research on nonverbal communication has revealed that

Nonverbal Communication

Affiliations.

• 1 Department of Psychology, Northeastern University, Boston, Massachusetts 02115, USA; email: [email protected].
• 2 Department of Psychology, University of Michigan, Flint, Michigan 48502, USA; email: [email protected].
• 3 Department of Psychology, Loyola Marymount University, Los Angeles, California 90045, USA; email: [email protected].
• PMID: 30256720
• DOI: 10.1146/annurev-psych-010418-103145

The field of nonverbal communication (NVC) has a long history involving many cue modalities, including face, voice, body, touch, and interpersonal space; different levels of analysis, including normative, group, and individual differences; and many substantive themes that cross from psychology into other disciplines. In this review, we focus on NVC as it pertains to individuals and social interaction. We concentrate specifically on ( a) the meanings and correlates of cues that are enacted (sent) by encoders and ( b) the perception of nonverbal cues and the accuracy of such perception. Frameworks are presented for conceptualizing and understanding the process of sending and receiving nonverbal cues. Measurement issues are discussed, and theoretical issues and new developments are covered briefly. Although our review is primarily oriented within social and personality psychology, the interdisciplinary nature of NVC is evident in the growing body of research on NVC across many areas of scientific inquiry.

Keywords: decoding; encoding; interpersonal accuracy; nonverbal behavior; nonverbal communication.

Publication types

• Interpersonal Relations*
• Nonverbal Communication* / psychology
• Social Perception*

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• March 1, 2024 | VOL. 19, NO. 3 CURRENT ISSUE pp.2-13

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The Utility of Assessing Nonverbal Communication in the Psychiatric Evaluation

• Khushminder Chahal , M.D.

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“You see, but you do not observe,” begins Sherlock Holmes in the 1891 short story A Scandal in Bohemia , by Arthur Conan Doyle. The passage that follows illustrates the idea of mindful observation, as Holmes makes a point to distinguish it from just seeing the steps that lead up to the room in which he and Watson stand ( 1 ). In fact, this concept of active observation is integral to the practice of medicine. As William Osler said, “the whole art of medicine is in observation” ( 2 ). Physicians perform evaluations based on the patient’s communication of ailments. Oxford Dictionary defines communication as “the imparting or exchanging of information” ( 3 ). This exchange can take many forms when interacting with a patient. Most commonly what physicians conceptualize as communication is that which is spoken by the patient. However, literature continues to reveal the importance of nonverbal behaviors in communication.

The Study of Nonverbal Communication

All forms of communication other than words can be considered nonverbal communication ( 4 ), including vocal tone, facial expressions, posturing, and bodily movements. In his 1882 book, The Expression of the Emotions in Man and Animals , Charles Darwin put forth the idea of bodily movements representing internal emotional states as a result of evolution and inheritance. He argued that these movements we see accompany certain emotional states are universal to our species and that they serve a purpose while in that emotional state ( 5 ). This was demonstrated by his understanding of the function of these movements, as muscular movements serve a purpose while in a certain emotional state. The “expression” is the sum of those underlying muscular movements. These expressions serve an evolutionary benefit for survival and evolve into habits that are inherited, known as “serviceable habits” ( 6 ).

An example of this can be demonstrated simply by the facial expression for “disgust.” Disgust can be defined as “a feeling of revulsion or profound disapproval aroused by something unpleasant or offensive” ( 7 ). From an evolutionary approach, this stimulus must therefore be one that threatens the individual. In the presence of such an offensive stimulus, whether it be a physical substance or a mental thought, the aim of the body is to prevent or remove it ( 8 ). The muscles of the face that contract, with the function of preventing/removing the toxin, give rise to the facial expression that represents disgust. This expression is that of a raised upper and lower lip, a raised and wrinkled nose, lowered eyebrows, and raised cheeks. The result is a functional closure of the mouth and nose, thereby preventing the inhalation or ingestion of a toxic substance ( 9 ). Over time, this facial expression has come to represent the emotional state of disgust. Thus, the presence of such a facial expression is communicating (nonverbally) disgust at the stimulus—that the stimulus is unpleasant or offensive.

Fast forward 90 years, and it was the paper by Ekman and Friesen ( 10 ), “Constants Across Cultures in the Face and Emotion,” that confirmed the universality of human expression of the core emotional states. In this study, in which Ekman and his team assessed facial expressions among isolated tribal members in New Guinea, it was shown that no difference was found in the ability to identify facial expressions when comparing them to other cultural groups. Emotions as separate, discrete entities, and the universal expression of them, have since been proven within many fields such as neuroscience and cross-cultural studies ( 6 ). In fact, 88% of experts within fields pertaining to nonverbal communication endorse the existence of “compelling evidence for universals in any aspect of emotion” ( 11 ).

Nonverbal Versus Verbal Communication

The importance of understanding nonverbal communication in isolation is of little benefit. Its utility is best served when in comparison with verbal communication. It is the assessment of congruency between the two forms of communication that yield the most valuable information. A patient who states “that’s fine” but shows the facial expression of disgust and looks away while saying it is communicating something much different than the patient who leans forward and looks directly at his or her physician and states “that’s fine” while nodding his or her head. Albert Mehrabian classically demonstrated that when inconsistencies in different forms of communication are present, tone and bodily movements are more trusted than is verbal content (words) ( 12 , 13 ). This demonstrated well that the influence of tone of voice and bodily movements was stronger than that of verbal content when incongruence was present. Attentiveness to such incongruence can be of great utility to physicians when interacting with their patients.

Utility in the Psychiatric Evaluation

Mindfulness of nonverbal communication will allow a physician to better understand the patient. This understanding may come in the form of obtaining more information than is verbally volunteered, distinguishing deception from truths, and achieving better diagnostic clarity. Often, these insights can be gained from only a short time of observing the patient.

These brief samples of patient behavior are known as “thin slices,” which are defined as brief excerpts of expressive behavior that are sampled from a behavioral stream ( 14 ). That is, any sample of the patient’s behavior that is enough to predict traits of the patient. In usually less than 5 minutes—even as short as seconds—these brief excerpts provide a window into the patient’s state ( 14 ). Often, they provide information that the patient may not volunteer.

A common example of brief moments of patient behavior that are very telling, in as short as seconds, is smiling. Patients often smile habitually, as a smile is socially accepted as warm, engaging, and overall positive. But a well-attuned physician may be able to identify the type of smile. For clinical purposes, a useful distinction to make may be of enjoyment versus nonenjoyment smiles. That is, smiles that are truly representing positive emotions of happiness and are subconscious (and hence, true representations) versus smiles that are consciously created for social purposes. The “Duchenne smile,” named after French neurologist Guillaume Duchenne, involves the orbicularis oculi, pars lateralis, and zygomatic major muscles in conjunction, whereas other types of smiles do not ( 15 ). The Duchenne smile is the best smile to indicate enjoyment and positive effects of happiness. It is distinguished from other smiles by the involvement of the musculature surrounding the orbit, which can be seen as wrinkling around the lateral sides of either eye. This visible difference can help identify smiles created deliberately to conceal the experience of negative emotion, which may aid physicians in identifying deception.

Deception in the patient-physician interaction has been a long-standing challenge to physicians. Usually deception in the clinical encounter is motivated by themes of exploitation, protection, and shame ( 16 ). Often, physicians rely on inconsistencies in the story or the patient’s report of symptoms to determine deceit ( 17 ). However, as Darwin stated in 1882, “They [the movements of expression] reveal the thoughts and intentions of others more truly than do words, which may be falsified” ( 5 ). In fact, even when facial movements are attempted to be falsified, there is leakage of those muscles that cannot be consciously controlled ( 18 ).

Later, the discovery of “microexpressions,” expressions lasting 1/25 to 1/5 of a second, were shown to represent such leakage and reveal true emotional states ( 19 , 20 ). The Facial Action Coding System has since been developed by Paul Ekman and his team as an objective method for quantifying facial movements, and it has been used not only in clinical settings but also in research, law enforcement, and behavioral detection settings.

Observation of the congruency of verbal and nonverbal communication provides physicians with a great amount of information that can guide their diagnostic formulation of the patient. The common “feel” of a patient within the first few moments of an encounter speaks to this and demonstrates the profound effect of nonverbal communication, even subconsciously. Studies have shown that “thin slices” can accurately predict personality disorders ( 21 ), as many psychiatrists will attest to when they speak of a patient giving off that “feel” of a personality disorder. The intuitive feel of a patient with schizophrenia, described in 1941 as “praecox feeling” by Dutch Psychiatrist H.C. Rumke, has also been associated with predicting the disorder ( 22 ). “Thin slices” also accurately predict depression ( 23 ), and even suicide risk for attempts ( 24 ) and reattempts ( 25 ). Anxiety varies based on whether it is an acute state anxiety or a chronic trait anxiety, as state anxiety is better communicated verbally, and trait anxiety is better communicated nonverbally ( 26 ). This demonstrates that even chronic states can be predicted by a momentary observation of nonverbal communication.

Conclusions

Physicians will benefit from being more mindful of nonverbal behaviors, as it allows for better diagnostic clarity in the psychiatric evaluation. Young physicians would benefit from increased education and training on the topic of nonverbal behaviors by their education and training programs. Doing so will allow for an increased emphasis on objective portions of documentation, such as the Mental Status Examination, and will also allow for more accurate assessments and evaluations.

Key Points/Clinical Pearls

Assessment of congruency between verbal and nonverbal communication can aid in determining the validity of a patient’s complaints.

Emotions can be assessed using understanding of facial expressions.

“Thin slices” represent brief excerpts of expressive behavior that are sampled from the interaction with a patient; these excerpts can provide diagnostic clarity.

Documentation of nonverbal behaviors in the Mental Status Examination can provide support of the diagnosis.

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Hands on: Nonverbal communication in Native and Non-Native American parent-child dyads during informal learning

Miriam a. novack.

1 Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine

5 Department of Psychology, Northwestern University

Murielle Standley

2 Department of Communication Sciences and Disorders, Northwestern University

3 Department of Learning Sciences, Northwestern University

Karen Washinawatok

4 Bowman Performance Consulting

Douglas Medin

Sandra waxman.

Parent-child communication is a rich, multi-modal process. Substantial research has documented the communicative strategies in certain (predominantly white) United States families, yet we know little about these communicative strategies in Native American families. The current study addresses that gap by documenting the verbal and nonverbal behaviors used by parents and their four-year-old children (N=39, 25 boys) across two communities: Menominee families (low to middle income) living on tribal lands in rural Wisconsin, and non-Native, primarily white families (middle income) living in an urban area. Dyads participated in a free-play forest-diorama task designed to elicit talk and play about the natural world. Children from both communities incorporated actions and gestures freely in their talk, emphasizing the importance of considering nonverbal behaviors when evaluating what children know. In sharp contrast to the stereotype that Native American children talk very little, Menominee children talked more than their non-Native counterparts, underlining the importance of taking into account cultural context in child assessments. For children and parents across both communities, gestures were more likely than actions to be related to the content of speech and were more likely than actions to be produced simultaneously with speech. This tight coupling between speech and gesture replicates and extends prior research with predominantly white (and adult) samples. These findings not only broaden our theories of communicative interaction and development, but also provide new evidence about the role of nonverbal behaviors in informal learning contexts.

Our understanding of the world is shaped not only by the objects and events that we encounter, but also by the culture(s) in which we are raised and by the belief systems of those who raise us. For this reason, parent-child interactions provide a window through which to view the shaping role of communication, exploration, and engagement. Adopting a cross-cultural lens offers more nuanced insight into the variation of parent-child interactions and their effects on children’s understanding of the world around them and their place within it (e.g., Cole & Bruner, 1971 ; Herrmann et al., 2010 ; Lew-Levy et al., 2017 ; Medin & Bang, 2014a ; Morelli et al., 2003 ; Rogoff, 2003 ; Schieffelin & Ochs, 1986 ; Shneidman & Woodward, 2016 ; Taverna et al., 2020 ). Nonetheless, the evidence on parent-child communication has thus far focused predominantly on the spoken word. Yet, communication involves more than words alone ( Loehr, 2007 ; McNeill, 1992 ), thus gaining a better understandings of gestures and other nonverbal behaviors that accompany speech is essential.

Although there is considerable evidence for the power of nonverbal communication, particularly in instructional contexts ( Goldin-Meadow, 2005 ), this comes primarily from Western-educated, white people, with scant evidence from a broader range of cultural communities. Moreover, although there is a strong cross-cultural research tradition documenting parent-child interaction in less formal instructional settings, these investigations have been designed to reveal the social scaffolding available within communities to support children’s learning (e.g., Rogoff, 2003 ). In the current paper, we take an initial step to broaden the empirical base by focusing on the communicative interactions among parent-child dyads from a rural Native American (Menominee Nation) community and an urban non-Native American sample. The key question is how dyads from each community integrate verbal and nonverbal behavior in their rich multimodal systems of communication.

