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Objective: Synchrony in the multi-person context of systemic therapy is a complex and understudied phenomenon. We analyzed respiratory and electrodermal synchronies within a couple therapy system with two therapists to determine whether dyadic subsystems between each client and therapist synchronized differently. We also studied synchrony in reflection periods, in which the therapists discussed the therapy process with clients listening. Finally, we examined the association of synchronies with alliance and outcome. Method: A sample of 22 therapy sessions in which electrodermal activity (EDA) and respiration were recorded were analyzed. Self-report measures of session alliance and outcome were obtained. Synchrony computation was based on windowed cross-correlation using surrogate synchrony and segment-wise shuffling of physiological time series. Results: The results supported the presence of EDA synchrony for the client-therapist and therapist-therapist dyads but not client-client dyads across entire sessions. No significant synchronies were found for respiration behavior. A similar picture was found in reflection periods. Clients' well-being as well as therapists' alliance ratings were significant predictors of client-client EDA synchrony. Conclusion: Our results point to the relational meaning of synchrony and its importance for understanding couple psychotherapy, particularly the reflection periods. Challenges involved in extending synchrony computation to multi-person settings were highlighted. [ABSTRACT FROM AUTHOR]

People with spider phobia experience excessive anxiety reactions when exposed to spiders that will interfere with daily life. Diagnosing and measuring anxiety levels in patients with spider phobia is a complex challenge. Conventional diagnosis requires psychological evaluations and clinical interviews that take time and often result in a high degree of subjectivity. Therefore, there is a need for a more objective and efficient approach to measuring anxiety levels in patients. This study performs anxiety level classification based on electrodermal activity, electrocardiogram (ECG) and respiratory signals using the dataset of Arachnophobia subjects. Each raw data is preprocessed using 24 types of features. Feature performance is processed using the recursive feature elimination method. Data processing was performed in 3 anxiety levels (high, medium, low) and two anxiety levels (high, low) with the support vector machine method and hold-out validation method (7:3). The performance of the model is evaluated by showing the accuracy, precision, recall and F1 score values. The polynomial kernel can perform optimal classification and obtain 100% accuracy in 2 classes and three classes with 100% precision, recall, and F1 score values. This result shows excellent potential in measuring anxiety levels that correlate with mental health issues. [ABSTRACT FROM AUTHOR]

The key function of storytelling is a meeting of hearts: a resonance in the recipient(s) of the story narrator's emotion toward the story events. This paper focuses on the role of gestures in engendering emotional resonance in conversational storytelling. The paper asks three questions: Does story narrators' gesture expressivity increase from story onset to climax offset (RQ #1)? Does gesture expressivity predict specific EDA responses in story participants (RQ #2)? How important is the contribution of gesture expressivity to emotional resonance compared to the contribution of other predictors of resonance (RQ #3)? 53 conversational stories were annotated for a large number of variables including Protagonist, Recency, Group composition, Group size, Sentiment, and co-occurrence with quotation. The gestures in the stories were coded for gesture phases and gesture kinematics including Size, Force, Character view-point, Silence during gesture, Presence of hold phase, Co-articulation with other bodily organs, and Nucleus duration. The Gesture Expressivity Index (GEI) provides an average of these parameters. Resonating gestures were identified, i.e., gestures exhibiting concurrent specific EDA responses by two or more participants. The first statistical model, which addresses RQ #1, suggested that story narrators' gestures become more expressive from story onset to climax offset. The model constructed to adress RQ #2 suggested that increased gesture expressivity increases the probability of specific EDA responses. To address RQ #3 a Random Forest for emotional resonance as outcome variable and the seven GEI parameters as well as six more variables as predictors was constructed. All predictors were found to impact Eemotional resonance. Analysis of variable importance showed Group composition to be the most impactful predictor. Inspection of ICE plots clearly indicated combined effects of individual GEI parameters and other factors, including Group size and Group composition. This study shows that more expressive gestures are more likely to elicit physiological resonance between individuals, suggesting an important role for gestures in connecting people during conversational storytelling. Methodologically, this study opens up new avenues of multimodal corpus linguistic research by examining the interplay of emotion-related measurements and gesture at micro-analytic kinematic levels and using advanced machine-learning methods to deal with the inherent collinearity of multimodal variables. [ABSTRACT FROM AUTHOR]

Children with physical impairments may have trouble effectively performing the hand movements used in haptic exploration and may miss information about object properties. Assistive robotic systems with haptic feedback may enable children with physical impairments to haptically explore objects. However, it is important to understand if they might be encountering difficulty in assessing object properties with the system. As such, we examined two methods to ascertain a user's uncertainty or stress when doing the exploration, user confidence and electrodermal activity (EDA). Twenty adults and ten children without physical impairments manipulated four pairs of objects to examine size, roughness, hardness and shape. All participants performed the manipulation by controlling a robotic system and by manual exploration in a randomized crossover design. Adults' confidence was lower when using the robotic system and correlated with lower accuracy at determining object properties. Children's responses indicated that they may not have understood how to self-rate confidence. EDA, a potentially objective measure of stress during the task, was actually lower for adults when they used the robotic system, suggesting less physiological arousal than when using their hands. Children's EDA was variable. [ABSTRACT FROM AUTHOR]

Feeling of co-presence in VR depends on the realism of virtual agents. Our study explores how three dimensions of realism—visual appearance, behavior, and interactability—affect co-presence and Orienting Response (OR), measured using heart rate (HR) and skin conductance response (SCR). Moreover, we test whether HR and SCR can be used as measures of psychological concepts that describe virtual interactions like co-presence. Fourty-five participants passively viewed virtual characters while their HR and SCR were recorded. Afterwards participants assessed the experience of interacting with the virtual agents. The interactability of the virtual characters increased co-presence, and so did heightened appearance realism, but only when the level of behavioral realism was high. High visual and behavioral realism led to increase in SCR while visual realism alone evoked deeper HR deceleration. Nonetheless, neither SCR nor HR correlated with any psychological concepts that describe virtual interactions. In conclusion, realism can increase both the co-presence and magnitude of the OR, yet physiological indices can not reliably gauge the experience of interactions with virtual characters. [ABSTRACT FROM AUTHOR]

