Skin Conductance Research Articles

When We Are Happy, We Are the Same—Emotions as a Boundary Condition for the Impact of Cultural Differences on Strategic Decisions

AbstractStrategic decision-making research has mainly relied on the values-based approach to culture. However, the dynamic constructivist approach to culture has shown that cultural tendencies may also be altered by contingency factors in the decision-making process itself. We theorize based on the appraisal tendency framework as well as the concept of cultural affordances that emotions, such as happiness, can alter the cultural dispositions of managers from Western and East Asian contexts. To test our hypotheses, we conduct a lab-in-the-field experiment with 187 executives from China and Germany, and measure emotions based on participants’ psychophysiological skin conductance responses. Our results show that happiness moderates and can even reverse initial cultural dispositions in executives’ strategic decision-making behavior. These findings suggest that emotions may be important contingency factors that can alter the initial cultural dispositions of decision makers in the strategy process.

Measurement of Visitors’ Subjective and Objective Emotional Response to Congestion in Public Spaces

Research on the ties between congestion and visitors’ experiences in a destination has primarily used subjective methods. The current study proposes that the emotional, subjective visitor response to congestion be measured alongside the objective experience, in real time and real-world conditions. To do so, advanced tracking methods in time and space (GPS) were combined with the Experience Sampling Method (ESM), which includes self-reporting and physiological monitoring of electrodermal activity (SCL). An intra-subject experiment was designed, with all participants asked to traverse an identical path in Jerusalem’s main market, Mahane Yehuda, under two different crowding conditions. The partial concordance between subjective and objective arousal highlights the methodology’s significance for increasing our understanding of a visit’s emotional dimension in urban destinations, particularly congested public spaces. Alongside the study’s limitations, the practical application of the methodology for tourist destinations and urban settings that face congestion and overcrowding is discussed, aiming to improve the quality of the visitor experience and urban well-being.

Human Activity Recognition Algorithm with Physiological and Inertial Signals Fusion: Photoplethysmography, Electrodermal Activity, and Accelerometry

Inertial signals are the most widely used signals in human activity recognition (HAR) applications, and extensive research has been performed on developing HAR classifiers using accelerometer and gyroscope data. This study aimed to investigate the potential enhancement of HAR models through the fusion of biological signals with inertial signals. The classification of eight common low-, medium-, and high-intensity activities was assessed using machine learning (ML) algorithms, trained on accelerometer (ACC), blood volume pulse (BVP), and electrodermal activity (EDA) data obtained from a wrist-worn sensor. Two types of ML algorithms were employed: a random forest (RF) trained on features; and a pre-trained deep learning (DL) network (ResNet-18) trained on spectrogram images. Evaluation was conducted on both individual activities and more generalized activity groups, based on similar intensity. Results indicated that RF classifiers outperformed corresponding DL classifiers at both individual and grouped levels. However, the fusion of EDA and BVP signals with ACC data improved DL classifier performance compared to a baseline DL model with ACC-only data. The best performance was achieved by a classifier trained on a combination of ACC, EDA, and BVP images, yielding F1-scores of 69 and 87 for individual and grouped activity classifications, respectively. For DL models trained with additional biological signals, almost all individual activity classifications showed improvement (p-value < 0.05). In grouped activity classifications, DL model performance was enhanced for low- and medium-intensity activities. Exploring the classification of two specific activities, ascending/descending stairs and cycling, revealed significantly improved results using a DL model trained on combined ACC, BVP, and EDA spectrogram images (p-value < 0.05).

Wearable Technology Insights: Unveiling Physiological Responses During Three Different Socially Anxious Activities

Wearable technology holds promise for monitoring and managing Social Anxiety Disorder (SAD), yet the absence of clear biomarkers specific to SAD hampers its effectiveness. This paper explores this issue by presenting a study investigating variances in heart rate, heart rate variability, and skin conductance between socially anxious and non-anxious individuals. One hundred eleven non-clinical student participants participated in groups of three in three anxiety-provoking activities (i.e., speech, group discussion, and interview) in a controlled lab-based study. During the study, electrocardiogram (ECG) and electrodermal activity (EDA) signals were captured via on-body electrodes. During data analysis, participants were divided into four groups based on their self-reported anxiety level (“None”, “mild”, “moderate”, and “severe”). Between-group analysis shows that discriminating ECG features (i.e., HR and MeanNN) could identify anxious individuals during anxiety-provoking activities, while EDA could not. Moreover, the discriminating ECG features improved the classification accuracy of anxious and non-anxious individuals in different machine-learning techniques. The findings need to be further scrutinized in real-world settings for the generalizability of the results.

