REPORT
Expectancy Effects Threaten the Inferential
Validity of Synchrony-Prosociality Research
S. Atwood1
, Adena Schachner2*
, and Samuel A. Mehr3,4*
1Department of Psychology, Princeton University, Princeton, NJ 08540 USA
2Department of Psychology, University of California San Diego, La Jolla, CA 92093-0109 USA
3Haskins Laboratories, Yale University, Nuovo paradiso, CT 06511 USA
4School of Psychology, University of Auckland, Auckland 1010, New Zealand
*These authors contributed equally.
Keywords: synchrony, prosociality, expectancy, experimenter bias, placebo effects
ABSTRACT
Many studies argue that synchronized movement increases prosocial attitudes and behavior.
We reviewed meta-analytic evidence that reported effects of synchrony may be driven by
experimenter expectancy, leading to experimenter bias; and participant expectancy, otherwise
known as placebo effects. We found that a majority of published studies do not adequately
control for experimenter bias and that multiple independent replication attempts with added
controls have failed to find the original effects. In a preregistered experiment, we measured
participant expectancy directly, asking whether participants have a priori expectations about
synchrony and prosociality that match the findings in published literature. Expectations about
the effects of synchrony on prosocial attitudes directly mirrored previous experimental findings
(including both positive and null effects)—despite the participants not actually engaging in
synchrony. On the basis of this evidence, we propose an alternative account of the reported
bottom-up effects of synchrony on prosociality: the effects of synchrony on prosociality may
be explicable as the result of top-down expectations invoked by placebo and experimenter
effects.
INTRODUCTION
From the sympathetic oscillation of clocks (Huygens, 1665) to the flight patterns of migratory
birds (Gunnarsson et al., 2004), synchrony is a widespread element of our physical, biologico,
and social worlds (Arenas et al., 2008; Bernieri & Rosenthal, 1991; Osipov et al., 2007;
Phillips-Silver et al., 2010; Pikovsky et al., 2003). In humans, synchronous behavior is univer-
sal (in the form of dance; Mehr et al., 2018, 2019) and sweeping claims about the importance
of synchrony to human social life, human cognition, and human evolution are common (per esempio.,
Clarke et al., 2015; Launay et al., 2016; McNeill, 1995 and many others; for discussion, Vedere
Mehr et al., 2021).
Many have argued that synchronized movement facilitates human social interaction,
aligning emotional and mental states and promoting social cohesion (Dissanayake, 2000;
Durkheim, 1912; McNeill, 1995; Tarr et al., 2016; Turner, 1995). More recently, studies have
found empirical evidence of synchrony’s positive effects on prosociality: Synchrony is reported
a n o p e n a c c e s s
j o u r n a l
Citation: Atwood, S., Schachner, A., &
Mehr, S. UN. (2022). Expectancy Effects
Threaten the Inferential Validity of
Synchrony-Prosociality Research.
Open Mind: Discoveries in Cognitive
Scienza, 6, 280–290. https://doi.org
/10.1162/opmi_a_00067
DOI:
https://doi.org/10.1162/opmi_a_00067
Supplemental Materials:
https://doi.org/10.1162/opmi_a_00067;
https://github.com/themusiclab
/synchrony-expectancy;
https://osf.io/n5fgh
Received: 28 ottobre 2021
Accepted: 23 ottobre 2022
Competing Interests: The authors
declare no conflict of interest.
Corresponding Authors:
S. Atwood
satwood@princeton.edu
Adena Schachner
schachner@ucsd.edu
Samuel A. Mehr
sam@yale.edu
Copyright: © 2022
Istituto di Tecnologia del Massachussetts
Pubblicato sotto Creative Commons
Attribuzione 4.0 Internazionale
(CC BY 4.0) licenza
The MIT Press
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Expectancy Effects In Synchrony Research Atwood et al.
to promote cooperation (Reddish et al., 2013; Valdesolo et al., 2010; Wiltermuth & Heath,
2009), affiliative behaviors (Macrae et al., 2008; Paladino et al., 2010), positive emotions
(Hove & Risen, 2009; Launay et al., 2014), connection (Hove, 2008; Lakens, 2010;
Wiltermuth & Heath, 2009), trust (Launay et al., 2013), and compassion for others ( Valdesolo
& DeSteno, 2011).