The field of emotion recognition from physiological signals is a growing area of research with significant implications for both mental health monitoring and human–computer interaction. This study introduces a novel approach to detecting emotional states based on fractal analysis of electrodermal activity (EDA) signals. We employed detrended fluctuation analysis (DFA), Hurst exponent estimation, and wavelet entropy calculation to extract fractal features from EDA signals obtained from the CASE dataset, which contains physiological recordings and continuous emotion annotations from 30 participants. The analysis revealed significant differences in fractal features across five emotional states (neutral, amused, bored, relaxed, and scared), particularly those derived from wavelet entropy. A cross-correlation analysis showed robust correlations between fractal features and both the arousal and valence dimensions of emotion, challenging the conventional view of EDA as a predominantly arousal-indicating measure. The application of machine learning for emotion classification using fractal features achieved a leave-one-subject-out accuracy of 84.3% and an F1 score of 0.802, surpassing the performance of previous methods on the same dataset. This study demonstrates the potential of fractal analysis in capturing the intricate, multi-scale dynamics of EDA signals for emotion recognition, opening new avenues for advancing emotion-aware systems and affective computing applications. [ABSTRACT FROM AUTHOR]

Background: Flying accuracy is influenced by pilots' affective reactions to task demands. A better understanding of task‐related emotions and flying performance is needed to enhance pilot training. Objective: Understand pilot trainees' performance and emotional dynamics (intensity, frequency and variability) based on training phase and difficulty level in a flight simulator. Methods: Twenty‐three volunteers performed basic flight manoeuvres. Trials were divided into three phases: Introduction (trials 1–7), session A (trials 8–15) and session B (trials 16–22). Three task difficulty levels were implemented (low, medium and high). Flying performance was evaluated using root mean square error (RMSE) and expert ratings. Emotional intensity was inferred from physiological (electrodermal activity) and behavioural (facial expressions) emotional responses. Emotional variability was calculated to understand fluctuations among multiple emotions. Emotional responses were mapped into task‐relevant emotions, like sadness with boredom, and fear with anxiety. Results and Conclusions: The most frequent facial expressions neutral, anger and surprise. Neutral and anger were interpreted as deep focus states. Surprise was likely a response to unexpected events. Flying performance and emotional dynamics varied across training phases and difficulty levels. During introduction, performance was less accurate, and emotions were less frequent. During session A, performance improved while participants experienced more physiological arousal and emotional variability. During session B, performance was the most accurate. In high‐difficulty tasks, performance was the least accurate, participants expressed emotions with more frequency, more variability and higher physiological arousal. Future studies can use simulated flying tasks for trainees to familiarize with their emotional reactions to task demands expecting to improve training outcomes. Lay Description: What is currently known about emotions in flight training?: Emotions influence pilots' decision‐making and flying accuracy.Flight simulations serve as a safe and authentic environment to develop flying skills.Emotions are dynamic processes that influence performance accuracy. What does this paper add to understanding emotions in flight training?: Flying performance improved with more practice, but it was less accurate during high difficulty manoeuvres.In simulated flight training, pilot trainees express more neutrality, anger, and surprise than happiness, fear and disgust.Pilot trainees experience more emotional fluctuations when there is no instructor feedback.Pilot trainees experience more emotional fluctuations during high difficulty flying manoeuvres. Implications for practice: Flight simulations help trainees familiarize themselves with the emotional reactions they have as training advances or encounter difficult tasks.Pilot trainees can learn emotion regulation techniques as part of their curriculum.Emotional awareness might help pilot trainees recognize key moments of disengagement or intense arousal and modify their behaviour. [ABSTRACT FROM AUTHOR]

Supplemental Digital Content is Available in the Text. Threat of pain triggers motor inhibition, which is topographically organized, mapped relative to the body part where pain is expected and enhanced by increasing trait anxiety. Pain-related motor adaptations may be enacted predictively at the mere threat of pain, before pain occurrence. Yet, in humans, the neurophysiological mechanisms underlying motor adaptations in anticipation of pain remain poorly understood. We tracked the evolution of changes in corticospinal excitability (CSE) as healthy adults learned to anticipate the occurrence of lateralized, muscle-specific pain to the upper limb. Using a Pavlovian threat conditioning task, different visual stimuli predicted pain to the right or left forearm (experiment 1) or hand (experiment 2). During stimuli presentation before pain occurrence, single-pulse transcranial magnetic stimulation was applied over the left primary motor cortex to probe CSE and elicit motor evoked potentials from target right forearm and hand muscles. The correlation between participants' trait anxiety and CSE was also assessed. Results showed that threat of pain triggered corticospinal inhibition specifically in the limb where pain was expected. In addition, corticospinal inhibition was modulated relative to the threatened muscle, with threat of pain to the forearm inhibiting the forearm and hand muscles, whereas threat of pain to the hand inhibited the hand muscle only. Finally, stronger corticospinal inhibition correlated with greater trait anxiety. These results advance the mechanistic understanding of pain processes showing that pain-related motor adaptations are enacted at the mere threat of pain, as sets of anticipatory, topographically organized motor changes that are associated with the expected pain and are shaped by individual anxiety levels. Including such anticipatory motor changes into models of pain may lead to new treatments for pain-related disorders. [ABSTRACT FROM AUTHOR]

Skin conductance is a commonly used physiological measure during psychology experiments, such as during fear conditioning. Methods for scoring skin conductance responses (SCRs) are highly heterogeneous, though most researchers agree that manually inspected scores provide the highest quality data when compared to most available fully automated scoring methods. However, manual scoring is extremely time‐consuming. We developed a semi‐automated scoring program that reduces the time required to process SCR data at a level of quality akin to manual scoring. In contrast to all previous scoring programs, our program enables scoring of first interval response (FIR), second interval response (SIR), and third interval response (TIR) SCRs. Using interclass correlation coefficients (ICCs), Bland–Altman plots and Pareto analysis, we show here that our method is highly reliable and produces data that are almost identical to data that are manually scored and scored using LEDALAB. This software is very easy to use and is freely available to download and modify. We expect that this software will be helpful in reducing the time required to produce high quality FIR, SIR, and TIR skin conductance data for psychology researchers around the world. Existing automated methods for scoring skin conductance responses (SCRs) without manual inspection leave ambiguity whether these methods are scoring SCRs accurately. Our program automatically scores SCRs and allows rapid manual inspection of multiple response intervals for each event. This program provides an option for researchers to produce high quality SCR data in a time‐efficient manner. The program is free, easy to use, and is opensource. The program is fully validated against manually scored data and between independent raters. [ABSTRACT FROM AUTHOR]

