An analysis of Non-verbal Behaviour and stress response in a dyadic Trier Social Stress Test Herman Bjørnstad

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An analysis of Non-verbal Behaviour and stress response in a dyadic Trier Social Stress Test

Herman Bjørnstad

Submitted as master thesis in psychology at the Department of Psychology Faculty of Social Sciences

University of Oslo Autumn 2021

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II Acknowledgements:

Isabell Meier for excellent supervision

Cecilia & Matthew for time and effort in behavioural coding Guro Løseth for advice with R and analysis

Siri Leknes and all the members of the Leknes Affective Brain Lab

Vegar, Gregory, Claudia, and the others from the 2019 Cognitive Neuroscience class

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An analysis of Non-verbal Behaviour and stress response in a dyadic Trier Social Stress Test By Herman Bjørnstad

Daily supervisor Dr. Isabell Meier

Department of Psychology, University of Oslo, Norway

Background: Using facial expressions, gestures, and various other movements of the body, human beings not only convey direct meaning in conjunction with verbal communication, but also reflect internal affective states. The human stress response is well documented in relation to physiological and psychological responses. Less attention, however, has been paid to the role of non-verbal behaviour in the human stress response. Objectives: Here I examine the interactions between non-verbal stress behaviours, physiological, and psychological stress responses in a dyadic version of the Trier Social stress test (dTSST). With this new, innovative set-up of the dTSST, involving pairs of friends participating in the TSST in tandem, the first objective is to validate the use of non-verbal behaviour analysis in the dTSST set-up. Secondly, I aimed to identify variations of non-verbal stress behaviours in the different stages dTSST (e.g. listening vs. speaking). The third objective is to examine the interactions between non- verbal behaviours, physiological (heart rate and cortisol levels), and psychological (self- reported stress, friendship & stress perception questionaries) measurements. Methods: A coding scheme adapted from the Ethological Coding System for Interviews (ECSI) was utilized to record the non-verbal behaviours of participants undergoing the dTSST. The adapted ECSI included 53 non-verbal behaviours divided into 10 separate behavioural categories. The non- verbal behavioural data was analysed in conjunction with heart rate, salivary cortisol, and questionnaire data collected during the pilot sessions. Results: Analyses revealed significant differences in frequency across non-verbal behavioural categories between active and passive participation in the task, indicating that some non-verbal behaviours, such as aggression and self-management behaviours, occur more frequently when participants are passively participating as compared to actively engaged in the dTSST. A correlational analysis between non-verbal behaviours and the physiological and psychological measures showed several significant correlations between psychological and behavioural measurements. Subjective stress response was positively correlated with both aggression and self-management behaviours, as was high ratings in the friendship questionaries. However, no strong significant correlations were found between behavioural and physiological stress measurements.

Conclusions: An analysis of non-verbal behaviours of participants completing a dyadic TSST

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revealed that participants engaged in certain behaviours more frequently when listening to a friend complete a stress task, than when actively participating themselves. Furthermore, frequency of non-verbal behavioural categories showed different correlations with the reported closeness between friends, indicating that the presence of a friend during a stress paradigm likely affects the behavioural response of participants. As there has not been any previous studies examining non-verbal behaviour in a dTSST, future investigation is necessary to examine the relationship between the effects of the presence of a friend during a TSST, and the behavioural stress response.

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Introduction

Research into the encompassing topic of stress and the myriad of ways it impacts our lives has been scrutinized and philosophised over since even before the term was coined by Hans Selye in 1936 as “the non-specific response of the body to any demand for change” (Tan &

Yip, 2018). The universality and the implications stress have on humanity at an individual and group level have naturally resulted in stress research being considered a topic of great interest in nearly all fields of scientific research dealing with human physiology, psychology, neurology, and behaviour (Kogler et al., 2015; Robinson, 2018; Schneiderman et al., 2005).

Typically, research considers stress to have three distinct response modalities; the physiological, psychological, and the behavioural (Chrousos & Gold, 1992; Frisch et al., 2015; Godoy et al., 2018), however, studies examining the effects on stress in human subjects traditionally focus on measuring the physiological and psychological, relying on such

measurements as respondent based questionnaires, analysis of neuroendocrine samples, biofeedback, neuroimaging, etc. (Figueroa-Fankhanel, 2014). Excluding studies examining the environmental and longitudinal behavioural correlates with stress, far less attention has been paid on the relationship between stress and the effect it has on immediate behaviour (behaviour occurring during the experience of acute stress), as well as how this non-verbal behaviour may attenuate or even exacerbate our experience of stress (Mohiyeddini & Semple, 2013; Troisi, 2002).

For a long time, non-verbal behaviours have been considered a window into an individual’s psychological state. Human beings are continuously reacting to external and internal influences through gestures, facial expressions, non-verbal utterances and other movements meant to convey meaning both conscious and unconsciously. Non-verbal behavioural analysis is utilized a myriad of different fields, with a unified belief that non- verbal behaviour serves important functions in our psychology. Research examining non- verbal behaviour investigate the frequency and origins of gaze, facial expressions, gestures, vocalizations, postures, and all other non-verbal body movements, and how they serve as carriers of relevant social, psychological and physiological information (Gatica-Perez et al., 2014). There is a vast amount of research on the nature of non-verbal behaviours itself, its role in communicating meaning, variations across cultures and individuals, and the origins and intrinsic meaning of individual behaviours (Buck & Knapp, 2006). However, non-verbal

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behavioural analysis is not unified in a single theoretical framework, and there is a lot of variation in perspectives and methodologies in the field (Hall et al., 2019)

In recent years, non-verbal behaviour has become regarded as a potential tool for understanding the behavioural components of various psychiatric disorders (Annen et al.

2012; Troisi.1999). Growing evidence from research into psychotherapeutic communication in clinical interviews has shown that non-verbal behaviours may constitute a large and significant part of the communication between a patient and a therapist (Santangelo et al.

2020), as well a tool for gaining deeper understanding of a patient's psychological and mental state by exposing clinical manifestations not seen in self-report and biological measures (Worswick et al., 2018). Similarly, the behavioural components show how we react to stress across situations and individuals and may reveal aspects of the human stress response which cannot be measured exclusively with physiological or psychological measures. Furthermore, by examining the interplay between the behavioural response to stress with the physiological and psychological, we may gain an overall deeper understanding of the human stress

response, and how established responses such as fight-or flight manifest at a behavioural level in controlled conditions (Taylor, 2000).