We begin by motivating our interest in gesture as a key component of communication. Then we turn to our specific observational context, both as relevant background for our cross-cultural comparisons and to underline the importance of context in speech, gesture and communication.

Communication spans beyond the spoken word

Human communication is not restricted to verbal behavior; gestures and other nonverbal behaviors, which often accompany speech, are also instrumental to interaction ( Goldin-Meadow, 2003 ). There is strong evidence that gestures produced in concert with speech (co-speech gestures) enhance comprehension and cognitive functions of both speakers and listeners.

Gestures, defined here as empty-handed hand movements that represent information without manipulating or acting upon objects, typically accompany speech. Substantial research with predominantly white children living in urban and suburban areas of the United States has demonstrated that gesture begins early and is ubiquitous throughout development ( Bates et al., 1975 ; Carpenter et al., 1998 ; Iverson & Goldin-Meadow, 2005 ; Özçalışkan & Goldin-Meadow, 2011 ). In addition, children’s gestures serve as an index of learning and developmental change ( Novack et al., 2017 ). For instance, children often express more information through speech and gesture together, than through speech alone ( Church & Goldin-Meadow, 1986 ; Gibson et al., 2019 ; Goldin-Meadow et al., 1993 ; Perry et al., 1988 ). Thus, attending to children’s gestures, in concert with their speech, offers additional insight into what children are thinking or what they can understand.

Moreover, there is a tight temporal coupling between speech and gesture ( Bernardis & Gentilucci, 2006 ; Church et al., 2014 ; Kelly et al., 2015 ; Kelly et al., 2010 ; Kita & Özyürek, 2003 ), which has been interpreted as evidence that speech and gesture emerge from a single integrated system ( Loehr, 2007 ; McNeill, 1992 ). Gestures combine with speech to influence thinking and learning, and do so in a way that other types of hand movements, like actions that directly manipulate objects, do not ( Novack & Goldin-Meadow, 2017 ). Importantly however, research on this speech-gesture coupling comes primarily from experimental paradigms with white adult participants. What remains unknown is whether this tight speech-gesture coupling is evident in a more diverse range of participants, and whether it is in place as early as four years of age.

Learning and interaction across diverse communities

It has been widely noted that advances in psychological research have been hampered by focusing on a narrow range of study samples. Research on communicative gesture is no exception: detailed evidence on communicative gesture among more diverse participants is desperately needed. For instance, although it has been shown that infants across the world’s communities begin to point at roughly the same developmental timepoint ( Liszkowski et al., 2012 ; Salomo & Liszkowski, 2013 ), there is also substantial variability across cultures in the rates and usage of co-speech gesture among adults (e.g., see Kita, 2009 for review). There is particularly scarce research on gesture production among diverse communities, including minority communities within the United States (although, see Mejía-Arauz et al., 2005 ; Tamis-LeMonda et al., 2012 ).

Although research on gesture in Indigenous communities is scarce – there has been considerable work on cultural approaches to both teaching and learning in these communities. For instance, within Indigenous communities, there is an emphasis on learning through observation and participation in community activities, rather than direct didactic interactions ( Correa-Chávez & Rogoff, 2009 ; López et al., 2010 ; Silva et al., 2010 ; Tsethlikai & Rogoff, 2013 ). This body of work underscores the advantages of maintaining cultural practices that have existed across generations, rather than imposing western ideologies on educational practices ( Tsethlikai, 2015 ). This idea is also supported by Vygotstky’s framework that cognitive development can best be understood in the context of the tools of the culture and society in which a child develops ( Vygotsky, 1980 ).

The Menominee Nation

Despite the rich literature on cultural learning and interaction in Indigenous communities, to the best of our knowledge, there has been no systematic investigation of the amount, types, or usage of gesture, in Native American families. The current investigation offers initial evidence of communicative interaction – involving speech and gesture -- among 4-year-old children and their parents who are part of one Native American tribe – The Menominee. The Menominee Nation is federally recognized; and despite a 19 th century effort to displace them and a 20 th century period of termination (See Grignon et al., 1998 ; Peroff, 1982 ), they continue to live on their (much reduced, treaty by treaty) ancestral lands in Wisconsin. The Menominee are well-known for their sustainable forestry. And although there are excellent summaries of the Menominee history in general, and the Menominee relation to the forest in particular (See Beck, 2002 ; Beck, 2005 ; and Grignon et al., 1998 respectievly), we are unaware of any literature on communication practices in Menominee parent/child dyads.

It is important to bear in mind that there are almost 600 federally recognized Native Nations living in distinct ecological contexts as well as many urban inter-tribal communities. Although the long and ongoing history of colonialism and assimilationist efforts provides considerable common experience across Native communities, caution is warranted in making broad generalizations in the absence of supporting empirical information. Specifically, generalizing across Native peoples erases cultural and sovereign variation and participates in racializing Native peoples on U.S. terms.

This caution often has been ignored. For example, it is often claimed that Native American children are reluctant to talk ( Connelly, 1985 ; Mitchell et al., 2011 ; Wolfe et al., 1996 ), a generalization made across tribes and contexts. In formal classroom settings this reticence to speak has been observed, but it has also been insightfully analyzed as a difference between cultural communicative practices and levels of cultural identification of Native children and their Non-Native teachers’ expectations (e.g., Fryberg et al., 2013 ; Philips, 1992 ; Philips et al., 1972 ). To give one concrete example, when a Native child avoids eye contact with an adult or remains quiet during an interaction, non-Native teachers or service providers may mistakenly interpret this as inattention of disrespect. However, within the Native community, avoiding direct eye contact or other forms of assertive behavior when engaged with unfamiliar adults carries a very different valence: not only is it considered a sign of respect, it is also a sign of Native students’ cultural identification, both of which are predictors of academic success in Native students ( Fryberg et al., 2013 ). As will be evident shortly, in many contexts Native children are quite verbal.

Central to Menominee perspectives is their close reciprocal relation to nature. As an example of this integral relation with the natural world, Menominee describe themselves as ‘part of” rather than ‘apart from’ nature ( Medin & Bang, 2014b ). For over a decade, we have worked in partnership with the Menominee community to study how Menominee adults and children conceptualize the natural world and their place within it ( Medin & Atran, 2004 ; Medin, Waxman, et al., 2010 ; Unsworth et al., 2012 ). We have found, for example, that Menominee children are less likely than non-Native children to assume that the biological world is centered around humans ( Herrmann et al., 2010 ).

There is literature suggesting that both Menominee children and adults are more ecologically-oriented than their rural European-American counterparts ( Unsworth, et al, 2012 ; Medin et al, 2006) and that Menominee children are more likely to take the perspective of animals than a comparable sample of rural European-American children ( Unsworth, et al, 2012 ; Washinawatok, et al, 2017 ). Although these observations suggest greater Menominee attention to relationships (at least those involving animals), whether and how this might be manifest in parent-child dyads is not clear.

In previous work, we considered the emergence of conceptualizations about natural kinds in this community by observing young children interacting with a forest diorama ( Washinawatok et al., 2017 ). This task was originally designed in collaboration with research partners in the Menominee community in an effort to uncover how 4-year-old children from Native American and non-Native American communities represent relations among biological entities (plants, animals) in their play (See Washinawatok et al., 2017 ). That is, the diorama was not initially developed with non-Native samples and then exported to Native communities (as often is the case) but rather largely developed by Menominee adults for Menominee children.

Washinawatok et al., (2017) employed the forest diorama with three samples of 4-year-old children, playing alone with the diorama: 1) Menominee children living on Menominee land in rural Wisconsin, 2) Urban Native children associated with the inter-tribal community in Chicago, and 3) Non-Native children living in the Chicago area. Children from all three samples actively engaged with the diorama using speech, actions, and gestures. The two Native samples displayed no reluctance to talk, and Menominee 4-year-olds actually talked more than the other two samples. Another striking result was that the two Native samples were more than twice as likely than non-Native children to take the perspective of an animal in play.

The current study

In the current investigation we turn the previously solitary, child-focused forest diorama task into an interactive dyadic task for parents and their children. The dyad version of this task yields rich and diverse data that can be analyzed from a variety of perspectives. In the present paper we step away from focusing on biological cognition per se to focus specifically on the question of how parents and their children use both verbal and nonverbal behaviors to communicate in this task. For pragmatic reasons we present data from two samples: an urban, predominantly white community, and the rural Menominee community. The dyadic version of the diorama task allows us to address four main research questions.

Question 1: How much talk do children and parents produce in the diorama task? As noted earlier, the argument has been made that Native American children speak less than their non-Native counterparts in clinical and formal educational settings ( Connelly, 1985 ; Wolfe et al., 1996 ). Here, we take a strengths-based approach, identifying rates of speech during a task which is inherently designed to be relevant to the experiences of the Menominee parents and children. Recall that Washinawatok et al. (2017) reported considerable talk in Menominee children in the solo version of the dyad task. Our goal here was to see if the presence of an adult (here, a parent) might engender in children a reticence to talk with the same forest diorama. We predict, instead, that this context will showcase the verbal abilities of Menonimee children and parents, rather than the previously reported “deficit”.

Question 2: Are verbal utterances produced alone or with accompanying nonverbal behaviors? Second, we ask how verbal communication is supported by nonverbal information. Because what and how children convey with their hands is key to gaining a full picture of their communicative abilities, here we consider how Menominee and non-Native dyads incorporate manual behaviors in their spoken communication. To the best of our knowledge, this is the first examination of nonverbal behaviors in any Native American sample of parents and children.

Question 3: Are the nonverbal behaviors that accompany verbal utterances more likely to be actions or gestures? Third, we consider the nature of these nonverbal behaviors. Because dyads engaged with a physical diorama with movable parts, we expect to see not only gestures, but also actions – direct manipulations of the objects in the diorama. Actions, like gestures, can be used to communicate. But unlike gestures, actions cause the object to change state (i.e., pointing to a bear does not change the state of the bear, but picking up the bear and moving it changes its location).

Question 4: Is speech coupled more tightly with gestures than with actions? Finally, the current design allows us to test whether the tight link between speech and gesture, that is proposed to be integral to gesture’s effects on thinking and learning, is indeed stronger for gestures than for other kinds of hand movements like actions. The dyad diorama task offers a particularly strong test of this prediction because its movable elements beckon participants to communicate with actions. Building upon prior experimental evidence, we predict that speech will be coupled more tightly to gesture than to action across all populations. Specifically, we predict that gesture should be more likely to co-occur temporally with speech, and should be more likely to be related to the content of the co-occurring speech, than action.

In addressing each of all these questions, we take a developmental perspective, comparing the communicative strategies of children and their parents in each community. Our decision to focus on four-year-old children was motivated by developmental matters. Four-year-old children sit at a transition, just about to enter kindergarten and thus participate in formal learning contexts. By considering the communicative strategies that they both use, and see during informal learning contexts at this developmental juncture, we can gain insight into the types of tools they bring with them to their kindergarten classrooms.

Participants

The Menominee (“Wild Rice People”) are the oldest continuous residents of Wisconsin. There are 4,000 to 5,000 Menominee living on tribal lands in and around northeastern Wisconsin (again, see Grignon et al., 1998 ). As in the past, the reservation is heavily forested. Hunting and fishing are important activities for most adult males and for many adult females and children. The Menominee have a clan system organized around five major clans (bear, thunder or eagle, wolf, moose, and crane).

The Menominee (M) sample: Twenty-one dyads were recruited from the local Head Start program and community meetings. The children (8 girls, 13 boys) ranged from 3.05–5.68 years (M Age =4.4). Among parents, there were four fathers, and 17 mothers. Dyads participated in their homes. Although socioeconomic data on the specific sample was not collected, median family income was $34,511 at the time of data collected ( U.S. Census Bureau, 2012f ).

Non-Native American sample (nNA): Twenty-one dyads from the Chicago area were recruited through a university database. Three of the original 21 dyads were excluded for technical error (1) or difficulties with the recording (2). The final sample included 18 children (6 girls, 12 boys 1 ) ranging in age from 3.3–4.93 years (M Age =4.3). Among parents, there were three fathers, and 15 mothers. Dyads participated in a university child development lab. Demographic information was not collected from this sample, however it reflected the general demographics of the laboratory database: 75% white, median family income for families living in this town was $68,051 in 2012 according to the U. S. Census Bureau (2012e) .

The diorama measured 30 × 46 inches, mounted on a piece of 1-inch thick polystyrene foam. It included both fixed and movable parts. Fixed parts included the ground cover (a textured green mat simulating grass), rocks, logs, as well as a pond, some bushes and trees around the perimeter. Movable parts included four additional trees (two deciduous, two evergreen) as well as seven toy animals (bear, deer, eagle, turtle, cow, gorilla, zebra 2 ), which were provided in a plastic bag for participants to play with by placing, moving and integrating into the set scene of the diorama (See Figure 1 ).