In spite of the development in technology and the recent innovations in dentistry, dental anxiety remains a common issue, and accurately assessing it is challenging due to reliance on patients' self-reports, which are often biased. Hence, this study was undertaken to determine whether dental anxiety can be quantified objectively using the EDA parameters. EDA (skin conductance (SC), skin susceptance (SS), and skin potential (SP)) parameters and heart rate (HR) were recorded from 40 participants during two different sessions (baseline and anxiety). In addition, the Modified Dental Anxiety Scale (MDAS) scale was also used to record the level of anxiety. The physiological data from EDA and HR were compared with the subjective self-reports of anxiety provided on the MDAS to show whether higher EDA and HR readings correspond to higher scores on the MDAS. To elicit dental anxiety, participants were exposed to several film clips associated with dental treatment. EDA signals were compared between the two sessions for all clips and all EDA scores. SC and HR significantly (p < 0.05) increased during the anxiety session compared to the baseline session. The number of fluctuations per minute in the SC, SS, and SP notably increased during the anxiety session. The MDAS results revealed that the participants had dental anxiety when they were exposed to video clips of dental procedures. The study results imply that EDA parameters could be used as a useful tool to monitor dental anxiety, in particular in young children and non-verbal patients or those with intellectual disabilities, which may aid the dentist in the successful management of dental anxiety during treatment. The moment-to-moment EDA data on a patient's anxiety levels throughout particular dental operations provides a clearer picture of anxiety variations than pre- or post-appointment surveys alone, in addition to offering unbiased tracking of dental anxiety levels over self-reports. This study seeks to encourage further research into the most effective EDA parameters for improving the management of dental anxiety. [ABSTRACT FROM AUTHOR]

Anxiety is a significant mental health concern that can be effectively monitored using physiological signals such as galvanic skin response (GSR). While the potential of machine learning (ML) algorithms to enhance the classification of anxiety based on GSR signals is promising, their effectiveness in this context remains largely underexplored. This study addresses this gap by investigating the performance of three commonly used ML algorithms, support vector machine (SVM), K-nearest neighbor (KNN), and random forest (RF), in classifying anxiety and stress activity using a benchmark dataset. We employed two feature extraction methods: traditional statistical feature extraction and an innovative automatic feature extraction approach utilizing a 14-layer autoencoder, aimed at improving classification performance. Our findings demonstrate the effectiveness of using GSR signals and the robust performance of the KNN algorithm in accurately classifying anxiety levels. The KNN algorithm achieved the highest accuracy in both the statistical and automatic feature extraction approaches, with results of 96.9% and 98.2%, respectively. These findings highlight the effectiveness of KNN for anxiety detection and emphasize the need for advanced feature extraction techniques to enhance classification outcomes in mental health monitoring. [ABSTRACT FROM AUTHOR]

Medical simulations allow trainees to work within teams to develop their self-regulated learning (SRL) and socially-shared regulated learning (SSRL) skills (Bransen et al., 2022). Both skillsets help to better prepare medical trainees for the multifaceted challenges inherent in clinical practice. SRL skills are imperative in empowering learners to optimize their performance and become autonomous guiders of their own learning (Jarvela & Hadwin, 2013), while SSRL skills are needed to ensure that teams can work collectively to regulate their behaviors and to regulate their own learning to make decisions (Hadwin & Oshige, 2011). Questions remain about not only how medical trainees' behaviors, regulation strategies, and physiological responses vary while they participate in a high-fidelity medical simulation, but how additional data channels to measure human response can provide indicators of teams' regulation strategies. Using a mixed-methods convergence design incorporating multimodal data (Azevedo & Gašević, 2019), including behavioral, SRL and SSRL codes, and electrodermal activity, researchers studied twenty-nine (N = 29) 1st to 3rd year medical residents as they engaged in high-fidelity simulation scenarios. Results suggest that the mean-level of psychophysiological activation increase as simulations progress, in conjunction with an increase in team-regulated learning strategies to manage the effective provision of patient care from initial contact through to the delivery of critical procedures. These results provide valuable insights into the advancement of a team regulation-based framework within a high-fidelity medical simulation environment, leveraging multimodal data to reach an understanding of medical trainees' adoption of team-based approaches to team-regulation during simulation scenarios. [ABSTRACT FROM AUTHOR]

The analysis of spontaneous mind wandering is crucial for comprehending an individual mental state and holds the potential to enhance performance and productivity. This paper proposes a framework using Continuous Wavelet Transform (CWT) based ResNet model to analyze Electrodermal Activity (EDA) signals for mind wandering detection. In this analysis, EDA signals are sourced from an openly accessible database and preprocessed for artifact and noise removal. Time-frequency analysis generates CWT spectrogram images, which are classified using a modified ResNet50 model that is custom built to classify the spectrogram images corresponding the mind wandering and awareness. Hyperparameter tuning is carried to obtain the optimal network parameters that provides the best accuracy. Results indicate that batch size of 32, learning rate 1e-5 provides better results. This hyperparameter tuned model achieved an accuracy of 64% in differentiating between the two classes. This paper proposes an adapted ResNet50 model that could be employed in wearable devices as a potential application of knowing the mind awareness of an individual. [ABSTRACT FROM AUTHOR]

Reading is an essential method for adults to learn new languages, but difficulty reading texts in a foreign language can increase learners’ anxiety. Identifying text difficulty from the reader’s perspective can aid language learning by tailoring texts to readers’ needs. There is little research focusing on L2 speakers or using a multimodal approach, i.e., using multiple sensors, to detect subjective difficulty. In this study ( $N=30$ ) we determined L2 speakers’ subjective difficulty while reading using language proficiency and objective text difficulty, combined with physiological data. We compared machine learning classifiers combining eye, skin and heart sensor data against models using each modality separately. Additionally, we assessed the effect on model performance of shifting the data to account for delayed physiological responses. The models detected 3 levels of subjective difficulty (low, medium, high) and were evaluated using leave-one-participant-out (LoPo) and leave-one-document-out (LoDo) cross-validation. The results showed acceptable levels of generalization to new participants ( $Acc_{LoPo} = 0.434$ ) and documents ( $Acc_{LoDo} = 0.521$ ). Combining sensor data from all modalities improved predictions in both LoDo and LoPo cross-validation, compared to each modality in isolation. Shifting the data to account for physiological response delay did not improve model performance compared to not shifting the data. These findings support refining subjective difficulty detection models and their implementation in adaptive language learning systems. Finally, this work contributes to the field of cognitive science and technology by laying the foundation for innovative approaches to cognitive state detection.