A Brief history of Non-verbal behavioural analysis

The study of non-verbal behaviour and its role in human emotion, communication, and cognition has a long and rather convoluted history, which can be traced back to even before there were written records (Buck & Knapp, 2006). Originally a topic of great interest and discussion in fields such as the arts, philosophy, and leadership; the study of how and why humans use their bodies the way we do has become widely studied in a myriad of sciences including but not limited to psychology, sociology, anthropology and more recently

neuroscience (Buck & Knapp, 2006; Plusquellec & Denault, 2018). The first notable works directly documenting the relationship between non-verbal behaviour and emotional

expression and the many nuances of its role in communication arrived in the 19^th century.

Perhaps the most influential of 19^th century research into non-verbal behaviours is Darwin's The Expression of the Emotions in Man and Animals (1872). This book, while largely ignored and misunderstood at the time (Ghiselin, 1974) was based on meticulous observations of facial expression and emotion. While his observations could be considered

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largely anecdotal, they were thoroughly examined and cross referenced with contemporary data in the 1970s by researchers Ekman, Friesen, and Ellsworth, who proceeded to release several publications vindicating Darwin’s view that facial expression were directly related with underlying emotional states (Hess & Thibault, 2009). Future research has been largely based on this notion, and has been an inspiration for the now widely accepted connection between emotional states and non-verbal behaviour in general (Buck & Knapp, 2006).

Following Darwin’s contributions (as well as many others), the 20^th century marked a vast expansion in the field. The availability of more sophisticated methods of recording behaviour marked an increase in researchers examining non-verbal behaviour in various fields (Buck & Knapp, 2006). The use of video recording first began to be utilized in the realm of behavioural research in the early 1930s by the anthropologist Franz Boas, who used motion picture to produce data of human gestures, motor habits and dance in a natural setting (Birx p188, 2006). But the use of film to document human behaviour quickly became popular in several other fields outside of anthropology. Experimental use of film by child

psychologist Henry Marc Halverson to study the development of grasping behaviours in infants (Halverson, 1931), is considered to be the first microscopic frame by frame analysis of human behaviour through video recording (Buck & Knapp, 2006; Davis, 1979).

As the use of video recording developed and became more available to researchers, the interest in non-verbal behaviours as a way of measuring internal states became of great interest in various fields of research (Plusquellec & Denault, 2018). Naturally, as researchers in the social sciences began to publish their findings and methods, various perspectives on how to appropriately measure non-verbal behaviours, and the implications for internal and external factors begun to arise. The 1950 & 1960s marked the rise of several important traditions and advancements in the field, laying many of the foundations onto which modern non-verbal behavioural analysis relies. It was in this time period the practice of systematically coding behaviour developed, with the work of ethologists such as Konrad Lorenz and Niko Tingberg, of measuring animal behaviour, playing a particular important role in developing such practices (Buck & Knapp, 2006).

The next decades were characterized by a deluge of research into non-verbal

behaviour, proliferated by the works of Ekman and colleagues, who published several papers on the categorization, coding, and usage of nonverbal behaviour, reviewing the wealth of previous research into the field (Ekman, 1957a; Ekman & Friesen, 1969). Out of the 1000

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most cited papers on non-verbal behaviours, Ekman is the most cited (Plusquellec & Denault, 2018). Ekman and his colleagues coding methods are that commonly used in behavioural analysis, that in methodological descriptions the precise behaviour categories are rarely defined, and rather replaced with a simple reference to Ekman and Friesen (1969).

Coincidentally, and highly applicable to this study, Ekman also spearheaded research into non-verbal behaviour recorded in interview settings, which focuses on the behaviour

responses of a participant to an interviewer, rather than another participant (Ekman, 1964).

Running on the momentum generated by researchers in the 1950s and 1960s, the following 60 years have produced a plethora of research of non-verbal analysis in a vast number of various fields. While analysis of non-verbal behaviour has become commonly utilized in fields such as education, business, politics, self-help books, public speaking, and even criminal justice (often used as so called “deception analysis”) (Denault et al., 2020;

Riggio & Feldman, 2014), the methodology and validity of this utilization is often considered questionable. In a bibliometric analysis of the 1000 most sited papers on the topic,

Plusquellec and Denault (2018) found that these peer-reviewed papers spanned between 1947 to present time, with a sharp upswing in publications in the 1970s, the most productive decade being that of 2000 to 2010. However, the proportion of published papers on non- verbal behaviour found in a random sample control group was largest in the in the decade 2010 to 2018, indicating that the research into non-verbal behaviour is continuing to increase till present time. The majority of papers (36.4%) were published in neuroscience journals, with the most cited papers being fMRI and PET studies examining activation of the amygdala in response to various salient facial expressions (Adolphs et al., 1994; Morris et al., 1996;

Whalen et al., 2001). However the fourth most cited paper is a study examining hand movements and facial mimicry in infants (Meltzoff & Moore, 1989), utilizing simple behavioural criteria such as tongue protrusion and grasping behaviours similar to that of Halverson’s 1931experiment. After neuroscience, papers published in psychology journals account for the second largest portion of the 1000 publications, accounting for 21.2%, in journals of developmental psychology, psychiatry, and behavioural sciences.

Measuring Non-verbal behaviour

Due to the rather fickle and sometimes subjective nature of non-verbal behavioural analysis, there is no single method for accurate measurement agreed upon between or even within fields of research. Rather, the methods depend largely on the ultimate hypothesis of each

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individual study, allowing researchers to measure non-verbal behaviour in a variety of different ways depending on several factors. The most prudent of these factors naturally being whether non-verbal behaviour is the dependent or independent variable in study (Gray

& Ambady, 2006). Studies where non-verbal behaviour is utilized as an independent variable most often aim to examine how non-verbal behaviour influence the physiological,

psychological, or neurological; such as Whalen et al., 2001 fMRI studies examining the effects of fearful and angry faces on activity in the amygdala. Such studies generally involve exposing a participant to some specific and highly controlled form of external non-verbal behaviour, for then to measure the physiological and psychological response. This allows for the methods used to be quite direct in comparison with the studies where non-verbal

behaviour is the dependent variable. Of course, non-verbal behaviour may also serve as both independent and dependent variable within a study, such as studies examining co-occurrence of various behaviours and their effect on affective responses (Bavelas & Chovil, 2000;

Santangelo et al., 2020).