Diorama provided to parent-child dyads. Note, animals typical to the North American forest ecosystem (e.g., deer), as well as those that are exotic (e.g., zebra), were included for the original purpose of the study, but a distinction between these was not made for the current purpose.

All procedures were approved by the IRB at Northwestern University under the protocol “Living and Learning in Relationships”, protocol number: STU00044698. The parent and child were seated next to each other in front of a table on which the diorama was placed. Dyads were encouraged to play in any way they liked and were assured that “…there is no right way or wrong way to play”. Sessions were videotaped from two cameras, one capturing a frontal angle and the other a side angle of the dyad diorama play. Dyads were invited to play for up to 15 minutes. Each dyad chose how long to play; there was no difference in the mean duration of the dyad sessions across communities (M M =12.53, SD=2.56; M nNA =11.67, SD=3.26, t (37)=0.92, p =.36). This provides assurance that the diorama task was equally engaging for dyads in both communities.

First, all speech was transcribed from audio alone by a transcription service. Utterances that were either inaudible or off-task (e.g., the child asked for a snack) were excluded from further analysis (8% of all utterances). Next, all nonverbal behaviors were identified from the videos. Trained coders added line-by-line descriptions of all nonverbal behaviors occurring within a “turn”. Turns were defined as either a single verbal utterance (with or without accompanying actions or gestures) or an action or gesture without accompanying speech (i.e., placing the bear next to the pond, pointing to a rock, showing how the eager flies). Turns were then coded to determine whether they included a verbal utterance only, nonverbal behavior only, or both verbal and nonverbal behavior together (intercoder agreement = 97%). Nonverbal behaviors were further coded as either actions or gestures (intercoder agreement = 90%) and for type (agreement = 84%) (see table 1 ), although here we only consider analyses on the former.

Examples of types of actions and gestures coded.

Turns that included both verbal and nonverbal behaviors were identified and coded for content relatedness. Turns in which verbal and nonverbal content was congruent were coded as “related” (e.g., participant says “look at this bear!” while pointing to the bear, or says “I think the bear wants some water” while walking the bear toward the water). Turns in which the verbal and nonverbal content differed were coded as unrelated (e.g., participant says “I think the bear wants some water” while placing the eagle in the tree) (intercoder agreement =. 88). Any disagreements were resolved by discussion.

Dependent Variables

The coding system provided a number of dependent variables that allowed us to explore the questions presented in the introduction. First, to ask how much talk was elicited during the task, we considered the number of verbal utterances produced per minute of interaction. Second, to ask whether verbal utterances were accompanied by nonverbal behaviors, we considered individual turns that contained a verbal utterance, and asked whether or not a nonverbal behavior occurred during the same turn. Note, this analysis is conducted as a binomial outcome at the level of the individual utterance, but we present graphs that show group-level data, reflected as the percent of utterances produced alone, or accompanied by actions or gestures. Finally, to test the hypothesis that gesture is unique in its ability to combine with speech compared to action, we considered all turns that included nonverbal behaviors, and compared the proportion of nonverbal behaviors that 1) were accompanied by a verbal utterance and 2) were related in content to the utterance.

This study was not preregistered. Analysis code is available at https://osf.io/s5nqb/ . Data are not publicly available, but may be made available upon request from the authors and subsequent approval by the Menominee Nation.

Verbal Behavior

Question 1: how much talk do children and parents produce in the diorama task.

This task elicited considerable verbal communication (11,424 total utterances, with, on average, 23.5 utterances per min, per dyad, see Table 2 ). To consider how the amount of talk varied between groups we submitted the average number of verbal utterances produced per minute by each speaker to a mixed effects ANOVA, with community (M, nNA) as a between-subjects variable and speaker (Parent, Child) as a within-subjects variable. This analysis revealed a main effect of speaker ( F (1,35) = 24.12, p <.001, η 2 =.40); across both communities parents talked more than their children (Menominee: t (20) = 2.31, p =.03, Hedges g=.59; nNA: t (17) = 4.66, p< .001, Hedges g = 1.38). This was qualified by a significant speaker by community interaction ( F (1,35)=3.98, p =.05, η 2 = .10). Among parents, there was no difference in the number of utterances produced in each community ( t (37)=.55, p =0.58, Hedges g = 0.19). In contrast, among children, Menominee children produced more utterances per minute than their non-Native counterparts ( t (37)= 2.12, p =.04, Hedges g = .68).

Average number of verbal utterances per minute, grouped by speaker and community. SD in parentheses.

This outcome, which stands in contrast to prior reports that Native American children speak less than non-Native children ( Connelly, 1985 ; Wolfe et al., 1996 ), suggests that in conversation with their parents, Menominee children are anything but reticent to speak.

Nonverbal Behaviors

We next explore the nonverbal behaviors elicited in the task and ask about their role in supporting verbal communication.

Question 2: Are verbal utterances produced alone or with accompanying nonverbals?

We asked how likely participants were to produce verbal utterances alone, or to accompany them with nonverbal behaviors. For example, if a parent asks, “Which one drinks water?”, their child might respond verbally (e.g., “the deer!”), or might augment this with nonverbal behavior (either a gesture: points to the deer; or an action: ‘walks’ the deer toward the pond). For this analysis, we asked a) whether verbal utterances were produced with or without nonverbal behaviors, and b) when verbal utterances were accompanied by nonverbals, whether these were actions or gestures (see Figure 2 ).

Utterances Produced with and without Nonverbals Note. Percentage of verbal utterances produced alone (gray) and produced together with a nonverbal action (patterned red) or a nonverbal gesture (solid red). Data here show percentage of all verbal utterances; analyses are conducted at the level of the individual utterance.

These analyses were conducted at the level of the utterance, using mixed-effects logistic regression models (lme4 package in R: Bates et al., 2014 ), with p -values computed using the lmerTest package ( Kuznetsova et al., 2017 ). For all analyses described, child age was initially considered, but removed because it had no significant effect on any of the dependent variables. All models included fixed effects for speaker (child, parent) and community (M: Menominee, nNA: non-Native American) as well as a random intercept for dyad (to allow for the variability contributed by each dyad) and speaker-by-dyad random slopes (to allow for the effect of speaker to vary by dyad). All final models include only main effects, since no interactions were found to be significant unless otherwise specified.

Figure 2 shows that the majority of child utterances were produced with some nonverbal behavior, either action or gesture. Therefore, only 31% of Menominee child utterances and only 32% of non-Native American child utterances were produced as verbal alone. In contrast, the majority of parent utterance were verbal alone (M: 55%, nNA: 60%). To consider whether this pattern differed significantly by speaker or community we submitted all verbal utterances (N=11,424) to a logistic regression model that predicted whether an utterance was produced together with a nonverbal behavior (1) or as verbal alone (0). The model included fixed effects for speaker (parent, child) and community (M, nNA) a random slope for speaker and random intercept of dyad. The analysis revealed a significant effect of speaker ( β = 1.15, SE=0.11, p <.001) confirming that children are more likely than adults to accompany their speech with nonverbal behaviors, but no effect of community ( β =0.09, SE=0.15, p = 0.54).

Question 3: Are nonverbal behaviors that accompany verbal utterances more likely to be actions or gestures ?

Figure 2 also shows that the majority of nonverbal behaviors that children used to accompany their verbal utterances were actions, whereas parent nonverbals were more evenly split between actions and gestures. To consider whether this observed pattern differed significantly by speaker or community, we submitted all verbal utterances that were accompanied by nonverbals (n = 6211) to a binomial model predicting whether the nonverbal was an action (1) or a gesture (0). This model included fixed effects for community (M, nNA), speaker (Child, Parent), as well as a random slope for speaker and random intercept of dyad. The analysis confirmed a main effect of speaker ( β = 0.71, SE= 0.12, p <.001): children accompanied their speech with proportionally more actions than did parents. There was no effect of community ( β = .20, SE= 0.20, p =.32).

Research Question 4: Is speech coupled more tightly with gestures than with actions?

Finally, we considered the relation between speakers’ actions and gestures and their speech. This would allow us to ask: is the tight coupling between speech and gesture specific to gesture , or it is a feature of all kinds of nonverbal behaviors? Because actions were so prevalent in this task, the current data provide a sufficiently strong base from which to assess whether action is coupled as tightly to speech as is gesture. We ask whether this tight coupling is a characteristic of the Menominee and whether it is already in place in children as young as 4.

We address this question in two ways, first by asking whether nonverbals were produced in conjunction with speech (1) or in silence (0). For instances, if asked about who lives in trees, a child could point to the bird while saying “the bird!” (speech+gesture), could place the bird in the tree while saying “the bird!” (speech+action), or could produce either of those nonverbals (the point, or the placement) without the accompanying verbal utterance. To determine whether likelihood to accompany a nonverbal with speech differed by the type of nonverbal, we submitted all nonverbal behaviors (n=7866), to a binomial regression which included main effects for nonverbal type (action vs gesture), speaker (Child, Parent), and community (M, nNA) as well as all two- and three-way interactions, random slopes for nonverbal type and speaker and a random effect of participant. As predicted, there was a main effect of nonverbal type: gestures were more likely than actions to be accompanied by speech ( β =1.08 SE= 0.20, p <.001) (or in other words, participants were more likely to produce silent actions than to produce silent gestures). There was also a significant main effect of speaker ( β =.92, SE= 0.31, p =.003), and an interaction between speaker and nonverbal type ( β =.66, SE= 0.25, p =.009). There was no significant effect of community ( β =.10 SE= 0.43, p =.81), and no other interactions reached significance ( p ’s > .12). To more clearly explore the effect of non-verbal type, we conducted follow up analyses comparing the relative likelihood that actions or gestures were accompanied by speech within each participant group. As can be seen in Figure 3a , we discovered that the pattern that gestures were more likely than actions to be produced together with speech, was significant for both parents and children and across both communities (all p ’s <.05).

Proportion of actions and gestures accompanied by speech. Graphs display the proportion of actions and gestures that a) are accompanied by speech and b) are related in content to speech. * p<.05, ** p<.001

As a second approach, we focused specifically on only the co-speech nonverbals (n=6073), to ask whether they were related to the content of the accompanying speech (1) or were unrelated (0). As a reminder, saying “look at this bear!” while pointing at a bear would be considered “related” whereas saying “I think the bear wants some water” while placing the eagle in a tree would be considered “unrelated”. We expected gestures to be more likely to be accompanied by related speech than actions. To analyze this, we submitted the data to a mixed-effects binomial logistic regression model that included effects for nonverbal type (action vs gesture), speaker (Child, Parent), and community (M, nNA) as well as all two- and three-way interactions, random slopes for nonverbal type and speaker and a random effect of participant.

As predicted, there was a significant effect of nonverbal type, demonstrating that speech-gesture combinations were more likely to be related in content than speech-action combinations ( β =1.5, SE= 0.39, p <.001). There was also a significant interaction between speaker and nonverbal type ( β =1.4, SE= 0.63, p =.02), but no main effects of community ( β =.46, SE= 0.51, p =.36) or speaker ( β =.79, SE= 0.63, p =.21), and no other interactions ( p’s >.30). Follow-up analyses within each of participant group confirmed that gestures were more likely than actions to be related in content to accompanying speech; this effect held up among both parents and children, and across both communities (all p ’s <.001, Figure 3b ). In short, the tight coupling of content in gesture and speech was robust across all groups.

To understand how children and parents across diverse communities communicate with one another, we need to look beyond words alone to consider non-verbal information as well. We also need to broaden the empirical base beyond primarily white samples. In the current paper, we considered the communicative interaction between parents and their four-year-old children in two distinct US communities as they interacted with a diorama designed in a culturally responsive way to represent a forest scene in the natural world. Adopting an inclusive view of communication, we considered nonverbal behaviors (actions and gestures) in addition to spoken language.

This task, designed by a research team that included Menominee adults, attests to the benefit of engaging collaboratively with community members to reduce cultural bias associated with exporting tasks developed with WEIRD (Western, educated, industrialized, rich and democratic) samples to other populations (e.g., Medin, Bennis, et al., 2010 ). Cultural bias can influence design decisions and hence results. For example, research on the sheer amount of talk tends to ignore the contexts in which the talk occurs ( Avineri et al., 2015 ).

This observation is likely related to one of our main findings (and the answer to Question 1). In contrast to reports documenting that Native American children talk less than their non-Native American counterparts ( Connelly, 1985 ; Wolfe et al., 1996 ), Menominee children showed the opposite pattern, producing more speech than non-Native children. The data reported here replicate prior evidence from four-year-olds playing with the forest diorama alone, and extend this work to include children’s interactions with their parents ( Washinawatok et al., 2017 ).