BACKGROUND. Common consequences of stroke are disabling neurological deficits, pain, cognitive and affective disorders that cause distress in patients, but generally accepted diagnostic methods are not always successful in detecting it. Currently, there is an increasing accumulation of data that the assessment of the level of sympathetic activation according to the parameters of electrodermalic activity (EDA) is effective for the diagnosis of stressful conditions. AIM. To evaluate the possibility of objectification of stress by EDA parameters in stroke patients using examples of clinical observations. CASES DESCRIPTION. In addition to clinical and metric assessment, EDA was registered in 3m stroke patients (I69.3) at the beginning and at the end of rehabilitation. In the 1st observation, the stress level of EDA indicators initially coincided with high levels of anxiety and depression, the reduction of which at the end of rehabilitation to optimal values led to normalization of EDA. In the 2nd case, at the beginning and at the end of rehabilitation, despite minimal neurological deficit, absence of pain and affective disorders and any complaints, stress indicators of EDA were recorded, due to previously undiagnosed alexithymia and persistent psychosomatic disorder. In the 3rd observation, a patient with a pronounced neurological deficit, who made increased demands on herself, initially normal EDA indicators, at the end of rehabilitation, in the absence of any complaints, changed to stressful ones due to overtraining. CONCLUSION. The presented clinical observations can be useful for neurologists, psychologists, psychiatrists and psychotherapists, they demonstrate that taking into account ED indicators in a comprehensive assessment of the condition of stroke patients can increase the detection of stress and optimize rehabilitation measures.

Driving is integral to many people's daily existence, but aggressive driving behavior increases the risk of road traffic collisions. Young drivers are more prone to aggressive driving and danger perception impairments. A driver's physiological state (e.g., fatigue, anger, or stress) can negatively affect their driving performance. This is especially true for young drivers who have limited driving experience. This research focuses on examining the connection between emotional arousal and aggressive driving behavior in young drivers, using predictive analysis based on electrodermal activity (EDA) data through neural networks. The study involved 20 participants aged 18 to 30, who completed 84 driving sessions. During these sessions, their EDA signals and driving behaviors, including acceleration and braking, were monitored using an Empatica E4 wristband and a telematics device. This study conducted two key analyses using neural networks. The first analysis used a comprehensive set of EDA features to predict emotional arousal, achieving an accuracy of 65%. The second analysis concentrated on predicting aggressive driving behaviors by leveraging the top 10 most significant EDA features identified from the arousal prediction model. Initially, the arousal prediction was performed using the complete set of EDA features, from which feature importance was assessed. The top 10 features with the highest importance were then selected to predict aggressive driving behaviors. Another aggressive driving behavior prediction with a refined set of difference features, representing the changes from baseline EDA values, was also utilized in this analysis to enhance the prediction of aggressive driving events. Despite moderate accuracy, these findings suggest that EDA data, particularly difference features, can be valuable in predicting emotional states and aggressive driving, with future research needed to incorporate additional physiological measures for enhanced predictive performance. [ABSTRACT FROM AUTHOR]

There are competing theoretical hypotheses regarding the consequences of early adversity, such as childhood maltreatment, for individuals' autonomic nervous system activity. Research examining potential implications of child maltreatment for sympathetic nervous system activity, specifically, is scarce. In this preregistered study, we examined whether childhood maltreatment history is associated with pregnant adults' sympathetic responses to different stressors. This population is particularly relevant, given potential intergenerational consequences of pregnant individuals' physiological responses to stress. Pregnant women's (N = 162) electrodermal levels were recorded while completing the Trier Social Stress Test (TSST), which elicits social‐evaluative threat, and while watching a video of an unfamiliar infant crying, which was intended to activate the attachment system. Pregnant women's retrospective reports of childhood maltreatment were negatively associated with their electrodermal reactivity to the TSST and to the video of the infant crying. Follow‐up analyses indicated that these associations were specific to reported experiences of childhood abuse and not childhood neglect. Altogether, these findings indicate that self‐reported childhood maltreatment experiences, and childhood abuse in particular, may result in blunted activity of the sympathetic nervous system in response to multiple types of stressors. [ABSTRACT FROM AUTHOR]

Complexity characterizes behaviour of all physiological systems whose components interact in multiple ways usually quantified by entropy techniques. However, complexity analysis regarding electrodermal activity (EDA)-related sympathetic cholinergic nervous system is rare. Thus, we aimed to study EDA dynamics complexity changes from aspect of various embedding dimensions (m) and timescales (t) (sample entropy (SampEn) with m ∈ <2,7>, and multiscale entropy (MSE) in t ∈ <1,20>) in association with traditionally used EDA indices (skin conductance level (SCL) and nonspecific skin conductance responses (NS.SCRs)) to mental stress (mental arithmetic test - MAT) in healthy participants at critical adolescent age. The cohort (total group) consisted of 60 adolescents (17.5 ± 0.5 yrs) divided into three groups: Group-1: early (13.1 ± 0.3 yrs), Group-2: middle (16.6 ± 0.2 yrs) and Group-3: late (22.9 ± 0.1 yrs) adolescence. SampEn (m > 2) and MSE (for all τ) were significantly higher during MAT than baseline in total group and Group-2 (p < 0.05). Index MSE for all t was significantly higher during MAT than baseline in total group, and Group-2; for t ∈ <2,13> in Group-1 (p < 0.05). Additionally, while SCL was significantly higher during MAT than baseline in all groups, NS.SCRs was lower during stress only in Group-3 (p < 0.05). In conclusion, this study revealed distinct EDA complexity characteristics in individual examined groups indicating importance of complexity evaluation in stress-related sympathetic regulatory mechanisms within individual adolescent age ranges. [ABSTRACT FROM AUTHOR]

Motivation is an interdisciplinary concept which encompasses various theories, concepts and frameworks. This paper aims to bring various motivational theories together, with interest development at its core, to develop a more streamlined framework of interest development. Interest is believed to play a vital role in student learning, and this "Growth cycle of interest" framework aims to provide a deeper understanding of interest development in the context of education. This paper begins with a brief overview of major motivational theories, synthesising them into the Growth Cycle of Interest framework, which is then exemplified through case studies. [ABSTRACT FROM AUTHOR]