These findings support theoretical arguments that synchrony plays a causal role in the evo-
lution of human social groups and the structure of human society (Clarke et al., 2015; Jackson
et al., 2018; Lakens, 2010; Launay et al., 2016; Loersch & Arbuckle, 2013; Pearce et al., 2015;
Savage et al., 2021; Weinstein et al., 2016). These in turn have been applied in real-world
settings to ameliorate intergroup conflict (Tunçgenç & Cohen, 2016) and to design social
robots (Delaherche et al., 2012).
Importantly, these claims go beyond the related idea that imitation, coordinated move-
menti, and shared goals—independent of synchrony—increase prosociality, for which other
literatures provide evidence (per esempio., Carpenter et al., 2013; Chartrand & van Baaren, 2009; Over
& Carpenter, 2015; Sherif, 1958). Infatti, recent work on synchrony aimed to control for these
factors as potential confounds (per esempio., Reddish et al., 2013; Tarr et al., 2018). The key claim is
that synchronized movement is reliably more effective at promoting prosociality than is move-
ment that is not synchronized (even if it is coordinated), as a result of bottom-up alignment of
motoric/visual input, with aligned sensory input increasing merging of representations of self
and other (per esempio., Clarke et al., 2015; Tarr et al., 2014).
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Here, we examine an alternative account for such claims. Meta-analytic evidence suggests
that the effects of synchrony on prosociality may be driven by expectancy effects generated by
a combination of (1) experimenter expectancy, leading to experimenter bias; E (2) partici-
pant expectancy (cioè., placebo effects). Rather than a result of bottom-up alignment of motoric
and visual input, or “self-other merging” (per esempio., Clarke et al., 2015; Tarr et al., 2014), we argue
that the link between synchrony and prosociality is more parsimoniously explained as the
result of top-down expectations. We evaluate the evidence for this claim in published studies,
report new evidence demonstrating expectancy in real participants, and suggest ways future
work can tease apart effects of synchrony from effects of expectancy.
Evidence of Experimenter Bias in the Synchrony Literature
Experimenter bias occurs when differences in an experimenter’s behavior shape participant
response to align with experimenters’ expectations (Harris & Rosenthal, 1985; Rosenthal,
1976). These are most evident in study designs where both participants and experimenters
are aware of their assigned experimental condition (Rosenthal, 1976). When experimenters
are not naïve to experimental condition, biases can be large and are common across many
study situations, even if experimenter-participant contact is limited. Rosenthal and Rubin
(1978) estimated the overall size of interpersonal expectancy effects (including those caused
by experimenter biases) across 345 studies in eight domains at d = .70.
Most published studies on synchrony and prosocial behavior involve experimenters who
were aware of participants’ condition during the study (estimated at 75%; where experi-
menters were categorized as naïve if the authors stated explicitly that the experimenter was
not aware of the hypotheses or condition, or was not present during the study; Rennung &
Göritz, 2016), raising the possibility that differences in the ways experimenters interacted with
participants unconsciously shaped their responses to align with experimenters’ expectations
(Rosenthal, 1976). Two meta-analyses found weak-to-moderate effects of interpersonal syn-
chrony on prosociality (Mogan et al., 2017; Rennung & Göritz, 2016), but when limiting
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Expectancy Effects In Synchrony Research Atwood et al.
the meta-analysis to experiments where the experimenter was naïve to condition, the effect of
synchrony on prosocial behavior was not distinguishable from zero (Rennung & Göritz, 2016).