We also found a consistent developmental pattern: children in both communities were more likely than their parents to accompany their speech with nonverbal behaviors, especially actions. This observation, which addresses Questions 2 and 3, may simply reflect the nature of the task: because the diorama was designed specifically to engage child play and interaction, it makes sense that children would be eager to touch, point, and explore with their hands. There is, however, another possibility, one that may work in concert with the first. Perhaps children produce more nonverbals because these serve to scaffold their talk. Prior evidence reveals that for both children and adults, gesturing while speaking frees up cognitive resources ( Goldin-Meadow et al., 2001 ; Ping & Goldin-Meadow, 2010 ; Wagner et al., 2004 ). Although it is not known whether the same is true for actions, it is possible that producing any kind of nonverbal behavior frees up cognitive resources, and that this helps children express their ideas better. It is also possible that children’s use of nonverbal behaviors was influenced by the fact that they were interacting with their parent, specifically. It is an open question whether we would see different rates of nonverbal communication if children were engaged with a different peer, for instance.

Documenting co-speech gesture among the Menominee, important in itself, also highlights that gesture is critical to cognitive outcomes. Previous work with non-Native samples has found that child gesture serves as an indicator of what children know ( Goldin-Meadow et al., 1993 ) and encouraging gesture can scaffold and enhance learning ( Broaders et al., 2007 ). On the input side, parent gesture has been linked to child language outcomes ( Rowe & Goldin-Meadow, 2009 ) and teacher gesture has been shown to support student learning ( Singer & Goldin-Meadow, 2005 ). Here, we report that gesture production was equivalent across both age and community. This research presented in the current study begins to broaden the scope of this prior work by demonstrating the robust use of gesture in a sample of Native-American parents and children.

These findings also have clear implications for the educational practices that may best support learning among children from Indigenous cultures. Past research suggests that children’s learning is deeply grounded in the cultural practices from which they are raised ( Correa-Chávez & Rogoff, 2009 ; López et al., 2010 ; Silva et al., 2010 ; Tsethlikai, 2015 ; Tsethlikai & Rogoff, 2013 ). For instance, children raised in communities with a rich oral tradition may benefit from educational practices that engage and support their strength in narrative expression ( Allen & Lalonde, 2015 ; Tsethlikai, 2015 ; Tsethlikai & Rogoff, 2013 ). This may contrast with a western perspective that places greater emphasis on written and on didactic expression. Because gesture spontaneously emerges with verbal expression, and because our findings suggest robust gesture use among the Menominee dyads, this may have implications for educators. Providing opportunities to talk (and therefore to gesture) may be a culturally congruent method of assessing what children from Native American communities know or understand. Teachers, particularly those working with these communities, should be aware of the rich and important information that children can express through their hands.

Studying the multimodal communicative strategies of parents and children in two distinct communities within the US also strengthens our theories of communicative interaction and development. For instance, the results reported here support the claim that speech and gesture may be part of a single, unified communicative system ( Loehr, 2007 ; McNeill, 1992 ) and that the ways in which gesture combines with speech is unique to gesture, and not other kinds of hands movements, like action ( Novack & Goldin-Meadow, 2017 ). Across all groups, there was a tight coupling between speech and gesture that was not observed for speech and action (Question 4). Specifically, gesture was more likely than action to co-occur with speech, and was more likely than action to be related to speech in its content. The current findings replicate constructs already observed in white adults ( Bernardis & Gentilucci, 2006 ; Church et al., 2014 ; Kelly et al., 2015 ; Kelly et al., 2010 ; Kita & Özyürek, 2003 ), and extend them to Menominee adults as well as children in both communities.

These findings also tie into the growing body of literature examining verbal and non-verbal expression in Indigenous groups ( Correa-Chávez & Rogoff, 2009 ; López et al., 2010 ; Silva et al., 2010 ; Tsethlikai, 2015 ; Tsethlikai & Rogoff, 2013 ). For instance, this literature has shown that children from Indigenous cultures demonstrate increased attention and learning from observing non-directed interactions compared to children from Euro-American families raised in western-educated families. The current study adds a new dimension: it was designed to engage a single parent and child in an open-ended play-based interaction, and not designed specifically to study third-party learning. In future work, it will be important to align studies of goal-based cooperation and observational learning, with broader verbal and nonverbal communicative strategies in diverse populations.

One limitation in the current work is that Menominee dyads played with the diorama at home while non-Native dyads participated in a university laboratory, albeit in a comfortable, home-like setting. It remains to be seen how interactions might differ as a function of the location in which the dyads participated.

Another difference may also be of consequence. This task was designed to showcase experiences of the Menominee children for whom the natural environment plays an especially strong role. In contrast, the non-Native sample live in a metropolitan area, and were less familiar with forest settings. Indeed, many non-Native dyads talked about visiting the forest for camping or vacations but did not discuss the same day-to-day experience with nature that the Menominee participants did. It is an open question how much these factors may have influenced speaker’s communicative strategies, and this could be a topic for future research. Data from rural non-Native American dyads or urban Native-American dyads would address this question while at the same time extending the generalizability of our findings.

Finally, there are other differences between the two communities in the current investigation. Families living in the Evanston community tend to have higher family income ( U.S. Census Bureau, 2012e ; 2012f ) greater education ( U.S. Census Bureau, 2012a ; 2012b ), and smaller average family sizes ( U.S. Census Bureau, 2012c ; 2012d ) compared to families living in the Menominee community. Yet despite evidence documenting differences in verbal and nonverbal behavioral communication based on socioeconomic status ( Farkas & Beron, 2004 ; Hart & Risley, 1995 ; Hoff, 2003 , 2006 ; Pan et al., 2005 ; Rowe & Goldin-Meadow, 2009 ), here we found more convergences than divergences in the communicative strategies used by parents and children across communities. This suggests that, at least in the context of this free play task, socioeconomic differences between the communities were unlikely to have had strong effects on our findings. Future work should consider the effect of socioeconomic factors more thoroughly.

The current study showcases how studying the multimodal communicative strategies of parents and children in two distinct communities within the US strengthens our theories of communicative interaction and development. It also provides a broader, more culturally inclusive foundation upon which to build on existing strengths of young children in classrooms and informal learning contexts. Further, this work supports educational research focused on the pedagogical role of “hand work” in teaching and learning (e.g., Rose, 2005 ; Vossoughi et al., 2020 ). We found that parents and children use rich representational repertoires when communicating about the natural world which emphasizes the benefit of considering a multimodal approach when investigating communicative interactions between parents and children across cultures.

Acknowledgments

This research was made possible by the following grants: NSF DRL 1114530 1109210, 1713368 to Medin, NSF DRL 1114555, 1109590, 1712796 to Bang, NSF DRL 1114556, 1109677 to Washinawatok, NSF DRL 1109210 to Waxman, NICHD 083310 to Waxman and F32HD095580 to Novack.

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Nonverbal Communication Skills: 19 Theories & Findings

In it, he introduces the concept of dramaturgy, which compares everyday social interactions to actors’ portrayals of characters, suggesting that one’s social interactions are analogous to a string of varying performances (Ritzer, 2021).

Goffman’s work also included the concept of impression management. The key to impression management includes appearance; your manner of interacting; and the attitudes conveyed through gestures, facial expressions, and nonverbal skills (Ritzer, 2021).

William Shakespeare said, “All the world’s a stage.”

I’m not a trained actor, but teaching public speaking courses has made me aware that audiences seem to prefer speakers who use a variety of hand gestures. These gestures signify the speaker as “warm, agreeable, and energetic” (Goman, 2021).

Just that nugget of information has taught me to incorporate hand gestures to develop my public speaking skills.

What other nonverbal communication skills enhance daily interactions?

Before you continue, we thought you might like to download our three Positive Communication Exercises (PDF) for free . These science-based tools will help you and those you work with build better social skills and better connect with others.

This Article Contains:

What is nonverbal communication, 9 types of nonverbal communication skills, is nonverbal communication important, 2 psychology theories and models, 8 fascinating research findings, importance in counseling and healthcare, resources from positivepsychology.com, a take-home message.

Nonverbal communication is a way to convey information “achieved through facial expressions, gestures, touching (haptics), physical movements (kinesics), posture, body adornment (clothes, jewelry, hairstyle, tattoos, etc.), and even the tone, timbre, and volume of an individual’s voice (rather than spoken content)” (Navarro & Karlins, 2008, p. 2–4).

In this YouTube video, Joe Navarro explains several nonverbal communication cues, exposes some myths, and discusses his work with nonverbal communication in law enforcement.

Marco Iacoboni (2008, p. 81), author of Mirroring People , takes it a step further, stating that “gestures accompanying speech have a dual role of helping the speakers to express their thoughts and helping the listeners/viewers understand what is being said.”

To competently read body language, Navarro and Karlins (2008) provide suggestions such as rigorous observation and a familiarity with the person’s baseline behaviors. They also recommend watching for changes, or ‘tells.’

Navarro and Karlins (2008) advise becoming familiar with universal behaviors and contextualizing nonverbal cues. However, cultural norms could inhibit rigorous observation.

Characteristics of nonverbal communication

The United States is considered a low-context communication culture (MacLachlan, 2010). This means that much of the information in a message comes directly from words rather than through implication or body language.

This style of communication involves lots of verbal detail so as not to confuse listeners. Low-context cultures rely less on nonverbal communication, which can obscure or censor portions of the message.

Nonverbal communication is culturally determined, and it is largely unconscious. It indicates the speaker’s emotional state. When nonverbal cues conflict with the verbal message, it may convey confusion or deception (Navarro & Karlins, 2008).

Finally, nonverbal communication varies by gender and displays power differentials, information effective leaders can use to influence others (Hybels & Weaver, 2015; Henley, 1977).

Nonverbal communication of successful leaders

It’s essential for leaders to read body language, also known as decoding. Deciphering between engagement (e.g., nodding, tilting the head, open body postures) and disengagement (e.g., body tilting away, crossed arms and legs) can be the difference between success and failure (Goman, 2021).

Successful actors could be considered professional first-impression artists. Like actors, leaders often find themselves center stage; they must learn the art of creating first impressions.

Subjective awareness and the ability to express yourself nonverbally are known as encoding – crucial for positive first impressions. Advice from professional actors includes a maintaining a pleasant facial expression, good posture, pausing, breathing, relaxing, and avoiding hiding your hands (Shellenbarger, 2018).

This video , 8 Things Successful People Do to Look Confident , provides quick tips for confident body language even if you’re not feeling confident.

First impressions are said to be formed in less than seven seconds (Goman, 2021). In this short time, others formulate labels such as “powerful,” “submissive,” or “trustworthy.” Evolved leaders incorporate mindfulness to help.

Naz Beheshti (2018) states, “Evolved leaders… use nonverbal tools mindfully and deliberately to reinforce their message.” She goes on to say, “this lifts the value of your communication and your value as a leader” (Beheshti, 2018).

Awareness of self, others, and the situation (mindfulness) allows us to ensure that our gestures and body language align with our spoken words. This creates congruence and generates trustworthiness (Beheshti, 2018; Newberg & Waldman, 2013).

This means we are analyzing several, simultaneous nonverbal cues. A frustrated person may tap their foot, cross their arms, and tightly squeeze their biceps (Jones, 2013). These clusters may cross over and include a variety of nonverbal categories, summarized below.

1. Kinesics

Kinesics is the study of how we move our body, specifically the head, hands, body, and arms (Jones, 2013). This includes sending messages through facial expressions, gestures, eye contact, and posture.

Haptics is the study of touch or coming into physical contact with another person (Hybels & Weaver, 2015). Throughout history, touch has been surrounded by mystery and taboo. We are perplexed by healing touch and riveted by stories of infants who perished due to lack of touch. Touch can denote relationship, status, power, and personality (Henley, 1977).

Cultural norms dictate guidelines regarding touch. Mindfulness regarding social and environmental settings is prudent. We greet a friend at an informal party differently than we would greet a boss or coworker in a professional setting.

3. Proxemics

The study of space and distance is called proxemics, and it analyzes how people use the space around them (Hybels & Weaver, 2015).

This YouTube video is a fun demonstration of students completing a school project on personal space and the discomfort felt by both humans and animals when social norms are violated.

4. Territory

Territory is often used to display power or reveal a lack thereof.

“'[P]osture expansiveness,’ positioning oneself in a way that opens up the body and takes up space, activated a sense of power that produced behavioral changes in a subject independent of their actual rank or role in an organization” (Goman, 2021).

Expansiveness conveys power.

5. Environment

Environment includes objects we use to adorn ourselves and the artifacts we surround ourselves with in order to create an impression. These objects provide nonverbal cues that help others form impressions (Jones, 2013).

6. Paralinguistics

Paralinguistics, also known as vocalics, is the study of how we speak and involves pitch, volume, rate of speech, tone, quality, tempo, resonance, rhythm, and articulation to help determine the context of the message (Jones, 2013).

7. Chronemics

Chronemics is the study of time, including how it is used. Nancy Henley (1977, p. 43), author of Body Politics: Power, Sex & Nonverbal Communication , asserts “Time is far from a neutral philosophical/physical concept in our society: it is a political weapon.”

Henley (1977, p. 47) describes the concept of “ritual waiting,” stating, “The more important the person, the longer we will ungrudgingly wait for the service or honor of attention.”