Studies examining non-verbal behaviour as a dependent variable naturally requires a way of quantifying non-verbal behaviour in an efficient and reliable fashion. Again, this requires researchers to make several considerations as to how they wish to measure non- verbal behaviour; which behaviours to quantify, how to categorize them, what type of coding scheme to utilize, and how to go about recording and sampling of the behaviours (Ekman &

Friesen, 1969). There are several factors to consider in the measurement of nonverbal behaviour, such the number of positions, actions, and miniscule changes in body positions possible and the degree of relevance one should ascribe to them. One must also consider the interactive quality of non-verbal behaviour, and how behaviours of the face, hands and torso work in unison to express certain behaviours. This makes creating a completely concise and all-inclusive coding scheme challenging and has resulted in a myriad of different methods and perspectives for doing so.

Perhaps two of the most notable attempts of creating such a comprehensive coding scheme of non-verbal behaviours are those of Hall (1963) and Frey and colleagues (1987).

Hall’s method of coding non-verbal behaviour involves intricate coding schemes with very specific notations for body posture, degrees of orientation, kinesthetic factors, retinal

combinations, and even more obscure elements of non-verbal behaviour such as temperature and even olfaction. This method of coding also focuses on the spatial relationship between interactants (hence the inclusion of factors such as olfaction and body heat) and was quite

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revolutionary in that regard. However, a limitation of this method is the large number of notations to consider, as it demands a great deal of coding for a relatively small number of behaviours in a short amount of time. It is also limited by the lack of categorization of

behaviours. Hall himself points out such a coding scheme is rather limited in its nature, and is meant to be continuously improved upon (E. T. Hall, 1963). Similarly, the Bernese system for coding non-verbal behaviour, developed by Frey and colleagues (Hirsbrunner et al., 1987), is an advanced numerically based system designed to be able to code for all

spontaneous movements of all limbs, trunk, head, and appendages. The Bernese system notes movements of body parts in relation to the Cartesian coordinate system, each movement being noted in a position-time-series-notation based on deviation of the body from a baseline in the horizontal, vertical, and depth. Again, such a coding scheme allows the researcher to highly accurately code for all individual body movements, however such a system cannot be organized into behavioural categories, relying on each individual raters to determine the nature of the behaviour at their own discretion (Hirsbrunner et al., 1987). Furthermore, this coding scheme is designed exclusively for participants who are sitting down, which is a rather large limitation if a researcher wishes to examine the non-verbal behaviour of a participant standing up.

In response to the challenge of decoding meaning out of body movements, researchers attempt to create specific categories of non-verbal behaviours. This, however, means one must consider a range of variables which contribute to variability of non-verbal behaviour between individuals and across groups. As mentioned above, there has been much discussion on the topic of universality of non-verbal behaviours (Buck & Knapp, 2006), and this is largely a unresolved topic (J. A. Hall et al., 2019), yet this has led researchers create various methods of combatting this issue. The most popular and cited method of doing so comes from Ekman and Friesen (1969), who gathered data in several cross cultural studies (Ekman, 1965, 1964; Ekman et al., 1969), to predict cultural differences and accurately categorize behaviour based on specific criteria. These criteria include, "usage", meaning the regular and consistent circumstances surrounding the occurrence of a non-verbal act, "origin", referring to how non- verbal behaviour originally became part of a personas repertoire, and "code", the

correspondence between a behaviour and its meaning (Ekman & Friesen, 1969). When analysing behaviour according to these criteria, Ekman and Friesen identified five categories of behaviour; emblems, illustrators, affect displays, regulators, and adaptors. These

behavioural categories, while admittedly not a final nor a completely comprehensive scheme

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of all non-verbal behaviours, have provided a framework for researchers to look at the interplay between behavioural categories (particularly hand movements) and affective states (Harrigan, 2008). Additionally it allowed for the design of individual coding schemes based on the various factors of individual studies, such as the methods of observation, interaction and independent variables (Gray & Ambady, 2006).

Naturally, the specific behaviours researchers choose to record and categorize may vary, depending often on how and where the behaviours are collected. Data collected from various fields such as anthropology, human and animal ethology, clinical psychology, and various other sciences all contributed to which behaviours are chosen for various studies (Troisi, 1999; Ekman & Friesen, 1969). Parallel to animal behaviour research, the coding schemes utilized for non-verbal behavioural analysis is often presented as an ethogram, a catalogue of specific behavioural patterns specific to a species (Bateson & Martin, 1993;

Troisi, 1999). Ethograms are typically designed around research questions and the variables that researchers deem relevant to address these questions (Jones et al., 2016), and are therefor malleable in nature, apt to chance over time. Most often, whether a behaviour is ultimately included in such an ethogram depends on whether the behaviour may be recorded reliably across multiple experimenters and studies. Hence, the inter-rater reliability (as well as consensus between studies) is considered an instrumental factor in the inclusion or exclusion of non-verbal behaviours to a studies ethogram (Baesler & Burgoon, 1987). There are several factors that play an important role when considering the reliability of the measurement of non-verbal behaviour; whether objective or subjective measures are used, the scope of the unit of analysis is, if the measurement is time or event based, and the nature of the sampling plan. While there are several ways of measuring inter-rater reliability (such as Percent agreement, Cohen's Kappa, Spearman's Rho, Pearson's r), the consensus of the degree of inter-rater reliability required for a non-verbal behaviour to be accurately measured has been somewhat arbitrarily at 0.80, as a lower figure increase the possibility of underestimating relationships between behaviours and other factors. However, this figure may also vary depending on several factors, such as sample size and number of raters (Baesler & Burgoon, 1987).

The most straight forward aspect of measuring non-verbal behaviour (especially in an interview setting) is arguably the method of recording the behaviour itself. The ability to record one or more participants digitally, allows us to accurately code for behaviour

according to an appropriate sampling procedure. There are essentially 4 methods of sampling

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behaviour (Ad libitum, focal, scan, and behavioural sampling), refering to which subjects to observe and when, and two recording rules (continuous recording and time sampling), which refers to how the behaviour is recorded. (Bateson & Martin, 1993). However, in an interview setting, where the participants and setting is highly controlled for, a focal time sampling method is generally deemed most appropriate, specifically a one-zero time sampling (Annen et al., 2012; Dimic et al., 2010; Mohiyeddini et al., 2013a, 2015; Mohiyeddini & Semple, 2013; Paas Oliveros et al., 2015; Sgoifo et al., 2003; Troisi, 1999a; Villada et al., 2014). In one-zero sampling, the recording is divided into intervals (usually ten to fifteen seconds), and at the moment of each sample point, the observer records whether or not a behaviour has occurred in the interval (a zero representing the lack of occurrence). When using a relatively short interval period (such as ten of fifteen), the scores obtained are highly correlated with that of scores obtained from a continuous recording. This method or recording behaviour allows the researcher to view the frequency of how behavioural patterns occur over time, as well as the proportion of sample intervals a behaviour occur in relation to another (by individual behaviour or category) which is particularly useful when one is accounting for a myriad of behaviours at once. Furthermore, by condensing the information being recorded by an observer, it significantly reduced the workload of the observer, which permits the

recording of more categories of behaviour (Bateson & Martin, 1993; Troisi, 1999a).