Exploring the Impact of Campus Landscape Visual Elements Combination on Short-Term Stress Relief among College Students: A Case from China

Although the effect of campus landscape space on stress relief among college students has been confirmed, few existing studies have considered the impact on stress recovery from the perspective of factor combination, and the key visual elements and the most effective combination of visual elements to relieve stress are still unclear. This study attempts to conduct a natural experiment within Chinese campuses, measuring physiological indicators of stress such as heart rate (HR), frequency domain index of heart rate variability (LF/HF), skin conductance level (SCL), skin temperature (SKT), and respiratory rate (RESP) using physiological instruments. It explored the effects of visual elements and their combinations in campus landscape spaces on short-term stress relief among college students through semantic segmentation, multifactorial analysis of variance, and post hoc multiple comparison methods. Research results demonstrate that the presence of water elements in the field of vision can effectively improve the stress relief effects of landscape spaces. Reasonable combinations of natural landscape elements and artificial landscape elements in the design can also effectively promote stress relief among students. Building facade area and sky area, water area and sky area, and plant species and pavement area are three combinations of factors with the strongest interactive effects. “Natural water scenery” and “exquisite artificial” are two campus landscape design patterns most conducive to short-term stress relief.

Unveiling emotion dynamics in problem-solving: a comprehensive analysis with an intelligent tutoring system using facial expressions and electrodermal activities

Emotions play a crucial role in the learning process, yet there is a scarcity of studies examining emotion dynamics in problem-solving with fine-grained data and advanced tools. This study addresses this gap by investigating the emotional trajectories during self-regulated learning (SRL) phases (i.e., forethought, performance, and self-reflection) among 47 medical students utilizing an intelligent tutoring system. Real-time facial expressions were analyzed through recurrence quantification analysis alongside an examination of electrodermal activities (EDA) across the SRL phases. The findings reveal that emotion stability varied across SRL phases, with students exhibiting more stable emotions during the performance phase. Compared to the forethought and self-reflection phases, students had less frequent and lower intensity of emotional arousal in the performance phase. Moreover, we found that students with better performance demonstrated more stable emotions in the forethought phase, less stable emotions in the self-reflection phase, and a higher level of emotional arousal in the self-reflection phase. These insights highlight the temporal and dynamic nature of emotions in SRL, offering methodological and educational implications for leveraging facial expressions and EDA to monitor and enhance students’ emotional experience during problem-solving.

The role of visuomotor synchrony on virtual full-body illusions in children and adults.

The present study explored the effects of visuomotor synchrony in virtual reality during the embodiment of a full human avatar in children (aged 5-6 years) and adults. Participants viewed their virtual bodies from a first-person perspective while they moved the body during self-generated and structured movement. Embodiment was measured via questions and psychophysiological responses (skin conductance) to a virtual body-threat and during both movement conditions. Both children and adults had increased feelings of ownership and agency over a virtual body during synchronous visuomotor feedback (compared to asynchronous visuomotor feedback). Children had greater ownership compared to adults during synchronous movement but did not differ from adults on agency. There were no differences in SCRs (frequency or magnitude) between children and adults, between conditions (i.e., baseline or movement conditions) or visuomotor feedback. Collectively, the study highlights the importance of visuomotor synchrony for children's ratings of embodiment for a virtual avatar from at least 5 years old, and suggests adults and children are comparable in terms of psychophysiological arousal when moving (or receiving a threat to) a virtual body. This has important implications for our understanding of the development of embodied cognition and highlights the considerable promise of exploring visuomotor VR experiences in children.

The influence of uncertainty visualization on cognitive load in a safety- and time-critical decision-making task

Decisions with spatial visualizations are often made under uncertainty and high time pressure. However, missing or improper representation of uncertainty can hamper the decision-making process. This paper investigates the impact of uncertainty visualization on cognitive load in the context of a safety-critical, time-sensitive decision-making task with a transportation system map. In a controlled experiment (n = 40) with a dual-task paradigm, we compared three different uncertainty visualization techniques and a baseline for different levels of time pressure. Cognitive load was measured using psycho-physiological metrics based on eye tracking and galvanic skin response, as well as self-reported. The results reveal significant differences in cognitive load among different visualization types, with line uncertainty representation techniques leading to lower cognitive load under both low and high-time pressure scenarios ( α < 0.05 ).

