periods to patients and investigators. Objective To examine the association of the use of PRI periods with the placebo response, drug response, and drug-placebo difference among RCTs of antidepressants. Data Sources MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, and PsycINFO, as well as repositories of unpublished studies, were systematically searched up to July 2021. Study Selection Included studies were double-blind, placebo-controlled RCTs of antidepressant medication among adults with depressive disorders. Data Extraction and Synthesis Data were extracted into a coding sheet, including the characteristics of studies, the characteristics of PRI periods, and the outcomes of studies. Main Outcomes and Measures Study outcomes were the primary depression symptom measure reported by the RCT. These outcomes were used to calculate effect sizes (Hedges g) of the within-group drug response and placebo response as well as the drug-placebo difference. Random-effects meta-analysis was used to calculate effect sizes, and subgroup analyses were used to compare outcomes depending on use of PRI periods. Results A total of 347 trials (representing 89 183 participants) were included; 174 studies (50%) reported using a single-blind PRI period. Response outcome data were available for 189 studies. Studies using PRI periods reported a smaller placebo response (g = 1.05 [95% CI, 0.98-1.11]; I² = 82%) than studies that did not use a PRI period (g = 1.15 [95% CI, 1.09-1.21]; I² = 81%; P = .02). Subgroup analysis showed a larger drug response size among studies that did not use a PRI period (g = 1.55 [95% CI, 1.49-1.61]; I² = 85%) than those that did use a PRI period (g = 1.42 [95% CI, 1.36-1.48]; I² = 81%; P = .001). The drug-placebo difference did not differ by use of PRI periods (g = 0.33 [95% CI, 0.29-0.38]; I² = 47% for use of a PRI period vs g = 0.34 [95% CI, 0.30-0.38]; I² = 54% for no use of PRI periods; P = .92). The likelihood of response to drug vs placebo also did not differ between studies that used a PRI period (odds ratio, 1.89 [95% CI, 1.76-2.03]) and those that did not use a PRI period (odds ratio, 1.77 [95% CI, 1.65-1.89]; P = .18). Conclusions and Relevance This study suggests that RCTs using PRI periods yield smaller within-group changes across both placebo and drug groups compared with RCTs without PRI periods. The reduction in effect size across groups was equivalent in magnitude. Consequently, PRI studies do not observe larger drug-placebo differences, suggesting that they do not increase trial sensitivity. As such, given the resources and probable deception required and risk to external validity, the practice of using PRI periods in RCTs of antidepressants should be ended.
Psychedelics have shown great promise in treating mental-health conditions, but their use is severely limited by legal obstacles, which could be overcome.
Background Classical psychedelics are a group of drugs which act as agonists on the serotonin-2A (5-HT2A) receptor. Evidence suggests they may have a uniquely rapid and enduring positive effect on mood. However, marked heterogeneity between methodological designs in this emerging field remains a significant concern. Aims To determine how differences in the type of psychedelic agent used and the number of dosing sessions administered affect subjects’ depression and anxiety outcomes and adverse drug reactions (ADR). Methods This review collected and screened 1591 records from the MEDLINE and Web of Science databases for clinical trials reporting objective data on mood for subjects with a known anxiety or depression. Results After screening, nine clinical trials met inclusion criteria. Meta-analysis of these studies showed significant, large positive effect sizes for measures of anxiety (Cohen’s d = 1.26) and depression (Cohen’s d = 1.38) overall. These positive effects were also significant at acute (⩽1 week) and extended (>1 week) time points. No significant differences were observed between trials using different psychedelic agents (psilocybin, ayahuasca or lysergic acid diethylamide (LSD)), however, a significant difference was observed in favour of trials with multiple dosing sessions. No serious ADR were reported. Conclusion Psilocybin, ayahuasca and LSD all appear to be effective and relatively safe agents capable of producing rapid and sustained improvements in anxiety and depression. Moreover, the findings of the present analysis suggest that they may show a greater efficacy when given to patients over multiple sessions as compared to the more common single session used in many of the existing trials.
Objective: This systematized review sought to fill a gap in psilocybin research by investigating the structure and format of psilocybin-assisted psychotherapy (PAP), with a focus on the counseling components of the treatment. Methods: A systematized review of PAP was conducted by using the PubMed and PsycInfo databases to search for peer-reviewed studies of human clinical trials, published within the past 25 years, in which psilocybin was administered with psychological support in a clinical setting. Results: Eleven articles matched the criteria necessary for inclusion in this review. PAP was found to consist of three stages: pretreatment sessions to prepare participants for psilocybin, treatment sessions in which psilocybin was administered, and posttreatment sessions to integrate the experience with daily life. Conventional psychotherapy was primarily seen in the pre- and posttreatment sessions. Psychotherapies included in PAP differed among studies, but most often included music therapy and a nondirective supportive approach to treatment. Conclusions: This systematized review found important commonalities among clinical trials of PAP published within the past 25 years and revealed key differences among studies in psychotherapy's incorporation into PAP. Additional research is needed to identify the unique effect of psychotherapy in PAP.