Non-verbal behavioural analysis in stress research

The relationship between stress and non-verbal behaviour has been a topic of study since the early days of non-verbal behaviour analysis, particularly in animal behaviour (Blanchard et al., 2001; Dantzer, 1986). Within human stress research, ethical considerations prevent us from exposing participants to inescapable shocks, or to unknown and frightening

environments. Hence stress paradigms in human research usually involves exposing participants in a controlled environment, to a relatively mild social stressor in an interview setting, which allows researchers to easily record non-verbal behaviour. This paradigm has become a staple in stress research examining non-verbal behaviour since the early studies by Paul Ekman, examining the relationship between verbal and non-verbal communication during standardized stress interviews (similar to contemporary stress tasks) (Ekman, 1964).

One of the main focuses in research examining behavioural responses to stress is to identify the categories of non-verbal behaviours and behavioural strategies associated with stress responses, such as tend-and befriend strategies versus fight-or flight strategies (Ripetti,

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1989, Taylor et al, 2000). Non-verbal behavioural response to stress has also been of interest as a way of differentiating individuals based on personality types, such as the Repression- Sensitization personalities (Slane et al, 1980). However, it was not until the late 1990's that research into the role of specific behavioural patterns and stress response gained traction due to the development of non-verbal behavioural analysis in the field of psychiatry, specifically for clinical interviews (Troisi, 1999).

Building on the increasing interest of ethological psychiatry, and the increasing belief that ethology may serve as an additional pathway of diagnosis in psychiatric disorders,

Alfonso Troisi developed an ethogram specifically designed to measure non-verbal behaviour during doctor-patient interactions, the Ethological Coding System for Interviews (ECSI) (Troisi, 1999). Building on extensive human ethological research particularly within clinical psychiatry, Troisi developed and applied a ethological method of examining non-verbal behavioural patterns of patients suffering from schizophrenia, depression, anxiety, and various other diagnostic types (as well as none), resulting in an integrated list of movements of the head, trunk, limbs and hands, aiming to asses specific gestures and their interpersonal meanings during interviews, incorporating each behaviour in a specific behavioural category.

The ECSI is originally comprised of s 37 different behaviour patterns, mostly involving facial expressions and hand movements, organized into seven domains; affiliation, submission, prosocial behaviors, flight, assertion, displacement, and relaxation(Santangelo et al., 2020;

Troisi, 1999b, 2002). Considered a highly reliable and valid tool, with high inter-observer reliability (Paas Oliveros et al., 2015), the ECSI is considered an excellent method for analysing non-verbal behavioural patterns during interviews within psychiatry as well as other fields of study (Annen et al., 2012; Dimic et al., 2010; Geerts & Brüne, 2009; Henry et al., 2012; Mohiyeddini et al., 2013b, 2015; Mohiyeddini & Semple, 2013; Paas Oliveros et al., 2015; Santangelo et al., 2020; Sgoifo et al., 2003; Villada et al., 2014; Worswick et al., 2018).

The ECSI, is an ethogram specifically designed to measure non-verbal behaviour in a controlled interview setting, this as well as the emphasis and application of the ECSI on stress research by Troisi himself (Troisi, 2002), resulted in it quickly becoming a popular

instrument for analysing non-verbal behaviour in stress research, as it has proven particularly useful in studies using an interview based stress paradigms investigating behavioural coping (specifically the Trier Social Stress Test) (Bellagambi et al., 2018; Mohiyeddini et al., 2013;

Villada et al., 2014; Vlisides-Henry et al., 2021). As the behavioural domains included in the

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ECSI is largely based on both human and animal ethological research spanning decades, there already existed literature of the relationship between some of these categories and various forms distress (Ingram, 1960; Maestripieri et al., 1992; Troisi, 2002; Troisi et al., 2000).

Specifically, the role of displacement behaviours as a coping mechanism in response to stress have been of great interest, as such behaviours have long been subject of interest in relation to distress among animals and non-human primates (Ingram, 1960; Maestripieri et al., 1992;

McFarland, 1966; Troisi, 2002; Troisi et al., 2000).

Displacement behaviours, recently also coined as “Shifting” and “Self-management behaviours” (Paas Oliveros et al., 2015), was originally defined in animal ethology as

“irrelevant behaviours”, “which occurs in nearly all vertebrates in challenging or novel situations, such as approach-avoidance situations such as fighting, agonistic contest,

courtship, and threat displays (Breed & Moore, 2016; Troisi, 2002). While somewhat limited in relation to the vast amount of research on the topic in research into animals and non-human primates, displacement activities in humans have gained substantial attention, and have been proven to have a strong correlational relationship with stress and anxiety levels (Ekman &

Friesen, 1972; Mohiyeddini et al., 2013a, 2015; Troisi, 2002). Defined as behaviours

"Expressed as sign of social tension and motivational conflict. Reflects increased autonomic arousal”, displacement behaviour includes self-directed behaviours involving the face and hands, such as grooming behaviours, scratching, lip-biting and other behaviours deemed irrelevant to the context in which they occur (Troisi, 1999b). While long acknowledged that displacement behaviours are related to negative affective states, with the frequency of displacement behaviour increasing when individuals experience stress and anxiety, previous studies into animal behaviour as well as more recently studies into human behaviour have provided evidence that such behaviour may serve an important role in regulating stress levels.

Studies into the behavioural consequences of stress among rodents have shown that displacement activities were correlated with reduced activation of the HPA-axis among mice exposed to novel environment as well as rats exposed to electric tail shocks (Hennessy &

Foy, 1987; Levine et al., 1989). When exposed to bright lights in an novel environment, displacement responses elicited a neuroanatomically and neurochemically specific attenuation of the prefrontal cortical dopaminergic system among mice and rats, a system previously associated with high activation during stressful situation (Berridge et al., 1999). in studies examining scent marking and cortisol response among male small-eared bushbabies, researchers have found that displacement behaviours including self-grooming behaviours

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such as foot rubbing, chest rubbing was systematically related to lower cortisol levels during a restraint stress paradigm (Watson et al, 1999). Furthermore, research into indices to measure animal well-being, particularly farm animals have found a strong relationship between “Stereotypies” (self-directed, repetitive, non-sensical behaviour) and physiological self-regulation when exposed to novel environments (Dantzer, 1986).