8. Attractiveness

The power of drawing attention to oneself doesn’t rely on physical appeal alone. Although facial symmetry and fashion of adornment are important (Jones, 2013), people who master good eye contact, have a lively face, offer encouragement, and use open gestures are also considered attractive (Kuhnke, 2012).

9. Olfactics

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Nonverbal communication is very important, as you could reveal unintentional information, as well as cause your communication to be misinterpreted.

Leakage: Unintentional messages

Teaching social–emotional skills to incarcerated people provided me with a powerful lesson about the nuances of nonverbal communication. On a particularly challenging day, I thought it wise to meditate and center myself prior to entering the jail. However, upon seeing me, the people inside began inquiring what was going on with me. What did they detect?

Nonverbal leakage can be shown through micro-expressions, which are “very fast facial movements lasting 1/25 to 1/5 of a second” and indicate a person’s real feelings (Ekman, 2003, p. 214).

This YouTube video is the opening scene of the series Lie to Me , based on the work of Paul Ekman regarding micro-expressions.

Varying statistics on the value of nonverbal communication may cause concern for those less practiced, but which statistics are accurate?

Crossed messages

The original research from Mehrabian and Ferris (1967) regarding nonverbal communication is widely interpreted. Elizabeth Kuhnke (2012, p. 10), author of Body Language for Dummies , interprets the study, saying, “55% of the emotional message in face-to-face communication results from body language.”

A nonverbal communication formula often cited is 7–38–55, which indicates 7% of the message comes from words, 38% vocal, and 55% facial. However, Lapakko (2007) believes this formula is reckless, faulty, and misleading. Sometimes the nonverbal elements of a message, such as gestures with directions, are incredibly important, and at other times incidental.

In addition, what something “means” in communication is connected to such variables as culture, history of the relationship, people’s intentions, personal experiences, time of day and specific words used. It would be naive to suggest all these nuances could be neatly quantified, and therefore attributing a precise formula to nonverbal communication is flawed in many ways.

So regardless of statistics and formulas, we know that nonverbal communication is essential and that people skilled at both reading and interpreting body language tend to enjoy greater success in life than those not skilled (Goleman, 1997).

Basic emotion theory

Basic emotion theory (BET) posits that emotions are a “grammar of social living” that situate us in the social and moral order of society (Keltner, Sauter, Tracy, & Cowen, 2019, p. 133). In addition, emotions structure interactions, particularly in relationships that matter. BET is integral to emotional expression.

Foundational to BET is the assumption that emotional expressions coordinate social interactions in three ways:

• Through rapid conveyance of important information to aid in decision making
• To evoke specific responses
• To serve as incentives for others’ actions

This is accomplished through reward systems such as parents smiling and caressing a child who exhibits specific behaviors (Keltner et al., 2019).

BET initially focused on six basic emotions. Literature reveals there are over 20 emotions with distinct, multimodal expressions, providing a deeper structure and highlighting the advancing nature of emotional expression (Keltner et al., 2019).

Neural resonance

Two people who like each other will mirror each other’s facial expressions, gestures, postures, vocalics, and movements. This is known as neural resonance, and it aids the accurate transfer of information from one person to another (Newberg & Waldman, 2013).

To fully understand what another is saying, “you have to listen to and observe the other person as deeply and fully as possible” (Newberg & Waldman, 2013, p. 81). Neural resonance uses mirror neurons to create cooperation, empathy, and trust.

Studying nonverbal communication is revealing and intriguing. Most experts will include aspects such as eyes, facial expressions, and hands, but digging deeper reveals less-acknowledged nonverbal nuggets.

1. The benefits of yawning

Yawning is one of the fastest and simplest ways to lower mental stress and anxiety (Waldman & Manning, 2017). Social norms dictate that we refrain from yawning in specific settings, but yawning has many benefits. Did you know that snipers are taught to yawn before pulling the trigger (Waldman & Manning, 2017)?

According to Waldman and Manning (2017), yawning stimulates alertness and concentration; optimizes brain activity and metabolism; improves cognitive functioning; increases recall, consciousness, and introspection; decreases stress and relaxes the upper body; recalibrates a sense of timing; enhances social awareness and empathy; and increases sensuality and pleasure.

2. Feet don’t lie

According to Navarro and Karlins (2008), the most honest part of our body is our feet, as demonstrated by small children who dance with happiness or stomp in frustration. Many people look to the face for truth; Navarro and Karlins take the opposite approach:

“When it comes to honesty, truthfulness decreases as we move from the feet to the head” (Navarro & Karlins, 2008, p. 56), reasoning that emotions are suppressed through fabricated facial expression.

3. Gestures that help

Gestures improve memory and comprehension skills. Gestures may convey information that can influence how listeners respond, depending on the hand being used. “We tend to express positive ideas with our dominant hand and negative ideas with the other hand” (Newberg & Waldman, 2013, p. 44).

4. The eyes have it

“Social network circuits are stimulated through face-to-face eye contact, decreasing cortisol, and increasing oxytocin. The result is increased empathy, social cooperation, and positive communication” (Newberg & Waldman, 2013, p. 135).

Eyes reveal a lot about us. When we are aroused, troubled, concerned, or nervous, our blink rate increases. Once we relax, our blink rate returns to normal (Navarro & Karlins, 2008).

5. Power posing for success

Body language affects how others see us and how we view ourselves. In this YouTube video, Amy Cuddy discusses her research on power posing and how it affects success.

Amy Cuddy’s book is also discussed in our article listing books on imposter syndrome .

6. Fingers crossed

One explanation of the origin of crossing fingers for good luck comes from early beliefs in the power of the cross. The intersection of the digits, epitomizing the cross, was thought to denote a concentration of good spirits and served to anchor a wish until it came true (Keyser, 2014).

7. Fake positivity is harmful

Positivity that doesn’t register in your body or heart can be harmful. According to Barbara Fredrickson (2009, p. 180), “fake smiles, just like sneers of anger, predict heart wall collapse.” To truly benefit from a smile, touch, or embrace, you need to slow down and make it heartfelt.

8. Stand up straight

Poor posture can reduce oxygen intake by 30%, resulting in less energy (Gordon, 2003). Stooping over can make us look and feel old and out of touch. By straightening up, we can make significant differences in how we think and feel. The effect is bi-directional; attitude influences posture, just as posture influences attitude.

Good rapport between clients and practitioners stems from mirroring and synchronicity associated with neural resonance (Finset & Piccolo, 2011; Newberg & Waldman, 2013).

Carl Rogers’s Client-Centered Therapy is based on an empathetic understanding of clients. Nonverbal communication provides valuable information for both the client and the therapist. Showing you like and accept a client may be the most important information a therapist can convey (Finset & Piccolo, 2011).

Nonverbal patterns in therapy evolve over time. Specific behaviors that further the therapeutic process include “a moderate amount of head nodding and smiling; frequent, but not staring, eye contact; active, but not extreme, facial responsiveness; and a warm, relaxed, interested vocal tone” (Finset & Piccolo, 2011, p. 122).

Conscious awareness of nonverbal cues can aid in rapport building. Leaning toward the other signals comfort, whereas leaning away or crossing your arms signals discomfort (Navarro & Karlins, 2008).

Torsos and shoulder blades seem innocuous; however, blading away (turning slightly) from another person shows discomfort, while blading toward or facing another squarely shows a level of comfort (Navarro & Karlins, 2008).

Open palms are an ancient sign of trustworthiness that help establish rapport and are considered nonthreatening (Kuhnke, 2012). Hidden hands (placed in pockets or behind backs) signal disconnection and reluctance to engage. To display respect, keep an open posture with your muscles relaxed and weight evenly distributed.

Mirroring and matching go a long way to show synchronicity. Be careful to avoid mimicry, which signals disrespect (Kuhnke, 2012). Too much of a good thing can jeopardize credibility. An extended, fixed gaze into another’s eyes or effortful smiling can seem awkward, or worse.

This short YouTube video explains the dynamics of fluctuating facial expressions, based on the work of Charles Darwin and Paul Ekman.

This Silent Connections worksheet is an exercise for groups that combines mindfulness and nonverbal communication to build connections.

Someone who lacks the ability to make eye contact during conversation can be easily misinterpreted. To overcome this nonverbal communication issue, our Strategies for Maintaining Eye Contact can be very useful.

Our blog post 49 Communication Activities, Exercises, and Games includes six nonverbal communication activities for adults and three nonverbal exercises that work for families and children.

The blog post What Is Assertive Communication? 10 Real-Life Examples includes nonverbal qualities that complement and enhance assertive statements. Hints for eye contact, facial expressions, and posture can be found throughout.

In the blog post Cultivating Social Intelligence : 3 Ways to Understand Others , we discuss characteristics of social intelligence, including body language.

If you’re looking for more science-based ways to help others communicate better, this collection contains 17 validated positive communication tools for practitioners. Use them to help others improve their communication skills and form deeper and more positive relationships.

17 Exercises To Develop Positive Communication

17 Positive Communication Exercises [PDF] to develop help others develop communication skills for successful social interactions and positive, fulfilling relationships.

Created by Experts. 100% Science-based.

Nonverbal communication is an essential communication skill. Nonverbal expertise aids in delivering clear messages and forming positive impressions. It doesn’t have to be a big gesture to make a difference. Gently stroking the hand of a grieving friend speaks volumes.

Viewing life as a series of dramatic performances, as implied by both Shakespeare and Goffman, can add a sense of intrigue and adventure to enhancing nonverbal communication. These essential skills will help us achieve goals.

Just as the highly motivated thespian will study and polish their craft, anyone wanting to succeed in their career or interpersonal relationships can study and practice the nuances of nonverbal communication.

Actors and public speakers often practice their craft in front of a mirror or videotape themselves to reflect on strengths and weaknesses.

This article includes a myriad of resources to help improve nonverbal communication skills with many additional resources available.

By starting with something as simple as posture, we exit stage right, headed toward the competency of center stage. Break a leg!

We hope you enjoyed reading this article. Don’t forget to download our three Positive Communication Exercises (PDF) for free .

• Beheshti, N. (2018, September 20). The power of mindful nonverbal communication. Forbes . Retrieved April 26, 2021, from https://www.forbes.com/sites/nazbeheshti/2018/09/20/beyond-language-the-power-of-mindful-nonverbal-communication/?sh=6f40b3d71501
• Ekman, P. (2003). Emotions revealed: Recognizing faces and feelings to improve communication and emotional life . Holt Paperbacks.
• Finset, A., & Piccolo, L. D. (2011). Nonverbal communication in clinical contexts. In M. Rimondini (Ed.), Communication in cognitive-behavioral therapy (pp. 107–128).  Springer Science + Business Media.
• Fredrickson, B. L. (2009). Positivity . Crown Publishing Group.
• Goffman, E. (1956). The presentation of self in everyday life . University of Edinburgh.
• Goleman, D. (1997). Emotional intelligence . Bantam Trade Paperback.
• Goman, C. K. (2018, August 26). 5 Ways body language impacts leadership results. Forbes. Retrieved May 1, 2021, from https://www.forbes.com/sites/carolkinseygoman/2018/08/26/5-ways-body-language-impacts-leadership-results/?sh=5c1b235c536a
• Gordon, J. (2003). Energy addict: 101 Physical, mental, & spiritual ways to energize your life . Berkley Publishing Group.
• Henley, N. M. (1977). Body politics: Power, sex and nonverbal communication . Simon & Schuster.
• Hybels, S., & Weaver, R. L. (2015). Communicating effectively . McGraw-Hill Education.
• Iacoboni, M. (2008). Mirroring people: The new science of how we connect with others . Farrar, Straus and Giroux.
• Jones, R. (2013). Communication in the real world: An introduction to communication studies . University of Minnesota Libraries.
• Keltner, D., Sauter, D., Tracy, J., & Cowen, A. (2019). Emotional expression: Advances in basic emotion theory. Journal of Nonverbal Behavior , 43 (3), 133–160.
• Keyser, H. (2014, March 21). Why do we cross our fingers for good luck? Mental Floss . Retrieved May 27, 2021, from https://www.mentalfloss.com/article/55702/why-do-we-cross-our-fingers-good-luck
• Kuhnke, E. (2012). Body language for dummies . John Wiley & Sons.
• Lapakko, D. (2007). Communication is 93% nonverbal: An urban legend proliferates. Communication and Theater Association of Minnesota Journal , 34 (2), 7–19.
• MacLachlan, M. (2010, February 12). Cross-cultural communication styles: High and low context. Communicaid. Retrieved May 10, 2021, from https://www.communicaid.com/cross-cultural-training/blog/high-and-low-context/
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• Waldman, M. R., & Manning, C. P. (2017). NeuroWisdom: The new brain science of money, happiness, and success . Diversion Books.