As economic growth and societal shifts reshape urban environments, cultural and creative industrial parks are emerging as vital contributors to sustainable urban development. The design of these landscapes plays a pivotal role in enhancing user satisfaction, increasing spatial attractiveness, and promoting eco-friendly urban practices. This study examines visitor landscape perception preferences in the Textile and Garment Cultural and Creative Industrial Park, located in Haizhu District, Guangzhou, through a novel methodology combining user-generated content (UGC), deep learning models, outdoor electrodermal activity (EDA) measurements, and questionnaire surveys. The UGC-based landscape recognition model achieved an accuracy of 86.8% and was validated against user preferences captured through questionnaires. Results demonstrate that visitors prefer areas featuring cultural landmarks and natural elements, while spaces dominated by human activity and transportation infrastructure are less favored. Key landscape elements, such as signage, thematic sculptures, brand logos, and trees, were identified as highly preferred features within the park. While EDA experiments revealed significant variations in physiological responses across different spatial settings, no strong correlation was observed between EDA indicators and subjective questionnaire scores. This integrative approach enables a comprehensive, objective assessment of landscape perception, providing a data-driven, user-centered framework for improving landscape design in cultural and creative industrial parks. [ABSTRACT FROM AUTHOR]

Understanding the complex and dynamic nature of experiences requires the use of proper measurement tools. As interest grows in the objective measurement of experiences within tourism and hospitality, there is an urgent need to consolidate and synthesize these studies. Thus, this study investigated prevalent objective measurement techniques via a systematic review. We analyzed physiological measures such as electroencephalography (EEG), heart rate variability (HRV), skin conductance (SC), and facial electromyography (fEMG) along with behavioral measures, including eye tracking and location tracking. This review identified 100 empirical studies that employed objective measurement to examine tourism and hospitality experiences over the last decade, highlighting trends, research contexts and designs, and the synergies between different methods. Our discussion on methodological issues and best practices will help researchers and practitioners identify the best tools to capture people's experiences and promote more standardized practices and comparable findings on studying experiences in tourism and hospitality settings. [ABSTRACT FROM AUTHOR]

Introduction: This study investigated the differences between males and females in autonomic functions and cognitive performance during cold-air exposure and cold-water partial-immersion compared to a room temperature-air environment. Although several studies have investigated the effects of cold-air or cold-water exposures on autonomic function and cognitive performance, biological sex differences are often under-researched. Methods: Twenty-two males and nineteen females participated in the current study. Subjects completed a battery of cognitive tasks based upon those used within the Defense Automated Neurobehavioral Assessment (DANA), consisting of five subtasks that assess simple and procedural reaction time, spatial manipulation, attention, and immediate memory. In total, subjects took the battery within a 15-minute period across 30-minute intervals throughout the duration of environmental exposure. Across three separate days, subjects were exposed to three different environmental conditions: room temperature air (23°C), cold air (10°C), and cold water (15°C; in which subjects were immersed up to their necks). Room temperature and cold-air conditions consisted of five sessions (about 2.5 h), and the cold-water condition consisted of three sessions (about 1.5 h). During each experimental condition, physiological data were collected to assess autonomic function, including electrodermal activity (EDA) data and heart rate variability (HRV) derived from electrocardiogram signals. Results: Females showed slower reaction time in spatial manipulation tasks, immediate memory, and attention during cold-air exposures compared to room temperature air, whereas the performance of males were similar or better during cold-air exposures compared to room temperature air. Cold-water immersion affected the immediate memory performance of males. Both males and females exhibited smaller EDA amplitudes during cold-air and cold-water conditions compared to room temperature air. For HRV, only male subjects exhibited significantly greater values in low-frequency and very-low-frequency components during cold air exposure compared to the normal condition. Discussion: Sex introduces important differences in cognitive performance and autonomic functions during exposure to cold-air and cold-water. Therefore, sex should be considered when assessing the autonomic nervous system in cold environments and when establishing optimal thermal clothing for performance in operational environments. Our findings can assist with determination of operational clothing, temperature in operating environment, and personnel deployment to operational sites, particularly in settings involving both males and females. [ABSTRACT FROM AUTHOR]

Despite the increasing popularity of ambulatory assessment, the reliability and validity of psychophysiological signals from wearable devices is unproven in daily life settings. We evaluated the reliability and validity of physiological signals (electrocardiogram, ECG; photoplethysmography, PPG; electrodermal activity, EDA) collected from two wearable devices (Movisens EcgMove4 and Empatica E4) in the lab (N = 67) and daily life (N = 20) among adults aged 18–64 with Mindware as the laboratory gold standard. Results revealed that both wearable devices' valid data rates in daily life were lower than in the laboratory (Movisens ECG 82.94 vs. 93.10%, Empatica PPG 8.79 vs. 26.14%, and Empatica EDA 41.16 vs. 42.67%, respectively). The poor valid data rates of Empatica PPG signals in the laboratory could be partially attributed to participants' hand movements (r = –.27, p =.03). In laboratory settings, heart rate (HR) derived from both wearable devices exhibited higher concurrent validity than heart rate variability (HRV) metrics (ICCs 0.98–1.00 vs. 0.75–0.97). The number of skin conductance responses (SCRs) derived from Empatica showed higher concurrent validity than skin conductance level (SCL, ICCs 0.38 vs. 0.09). Movisens EcgMove4 provided more reliable and valid HRV measurements than Empatica E4 in both laboratory (split-half reliability: 0.95–0.99 vs. 0.85–0.98; concurrent validity: 0.95–1.00 vs. 0.75–0.98; valid data rate: 93.10 vs. 26.14%) and ambulatory settings (split-half reliability: 0.99–1.00 vs. 0.89–0.98; valid data rate: 82.94 vs. 8.79%). Although the reliability and validity of wearable devices are improving, findings suggest researchers should select devices that yield consistently robust and valid data for their measures of interest. [ABSTRACT FROM AUTHOR]