In human studies, the use of the ECSI has allowed researchers to examine the role of displacement behavior as well as other behavioral patterns (e.g Evasion, aggression,

affiliation behaviors ect), and their interactions in self-regulation of the physiological and psychological responses to stress. In a study of Pico-Alfonso et al. (date) examining the role of estrogens, corticosteroids, and behavioural coping in relation to acute stress, the

researchers found that women demonstrating higher levels of displacement activities during a stress interview showed lower heart rate increments post-stress recovery. Furthermore, women who showed higher levels of submission behaviours (Behaviours to prevent or inhibit hostile responses, such as nodding or pressing the lips together), demonstrated higher heart rate acceleration during both the interview and the recovery phase (Pico-Alfonso et al., 2007).

In a similar study by Sgoifo et al. (2003), researchers found significant experimental evidence that participants with higher submission category scores had higher heart rates during

baseline and recovery period of a stress interview procedure, indicating a that subjects prone to submissive behaviour in an stress interaction demonstrate a more pronounced sympathetic dominance. Furthermore, Sgoifo et al. found a negative correlation between scores in the flight category (also referred to as evasion behaviours; Behaviours to cut off social stimuli perceived as stressful or aversive, such as closing of the eyes or crossing of the arms) and delta cortisol, as well as a positive correlation between delta cortisol and eye contact (Sgoifo et al., 2003). In a study examining neuroendocrine stress responses and non-verbal

behavioural patterns through the ECSI in psoriatic subjects, Bellagambi et al (2017) found that the subjects which produced higher displacement scores during a TSST showed a blunted neuroendocrine response demonstrating lower levels of cortisol and salivary α-amylase (sAA), an indicator of stress-reactive bodily changes (Nater et al., 2006), while subjects with higher scores in the relaxation category demonstrated neuroendocrine hyper arousal with higher levels of sAA activity (Bellagambi et al., 2018). In experiments by Mohiyeddini and Semple (2013), displacement behaviours were quantified during the Trier Social Stress Test and the authors found that displacement behaviours were associated with a lower heart rate

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acceleration during the stress test, and attenuated the relationship between reported anxiety before and after the test was implemented.

The ECSI has also proven to be a useful tool in examining stress response variations between groups, such as gender and various diagnosis, as well as individual differences such as personality. Ethological strategies for emotional regulation in response to stress have often proven to be impaired among patients suffering from psychiatric disorders, particularly schizophrenia (Jansen et al., 2000; Lee et al., 2011). Further, we know that there are substantial differences in non-verbal behavioural patterns in clinical interviews between patients suffering from schizophrenia, mania, and depression (Annen et al., 2012; Troisi, 1999b), begging the question of how non-verbal behavioural may serve different roles in emotional regulation between diagnosis. This of course would be rather difficult to study in a highly controlled setting such as with the implementation of the TSST due to ethical

considerations. In a study utilizing the ECSI to examin the relationship between non-verbal behaviour and symptom domains in patients suffering from schizophrenia, researchers found that patients with a higher level of negative symptoms displayed significantly fewer prosocial and displacement behaviours, but significantly more flight behaviours during a standardized interview, with no significant gender differences (Worswick et al., 2018). Individuals with high levels of neuroticism have also shown to be prone to employ maladaptive coping strategies in response to stress. Mohiyeddini et al conducted a study examining the role of displacement activities in relation to neuroticism and stress, finding that displacement

behaviour scores were negatively correlated with self-reported experience, physiological, and cognitive measures of stress, as well serving as a moderating factor between neuroticism and cognitive and self-report measures of stress (Mohiyeddini et al., 2015).

It is well established that there are substantial sex differences in stress responses, and particularly in emotional regulation in response to social stress (McRae et al., 2008; Troisi, 2001). Pico-Alfonso’s (2007) study demonstrated that higher rates of displacement behaviour during a stressful interview was correlated with lower heart rate during the post-stressor recovery period for women. However, a study by Mohiyeddini et al. (2013) the researchers examined the gender differences in displacement activity between men and women utilizing the same stress paradigm (the TSST), building on previous research into the differences in emotional regulation between men and women. In their study (N=82), displacement

behaviour via the ECSI, heart rate and cognitive performance were recorded during the Trier Social Stress Test.Self-report questionnaires were used to assess the stress experience. The

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results showed that displacement behaviour was associated with decreased self-reported stress, fewer mistakes in the cognitive task and a lower heart rates for men, but not women.

Furthermore, displacement behaviours were in fact associated with poorer cognitive performance among women, demonstrating how there are significant variation in how behavioural patterns contribute to emotional regulation among between the sexes.

Unfortunately, Mohiyeddini et al (2013) neglected to include the other behavioural categories in their study, with few other studies including or finding sex differences in behavioural and physiological stress response (Sgoifo et al., 2003).

Present Study

Aims and Hypotheses

In the present study we utilized a dyadic version of the Trier Social Stress Test (dTSST) to examine stress responses and the effects of social support on pairs of close friends

participating in tandem. My aim was to examine the interaction of non-verbal behavioural patterns with subjective and physiological markers of stress, including self-reported stress experience, heart rate, salivary cortisol levels, stress perception. My second aim was to validate the use of nvb in the dyadic TSST set-up by examining the effects the task-based variations of active versus passive participation in the dTSST on non-verbal behaviour, and the potential effects on task order. As this analysis utilized TSST recordings gathered from a pilot study, I also wished to examine the advantages and limitations non-verbal behaviour coding may demonstrate in a large-scale study.

As there are no previous studies examining non-verbal behaviours in a dyadic version TSST, there is no precedence regarding variations in the behavioural response between active versus passive participation in the TSST. The effect of task order, meaning the order in which participants complete the stress tasks (public speaking & arithmetic tasks), is also unexplored.

Due to the unprecedented nature of this paradigm, I have an open hypothesis that we can expect some variation in behavioural categories between the active and passive conditions, but as the passive condition does not require any engagement from the participant, I expect most categories will be more frequent in the active condition. Behaviours such as relaxation shifting behaviours may prove more frequent in the passive condition, as these are defined as

“Behaviours occur which suggest low levels of emotional stimuli and a high level of comfort

“(Troisi, 1999), and therefore likely not be very frequent in the active stress condition.

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I expect no significant relationship between non-verbal behaviours and task order, meaning that the order in which participants complete the active portion of either the public speaking or arithmetic task should not produce different non-verbal behavioural responses.