Così, methodological choices, such as allowing experimenters to be aware of participants’
condition assignment, or unequal degrees of participant expectancy, may leave synchrony-
prosociality literature vulnerable to the role of bias via experimenter demand effects (Rennung
& Göritz, 2016).
In line with this meta-analytic finding, multiple attempts to replicate the effects of highly-
cited studies in the synchrony literature with added controls for experimenter bias have failed
(Kirschner & Ilari, 2013; Schachner & Garvin, 2010). Per esempio, Schachner and Garvin
(2010) conducted two replications of the synchrony manipulation used in Wiltermuth and
Heath (2009; Exp. 3) with experimenters naïve to condition and found that, unlike the original
study, synchrony did not increase interpersonal cooperation, conformity, trust, similarity, O
feelings of being in the same team. Additionally, other studies found no prosocial effects of
synchrony in young children (Kirschner & Ilari, 2013).
The Potential for Placebo Effects Caused by Participant Expectancy
A placebo effect occurs when a response is misattributed to an inert treatment or experimental
condition, but is actually due to contextual factors such as pre-existing beliefs (Benedetti et al.,
2005). Placebo effects exist across many clinical studies (see reviews: Finniss et al., 2010;
Kaptchuk & Mugnaio, 2015; Price et al., 2008), including those in psychology (per esempio., Kirsch &
Sapirstein, 1998; Leuchter et al., 2002). While the psychological mechanisms underlying
placebo effects are controversial (per esempio., Moerman, 2002; Moerman & Jonas, 2002; Stewart-
Williams & Podd, 2004), their results are clear: When people expect that a particular inter-
vention will lead to a particular effect, this expectation alone can cause them to experience
that effect (Hahn, 1997; Kirsch, 1985, 1990; Montgomery & Kirsch, 1997; Peck & Coleman,
1991).
Participant expectancy effects are a well-documented form of placebo effects in the clinical
and experimental psychology literature (Chan & Lovibond, 1996; Colagiuri, 2010; Goldstein,
2013; Oettingen, 2000; Younger et al., 2012). Per esempio, participant expectancy affects
memory for previous experiences, biasing subjective outcome measures in favor of an inter-
vention (Price et al., 1999). Inoltre, randomized-controlled trials investigating the role of
placebo effects find that participants in pain studies who expect a particular treatment to be
effective (per esempio., acupuncture) report significantly less pain, irrespective of whether they experi-
enced actual acupuncture, or a control treatment (Linde et al., 2007). Recent work has also
found that highly structured interventions lead to stronger placebo effects than less-structured
interventions (Shen et al., 2020).
The elimination of bias introduced by expectation-based placebo effects is an essential step
to ensure the validity of findings in psychological science—yet is often overlooked. In many
studies, intervention groups are compared to control groups without accounting for differences
in expectations (Boot et al., 2013). In the case of motor synchrony, expectation-based effects
may arise due to explicit instruction (per esempio., from an experimenter, to “walk in step” as in
Wiltermuth & Heath, 2009). Tuttavia, they may also arise incidentally: By observing their
own participation in the task, participants become aware of the level of synchrony involved,
and rate the level of synchrony as different across conditions (per esempio., Tarr et al., 2018). Placebo
effects therefore remain a potential concern even in tasks where synchrony arises without
explicit instruction. Regardless of origin, participants’ a priori expectations about the height-
ened effects of an experimental manipulation on a dependent variable may be attributable to
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Expectancy Effects In Synchrony Research Atwood et al.
placebo rather than to the manipulation itself. Così, comparison to an active control that is
matched for participant expectations is necessary to fully attribute effects to the intervention,
rather than participant expectancy (Boot et al., 2013).
Do participants in synchrony experiments enter with a priori expectations about the rela-
tionship between synchrony and prosociality? If so, this would leave the synchrony literature
vulnerable to placebo effects, and imply that participant expectancy, rather than the experi-
ence of synchrony itself, may be responsible for increases in prosociality after synchrony.
If true, the bottom-up effects of synchronized behavior may be small or nonexistent, E
top-down expectations would the primary driver of synchrony’s prosocial effects.