Aim of the study: The aim of the study was to examine the physiological activity in patients and psychotherapists during psychodynamic psychotherapy in relation to: gender, presence of personality disorder traits and anxiety symptoms. Subject or material and methods: Physiological data of 24 patients with a diagnosis of neurotic disorders and/or personality disorders were analysed. Psychotherapy was conducted by two psychotherapists. Most patients had an anxiety disorder or a specific personality disorder. Physiological data were collected using a galvanometer and a pulsometer. Results: The physiological activity of the psychotherapists differed, probably due to their professional experience. The physiological activity of the patients differed due to the psychotherapist providing therapy, gender, personality traits, and level of neurotic symptoms. Discussion: Differences in the physiological parameters of psychotherapists could be related to individual differences between them: gender, age, education, and length of professional experience. Length of the experience and gender of therapists could have influenced patients' physiological reactions. Patients' dominant symptoms could be related to the intensity of their physiological reactions. Due to the significant and interesting results of the study it would be worth repeating it on a larger number of patients and psychotherapists. Conclusions: The physiological state of the psychotherapists correlate with the physiological reactions of the patients. The results suggest higher EDA (electrodermal activity) and lower HR (heart rate) in neurotic disorders and higher HR activity and lower EDA in personality disorders. [ABSTRACT FROM AUTHOR]

While social robots show promise for therapeutic interventions, accurate assessments of (vulnerable) participants' affective outcomes require attention. The careful selection of devices for recording autonomic processes in response to stress-inducing and relaxing exercises is essential to ensure data quality recordings and participants' comfort. This foundational study assessed two commonly utilized devices to record electrodermal activity (EDA), indexed through skin conductance, concerning their sensitivity to stress-relaxation manipulations and social validity during a robot intervention: a sock with a Shimmer device and a wrist-worn Empatica E4. We aimed to select the most sensitive and easy-to-wear one as a precursor to a larger intervention study featuring mindfulness-based relaxation exercises delivered by an NAO robot. The findings, based on 28 healthy Dutch-speaking adult volunteers wearing both devices, revealed sensitivity in detecting EDA variations in arousal following stressful (increase) and Robot-delivered mindfulness-based relaxation (decrease) exercises, further corroborated by self-reports. Bland-Altman results suggested little agreement between the two devices and lower sensitivity for the Empatica E4. No statistically significant differences concerning wearing comfort between the Empatica E4 and the Shimmer devices emerged. Although both devices independently showed sensitivity to stress/relaxation manipulation, the choice for one or the other should be informed by the activities in the intervention. [ABSTRACT FROM AUTHOR]

Purpose: This study aims predicting the stress level based on the ergonomic (kinematic) and physiological (electrodermal activity—EDA, blood pressure and body temperature) parameters of the surgeon from their records collected in the previously immediate situation of a minimally invasive robotic surgery activity. Methods: For this purpose, data related to the surgeon's ergonomic and physiological parameters were collected during twenty-six robotic-assisted surgical sessions completed by eleven surgeons with different experience levels. Once the dataset was generated, two preprocessing techniques were applied (scaled and normalized), these two datasets were divided into two subsets: with 80% of data for training and cross-validation, and 20% of data for test. Three predictive techniques (multiple linear regression—MLR, support vector machine—SVM and multilayer perceptron—MLP) were applied on training dataset to generate predictive models. Finally, these models were validated on cross-validation and test datasets. After each session, surgeons were asked to complete a survey of their feeling of stress. These data were compared with those obtained using predictive models. Results: The results showed that MLR combined with the scaled preprocessing achieved the highest R2 coefficient and the lowest error for each parameter analyzed. Additionally, the results for the surgeons' surveys were highly correlated to the results obtained by the predictive models (R2 = 0.8253). Conclusions: The linear models proposed in this study were successfully validated on cross-validation and test datasets. This fact demonstrates the possibility of predicting factors that help us to improve the surgeon's health during robotic surgery. [ABSTRACT FROM AUTHOR]

Background: Virtual reality is no longer created solely with design graphics. Real life 360° videos created with special shooting techniques are now offered as open access to users' experience. As a result, this widespread use of VR systems has increased the incidence of visually induced motion sickness. Objective: In the present study, we aimed to investigate impact of brightnesscontrast levels of real-life 360° videos on susceptibility to visually induced motion sickness during immersive virtual reality headset viewing. Methods: In this study, 360° real-world day and night driving videos publicly available on YouTube VR were used as stimuli. Stimuli were presented in 2-min segments. Electrodermal activity was recorded throughout the stimulus presentation, and SSQ was administered immediately afterward. Results: No significant difference was found between the experiments in terms of dermal activity. There is a statistically significant difference in total SSQ scores and in symptoms of fatigue, eye strain, head fullness, blurred vision, and dizziness (p < 0.005; p < 0.01) after then the night video. Conclusion: The present study examined the likely impact of brightness and contrast levels in VR environments on VIMS provocation. [ABSTRACT FROM AUTHOR]

An unannounced balance loss during walking, i.e., balance perturbation, is a stressful event, which changes the activity of the sympathetic nervous system (SNS). We examined SNS response to unannounced balance perturbation during walking, simulating real-life condition of balance loss. We asked: do laboratory-induced unannounced balance losses during walking cause a sympathetic response, and—if so—does it habituate after a series of perturbations? Thirty-four young adults underwent a series of six successive unannounced balance perturbations while walking on a treadmill. Sympathetic activity was monitored continuously using electrodermal activity and compared before and immediately after each unannounced perturbation. All perturbations elicited a significant increase of electrodermal activity (P < 0.001), indicating a phasic increase in the sympathetic drive. The relative phasic increase of electrodermal activity caused by the first perturbation was significantly higher than the last perturbation (P < 0.05). Three different types of electrodermal activity behavior were observed: steady-level tonic SNS activity, increased SNS activity, and decreased SNS activity. Balance loss during walking triggers phasic SNS response, this response habituates after a series of unannounced balance perturbations. In addition, three distinct patterns of tonic sympathetic activity may imply variations in the ability of the SNS response to habituate across individuals. NEW & NOTEWORTHY: Up to date, the literature typically provides information about sympathetic nervous system activity and relatively static balance. We believe that exposing participants to a balance loss during walking, i.e., unexpected perturbation, provides a more ecologically valid situation to measure sympathetic nervous system response; this provides new and vital knowledge that can have a significant impact and understanding of how the SNS responds to a loss of balance in a real-life situation. [ABSTRACT FROM AUTHOR]