In accordance with previous studies utilizing the ECSI to record non-verbal

behavioural patterns during the trier social stress test, I hypothesise that self-management, submission, evasion and relaxation behaviours will prove to have specific relationships to both the physiological and psychological stress response. I expect to see a negative

correlation between self-management behaviours and self-reported subjective stress response, as well as with cortisol levels and average heart rate across all conditions of the dTSST. I also hypothesise that participants with higher levels of submission behaviours will demonstrate higher heart rate acceleration during the dTSST. I expect evasion behaviours to be associated with a lower salivary cortisol response, while we should see the opposite relationship

between salivary cortisol and relaxation behaviours. The behavioural category created for this study “partner-affiliation “, is unique, and designed to measure affiliative behaviours aimed towards the friend. I therefore hypothesise that a positive correlation between the friendship questionnaires and this behavioural category.

In accordance with previous studies utilizing the TSST as a stress paradigm expect the dTSST to evoke a significant stress response across participants. The sress response should be marked by elevated heart rate and cortisol levels from baseline measurements, as well as high scores on self-reported subjective stress (Frisch et al., 2015; Hellhammer & Schubert, 2012).

As for the subjective data, cortisol levels have previously shown to have an inverse relationship with scores in the perceived stress scale (PSS) in studies utilizing the TSST as a stress paradigm (Seitz et al., 2019), hence I hypothesise a positive correlation between self- management behaviours and the PSS. Individuals who perceive stress as harmful and debilitating rather that engaging (indicted by the Stress Mindset Measure (SMM)) may experience a heightened stress response during the TSST, and therefor likely demonstrate lower scores of self-management behaviours compared to submission behaviours. With this being the first study to examine non-verbal in a dyadic TSST set-up, I will examine the relationship between self-reported friendship closeness and non-verbal behaviour. This is particularly interesting with regard to the newly created partner-affiliation category, as well as affiliative and relaxation behaviours.

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Materials and Methods

Study Paradigm

Data was obtained from a pilot to a large-scale ERC-funded fMRI study examining the relationship between the human mu-opioid system and the stress relieving effects of social support. The aim of the pilot was to study the role of social support in stress recovery after completing a dyadic version of the Trier Social Stress Test (dTSST), a widely used stressed task requiring the participant to perform in an interview setting in front of a panel. Pairs of friends were recruited and randomly assigned to a social support condition or a control condition, after completing a dyadic version of the TSST, see figure 1.

During the dTSST the dyad was able to hear but not view or communicate with each other, as demonstrated in figure 3, whereas the participants were seated in individual cubicles

throughout the testing session as can be seen in figure 2.

Figure 1: Timeline of the Dyadic TSST & Support intervention

Figure 3: Participant placement throughout session,

before and after dTSST & Support intervention Figure 2. Participant placement during dTSST

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The support intervention consisted either of a 5-minute social interaction with the friend (support condition), or a 5-minute neutral interaction with an experimenter (non-support condition). The sessions lasted for approximately 3 hours, consisting of a 90-minute baseline period, a 25-minute period of the stress induction followed by 5 minutes of social support or non-support, and a 40-minute test period, with the session ending with an end-of session questionnaire and a debrief. Each session was conducted by 2 experimenters who also served as panel members during the dTSST, alternating between silent and speaking panel for each participant (see Methods/dTSST). Participants completed in total 9 mood-state questionnaires throughout the session, including stress subjective state questionnaires post stress induction.

Cortisol measures were collected at baseline and post stress induction, and heartrate was recorded throughout the session, including baseline, stress induction, and post stress induction.

Participants

21 pairs of close friends (n=42) were recruited through social media ads as well as pamphlets distributed on university campuses and community centres, requesting close friends to attend a study examining brain mechanisms and decision making. Participants were required to be between the age of 18 to 65, to have known each other for a minimum of 6 moths, consider each other as trusted friends, and be same sex. Exclusion criteria included ongoing self- reported mental illness, and any phobia of public speaking. Out of the 42 participants, 31 were women, with a mean age of 25.5, a standard deviation of 8. Participants completed a screening and recruitment form prior to attending the study. The first pair of pilot participants was a non-same sex dyad which was excluded from the analysis. An additional pair of friends were excluded from analysis due to lack of recorded video resulting from camera

malfunction, the final sample size n=38. All other missing data was excluded pairwise.

Ethical considerations

The study was approved by the Regional Ethics Committee (REK Sør-Øst D: 2018/672). All participants provided written informed consent at the beginning of the study and were

debriefed after completing the session. All data containing personal information of

participants, including screening questionnaires, recruitment information, contact info, video recordings, and corresponding participant ID’s was stored on an offline secure data server via The university of Oslo’s Services for sensitive data (TSD).

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17 The Dyadic Trier Social Stress Test

The Trier Social stress task (TSST) is a paradigm commonly utilized in stress research, which reliably elicits psychological and physiological stress responses in participants, including heighted heart rate and hypothalamic-pituitary-adrenal (HPA) axis activity, as well as self- reported stress experience (Hellhammer & Schubert, 2012; Kirschbaum et al., 1993). The TSST involves an interview-style presentation, followed by a mental arithmetic task, and it is considered one of the most ethologically valid stress paradigms to be utilized in a laboratory setting (Allen et al., 2017; Kexel et al., 2021).

The TSST is originally comprised of three parts; during the preparation period (1), participants are informed that they will complete a mock job interview with 5 minutes of preparation time. During the mock job-interview (2), the participant holds a presentation explaining why they would be an appropriate candidate for a job of their choice, and lastly participants receive a surprise mental arithmetic task (3). Both tasks are performed in front of a panel of 2, consisting of a speaking panel member who issues instructions and questions, and a silent panel member who visibly takes notes. However, the TSST has a history of being adapted in order better fit specific study designs, such as with groups, children, in

combination with neuroimaging, and in virtual committees (Allen et al., 2017).

In our dyadic version of the TSST (dTSST), participants were asked to perform the arithmetic and public speaking task while the friend is present and listening. The participants alternated between the presentation portion and mental arithmetic task in a pseudo-

randomized fashion. This paradigm allowed for 2 dimensions in contrast to the original TSST design, a speaking condition, in which a participant completed either the presentation or arithmetic task, and a listening condition where the participant listens to their friend completing the speaking condition, as can be seen in figure 1. This results in 2 additional factors not present in the original TSST; listening to the friend’s presentation, and listening to the friend complete the arithmetic task. In the pilot study the experimenters functioned also as panel members. To avoid a stress-carry over effect, the panel member questioning one

participant in the dyad, afterwards continued the session with the other participant of the dyad and vice versa.