Psychophysiological Investigation of the Effects of Virtual Reality, the New Dimension of Retail Shopping, on Generation Z

Virtual reality has begun to show itself in many areas of our lives as its accessibility becomes easier. Especially in recent years, it has been observed that investments have been made in this field in the retail sector and many brands have created virtual reality stores. The research emphasizes the need for new studies on consumer behavior in virtual reality stores, the new interface of the retail sector, in order to shed light on future investments. The attitude of Generation Z, who grew up with technology and is open to innovation, towards the virtual reality store is important because they are the consumers of today and the future. Given this situation, in the current study, the attitude of Generation Z towards the virtual reality store is examined psychophysiologically. The physiological outcomes of university students (n = 40) between the ages of 18–29 during the shopping experience in a virtual reality store were analyzed with electrodermal activity (EDA) and photoplethysmography (PPG) research techniques. Physiological data were analyzed by comparing them with the data obtained from the Socio-Demographic characteristics and the Hedonic and Utilitarian Consumption Behaviors Scale. In line with the findings in the study, the psychophysiological effects of the virtual reality store on Generation Z participants did not show significant differences in terms of demographic characteristics and hedonic and utilitarian consumption behaviors. However, the increase in the heart rate averages of the majority of the participants during the experience was significant. This is attributed to the fact that virtual reality adresses both hedonic and utilitarian consumption.

Identifying physiological indicators of the cognitive, thermal, and combined (cognitive-thermal) stress conditions.

Physiologically based stress detection systems have proven to be effective in identifying different stress conditions in the body to determine the source of stress and be able to counteract it. However, some stress conditions have not been widely studied, including thermal stress, cognitive stress, and combined (thermal-cognitive) stress conditions, which are frequently encountered in work or school environments. In order to develop systems to detect and differentiate these conditions, it is necessary to identify the physiological indicators that characterize each of them. The present research aims to identify which physiological indicators (heart rate, respiratory rate, galvanic skin response, and local temperature) could differentiate different stress conditions (no-stress, cognitive stress, thermal stress, and combined (thermal-cognitive) stress conditions). Thirty participants were exposed to cognitive, thermal, and combined stress sources while recording their physiological signals. The findings indicate that both mean heart rate and mean galvanic skin response identify moderate thermal and cognitive stress conditions as distinct from a no-stress condition, yet they do not differentiate between the two stress conditions. Additionally, heart rate uniquely identifies the cognitive-thermal stress condition, effectively distinguishing this combined stress condition from the singular stress conditions and the no-stress condition. Mean local temperature specifically signals thermal stress conditions, whereas mean respiratory rate accurately identifies cognitive stress conditions, with both indicators effectively separating these conditions from each other and from the no-stress condition. This is the first basis for differentiating thermal and cognitive stress conditions through physiological indicators.

Digital Interventions to Understand and Mitigate Stress Response: Protocol for Process and Content Evaluation of a Cohort Study.

Staffing and resource shortages, especially during the COVID-19 pandemic, have increased stress levels among health care workers. Many health care workers have reported feeling unable to maintain the quality of care expected within their profession, which, at times, may lead to moral distress and moral injury. Currently, interventions for moral distress and moral injury are limited. This study has the following aims: (1) to characterize and reduce stress and moral distress related to decision-making in morally complex situations using a virtual reality (VR) scenario and a didactic intervention; (2) to identify features contributing to mental health outcomes using wearable, physiological, and self-reported questionnaire data; and (3) to create a personal digital phenotype profile that characterizes stress and moral distress at the individual level. This will be a single cohort, pre- and posttest study of 100 nursing professionals in Ontario, Canada. Participants will undergo a VR simulation that requires them to make morally complex decisions related to patient care, which will be administered before and after an educational video on techniques to mitigate distress. During the VR session, participants will complete questionnaires measuring their distress and moral distress, and physiological data (electrocardiogram, electrodermal activity, plethysmography, and respiration) will be collected to assess their stress response. In a subsequent 12-week follow-up period, participants will complete regular assessments measuring clinical outcomes, including distress, moral distress, anxiety, depression, and loneliness. A wearable device will also be used to collect continuous data for 2 weeks before, throughout, and for 12 weeks after the VR session. A pre-post comparison will be conducted to analyze the effects of the VR intervention, and machine learning will be used to create a personal digital phenotype profile for each participant using the physiological, wearable, and self-reported data. Finally, thematic analysis of post-VR debriefing sessions and exit interviews will examine reoccurring codes and overarching themes expressed across participants' experiences. The study was funded in 2022 and received research ethics board approval in April 2023. The study is ongoing. It is expected that the VR scenario will elicit stress and moral distress. Additionally, the didactic intervention is anticipated to improve understanding of and decrease feelings of stress and moral distress. Models of digital phenotypes developed and integrated with wearables could allow for the prediction of risk and the assessment of treatment responses in individuals experiencing moral distress in real-time and naturalistic contexts. This paradigm could also be used in other populations prone to moral distress and injury, such as military and public safety personnel. ClinicalTrials.gov NCT05923398; https://clinicaltrials.gov/study/NCT05923398. DERR1-10.2196/54180.