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Cross-cultural Differences in Using Nonverbal Behaviors to Identify Indirect Replies

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• Published: 06 February 2024

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• Hio Tong Pang   ORCID: orcid.org/0000-0002-3389-7120 1 ,
• Xiaolin Zhou   ORCID: orcid.org/0000-0001-7363-4360 2 &
• Mingyuan Chu   ORCID: orcid.org/0000-0002-0266-0104 1  

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The ability to decode nonverbal cues is essential for effective cross-cultural communication. Despite the significance of nonverbal communication, research in this area has primarily focused on spoken language. This is particularly problematic during indirect communication, where there is a discrepancy between the surface meaning and the true intention (e.g., “Well, there is still room for improvement in your writing skills”). Misinterpretation of nonverbal cues during indirect communication can impede the decoding of true intention and potentially create hostile situations. The present study investigated cross-cultural differences in the use of nonverbal cues in decoding indirect messages. British and Chinese raters watched silent video clips and identified the types of replies from models of their own and the other culture. Results revealed that British raters were able to recognize indirect replies from British models but not from Chinese models above chance level, whereas Chinese raters were able to recognize indirect replies from models of both cultures above chance level. Furthermore, British raters showed higher accuracy and confidence in identifying indirect replies from British models than Chinese models. In contrast, Chinese raters were equally skilled and confident in identifying indirect replies from both British and Chinese models. Additionally, British and Chinese raters employed different nonverbal cues to recognize indirect replies from models of their respective cultures. These findings underscore the importance of cross-cultural differences in identifying indirect replies through nonverbal communication and provide insights to enhance intercultural communication between British and Chinese individuals.

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Introduction

Successful social interactions and relationship maintenance depend on effective communication (Cushman & Cahn, 1985 ). As a result of globalization, people are increasingly likely to interact with people from different cultures. Research on cross-cultural communication has primarily focused on spoken language, while nonverbal aspects have been largely overlooked. Decoding nonverbal messages is crucial for effective cross-cultural interaction (Dohen et al., 2010 ; Matsumoto, 2006 ). In social situations, people often use indirect communication, where the intended meaning is different from the surface meaning, to prevent disapproval or criticism and maintain social harmony (e.g., “I don’t believe everyone shares the same sense of humor”; Brown & Levinson, 1987 ; Clark, 1996 ). It is crucial to comprehend cultural variances in nonverbal behaviors during indirect communication, as misinterpreting nonverbal cues can lead to misunderstanding and hostility. Thus, this study aims to explore cross-cultural differences in nonverbal cue use when decoding indirect replies among British and Chinese individuals.

Nonverbal behaviors such as hand gestures, head movements, facial expressions, and eye gaze have long been recognized as critical aspects of communication. For example, research has shown that hand gestures help listeners comprehend the context of a conversation (Hostetter, 2011 ), facial expressions and head movements enhance the perception of expressers’ emotional status (Krumhuber et al., 2013 ; Livingstone & Palmer, 2016 ), and eye gaze indicates social closeness between individuals in a conversation (Breil & Böckler, 2021 ; Willis et al., 2011 ). In indirect communication nonverbal cues can be particularly important (Dohen et al., 2010 ; Kendon, 1997 ; McNeill, 1985 , 1987 , 1992 ). Several studies have highlighted the significant contribution of nonverbal cues in indirect communication. For example, Kelly ( 2001 ) found that children better understand their mother’s indirect request (e.g., “Don’t forget it’s raining outside.”) when accompanied by nonverbal behaviors, such as pointing to a raincoat, compared to verbal messages only. Similarly, Kirk et al. ( 2011 ) found that children with difficulties in pragmatic comprehension were more likely to comprehend hidden meanings correctly when nonverbal behaviors accompanied verbal scenarios. However, these studies have only examined the impact of hand gestures on children’s interpretation of indirect messages.

Chu and colleagues ( 2022 ) recently conducted a series of experiments to explore the role of verbal and nonverbal behaviors in encoding and decoding indirect replies. Of particular relevance to the present study are Experiments 2a and 2b, which involved participants viewing silent video clips of individuals responding to moderately face-threatening (involving breaking bad news) or neutral (involving a similar situation without any bad news) questions. Participants were instructed to identify the type of reply (direct, indirect, lie or neutral) based solely on nonverbal cues (see the Materials section for details). Results showed that four nonverbal behaviors signaling uncertainty, including palm-revealing gestures, head tilt, facial shrug, and gaze aversion (see definitions in the Nonverbal Behavior Coding section), as well as reply duration, were significant predictors of indirect categorization. That is, individuals were more likely to categorize a reply as indirect if it was longer or included those four nonverbal cues. Although Chu et al. ( 2022 ) demonstrated the importance of nonverbal cues in identifying indirect replies, the study was limited to Western participants, and it remains unclear how individuals from Eastern cultures decode indirect replies from nonverbal behaviors.

Communication is deeply rooted in culture and varies in the extent to which people use nonverbal cues to convey a message (Hall, 1976 ). For example, in individualistic cultures, there is a greater emphasis on personal autonomy and self-expression. Consequently, individuals from such cultures may use a wide range of nonverbal behaviors to convey their emotions and thoughts. In contrast, collectivist cultures emphasize group cohesion, social harmony, and the avoidance of conflict. Therefore, nonverbal behaviors are often discouraged, as they could draw attention to an individual and disrupt group harmony (Matsumoto, 2006 ; van de Vijver, 2017 ). Matsumoto et al. ( 2008 ) examined cross-cultural differences in the nonverbal display of emotions in individualistic and collectivist cultures across more than 30 countries. Their results showed that collectivist societies generally exhibit lower levels of overall emotional expressiveness compared to individualistic ones. In another study conducted by So ( 2010 ), it was found that Americans use hand gestures more often than Chinese during face-to-face communication.

Nonverbal cues can be interpreted differently by people from different cultural backgrounds (Matsumoto & Hwang, 2016 ). For example, in Western cultures, eye contact often indicates self-confidence, politeness, honesty, liking, and attention (Kleinke, 1986 ). In contrast, Eastern cultures, such as Chinese and Japanese, usually try to avoid direct eye contact as a sign of respect, courtesy, and obedience (Akechi et al., 2013 ; Vargas-Urpi, 2013 ). Similarly, in Western cultures, pointing at someone with the index finger is generally considered acceptable and is often used to draw attention or make a specific reference to someone. However, in Chinese culture, pointing at someone with the index finger is often seen as confrontational and disrespectful, considered rude or impolite. Instead, the Chinese use an open hand to refer to someone (Kita, 2009 ). Raised eyebrows provide another example of clear cultural differences. In Western culture, a raised eyebrow often signifies surprise, interest, skepticism, or curiosity (Rozin & Cohen, 2003 ). On the other hand, in Chinese culture, a raised eyebrow can also indicate joy, excitement, and pride (Yu, 2002 ).

Given these cross-cultural differences in the production and interpretation of nonverbal behaviors, it is possible that individuals are better at recognizing and understanding nonverbal cues from members of their own cultural group compared to individuals from outside that group. This is because they have higher familiarity and exposure to nonverbal behaviors within their own culture than those from other cultures. Supporting evidence primarily comes from cross-cultural research on the facial expression of emotion. For example, Elfenbein and Ambady ( 2002 ) conducted a meta-analysis on the universality and cultural specificity of emotion recognition, analyzing a total of 97 studies with 22,148 participants from 42 different nations, 23 different ethnic groups, and a wide range of cultural backgrounds. The findings revealed that while emotions were universally recognized at better-than-chance levels, the accuracy of emotion recognition was significantly higher within the same cultural group, suggesting the presence of an in-group advantage. It’s worth noting that majority groups were often less accurate at judging emotions of minority groups than the reverse, and the in-group advantage tended to diminish when cultural groups had greater exposure to one another. To date, cross-cultural research on nonverbal communication has primarily focused on nonverbal behaviors in encoding and decoding emotions. Yet, it remains unknown whether such an in-group advantage also exists in identifying indirect replies from nonverbal cues.

The Present Study

The study had three main objectives: to investigate whether British and Chinese raters could identify indirect replies from nonverbal cues at above-chance levels, to examine whether British and Chinese raters showed in-group advantage when they identified indirect replies in each other’s cultures, and to explore cross-cultural differences in using nonverbal cues for indirect reply categorization. We focused on four types of nonverbal behaviors that indicate uncertainty in communication, including palm-revealing gestures, head tilt, facial shrug, and gaze aversion (Bonnefon & Villejoubert, 2006 ; Juanchich & Sirota, 2013 ; Youmans, 2001 ). These nonverbal behaviors were found to be associated with the identification of indirect replies by western participants (Chu et al., 2022 ). To address the three research goals, British and Chinese raters viewed silent video clips of four types of replies (i.e., direct, indirect, lie, and neutral) collected from British and Chinese models and were asked to categorize the replies and indicate their confidence level.

The selection of British and Chinese cultures for this study is based on a combination of theoretical considerations and societal relevance. British and Chinese cultures have distinct norms and values. For example, British culture places a strong emphasis on individualism, which encourages individuals to freely express their thoughts and emotions (Triandis et al., 1988 ). In contrast, Chinese culture is a typical collectivist culture deeply rooted in Confucianism, emphasizing composure, poise, and a high degree of self-control (Zhang et al., 2005 ). By comparing these two cultures, researchers can gain insights into how culture shapes the use of nonverbal cues to decode hidden meanings during indirect communication. With an increasing number of Chinese students, tourists, and professionals visiting the UK, it is crucial to improve the ability of both British and Chinese people to ‘read’ each other’s nonverbal behavior. This improvement will allow for greater levels of trust to be built between UK-China communication partners and help avoid conflicts resulting from misunderstandings of nonverbal behavior.

To examine whether they could identify indirect replies purely from nonverbal cues, British and Chinese raters’ accuracy in indirect categorization will be compared against chance level. In addition, the accuracy and confidence of indirect reply categorization will be compared between the British and Chinese raters. If there was an in-group advantage, the raters should be better and more confident in identifying indirect replies from models of their own culture than those of the other culture. Finally, correlational and regression analyses were conducted to determine the contributions of different nonverbal behaviors in indirect reply categorization. The results of the study will provide insights into cross-cultural differences in the use of nonverbal cues for decoding indirect replies.

Participants

Eighty-two native Chinese raters aged between 18 and 31 years old ( M  = 23.78, SD  = 2.33, 44 females) and 80 native British raters aged 18 and 32 years old ( M  = 21.04, SD  = 2.49, 51 females) took part in this study. Sensitivity analysis using G*Power 3.1 (Faul et al., 2007 ) indicated that this sample size was sufficient to detect a small ( f  = 0.2) between-subjects main effect and a small between-within interaction effect ( f  = 0.12) at 80% statistical power (α = 0.05). The Chinese raters were students at the University of Aberdeen and had never lived outside of China for more than a year. The British raters were UK students at the University of Aberdeen and the Robert Gordon University in Aberdeen. Two Chinese raters were excluded from the study for not following the instructions (i.e., pressing one key for all trials). Participants were compensated with course credits or a £6 monetary reward. This study was approved by the Psychology Ethics Committee at the University of Aberdeen.

The stimuli consisted of silent video clips that were extracted from previous experiments that investigated nonverbal behaviors of native British and Chinese participants during face-to-face communication while delivering moderately bad news. In these experiments, a dyad first heard a face-threatening scenario (e.g., Simon is out of shape and unlikely to qualify for the cross-country running team.). A questioner (confederate) then asked a question based on the scenario (e.g., Are they likely to accept me onto the team?). A responder (participant) sat face-to-face to the questioner then replied to the question. Before commencing the experiment, a fake random group assignment procedure was employed to ensure that the confederate was always assigned the role of the questioner, and the real participant was always assigned the role of the responder. The confederate was used to promote participants’ natural responses, as they believed they were interacting with another naive participant rather than the experimenter. No participant reported awareness of the use of a confederate after the experiment. During the experiment, the responder (participant) was asked to provide four types of replies to the questioner spontaneously. A direct reply was a straightforward response (e.g., No, I think your chances of making the team are very slim.). An indirect reply was given to avoid hurting the questioner’s feelings (e.g., They are a very fit and competitive team of runners.). A lie reply was given to avoid breaking the bad news (e.g., In my opinion, you have every chance of getting on the team.). In addition, there was a neutral reply condition, in which the pair first heard a neutral scenario (e.g., You and your roommate Simon are discussing the running team at your university. Simon asks you why they seem to have improved dramatically from the previous year.). The questioner then asked a neutral question (e.g., Why do you think the running team is successful this year?) and the responder gave a fact-based neutral answer (e.g., We just have some excellent runners this year).