Each participant was issued instructions by an individual experimenter throughout the baseline period of the session until initiation of the dTSST. The experimenter issuing

instructions to one participant during the baseline period, served as speaking panel to the

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friend of that participant, to avoid any stress alleviation resulting from familiarity. The panel members had been trained to avoid any affective communication, and retained a neutral expression and cadence throughout the TSST, as is deemed the best practice when conducting a TSST (Allen et al., 2017). As the stress response elicited by the TSST is historically rather short, various methods were utilized to sustain the affective response elicited by the dTSST.

These methods included switching the language from Norwegian to English directly before initiation of the first task, as well as two other arithmetic stress tasks completed by the participants in the recovery period.

Each participant was separately instructed that they were to give a five-minute presentation about themselves. They were asked to prepare for their dream job interview, a job that matched their actual qualifications. The participants were instructed that their presentation should focus on informing the panel which personal abilities the participant had which would make them a strong candidate for this position.. The participant was then told they would be given 3 minutes to prepare for the presentation and given a pen and a sheet paper to write notes. After 3 minutes of preparation, the participants were asked to surrender their notes, and to stand on a mark next to their friend in front of the panel members seated at a large table, with an audio-recording device and a camera placed on a tripod. Before

initiating the first presentation, the camera was switched on, and set to record, the screen of the camera turned to be visible to the participants. The participants remained standing for the duration of the TSST, separated by a pair of cubicle doors, allowing the participants to hear but not see each other, as demonstrated in figure 3. Up to this point, all communication between participants and experimenters had been conducted in Norwegian, to increase the unpredictability and to unsettle the participants further, they were instructed immediately before initiating the presentation, that the task was to be completed in English, due to “the video material needs to be in English for analysis purposes”. The participant to complete the presentation task first was decided by a visible lottery draw by the panel members. In order to further decrease predictability, after the first participant completed the presentation, the second participant was then instructed to complete a 3-minute mental arithmetic task, after which the first participant would complete different version of the same task, and finally the second participant completed the presentation. When the final presentation was complete, the participants were instructed to return to their cubicles, and complete stress-specific state mood questionnaires. The experimenter who served as that participants speaking panel member gave all further instructions.

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19 Presentation

During the 5-minute presentation, the participant would be interrupted by the speaking panel member whenever the participant would refer to any personal experience and instructed that

““we are only interested in you as a person, not in your previous experiences. Please keep talking about your personal abilities”. While the panel would allow for extended silences, to increase the discomfort of the participant, the participant could be prompted with difficult questions such as “What aspect of your personality are you the least proud of?”, and “How would you handle undeserved criticism from a superior?”. These questions were mostly utilized as abrupt interruptions if the participants presented an extended and articulate dialog to disrupt and unsettle the participant further. After 5 minutes, the participant would be interrupted and told the task was completed.

Mental Arithmetic Task

For the 3-minute mental arithmetic task, participants were instructed to audibly count backwards from either 2023 or 3333 in steps of 17 or 27 as quickly and accurately as possible. For every time they made a mistake, they were required to start over again. The participants were told this this task was “a simple calculation task, which is designed to test attention, analytical thinking and processing speed”. During the task, participants were informed that they were performing too slow, prompted to increase the speed of their calculations at any pause. If the participants were unable to complete the first two

calculations, they were interrupted and instructed to complete a simperer task, told to count down in steps of 7 rather that 17/27.

Perceived Stress Scale & Stress Mindset Measure

Prior to complete the dTSST, participants filled out 2 questionnaires aimed to assess the participants personal perception of stress; the Perceived Stress Scale (PSS), and the Stress Mindset Measure (SMM). The PSS is a wildly used measurement of participants personal perception of stress in their lives, the degree to which their life events during the last month are perceived as stressful. The PSS is comprised of a scale of 0 to 4, with zero indicating never, and 4 indicating very often, pertaining to questions about the current levels of

experienced stress in the participants life (Cohen et al., 1983). The SMM is a 8-item measure answered with a 4 point scale (0 = Strongly Disagree, 4 = Strongly Agree) of the extent to which a participant believes stress is debilitating or enhancing (Crum et al., 2013).

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20 Subjective Stress Perception

The participants’ self-reported experience of stress during the dTSST was collected from the end-of-session-questionnaire. The Questionnaire was comprised of questions retaining to the participants experience of the session as a whole and included 3 direct questions of the degree to which they experienced the aTSST as stressful on a scale of 1-10. These questions

included; “How stressful did you find holding the job-interview presentation on a scale of 1- 10”, “How stressful did you find the first math task on a scale of 1-10”, and “How stressful did you find the panel-members on a scale of 1-10”.

McGill Friendship Questionnaires (MFQ)

The McGill Friendship Questionnaires are two questionaries filled out by the participants prior to arriving the session. The McGill Friendship Questionnaires - Respondent's Affection (MFQ–RA) quantifies the participants feelings for a friend and friendship satisfaction, and the McGill Friendship Questionnaire–Friend's Function (MFQ–FF) assess the degree of which a participant feels the friend fulfils 6 friendship functions (stimulating companionship, help, intimacy, reliable alliance, self-validation, and emotional security) (Mendelson &

Aboud, 1999). The MFQ-RA is a 16-item questionnaire, while the MFQ-FF includes 30 items. The MFQ-FF have participants respond on a 9-point scale, between 0 to 8, while the MFQ-RA consists of a scale from -4 to 4.

Heart rate measurement

Heart rate measurements (recorded as R waves and converted to beats per minute (BPM) were collected continuously throughout the session, a 7-minute period were dedicated to recording heart rate while participants rested in their chairs using pre dTSST as a baseline measure. Heart rate was recorded via the Polar V800 heart rate monitor with a Polar H7 chest strap at a sampling rate of 1000Hz. The Polar V800 has proved a valid and reliable tool to produce RR interval recordings consistent with an ECG (Giles et al., 2016)

Salivary Cortisol

Salivary cortisol was sampled via using Sarstedt Salivette® synthetic swabs designed for cortisol determination, at baseline prior to the dTSST (at 90 minutes) and post dTSST (at 145 minutes). Samples were immediately placed in a 4C refrigerator after collection, and

refrigerated for a maximum of 7 days before being centrifuged for 2 minutes at 1000 x g.

After being centrifuged, the swabs were removed from the tube, and the tube containing the saliva samples was frozen at negative 20C until analysis.