Physiological measures associated with emotional expressions have been used extensively in lab- and, more recently, digital-learning settings. However, the portable and ubiquitous nature of hardware that measures these physiological features makes them particularly useful in situations where you do not want the hardware to be too obtrusive, like in contexts of informal learning. In this proof-of-concept study, we apply skin conductance methods that measure Electrodermal Activity (EDA) to a family everyday activities context, in which a parent and their children, complete several science learning activities, while being recorded by both video and EDA hardware. We analyse the resulting data in three different ways: (i) a peak analysis in software recommended by the hardware provider, (ii) a conventional, qualitative microanalysis, and (iii) a method mainly used by econometricians to discover 'structural breaks' in time series data. We conclude that all three provide a piece of the overall puzzle, revealing up- and down-sides of each method. [ABSTRACT FROM AUTHOR]

Simple Summary: The venoarteriolar reflex (VAR) consists of a local vasoconstriction occurring in response to an increase in venous transmural pressure. Its underlying mechanisms, including its impact on contralateral perfusion, still need clarification. In this study we assessed VAR in a group of healthy subjects by performing a unilateral limb dependency procedure. During dependency skin perfusion decreased significantly in both the dependent and the contralateral hands. Cutaneous sympathetic activity increased during dependency and upon returning to the initial position. These results corroborate previous reports that unilateral limb dependency impacts contralateral perfusion and suggest the participation of the sympathetic nervous system. This sympathetic activation seems to occur in response to the postural change itself and does not seem to be related to the VAR. The venoarteriolar reflex (VAR) is described as a vasoconstriction occurring in response to an increase in venous transmural pressure. Its underlying mechanisms are still not clarified, particularly the neural pathway that supposedly evokes this reflex. In addition, recent studies have shown that the postural maneuvers that evoke VAR also produce a decrease in contralateral perfusion, which is also poorly understood. Our study aimed to explore the contralateral response to unilateral upper limb dependency and its underlying mechanisms. Fifteen young, healthy subjects (24.1 ± 5.8 y.o.) participated in this study after giving informed consent. While seated, subjects remained for 7 min with both arms at heart level (baseline), after which a random hand was placed 40 cm below the heart level for 5 min (dependency) before resuming the initial position for another 7 min (recovery). Skin perfusion was assessed bilaterally with photoplethysmography, and electrodermal activity (EDA) was assessed in the contralateral hand. During hand dependency, perfusion decreased significantly in both limbs, although it was more pronounced in the dependent limb, corroborating previous reports that unilateral limb dependency evokes a decrease in contralateral perfusion. Transient EDA peaks were detected in the first seconds of the dependency and recovery phases. These results support the participation of the sympathetic nervous system as a mechanism regulating contralateral perfusion during unilateral limb dependency. This sympathetic activation is probably attributed to the postural changes themselves and is likely not related to the VAR. [ABSTRACT FROM AUTHOR]

Objective: 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. Method: 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. Results: 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. Discussion: 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. Highlights: Patients with anorexia nervosa (AN) show a regulation of interpersonal distances to social emotional stimuli similar to healthy controls (CTL) but lack the corresponding physiological response.Patients with AN, not CTL, prefer shorter interpersonal distance with underweight social stimuli and larger interpersonal distance with overweight ones and show increased physiological response to both of them.Patients with AN show a bias towards morphological rather than emotional cues when processing information to optimise social interaction. [ABSTRACT FROM AUTHOR]

Depressed individuals exhibit altered sensitivity to both positive and negative social contact, and may not reap the same psychological and emotional benefits to socializing as non‐depressed individuals. Although depressive symptoms and loneliness predict social withdrawal and decreased pleasure, little is currently understood about immediate affective arousal dynamics during real‐time socializing. Using a novel ambulatory protocol that tracked both objective features of affective arousal (electrodermal activity) and subjective valence (self‐reported) during college students' social interactions, we evaluated the moderating role of depression and loneliness symptoms on the associations between socializing with others (specifically, with a romantic partner, a close friend, or a group of friends) and the arousal and valence dimensions of affect. Among a racially and ethnically diverse sample of 118 college students (64% African American/Black/Continental African, 20% Latinx, 8% Asian, and 8% White) recruited from a large, predominantly White Midwestern university, those lower in depression and loneliness symptomatology evinced decreased average arousal (Β = −0.10, SE = 0.04, p <.01) when in relaxed and intimate socializing contexts (e.g., with a romantic partner and a close friend), consistent with the idea that these contexts facilitate important opportunities for psychological rest and recovery. Those lower in depression and loneliness symptoms also showed higher average arousal when socializing in the energizing context of being with a group of friends. Overall, the results suggest psychopathology is reflected in patterns of sympathetic arousal when socializing, with more depressed and lonely individuals generally feeling worse while receiving fewer psychophysiological rewards in multiple socializing contexts. Our findings add a new perspective on psychopathology as an individual difference factor which may impact how spending time with others influences health. Young people who contend with depression and loneliness might lose out on the psychophysiological benefits of intimate socializing experiences which facilitate rest and recovery, as well as the positively arousing and energizing experiences. [ABSTRACT FROM AUTHOR]

The key function of storytelling is a meeting of hearts: a resonance in the recipient(s) of the story narrator’s emotion toward the story events. This paper focuses on the role of gestures in engendering emotional resonance in conversational storytelling. The paper asks three questions: Does story narrators’ gesture expressivity increase from story onset to climax offset (RQ #1)? Does gesture expressivity predict specific EDA responses in story participants (RQ #2)? How important is the contribution of gesture expressivity to emotional resonance compared to the contribution of other predictors of resonance (RQ #3)? 53 conversational stories were annotated for a large number of variables including Protagonist, Recency, Group composition, Group size, Sentiment, and co-occurrence with quotation. The gestures in the stories were coded for gesture phases and gesture kinematics including Size, Force, Character view-point, Silence during gesture, Presence of hold phase, Co-articulation with other bodily organs, and Nucleus duration. The Gesture Expressivity Index (GEI) provides an average of these parameters. Resonating gestures were identified, i.e., gestures exhibiting concurrent specific EDA responses by two or more participants. The first statistical model, which addresses RQ #1, suggested that story narrators’ gestures become more expressive from story onset to climax offset. The model constructed to adress RQ #2 suggested that increased gesture expressivity increases the probability of specific EDA responses. To address RQ #3 a Random Forest for emotional resonance as outcome variable and the seven GEI parameters as well as six more variables as predictors was constructed. All predictors were found to impact Eemotional resonance. Analysis of variable importance showed Group composition to be the most impactful predictor. Inspection of ICE plots clearly indicated combined effects of individual GEI parameters and other factors, including Group size and Group composition. This study shows that more expressive gestures are more likely to elicit physiological resonance between individuals, suggesting an important role for gestures in connecting people during conversational storytelling. Methodologically, this study opens up new avenues of multimodal corpus linguistic research by examining the interplay of emotion-related measurements and gesture at micro-analytic kinematic levels and using advanced machine-learning methods to deal with the inherent collinearity of multimodal variables.