For the present study, a total of 640 silent video clips were used, with 320 clips created from 32 Chinese models’ responses and 320 from created from 38 British models’ responses. Each set included an equal number of clips ( n  = 80) across the four reply categories (direct, indirect, lie, and neutral). Adobe Premiere Pro 5 was utilized to eliminate the audio from all video clips and conceal the experimenter’s face in the backdrop to prevent distracting participants from concentrating on the models. The use of silent video clips was necessary because the Chinese raters were fluent in English, while the British raters had no knowledge of Chinese. Including speech in the videos would have allowed the Chinese raters to consider both verbal and nonverbal cues, whereas the British raters could only rely on nonverbal cues. The selected clips were divided equally into four testing lists, with each containing 160 clips (40 responses in each reply category), half of which were from the Chinese models and half from the British models.

A post-study questionnaire was administered to gather further insight into the participants’ use of indirect replies in daily communication and their reliance on nonverbal cues to categorize different types of replies. The questionnaire comprised five questions. The first question asked participants to rate how frequently they use indirect replies when delivering bad news on a five-point scale ranged from 1 ( daily ) to 5 ( never ). The second question asked them to rate their comfort level when someone else uses indirect replies on them on a five-point scale ranged from 1 ( very comfortable ) to 5 ( very uncomfortable ). Question 3 asked them to indicate the extent to which they relied on various nonverbal cues, such as facial expression, eye contact, and hand gestures, to categorize different types of replies in the experiment on a seven-point scale ranged from 1 ( never ) and 7 ( always ). The fourth question was open-ended and asked about any other nonverbal cues participants used during the experiment. The fifth and final question inquired whether participants attempted to read the lips of the speakers in the video clips.

Participants were tested individually. After giving informed consent, participants were instructed that they would be presented with silent video clips that contained replies from participants in a previous study, and that they would need to categorize each reply as direct, indirect, lie or neutral, while indicating their level of confidence in each categorization. To ensure that the participants understood the different types of replies, they were given identical example scenarios and replies as those used in the original experiments. The video clips were presented using Presentation® software (Version 20.3, Neurobehavioral Systems, Inc., Berkeley, CA, www.neurobs.com ) at the center of a computer screen, with a size of approximately 34 cm in width and 20 cm in height.

Each trial consisted of three phases (see Fig.  1 ). First, participants viewed a silent video clip of a response from a Chinese or British model. Next, they classified the response type using corresponding keys (1 = direct, 2 = indirect, 3 = lie, 4 = neutral), with no time limit. Participants could re-watch the clip as often as they wished by pressing the Space key. Finally, they indicated their confidence level on a seven-point scale ranged from 1 ( not confident at all ) to 7 ( extremely confident ). The inter-trial interval was 500 ms.

An Illustration of the Three Phases in Each Trial

The experiment comprised two blocks of video clips, one featuring Chinese models and the other featuring British models. The order of the two blocks was counterbalanced across participants. Each block contained 80 clips, with 20 in each reply condition. The trials within each block were randomly presented. Two practice trials were given at the beginning of each block to ensure the participants were familiar with the task. After the experiment, the participants completed a questionnaire regarding their everyday use of indirect replies and the nonverbal cues they used to categorize different types of replies. Participants were debriefed at the end of the experiment. The entire study lasted approximately 50 min.

A 2 × 2 × 4 mixed design was used, with rater culture (British and Chinese) being a between-subject factor, model culture (British and Chinese) and reply type (direct, indirect, lie, and neutral) being within-subject factors. The dependent variables were the categorization accuracy and the confidence level.

Nonverbal Behavior Coding

Nonverbal behavior coding was performed using the ELAN software (Wittenburg et al., 2006 ). The procedure of nonverbal behavior coding was identical to that used by Chu et al. ( 2022 ). Examples are illustrated in Fig.  2 . The nonverbal behaviors of each model group were coded by coders from the same culture.

Examples of ( a ) Palm-revealing Gesture, ( b ) Head Tilt, and ( c ) Facial Shrug

Palm-revealing Gesture

Palm-revealing gesture was coded when the models produced a palm up or revealed more of their palm when doing hand turns (Chu et al., 2014 ). Given that shoulder shrugs are sometimes generated with palm-revealing and are considered to have the same function, it was also coded as a palm-revealing gesture (Ferré, 2011 ; Cooperrider et al., 2018 ). The frequency of palm-revealing gestures was calculated by dividing the number of occurrences by the reply duration in each video clip.

Head tilt was defined as a single lateral head movement. The frequency of head tilt was calculated by dividing the number of occurrences by the reply duration in each video clip.

Facial Shrug

Facial shrug involved the movements of pulling mouth concerns back and raising cheeks and eyebrows (Chovil, 1991 ; Takeuchi & Nagao, 1993 ; Stone & Oh., 2008 ; Debras, 2017 ). A typical facial shrug often consists of the following action units described in the facial action coding system (FACS, Ekman et al., 2002 ), including dimpler, cheek raiser, cheek puffer, nose wrinkler, inner brow raiser or brow lowerer. The frequency of facial shrug was calculated by dividing the number of occurrences by the reply duration in each video clip.

Gaze Aversion

Gaze aversion was coded when the model did not have eye contact with the questioner. The frequency of gaze aversion was calculated by dividing the gaze aversion duration by the reply duration in each video clip.

Intercoder Reliability

To establish the intercoder reliability of the nonverbal behavior coding, second trained coders, who were from the same culture as the models and were blind to the reply conditions, independently identified palm-revealing gestures, head tilts, facial shrugs and gaze aversion from all video clips. The agreements for coding of palm-revealing gestures, head tilts, and facial shrugs were calculated by dividing the number of nonverbal behaviors agreed between the two coders by the total number of nonverbal behaviors identified by the two coders. They were 92%, 90%, and 89% in Chinese models and 94%, 87% and 91% in British models, respectively. The intercoder reliability for gaze aversion was assessed by the intraclass correlation coefficients (ICC) from the two coders. Results revealed high intercoder reliabilities for both Chinese models ( ICC  = 0.985, p  < .001) and British models ( ICC  = 0.999, p  < .001). Any disagreements were resolved through consensus-based discussions between the two coders, and the primary coder’s coding was used in the final analyses.

Data Screening

To avoid the influence of extreme outliers on the results of correlational and multiple regression analyses, any data point that deviated more than 3 standard deviations from the mean was adjusted to the value that was 3 standard deviations from the mean. This trimming procedure was employed to avoid losing data while preventing biased results from extreme values (Miyake et al., 2000 ). In total, this trimming procedure only affected 2% of all observations.

Descriptive Statistics of the Nonverbal Behaviors from all Video Clips

Table  1 displays the descriptive statistics of the palm-revealing gesture, head tilt, facial shrug, gaze aversion and reply duration from all video clips. It presents the total count of each type of nonverbal behavior, the percentage of video clips containing at least one such nonverbal behavior, as well as the mean, minimum and maximum frequency of each nonverbal behavior. For gaze aversion, the total duration (in seconds), the percentage of clips containing at least one gaze aversion and the mean, minimum, and maximum proportion of gaze aversion were reported. For reply duration, the mean, minimum and maximum reply duration (in seconds) was reported.

Accuracy Analysis in Indirect Replies

We first examined whether British and Chinese raters could correctly identify indirect replies from the silent video clips of British and Chinese models significantly better than chance level. Although the theoretical chance level for a 4-alternative forced-choice task is 25%, such threshold only holds for an infinite number of data samples. Corrected chance levels are more suitable for smaller sample sizes (Combrisson & Jerbi, 2015 ; Steffens et al., 2020 ). Following the approach of Combrisson and Jerbi ( 2015 ), we calculated the threshold for corrected chance level by using the MATLAB (Mathworks Inc., MA, USA) function binoinv (1- α, N , 1/c) * 100/ N , where α is the significance level, N is the sample size, c is the number of alternative choices. For N  = 80 and c = 4, the corrected threshold for chance was 32.5% at α = 0.05 and 36.2% at α = 0.01. As a result, British raters could identify indirect replies from British models at a level significantly better than chance, but not from Chinese models. In contrast, Chinese raters could identify indirect replies from both British and Chinese models at a level significantly better than chance. The accuracies for all four types of categorizations are presented in Table  2 .

To examine whether the British and Chinese raters showed in-group advantage when they identified indirect replies, 2 (rater: British, Chinese) x 2 (model: British, Chinese) ANOVA was performed on the categorization accuracy of indirect replies. Analyses of other types of replies were reported in the supplemental materials. There was no main effect of rater culture ( F (1, 158) = 0.67, p  = .413, η p 2  = 0.004). There was a main effect of model culture ( F (1, 158) = 12.18, p  = .001, η p 2  = 0.07). There was a significant interaction between rater and model culture ( F (1, 158) = 13.36, p  < .001, η p 2  = 0.08; see Fig.  3 for descriptive statistics). Bonferroni corrected posthoc t -tests, with a corrected alpha level at p  = .013, showed that British raters were more accurate in identifying indirect replies from British models compared to Chinese models ( p  < .001), whereas Chinese raters performed equally well in categorizing indirect replies of British and Chinese models ( p  = .891). Additionally, British raters’ accuracy in identifying indirect replies of British models was significantly higher than that of Chinese raters for both British models ( p  = .006) and Chinese models ( p  = .010).

Mean accuracy of indirect categorization of British and Chinese models from British and Chinese raters. Error bars represent standard errors

Confidence Rating Analysis in Indirect Replies

A 2 (rater: British, Chinese) x 2 (model: British, Chinese) ANOVA was conducted on the mean confidence level of the correct categorization of indirect replies. Analyses of other types of replies were reported in the supplemental materials. There was a main effect of rater culture ( F (1, 158) = 6.19, p  = .014, η p 2  = 0.04) and a main effect of model culture ( F (1, 158) = 14.41, p  < .001, η p 2  = 0.08). There was a significant interaction between rater and model culture ( F (1, 158) = 10.15, p  = .002, η p 2  = 0.06; see Fig.  4 for descriptive statistics). Bonferroni corrected posthoc t -tests, with a corrected alpha level at p  = .013, showed that British raters had higher confidence in categorizing indirect replies of British models compared to Chinese models ( p  < .001), whereas Chinese raters had similar levels of confidence in categorizing indirect replies of both British and Chinese models ( p  = .661). Additionally, British raters’ confidence level in categorizing indirect replies of British models was significantly higher than that of Chinese raters for both British models ( p  = .001) and Chinese models ( p  = .001).

Mean confidence level of correct indirect categorization of British and Chinese models from British and Chinese raters. Error bars represent standard errors

Correlation Between Accuracy and Confidence Rating in Indirect Replies

To examine the relationship between participants’ indirect categorization accuracy and confidence levels, Pearson correlation coefficients were computed between each participant’s mean indirect categorization accuracy and confidence scores. The results showed no significant relationships between indirect categorization accuracy and confidence levels (British raters rated British models: r (78) = − 0.15, p  = .191; British raters rated Chinese models: r (78) = − 0.02, p  = .832; Chinese raters rated British models: r (78) = 0.11, p  = .341; Chinese raters rated Chinese models: r (78) = − 0.15, p  = .172).

Predicting Indirect Categorization from Nonverbal Cues

Correlations.

Correlational analyses were conducted to investigate the cross-cultural difference in raters’ use of nonverbal behavior cues in identifying indirect replies from British and Chinese models. The outcome variable was the proportion of indirect categorization of each video clip (the number of times a clip was categorized as an indirect reply, regardless of accuracy, divided by the total number of times this clip was categorized). The predictor variables included the frequency of each type of nonverbal behaviors and the reply duration. The duration of indirect replies was included as a predictor variable because it was generally longer than other types of replies.

For British raters, the proportion of indirect reply categorization of both British and Chinese models was positively correlated to the frequencies of all four types of nonverbal behaviors and reply duration. For Chinese raters, the proportion of indirect reply categorization for British models was positively correlated with the frequency of facial shrug, the proportion of gaze aversion and reply duration, while the proportion of indirect reply categorization of the Chinese models was positively correlated to the frequencies of palm-revealing gesture, head tilt, gaze aversion and reply duration. Tables  3 , 4 , 5 and 6 present the Pearson correlation coefficients among the outcome variable and the predictor variables.

Multiple Regression Analyses

Two multiple regression analyses were conducted, one with British raters and the other with Chinese raters, to investigate the independent contributions of each predictor in indirect reply categorization and to determine whether participants relied on different nonverbal cues when categorizing models from different cultures. The outcome variable was the proportion of indirect categorization for each video clip. The predictor variables included the frequency of each type of nonverbal behavior, reply duration, and their interactions with model culture. Model culture was coded as a dummy variable with − 1 for British models and 1 for Chinese models. All predictor variables were mean-centered. Both multiple regression analyses satisfied the assumptions proposed by Field ( 2009 ). The sample sizes were considered adequate for the inclusion of ten predictor variables (Green, 1991 ). The normality, linearity, and homoscedasticity assumptions were met by visually inspecting residual scatterplots between errors of predictor variables and the outcome variables. The Durbin-Watson test indicated that the independence of errors assumption was met, as no values fell outside the range of 1–3. The predictor variables did not exhibit multicollinearity problems, as the VIF (Variance Inflation Factor) values ranged from 1.07 to 1.27, which were not substantially larger than 1. All Cook’s distance values were below 1, indicating that the regression models were not influenced by any single case.