Body shape rather than facial emotion of others alters interpersonal distance in patients with anorexia nervosa.

The study investigated interpersonal distance in patients with anorexia nervosa (AN), focussing on the role of other's facial expression and morphology, also assessing physiological and subjective responses. Twenty-nine patients with AN and 30 controls (CTL) were exposed to virtual characters either with an angry, neutral, or happy facial expression or with an overweight, normal-weight, or underweight morphology presented either in the near or far space while we recorded electrodermal activity. Participants had to judge their preferred interpersonal distance with the characters and rated them in terms of valence and arousal. Unlike CTL, patients with AN exhibited heightened electrodermal activity for morphological stimuli only, when presented in the near space. They also preferred larger and smaller interpersonal distances with overweight and underweight characters respectively, although rating both negatively. Finally, and similar to CTL, they preferred larger interpersonal distance with angry than neutral or happy characters. Although patients with AN exhibited behavioural response to emotional stimuli similar to CTL, they lacked corresponding physiological response, indicating emotional blunting towards emotional social stimuli. Moreover, they showed distinct behavioural and physiological adjustments in response to body shape, confirming the specific emotional significance attached to body shape.

Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: study protocol of a randomized controlled trial

BackgroundStress is a widespread phenomenon and reality of everyday life, entailing negative consequences for physical and psychological wellbeing. Previous studies have indicated that exposure to greenspaces and nature-based interventions are promising approaches to reducing stress and promoting restoration. However, an increasing percentage of the population lives in urban regions with limited opportunities to spend time in greenspaces. In addition, urban settings typically feature increased levels of noise, which represents a major environmental stressor. Although various studies have compared the effects of exposure to greenspaces versus urban built environments, evidence of the effects of noise in this context is very limited. Psychophysiological benefits of exposure to greenspaces compared to urban built environments reported in earlier studies might be less (or at least not only) due to features of the greenspaces than to additional stressors, such as road traffic noise in the urban built environment. Hence, differences in the effects attributed to greenness in previous studies may also be due to potentially detrimental noise effects in comparison settings. This paper reports the study protocol for a randomized, controlled intervention study comparing the effects of walking in forest versus urban built environments, taking road traffic noise exposure during walks in the respective settings into account.MethodsThe protocol envisages a field study employing a pretest–posttest design to compare the effects of 30-min walks in urban built environments and forests with different road traffic noise levels. Assessments will consist of self-reported measures, physiological data (salivary cortisol and skin conductance), an attention test, and noise, as well as greenness measurements. The outcomes will be restoration, stress, positive and negative affect, attention, rumination, and nature connectedness.DiscussionThe results will inform about the restorative effect of walking in general, of exposure to different types of environments, and to different noise levels in these sites. The study will provide insights into the benefits of walking and nature-based interventions, taking into account the potential detrimental effects of noise exposure. It will thus facilitate a better understanding of low-threshold interventions to prevent stress and foster wellbeing.Trial registrationISRCTN48943261; Registered 23.11.2023.

A threat from within: Learning to fear by observing aversive bodily symptoms in others

Although observational fear learning has been implicated in the development of phobic-related fears, studies investigating observational learning of fear of bodily symptoms remain scarce. Therefore, the aim of the present study was to investigate whether fear in response to bodily symptoms can be acquired simply by observing a fearful reaction to provocation of aversive bodily symptoms in others. Forty healthy participants underwent an observational fear conditioning paradigm consisting of two phases. In the first phase, participants observed a demonstrator reacting to an aversive bodily symptom provocation (unconditioned stimulus or US, i.e., labored breathing) paired with one conditioned stimulus (CS+) but not with the other one (CS-, both CSs were geometric symbols presented on a screen the demonstrator was watching). In the second phase, participants were directly presented with the same conditioned stimuli, but in the absence of the US. Our results revealed enhanced conditioned fear responses in the beginning of the second phase to the CS + as compared to CS-, as indexed by greater skin conductance and subjective fear responses, as well as greater potentiation of startle eyeblink responses to the CS + as compared to the ITI. Taken together, these findings implicate that fear of bodily symptoms can be learned through observation of others, that is, without first-hand experience of bodily threat.