Do Participants Have A Priori Expectations about Synchrony and Prosociality?
To test this question, we conducted a preregistered experiment (see https://osf.io/6g2vy) A
measure the degree to which participants have a priori expectations about synchrony and pro-
socialità, and whether these expectations match the findings reported in the literature (see full
methods details in Supplementary Information Text S1–S3). Participants read about a hypothet-
ical experiment (Exp. 1 in Wiltermuth and Heath (2009), among the most-cited synchrony
papers in the literature), and were asked to predict the attitudes and emotions others would
have after participating. In the original experiment, participants took a 7-minute walk around a
college campus together with two other participants and an experimenter. Participants in the
experimental condition were instructed to walk in synchrony, while participants in the control
condition were not ( Wiltermuth & Heath, 2009; S. Wiltermuth, personal communication).
Afterward, participants were surveyed regarding their attitudes toward the other participants
and their emotions, including the extent of interpersonal coordination, connection, trust, sim-
ilarity, synchrony, feeling of being on the same team, happiness, and frustration. Participants in
the synchrony condition showed greater levels of connection, trust, same team feeling, E
feelings of similarity to their partner in comparison to participants in the control condition;
but did not differ on levels of happiness ( Wiltermuth & Heath, 2009).
We asked participants (N = 216) to imagine this hypothetical experiment, and probed their
expectations by asking them to predict how other people would feel and act after participating
in such a task, using measures that mirrored those of the original study (provided by the
authors; S. Wiltermuth, personal communication). We then compared our participants’ expec-
tations to the real effects (both positive and null) reported by Wiltermuth and Heath (2009). Noi
reasoned that if participants in our hypothetical scenario study showed the same distinct pat-
tern of positive and null expectations as participants in the original study showed after actually
experiencing synchrony or asynchrony, then participant expectancy is likely to play a role in
the original experimental findings. To isolate participant expectancy from the effects of first-
person mental simulation of synchrony (see Atherton et al., 2019; Stupacher et al., 2017), we
asked participants to make predictions about other people, not themselves; and minimized
vivid imagery by keeping vignettes brief and not prompting participants to take any additional
time elaborating on what they read (as done in Atherton et al., 2019). We note that while
such measures do not preclude the possibility of all mental simulation, it is likely that partic-
ipants in our study engaged in minimal mental simulation as a result of these aspects of the
study design.
RESULTS
Participants’ expectations about the effects of synchrony tightly matched the effects of the first-
person experience of synchrony (Guarda la figura 1): Participants predicting people’s attitudes after
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Expectancy Effects In Synchrony Research Atwood et al.
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Figura 1. Participants’ expectations about synchrony match reported effects of the experience of synchrony, from a previous study. Each
set of bars represents participants’ ratings of emotions and attitudes toward other people in one of five different categories (x-axis) after actually
walking with them in synchrony (Experienced Synchrony; data from Wiltermuth & Heath, 2009; Exp. 1); actually walking normally/out of
synchrony (Experienced Control; data from Wiltermuth & Heath, 2009; Exp. 1); imagining how other people would expect to feel after walking
in synchrony (Imagined Synchrony); or imagining how others would feel after walking normally (Imagined Control). Error bars represent 95%
confidence intervals. **P < 0.00625,^p < 0.05.
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walking in synchrony (versus the control condition) predicted that they would feel more con-
nected, trusting, more on the same team (ps < .00625, the Bonferroni-adjusted alpha for 8 com-
parisons), and more similar to their group members (p < .05; this test did not survive
the correction for multiple comparisons). Notably, participants did not expect differences in
levels of happiness (p = .17), mirroring the null result reported in Wiltermuth and Heath
(2009; Exp. 1). Participants in our study also expected people to feel more coordinated and
synchronized (p’s < .00625), but not more frustrated (p > .78) after walking in synchrony (Vedere
Supplement Table S1 and Figure S2 for means, standard deviations, and visualization of all
comparisons).