Using the forced entry method, both multiple regression models on the proportion of indirect replies categorization were significant (British raters: R 2  = 42.80%, F (10, 629) = 38.60, p  < .001; Chinese raters rating British models: R 2  = 23.30%, F (10, 629) = 15.65, p  < .001).

For British raters, the frequencies of palm-revealing gesture, head tilt, facial shrug, and reply duration were significant predictors of the proportion of indirect categorization for both British and Chinese models. Additionally, there was a significant interaction between model culture and reply duration, indicating that reply duration was a stronger predictor when British raters categorized indirect replies from British models than from Chinese models.

For Chinese raters, the proportion of gaze aversion and reply duration were significant predictors of the proportion of indirect categorization for both British and Chinese models. Additionally, there was a significant interaction between model culture and facial shrug, indicating that facial shrug was used as a cue for indirect replies when Chinese raters categorized indirect replies from British models but not from Chinese models.

Tables  7 and 8 present the individual contribution of each predictor variable on the proportion of indirect reply categorization.

Questionnaire Data

Fifty-eight British raters and fifty-six Chinese raters completed the post-study questionnaire. Results from between-subject t -tests on the answers to the first two questions showed no differences between British and Chinese raters in how frequently they used indirect replies to convey bad news in everyday communication or their level of comfort when others used indirect replies. Furthermore, Bonferroni corrected t -tests on the answers to question 3, with a corrected alpha level at p  = .008, revealed that British raters relied more on facial expressions and eye contact than Chinese raters when categorizing different types of replies. However, both groups relied similarly on hand gestures, self-touches, body postures, and head gestures to categorize different types of replies. Table  9 shows the results of the t -tests on questions 1 to 3. Answers to question 4 showed that both British and Chinese raters also used silent pauses and reply duration to categorize different types of replies. Finally, answers to question 5 indicated that both British (79.25%) and Chinese raters (73.21%) attempted to read lips to aid their categorization.

The present study aimed to investigate cross-cultural differences in the use of nonverbal behaviors in identifying indirect replies. British and Chinese raters viewed silent video clips of British and Chinese models giving direct, indirect, lie and neutral replies, and were then asked to categorize the type of reply conveyed in each clip. The results revealed that British raters could only identify indirect replies from models of their own culture at above-chance levels, while Chinese raters could identify indirect replies from models of both cultures at above-chance levels. Furthermore, British raters identified indirect replies more accurately and confidently from British models than from Chinese models. Conversely, Chinese raters identified indirect replies equally accurately and confidently from British and Chinese models. Finally, cultural differences were observed in the use of nonverbal cues by both British and Chinese raters. The following sections provide a comprehensive analysis and discussion of the observed cultural differences in decoding indirectness.

Accuracy and Confidence in Identifying Indirect Replies

Our results showed that British raters were better at identifying indirect replies from models of their own culture than from Chinese models. This finding was not surprising as the British raters in the present study were primarily undergraduate students who did not have much exposure to Chinese culture. This result shows an in-group advantage of the British raters in identifying indirect replies from nonverbal cues. It is consistent with previous research showing that people are better at judging emotional expressions from their own cultural group than from other cultural groups (Elfenbein, 2013 ). In contrast, Chinese raters were equally good and confident in identifying indirect replies from British and Chinese models. This might be due to the increasing global influence of Western culture (Odinye & Odinye, 2013 ). English has become more international and modern than other languages (Pan & Block, 2011 ). Young Chinese have frequent exposure to nonverbal behaviors from English movies, TV series and other media resources (Dong et al., 1998 ; Huang & Yeh, 2019 ; Willnat et al., 1997 ). Additionally, the Chinese raters in this study were Chinese international students, who may have had more exposure to Western culture and a higher level of English proficiency compared to the majority of individuals from China. As a result, they might have already been familiar with Western nonverbal cues and able to use them to identify indirect replies from British models. Future research could consider incorporating a separate group of Chinese speakers with less exposure to Western culture and a lower level of English proficiency.

Furthermore, British raters were more accurate and confident than Chinese raters when categorizing indirect replies from models of their own cultures. This indicates that British people are better at using nonverbal cues from their own culture to identify indirect replies than Chinese people. One possible explanation for this is that British people might use indirect replies more frequently and feel more comfortable about indirect replies than Chinese people in everyday communication. However, this explanation is not supported by our questionnaire data, which showed no differences in the frequency and comfortableness of indirect replies between the British and Chinese raters. Another possibility is that people from individualistic cultures, such as Britain, may be more used to expressing their thoughts and feelings through external nonverbal behaviors. In contrast, those from collectivistic cultures, such as China, are taught to suppress nonverbal behaviors that can reveal personal feelings (Nisbett & Masuda, 2003 ). This explanation is consistent with the questionnaire data, which showed that British raters relied more on facial expressions and eye contact to categorize different types than Chinese raters, although the use of the other nonverbal cues did not differ between British and Chinese raters.

Our results indicated no significant relationships between categorization accuracy and confidence level in either British or Chinese raters, regardless of the model culture. This lack of correlation could be attributed to the raters’ inexperience in categorizing reply types from silent video clips without speech. In such an unfamiliar task, confidence levels may be interpreted differently by different raters. Furthermore, previous research has suggested that accuracy correlates more strongly with less granular confidence scales, such as a binary low/high confidence scale, than with more granular scales involving continuous responses. Scales with continuous responses can be subject to varying interpretations by different participants, potentially leading to more divergent biases. (Jin et al., 2022 ).

Cultural Differences in Using Nonverbal cues to Identify Indirect Replies

The results indicated that British and Chinese raters relied on different nonverbal cues to identify indirect replies, except for reply duration which was used as a signal of indirectness by both British and Chinese raters in both British and Chinese models. Since beating around the bush is a major strategy to convey messages during indirect replies, longer reply duration was a reliable cue for indirect replies. This idea is supported by the finding from Chu et al. ( 2022 ) that indirect replies had the longest duration compared to direct, lie and neutral replies. This result also replicated Chu et al. ( 2022 )’s result that reply duration was a significant predictor of indirect reply categorization when westerners rated western models. Hence, reply duration may serve as a cue that indicates indirect communication in both British and Chinese cultures.

British raters used palm-revealing gesture, head tilt, and facial shrug as nonverbal cues to identify indirect replies. This is consistent with the findings in Chu et al. ( 2022 ) that nonverbal behaviors that signify uncertainty, including palm-revealing gestures, head tilt, and facial shrug, were used to identify indirect replies when western raters judged silent video clips of western models. The present study extended this finding by showing that British raters also rely on these nonverbal cues to identify indirect replies in Chinese models. However, gaze aversion in Chu et al. ( 2022 ) was a significant cue for indirect categorization, whereas in the current study gaze aversion was not a significant predictor of indirect categorization. This discrepancy may be because Chu et al. ( 2022 ) included more indirect clips ( n  = 179 in Experiment 2a and n  = 320 in Experiment 2b) than the current study ( n  = 80). As gaze aversion was the weakest predictor of indirect categorization in Chu et al. ( 2022 ), the current study may lack the statistical power to establish a significant relationship between gaze aversion and indirect categorization. Furthermore, the results revealed that British raters relied more strongly on reply duration to categorize indirect replies from British models than from Chinese models. This difference may be attributed to the fact that in British models, the duration of the indirect replies was the longest among the four types of replies (Indirect: M  = 6.18, Direct: M  = 3.54; Lie: M  = 2.78; Neutral: M  = 5.35). In contrast, in Chinese models, the duration of the indirect replies was only longer than direct and lie replies but shorter than neutral replies (Indirect: M  = 7.11, Direct: M  = 3.31; Lie: M  = 3.81; Neutral: M  = 7.23). Consequently, reply duration was a more salient cue for identifying indirect replies in British models than in Chinese models.

Chinese raters relied on gaze aversion and reply duration to categorize indirect replies from both Chinese and British models. In Chinese culture, avoiding direct eye contact can help preserve social harmony, especially in potentially sensitive or confrontational conversations. It can be a way to show deference and avoid embarrassing or challenging others (Chang, 2001 ; Wei & Li, 2013 ). Thus, gaze aversion served as a nonverbal cue of indirect reply for Chinese raters. Furthermore, the significant interaction between model culture and facial shrug indicated that Chinese raters used facial shrug as a cue for indirect replies of British models but not for indirect replies of Chinese models. One might wonder whether this difference is linked to the difference in the production of facial shrug by British and Chinese models. For example, if facial shrugs were used more frequently by the British models than by the Chinese models, then Chinese raters simply relied on the more frequent nonverbal cues produced by the British model group to categorize indirect replies. Instead, it might be associated with the collectivist nature of Chinese culture, where individuals tend to maintain harmonious social interactions and are less likely to overtly express their inner states (Lim, 2016 ; Tsai et al., 2007 ). Chinese culture encourages reserved and less overt facial expressions compared to North American cultures (Gao, 1998 ). Emotions like joy, anger, and sadness are often contained to avoid imposing feelings on others and to maintain harmony (Bond, 1993 ; Bond & Hwang, 1986 ). This could explain why Chinese raters did not rely on subtle facial cues, such as facial shrug, to identify indirect replies in Chinese models. In contrast, Western cultures, often characterized as individualistic, are more likely to openly express their feelings. Therefore, Chinese raters relied on British models’ facial shrug to identify indirect replies. Additionally, palm-revealing gestures and head tilts were not considered reliable nonverbal cues for indirect replies by Chinese raters. This may be because, in Chinese culture, maintaining composure and poise in public and interpersonal interactions is seen as a sign of maturity and social grace, and overly expressive body language may be considered impolite or disruptive (Zhang et al., 2005 ).

Limitations and Future Research

It is important to consider some limitations of the present study. First, the use of video clips instead of face-to-face interaction is a potential limitation as it may not fully capture the richness and complexity of real-world social interaction. Although stimuli such as video clips were more socially relevant and perceived as more comprehensible than static images, vital aspects of social interaction may be lacking in video stimuli (Risko et al., 2012 ; Tsunemoto et al., 2022 ). Previous research has shown that live hand movements elicit stronger neural responses than recorded hand movements (Järveläinen et al., 2001 ), indicating that video stimuli may reduce the perception of real-world social interaction and weaken the associations between nonverbal behaviors and indirectness identification in the current study. To address this limitation, future research could employ virtual reality technology, which offers both experimental control and ecological validity, to further investigate the role of nonverbal cues in indirect communication.

The second limitation of the present study is that the raters only viewed silent video clips without speech. However, in real-life communication, both verbal and nonverbal cues are important in decoding indirect meanings, and people may not exclusively rely on nonverbal cues. In future studies, it would be beneficial to investigate the cross-cultural differences in the use of both verbal and nonverbal cues by testing two cultural groups who know each other’s language.

The third limitation worth noting in the present study is that the models in the video recordings were communicating with people from their own culture, which may have affected their use of nonverbal cues. As people tend to adjust their communication style according to the social context, they may use different nonverbal cues or vary the intensity of their behaviors when communicating with individuals from different cultures (Anawati & Craig, 2006 ; Pekerti & Thomas, 2003 ; Tian & McCafferty, 2021 ). To address this issue, future studies could investigate whether raters are more successful in identifying indirect replies when they perceive nonverbal behaviors produced by a foreign speaker towards listeners from the raters’ culture rather than the speaker’s culture.

Understanding cultural differences in nonverbal behaviors is particularly important during cross-cultural indirect communication. This is because the true intention behind the words goes beyond the surface meaning and misinterpretation of nonverbal cues could lead to misunderstandings and hostile interactions. The current study revealed that British and Chinese raters could identify indirect replies at above-chance levels based solely on nonverbal cues. Furthermore, British raters demonstrated an in-group advantage, performing better in identifying indirect replies from British models compared to Chinese models. In contrast, Chinese raters showed no in-group advantage, performing equally well in identifying indirect replies from both cultural groups. Finally, our research also highlights cultural differences in the use of nonverbal cues to identify indirect replies, except for reply duration being a cue for identifying indirect replies in both cultures. These findings have important implications for raising public awareness of cross-cultural differences in nonverbal behavior and improving British and Chinese people’s ability to “read” each other’s nonverbal behavior during indirect communication.

Data Availability

The stimulus materials will be available on request. Video recording data will be available once related manuscripts based on the same data set have been published.

Code Availability

Not applicable.

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This research was partly supported by the Carnegie Research Incentive Grant RIG007806 to Mingyuan Chu. We thank Duan Wang, Xiran Zhou, Maria Sadlowska, and Eadie Elizabeth Cook for their help with data collection.

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Pang, H.T., Zhou, X. & Chu, M. Cross-cultural Differences in Using Nonverbal Behaviors to Identify Indirect Replies. J Nonverbal Behav (2024). https://doi.org/10.1007/s10919-024-00454-z

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