Stress Detection in IT Employees using Machine Learning

In today's fast-paced technology landscape, stress management is becoming increasingly important, especially among IT professionals. The work environment in the IT industry is often characterized by long hours, tight deadlines, and high expectations, which can lead to elevated stress levels. Unchecked stress not only impacts the health and well-being of professionals but also affects productivity and job satisfaction. This study aims to predict the stress levels of IT professionals using machine learning techniques, thereby aiding in proactive stress management. We utilize a range of features indicative of work stress, including Heart Rate, Skin Conductivity, Hours Worked, Number of Emails Sent, and Meetings Attended. These features provide a comprehensive view of both the physiological and work-related factors that contribute to stress. The application of machine learning in this context serves as an innovative approach to an increasingly pertinent issue. By leveraging the power of data analytics, this model aims to provide actionable insights for both individuals and organizations. Individuals can use these predictions for self-monitoring and early intervention, while organizations can utilize them to identify high-stress environments or roles, thereby allocating resources or interventions more effectively. Our preliminary results indicate a strong correlation between the chosen features and stress levels, demonstrating the viability of using machine learning for stress prediction in IT professionals. This study stands as a crucial step towards a more data-driven approach to mental health and well-being in the workplace Key Words: Random Forest , AdaBoost Classifier, Extra Tree Classifier, Decision Tree, Stacking etc.

Gastrointestinal symptom burden in diabetic autonomic and peripheral neuropathy – A Danes cohort study

ObjectiveWe investigated associations between gastrointestinal symptoms - evaluated as a combined weighted symptom score (CWSS) – Diabetic autonomic neuropathy (DAN), and distal symmetrical polyneuropathy (DSPN) in type 1 and type 2 diabetes. Research design and methodsCross-sectional study in a tertiary outpatient clinic. CWSS was calculated based on questionnaires: gastroparesis composite symptom index (GCSI) and gastrointestinal symptom rating score (GSRS). DAN and DSPN were addressed using the composite autonomic symptom score 31 (COMPASS-31) questionnaire, cardiac autonomic reflex tests (CARTs), electrochemical skin conductance (ESC), vibration perception threshold (VPT), Michigan Neuropathy Screening Instrument (MNSI), pain- and thermal sensation.Analyses were adjusted for age, sex, diabetes duration, smoking, LDL-cholesterol, HbA1C and systolic blood pressure. Type 1 and type 2 diabetes were evaluated separately. ResultsWe included 566 with type 1 diabetes and 377 with type 2 diabetes. Mean ± SD age was 58 ± 15 years and 565 (59.9 %) were women. A high CWSS was present in 143 (25 %) with type 1 and 142 (38 %) with type 2 diabetes. The odds of DAN by COMPASS-31 (p < 0.001) were higher in the high score group. For type 1 diabetes, odds of cardiac autonomic neuropathy were higher in the high CWSS group. The odds of DSPN by VPT and MNSI in type 1 diabetes, and by ESC, VPT and pain sensation in type 2 diabetes were higher in the high score group. ConclusionsA high symptom score was associated with neuropathy by COMPASS-31 and vibration perception. Gastrointestinal symptom burden associated inconsistently with other neuropathy tests between diabetes types.