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Non-verbal behavioural coding

I first needed to identify a coding scheme and ethogram appropriate to a study conducting a stress interview paradigm, and which could utilize the recordings of the TSST sessions conducted in the present study. As non-behavioural coding requires multiple raters to

establish reliability of the recorded behaviours, I also had to consider the time and manpower requirements of the task. The Ethological Coding System for Interviews (ECSI) is an

established behavioural coding scheme with high reliability and validity designed for controlled interview setting (Paas Oliveros et al., 2015). The ECSI has in recent years been repeatedly utilized for non-verbal behavioural coding of participants completing the TSST in stress research (Bellagambi et al., 2018; Mohiyeddini et al., 2013a, 2013b, 2015;

Mohiyeddini & Semple, 2013; Pico-Alfonso et al., 2007; Santangelo et al., 2020; Sgoifo et al., 2003). This established the ethogram as an optimal for the present study, as it also allows for a practical and well-established sampling procedure of the non-verbal behaviours. Next, I needed to establish a recording protocol, and identity an appropriate event-logging software, that would be flexible enough to allow me to differentiate between participants and task- order, as the participants completed the TSST in pairs, alternating between the self-

presentation task and the mental arithmetic task. I landed on a one-zero time sampling with 15 second time intervals, as it has proven an reliable and accurate sampling procedure (Annen et al., 2012; Breed & Moore, 2016; Mohiyeddini et al., 2013a, 2013b, 2015; Troisi, 1999), and the software coder BORIS (Behavioral Observation Research Interactive

Software), which is open-source and multiplatform program which allows for project specific coding environment and the import of project specific ethograms (Friard & Gamba, 2016;

Troisi et al., 2000).

Non-verbal behaviour requires first and foremost a strong inter-rater reliability (Baesler & Burgoon, 1987), which requires a large degree of training of multiple raters. So, I recruited two other raters from the Leknes Affective brain Lab and proceeded with training until a passable inter-rater reliability was achieved on a subset of the recordings between all three raters, not until then could we proceed to code for all participants dTSST’s.

The Ethological Coding System for Interviews

The Ethological Coding System for Interviews (ECSI) has been adopted and repeatedly utilized for analysing non-verbal behaviours in studies conducting stress research with the TSST (Bellagambi et al., 2018; Mohiyeddini et al., 2013a, 2013b, 2015; Mohiyeddini &

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Semple, 2013; Pico-Alfonso et al., 2007; Santangelo et al., 2020; Sgoifo et al., 2003). Our version of the ECSI is a revised version of Paas Oliveros et al.’s ethogram, adopted from the original by Troisi (1999) (Paas-Oliveros et al. 2015, Troisi 1999). In our version, adapted to the dTSST, an additional behavioural category was included to differentiate between

affiliation directed to the panel, and affiliation directed to the friend during the dTSST. This category, labelled “partner-affiliation” includes laughing with friend while in listening condition, laughing with friend during the speaking condition, and glancing overtly towards the friend. The behaviour of eye-contact was excluded form the ethogram, as the placement of the camera in relation to the participants and panel member made determining the specific direction of gaze challenging. The ethogram ultimately utilized for the non-verbal

behavioural coding includes 53 non-verbal behaviours organized into 10 behavioural

categories: Affiliation, partner affiliation, submission, evasion, assertiveness, movement, self- management, relaxation-shifting, sadness, & aggression (Table 1).

Table 1: The Ethological Coding System for Interviews (ECSI), adapted.

Ethogram of behaviours in the Trier Social Stress Test (TSST).

Non-verbal behaviours (adapted from ECSI, for details see Troisi 1999&Paas-Oliveros et al. 2015 )

Category Function Description

Affiliation Facial expressions and head movements which invite social interactions and reflect a positive

attitude

• Head to one side: Head tilted to one side

• Bob: A swift upwards movement of the head, like a reverse nod.

• Flash: Eyebrows briefly raise and lower.

• Raise eyebrows: The eyebrows are raised and remain so for two seconds or more.

• Smile: The corners of the mouth stretch backwards and upwards.

• Surprise: The upper eyelids and eyebrows are raised, the jaw is lowered. Shoulders may be raised with inhalations.

Partner Affiliation Affiliative behaviours in direction of friend.

• Listen laugh with partner: Laugh with partner while in listening condition.

• Speech laugh with partner: Laugh with partner while in speaking condition.

• Glance Partner: Glance overtly towards Partner

Submission Behaviours to prevent or inhibit hostile responses

• Nod: The normal gesture of agreement.

• Pressed Lips: The lips are lightly and inwardly pressed together.

• Corners moved backwards: The corners of the mouth are stretched backwards, but not upwards as in a smile.

Evasion Behaviours to cut off social stimuli perceived as stressful or aversive

• Looking Elsewhere: Directing the gaze towards another part of the room away from the interviewer.

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• Looking down: Directing the gaze

downwards looking at the feet, the lap, or the floor.

• Eyes closed: The eyes are closed for two seconds or more.

• Chin: The chin is directed towards the chest.

• Huddle: The torso is inclined forward until the head is near the knees

• Still: A sudden pause of any movement, as though frozen.

• Crossed arms: Arms are crossed at chest height accompanied and/or followed by evasive behaviours.

• Fear: The upper eyelids and eyebrows are raised and the corners of the mouth are stretched horizontally. This facial expression may be accompanied by the head and body recoiling.

Assertiveness Facial expressions and head movements that signal low-level aggression or hostility

• Shake head:The normal gesture of denial

• Extending the head: A swift forward movement of the head in the direction of the interviewer.

• Lean: Leaning forwards from the hips towards the interviewer, lean against door frame.

• Furrowed brow: Wrinkling the inner part of the eyebrows and forehead.

• Shoulders: The shoulders are raised and allowed to fall.

• Small mouth: The corners of the mouth contract so that the mouth appears smaller.

• Wrinkled nose: Wrinkling of the skin of the nose.

Movement Various hand and arm movements during speech.

• Movement: Various hand and arm movements during speech.

Self-management (Displacement): Expressed as sign of social tension and motivational conflict.

May reflect increased autonomic arousal

• Grooming:Passing the fingers through the hair in a combing movement.

• Hand to face: Hand(s) in contact with the face.

• Hand to mouth: Hand(s) in contact with the mouth.

• Scratching: Using the hands to scratch any part of the body

• Yawning: The mouth is opened widely and roundly and then slowly closed. This movement of the mouth is accompanied by a deep breath and frequently with closed eyes and lowered eyebrows.

• Finger movement: Rapid and repetitive movement of the fingers touching a nail, a handkerchief, the other hand, etc.

• Twisted mouth: The closed lips are pushed forwards and to one side.

• Licking lips: Passing the tongue across the lips.

• Biting lips: One lip, generally the lower one, is drawn in and bitten by the teeth.

An analysis of Non-verbal Behaviour and stress response in a dyadic Trier Social Stress Test Herman Bjørnstad