On the suggestion of an anonymous reviewer, we continued by testing whether the expec-
tancy effects reported above differ in magnitude from the effects in Exp. 1 of Wiltermuth and
Heath (2009; many thanks to Scott Wiltermuth for providing the original data to enable this
analysis). We ran linear regressions predicting each variable tested in both samples (connec-
zione, trust, similarity, synchrony, feeling of being on the same team, and happiness) from the
predictors of study type (imagined, in the current study; vs. experienced, in the Wiltermuth &
Heath study), condition (synchrony vs. control/neutral), and their interaction.
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Expectancy Effects In Synchrony Research Atwood et al.
We found no evidence of differences in magnitude of the main effects across the two study
types for connection, trust, similarity, same team, or happiness; and interactions between study
type and condition were also not significant (all ps > .1). There was a difference by study type
only for the feeling of being in synchrony, such that people who experienced synchrony (rel-
ative to those who imagined it in others) showed a greater difference between synchrony vs.
control condition in how synchronized they felt (or imagined others felt) with their partner (β =
1.52, T(242) = 2.75, p = 0.006. The full regression results are reported in Appendix S3 in the
Supplementary Information.
DISCUSSION
Effects of synchrony on prosociality are typically attributed to the experience of synchrony,
with first-person sensory experience of moving in synchrony with another person causing
increased prosociality. Based on patterns of reproducibility and the results outlined above,
we suspect an alternative: Synchrony may lead to prosocial effects not because of experienc-
ing the content of the manipulation, but rather, due to systematic a priori expectations about
the effects of synchrony, held by both participants and experimenters.
We are not the first to address the role of expectancy in the synchrony literature. Past work
raised the possibility of a moderating role for experimenter effects, in that experimental designs
that did control for experimenter effects (of which there were fairly few) showed small to null
effects of interpersonal synchrony on prosocial attitudes and behaviors (see Rennung & Göritz,
2016). While this conclusion is not necessarily reflective of Rennung & Goritz’s interpretation,
these data are consistent with the idea that expectancy in general inflates effect sizes (Price
et al., 2008; Rosenthal & Rubin, 1978). The data presented here take these ideas one step
ulteriore: we provide an existence proof that expectancy regarding prosocial attitudes can be
elicited in studies of synchrony, supporting the idea of a generalized, top-down causal path-
way for effects of synchrony on prosociality that may be overlooked in favor of bottom-up
perceptual explanations.
Neither the existing literature nor our survey demonstrate an absence of a link between
synchrony and prosociality. Experimenter bias and placebo effects may only account for a
fraction of a true effect of synchrony on prosociality, and may apply differently depending
on the type of movement (finger tapping vs. walking) or social context (in virtual reality vs.
walking around campus). Ancora, given the propensity of expectations to produce large effects,
their effects are likely to be substantial. Understanding the role of expectancy is therefore
essential to understanding the psychological mechanisms underlying synchrony’s effects.
Coordinated behaviors such as imitation or having a shared goal are also thought to increase
prosociality, whether or not they involve synchronized movement (per esempio., Carpenter et al., 2013;
Chartrand & van Baaren, 2009; Over & Carpenter, 2015; Sherif, 1958). Così, even if differences
between synchrony and asynchrony are attributable to expectancy, activities that promote
coordinated behavior (such as music and dance) could be expected to promote prosociality,
independent of putative effects of synchrony.
Where might people’s expectations about synchrony come from? One possibility is that
they reflect accurate metacognition: People may be aware of the impact of synchrony on their
attitudes, emozioni, and behavior. We find such nuanced metacognition unlikely; Tuttavia,
even accurate expectations would create placebo effects. In questo caso, placebo effects would
systematically inflate the effect size of the experience of synchrony in the literature.