Physical and biophysical markers of assessment in medical training: A scoping review of the literature

Purpose Assessment in medical education has changed over time to measure the evolving skills required of current medical practice. Physical and biophysical markers of assessment attempt to use technology to gain insight into medical trainees’ knowledge, skills, and attitudes. The authors conducted a scoping review to map the literature on the use of physical and biophysical markers of assessment in medical training. Materials and methods The authors searched seven databases on 1 August 2022, for publications that utilized physical or biophysical markers in the assessment of medical trainees (medical students, residents, fellows, and synonymous terms used in other countries). Physical or biophysical markers included: heart rate and heart rate variability, visual tracking and attention, pupillometry, hand motion analysis, skin conductivity, salivary cortisol, functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS). The authors mapped the relevant literature using Bloom’s taxonomy of knowledge, skills, and attitudes and extracted additional data including study design, study environment, and novice vs. expert differentiation from February to June 2023. Results Of 6,069 unique articles, 443 met inclusion criteria. The majority of studies assessed trainees using heart rate variability (n = 160, 36%) followed by visual attention (n = 143, 32%), hand motion analysis (n = 67, 15%), salivary cortisol (n = 67, 15%), fMRI (n = 29, 7%), skin conductivity (n = 26, 6%), fNIRs (n = 19, 4%), and pupillometry (n = 16, 4%). The majority of studies (n = 167, 38%) analyzed non-technical skills, followed by studies that analyzed technical skills (n = 155, 35%), knowledge (n = 114, 26%), and attitudinal skills (n = 61, 14%). 169 studies (38%) attempted to use physical or biophysical markers to differentiate between novice and expert. Conclusion This review provides a comprehensive description of the current use of physical and biophysical markers in medical education training, including the current technology and skills assessed. Additionally, while physical and biophysical markers have the potential to augment current assessment in medical education, there remains significant gaps in research surrounding reliability, validity, cost, practicality, and educational impact of implementing these markers of assessment.

Effect of Sensory Adapted Dental Environment (SADE) on physiological and behavioral parameters related to stress and anxiety in children with Autism Spectrum Disorder (ASD) undergoing dental treatment: A systematic review and meta-analysis.

Children with autism exhibit a higher general and dental anxiety, due to altered sensory sensibilities. This current systematic review aims to evaluate the effectiveness of Sensory adapted dental environment (SADE) over regular dental environment (RDE) on behavioral, physiological stress and overt anxiety in children with autism spectrum disorders (ASDs). Prospero registered (CRD42024508336). PubMed, Cochrane, Scopus databases are searched from years January 1, 1980-January 1, 2024 using pre-defined search strategy. A total of 269 titles, were obtained from the included databases after application of filters, exclusion of duplicates and reviews and irrelevant articles led to the final inclusion of 12 articles for full text screening from which, three studies sustained the targeted PICO search. Skin conductance level (parameter indicating physiological stress) is lower in SADE environment in children with ASD, other behavior stress related parameters there is no significant difference between SADE and RDE environments.

IOT Based Remote Patient Monitoring System

Abstract: A remote monitoring technique that can accurately track human physiological indicators has applications in virtual reality, sports science, medicine, rehabilitation, and surveillance. The majority of systems now in use for tracking bodily parameters in humans need wiring that limits natural movement. In order to get over this restriction, a wearable wireless sensor network that monitors physiological human body characteristics has been built using an accelerometer, a pulse oximeter, a heart-rate sensor, a temperature sensor, and a galvanic skin response sensor. The individual is being tracked wirelessly using his own location. It would be simple to modify this system to watch athletes and young children. Unlike a tethered monitoring equipment, the wireless feature allows the human body to move freely, making the system genuinely portable, quick, and dependable. The portable and the designed sensor node's small size makes it simple to attach to the body.

Interpersonal physiological and psychological synchrony predict the social transmission of nocebo hyperalgesia between individuals

Witnessing another’s pain can heighten pain in the observer. However, research has focused on the observer’s intrapersonal experience. Here, a social transmission-chain explored the spread of socially-acquired nocebo hyperalgesia. Dyads of genuine participants were randomised to ‘Generations’ (G1–G3). G1-Demonstrators, observed by G2-Observers, experienced high/low thermal pain contingent on supposed activity/inactivity of a sham-treatment. G2 became Demonstrators, witnessed by G3-Observers. They experienced fixed low-temperature stimuli irrespective of sham-treatment ‘activity’. G3 then Demonstrated for G4-Observers (a confederate), also experiencing low-temperature stimuli only. Pain ratings, electrodermal activity, and facial action units were measured. G1’s treatment-related pain propagated throughout the chain. G2 and G3 participants showed heightened subjective and physiological response to sham-treatment, despite equivalent stimulus temperatures, and G3 never witnessing the initial pain-event. Dyadic interpersonal physiological synchrony (electrodermal activity) and psychological synchrony (Observer’s ability to predict the Demonstrator’s pain), predicted subsequent socially-acquired pain. Implications relate to the interpersonal spread of maladaptive pain experiences.