Abstract Background Attention-Deficit/Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental psychiatric condition that typically emerges during childhood but often persists into adulthood, significantly impacting individuals’ functioning, relationships, productivity, and overall quality of life. However, the current diagnostic process exhibits limitations that can significantly affect its overall effectiveness. Notably, its face-to-face and time-consuming nature, coupled with the reliance on subjective recall of historical information and clinician subjectivity, stand out as key challenges. To address these limitations, objective measures such as neuropsychological evaluations, imaging techniques and physiological monitoring of the Autonomic Nervous System functioning, have been explored. Methods The main aim of this study was to investigate whether physiological data (i.e., Electrodermal Activity, Heart Rate Variability, and Skin Temperature) can serve as meaningful indicators of ADHD, evaluating its utility in distinguishing adult ADHD patients. This observational, case-control study included a total of 76 adult participants (32 ADHD patients and 44 healthy controls) who underwent a series of Stroop tests, while their physiological data was passively collected using a multi-sensor wearable device. Univariate feature analysis was employed to identify the tests that triggered significant signal responses, while the Informative k-Nearest Neighbors (KNN) algorithm was used to filter out less informative data points. Finally, a machine-learning decision pipeline incorporating various classification algorithms, including Logistic Regression, KNN, Random Forests, and Support Vector Machines (SVM), was utilized for ADHD patient detection. Results Results indicate that the SVM-based model yielded the optimal performance, achieving 81.6% accuracy, maintaining a balance between the experimental and control groups, with sensitivity and specificity of 81.4% and 81.9%, respectively. Additionally, integration of data from all physiological signals yielded the best results, suggesting that each modality captures unique aspects of ADHD. Conclusions This study underscores the potential of physiological signals as valuable diagnostic indicators of adult ADHD. For the first time, to the best of our knowledge, our findings demonstrate that multimodal physiological data collected via wearable devices can complement traditional diagnostic approaches. Further research is warranted to explore the clinical applications and long-term implications of utilizing physiological markers in ADHD diagnosis and management.

Electrodermal activity (EDA) is a widely used psychophysiological measurement in laboratory-based studies. In recent times, these measurements have seen a transfer from the laboratory to wearable devices due to the simplicity of EDA measurement as well as modern electronics. However, proper conditions for EDA measurement are recommended once wearable devices are used, and the ambient conditions may influence such measurements. It is not completely known how different types of ambient noise impact EDA measurement and how this translates to wearable EDA measurement. Therefore, this study explored the effects of various noise disturbances on the generation of EDA responses using a system for the simultaneous recording of all measures of EDA, i.e., skin conductance responses (SCRs), skin susceptance responses (SSRs), and skin potential responses (SPRs), at the same skin site. The SCRs, SSRs, and SPRs due to five types of noise stimuli at different sound pressure levels (70, 75, 80, 85, and 90 dB) were measured from 40 participants. The obtained results showed that EDA responses were generated at all levels and that the EDA response magnitudes were significantly (p < 0.001) influenced by the increasing noise levels. Different types of environmental noise may elicit EDA responses and influence wearable recordings outside the laboratory, where such noises are more likely than in standardized laboratory tests. Depending on the application, it is recommended to prevent these types of unwanted variation, presenting a challenge for the quality of wearable EDA measurement in real-world conditions. Future developments to shorten the quality gap between standardized laboratory-based and wearable EDA measurements may include adding microphone sensors and algorithms to detect, classify, and process the noise-related EDA. [ABSTRACT FROM AUTHOR]

This intensive longitudinal study examined Finnish technical university teachers’ (N = 22) self-reported emotions and electrodermal activity during teaching-related events (teaching, tutoring, planning, assessing). Emotions were examined in the context of control-value theory (Pekrun, R. 2006. “The Control-Value Theory of Achievement Emotions: Assumptions, Corollaries and Implications for Educational Research and Practice.” Educational Psychology Review 18 (4): 315–41. https://doi.org/10.1007/s10648-006-9029-9). An experience sampling method with event-contingent sampling was applied via a smartphone application for a measurement period of two weeks. Participants were also equipped with a smart ring biosensor that recorded their electrodermal activity (EDA, an indicator of physiological arousal). Results indicated that teaching-related events led to predominantly positive prospective and retrospective emotions. Interactive events, such as teaching and tutoring, were especially effective in generating positive outcomes and activating emotions. Results showed that that teaching-related events had higher EDA levels than typical work hours. In addition, higher within-teacher EDA levels during teaching-related events slightly increased the likelihood of reporting positive emotional valence after teaching. Further, results indicated that teacher-student interaction (teaching and tutoring events) and higher EDA during, and emotional activity before, teaching-related events increased the likelihood of activating emotions after teaching. The results can be generalized with reservations due to the small number of participants. [ABSTRACT FROM AUTHOR]

The aim of the present study was to evaluate the interaction of cognitive reserve (CR) and state anxiety in adrenocortical and electrodermal responses. Thirty-nine healthy, middle-aged men completed the State–Trait Anxiety Inventory and Escala de Reserva Cognitiva (Cognitive Reserve Scale). Following this, they performed a cognitively demanding task adapted from the Trier Social Stress Test. Electrical skin conductance level and cortisol concentrations were recorded during the task. These measures were used as indicators of stress response. Our results seem to indicate that CR has a protective effect against cortisol responses in stressful situations. This effect was observed in participants who showed high CR and high state anxiety. At the same time, CR showed a positive correlation with "recovery to baseline conductance level" after the occurrence of stressful events. As a whole, these results suggest that having high CR could protect against the development of allostatic load. The regulatory system of physiological and endocrine activity would be more efficient in individuals with high scores in CR, thus avoiding the development of allostatic load. [ABSTRACT FROM AUTHOR]