An alternative possibility is that people have intuitive beliefs about synchrony as a part of
their folk theories of social behavior. From childhood, humans develop intuitive mental
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Expectancy Effects In Synchrony Research Atwood et al.
theories of how the social and physical worlds work. These are shaped both by experience
and by innate biases about how people learn and think (Gopnik & Meltzoff, 1997; Spelke
& Kinzler, 2007). While rich, these intuitive theories are often wrong (Gelman, 2003;
Shtulman, 2017). Mistaken beliefs about synchrony’s impact on prosociality might result
from biases in attention and memory: Per esempio, synchrony may be a particularly salient
form of coordinated movement, such that people notice and remember interactions involving
synchronized movement more than others types of coordinated action. This would make
it easier to recall instances when synchrony led to prosociality than instances when non-
synchronized coordinated interactions led to prosociality, via an availability bias (per esempio.,
Gilovich et al., 2002), creating the belief that synchronized actions drive prosocial behavior
more than coordinated actions do.
We suspect some middle ground between these accounts to be most parsimonious. Syn-
chrony has been reported to impact a variety of attitudinal and behavioral measures, including
perceived entativity (Lakens, 2010), likeability (Hove & Risen, 2009), conformity ( Wiltermuth,
2012), trust (Tamborini et al., 2018), inclusion of other in the self (Tarr et al., 2016), prejudice
reduction (Atherton et al., 2019), and cooperative ability ( Valdesolo et al., 2010). We hypoth-
esize that the experience of synchrony likely impacts a smaller, more restricted range of social
variables, with reported effects on some variables in the literature attributable to placebo and
experimenter expectancy effects. In definitiva, identifying which (if any) of these variables are
most susceptible and to what extent they are impacted by placebo and/or expectancy effects
remains an open question and an important direction for future work.
In particular, the current study provided evidence that participants have expectations about
prosocial attitudes – and did not measure whether these expectations extended to prosocial
behaviors, like cooperation or helping. There is considerable evidence in the synchrony liter-
ature to suggest that attitudes and behaviors are linked ( Jackson et al., 2018; Lang et al., 2017;
Reddish et al., 2013; Tunçgenç & Cohen, 2016; Wiltermuth & Heath, 2009). The extent to
which expectancy effects regarding synchrony impact prosocial behaviors is an open ques-
zione, and an important direction for future work.
To determine which dependent measures are directly impacted by the experience of syn-
chrony (versus those which reflect participants’ expectations), future work should attempt to
eliminate or manipulate expectations directly. Ideally, this can be done using experimental
designs where experimenters and participants are both unaware of condition. Such methods
may be difficult to implement in synchrony experiments, as keeping participants naïve to
the level of synchrony in their own movements while maintaining a social context may be
impossible (O, almeno, would require the creative use of one-way mirrors and similar exper-
imental hijinks).
Synchrony may also be made less conspicuous by using a cover story regarding the purpose
of the study, reducing the saliency of motor synchrony in the manipulation. This would require
deception of both participants and experimenters, and all parties would need to be kept
unaware of the motivation of the study until data collection is finished. This means that for
experimenters, the cover story must be maintained over the course of data collection and
be robust against experimenters’ expectations about synchrony and the true hypothesis of
the study over time. If this method is used, researchers should provide periodic checks (per esempio.,
open-ended questions) throughout data collection to ensure that the participants and experi-
menters have not inferred the true hypothesis. Tarr et al. (2018) used this approach, taking
steps to decrease expectancy, including a cover story, a experimenter who was unaware of
the hypothesis, and conducting the synchronous/asynchronous interaction in a virtual reality
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environment with tight control over simulated movement. Results were mixed: predicted
effects of synchrony were found on only two of six measures, and most participants also
did not believe their virtual partners were real, complicating interpretation.
Past work has demonstrated that the magnitude of expectancy effects may be related to the
strength of participants’ expectations (cioè., a dose-dependent relationship; Sterzer et al., 2008).
Così, another potential way to account for expectancy effects is to use a control manipulation
that is matched for participant expectations (Boot et al., 2013). In many cases, including the
study we examine (Wiltermuth & Heath 2009; Exp. 1), the control condition is active, E
matched on many salient features (per esempio., it involves taking a walk that is similar to the manip-
ulation condition), but is not matched on participant expectations (as the results of our study
show). To tease apart the effect of the intervention from the effect of expectations, a new con-
trol condition could be created that matches the experimental condition in the degree to
which participants expect it will impact their response to the dependent variable or variables.
Alternatively, conditions could be matched by choosing a different dependent variable—one
that does not evoke differential participant expectations across conditions, but that theory pre-
dicts should be impacted by the experience of synchrony.
Achieving neutral expectations through these methods is likely to be challenging as
commonly used manipulations like walking, bouncing, or hand motions may incidentally or
intentionally engender participants’ expectations via awareness of synchronous movement.
Fortunately, there are ways to counteract this. For instance participants’ expectations may also
be experimentally manipulated, by presenting participants with evidence to change their
a priori expectations before the task. By these methods, neutral expectancy can be achieved
by presenting participants with different evidence, leading half the participants in each con-
dition to believe that the intervention (per esempio., synchronous movement) will influence their
response to the dependent variable, while the other half is led to have neutral expectations
(Clifasefi et al., 2006). It is also possible to explore the contributions of expectations to the
effects of synchrony without creating neutral expectancy. Per esempio, using the counterde-
mand design, participants could be led to believe that synchrony will only change their
response to the dependent variable after a particular amount of time or exposure, and then
be tested before and after this period (Boot et al., 2013).
Finalmente, the role of expectancy could be further tested by inducing the opposite expectation:
leading participants to believe that motor synchrony decreases prosociality. Past research has
demonstrated that conscious processes are vulnerable to expectations regardless of direction-
ality (Benedetti et al., 2003). Così, we believe that manipulating expectancy in the opposite
direction would yield decreases in self-reported prosociality following synchrony or, almeno,
attenuated positive effects of synchrony. Attenuated positive effects would be expected if the
expectation-change manipulation was not effective in every participant, or if expectation
effects are one of multiple factors that drive synchrony’s prosocial impact. Any or all of these
methods would help to determine the effects of the experience of synchrony on prosociality,
over and above placebo effects, the effects of participants’ expectations.
CONCLUSIONS
The issues we outline here threaten the validity of causal inferences in the synchrony literature,
and provide an alternative causal account of how synchrony may promote prosociality (cioè.,
top-down expectations vs. the experience of synchrony itself ). While we have not shown
that no link exists between synchrony and prosociality, the existence of nuanced top-down
expectations about the effect of synchrony in naïve participants suggests that experimenter
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bias, participant expectancy, and placebo effects likely account for some portion of a putative
true effect of synchrony on prosociality. Così, future work addressing the role of expectancy is
essential for understanding the mechanism and extent to which synchrony impacts interper-
sonal attitudes and social behavior.
ACKNOWLEDGMENTS
The authors thank Bronwyn Tarr and Joshua S. Bamford for valuable discussion and feedback,
Michelle Lee and Jordan Legaspi for assistance with data collection, and Scott Wiltermuth for
his timely assistance clarifying the method and providing original data gathered in his original
pubblicazione ( Wiltermuth & Heath, 2009).
AUTHOR CONTRIBUTIONS
(cid:129) Contributed to conception and design: AS, SA, & SAM
(cid:129) Contributed to acquisition of data: AS, SA, & SAM
(cid:129) Contributed to analysis and interpretation of data: AS, SA, & SAM
(cid:129) Drafted and/or revised the article: AS, SA, & SAM
(cid:129) Approved the submitted version for publication: AS, SA, & SAM
FUNDING INFORMATION
This research was funded by the Harvard Data Science Initiative (S.A.M.), the National Insti-
tutes of Health Director’s Early Independence Award DP5OD024566 (S.A.M.), and a National
Science Foundation Graduate Research Fellowship (S.A.).
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