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Context: Anterior cruciate ligament (ACL) injuries, prevalent in athletic contexts have profound physical and psychological impacts. Despite extensive research on the physiological aspects of ACL recovery, the psychological dimensions of this process have gained increased attention. This scoping review delves into the intricate landscape of psychological factors influencing ACL rehabilitation. Design: Scoping review. Methods: A literature search across multiple databases was conducted to identify relevant published studies that provide insight into the psychological aspects of ACL recovery. This search spanned various study designs, enabling a nuanced understanding of the psychological intricacies surrounding ACL recovery. Overall, a total of 1830 unique articles were screened, of which 66 were included in this review. Our findings are further contextualized through alignment with insights from prior reviews on similar themes. Through a comprehensive analysis of diverse literature, we explore 3 key themes: psychological challenges, current rehabilitation programs, and the integration of psychological support. Results: Psychological challenges emerged as a pervasive aspect of ACL rehabilitation, encompassing fear, anxiety, motivation, and depression. The nuanced emotional responses, particularly the fear of reinjury, impact treatment adherence and overall well-being. Contemporary rehabilitation programs revealed inconsistencies in incorporating psychological support, emphasizing the need for standardized, multidisciplinary approaches. The alignment with prior reviews in the literature reinforced the importance of psychological traits, such as knee self-efficacy, in predicting positive outcomes. Conclusion: This scoping review provides a comprehensive overview of psychological factors within ACL rehabilitation, highlighting the importance of tailored interventions and standardized approaches. The integration of multidisciplinary expertise emerges as crucial for optimizing patient outcomes. Our findings not only contribute to a nuanced understanding of psychological nuances in ACL rehabilitation but also offer valuable implications for clinical practice and policy development. [ABSTRACT FROM AUTHOR]

Workplace procrastination is a prevalent phenomenon that significantly impacts employee productivity and organizational competitiveness. Drawing on cognitive–motivational–relational theory, this study adopts an emotional perspective to investigate how and when job characteristics (i.e. hindrance job demands, challenge job demands and job resources) impact employees' workplace procrastination in distinct ways. We suggest that both hindrance and challenge demands may evoke fear of tasks, eliciting an action tendency of escape and avoidance, thus indirectly leading to procrastination. Notably, challenge demands may exhibit a dual effect by simultaneously enhancing interest in tasks with an action tendency of exploration, thus negatively and indirectly influencing procrastination. Job resources may generate joy about tasks, fostering an action tendency of free activation, thereby indirectly reducing procrastination. We further investigate how psychological capital, which largely shapes employees' appraisal of job characteristics, may alter the above relationships. We conducted two studies to examine our hypotheses and delve into the potential reversed relationships between job characteristics and procrastination. Theoretical and practical implications are discussed. [ABSTRACT FROM AUTHOR]

Anomalous aortic origin of a coronary artery (AAOCA) is associated with sudden death in the young. Risk stratification and management decision-making remain challenging. Data addressing post-diagnosis perceptions of exercise behavior and safety are lacking. We aimed to determine how AAOCA affects exercise behaviors, safety perceptions, and emotional well-being of patients/parents. Qualitative and quantitative analysis of AAOCA patient-/parent-specific survey was conducted to examine exercise frequency/restrictions, perceived safety of competitive/recreational exercise, and psychosocial well-being. Subgroups stratified by AAOCA subtype, surgical intervention, and physician-driven restrictions were compared using chi-squared and Fisher's exact tests. Cohen's kappa determined agreement in parent/child responses. AAOCA subtypes included 13 (24%) left AAOCA, 36 (67%) right AAOCA, and 5 (9%) other/unknown. Of 54 parents and 41 paired child responses, 22% of patients were physician-restricted from exercise. Parents imposed restrictions on competitive/recreational exercise 34%/26% of the time, respectively. Children without physician restrictions still self-restricted exercise 35% of the time. Parents reported feeling their child was unsafe exercising 61% competitively and 33% recreationally. Twenty-two percent of children reported feeling unsafe exercising, with good agreement to parental perceptions of competitive exercise safety (kappa = 0.779, p < 0.001). One-third of parents and children reported feeling sad, angry, or lonely, and about half reported feeling different. Importantly, 47% of children desired to exercise more. No difference was seen across restriction status, AAOCA subtype, or surgical management strategy. Conclusion: There are different perceptions of exercise behavior and safety following AAOCA evaluation, regardless of risk category or management strategy, impacting their well-being. These unmet needs should be at the forefront of care. What Is Known: • AAOCA is one of the leading causes of sudden cardiac death in the young. • Exercise restriction varies according to AAOCA subtype and its perceived risk of inducing myocardial ischemia. What Is New: • There are different perceptions of exercise behavior and safety in patients and parents following a diagnosis of AAOCA, impacting their well-being. • Risk category or management strategy has no effect in patients' and parents' perception of exercise safety. • These unmet needs in this population should be at the forefront of care. [ABSTRACT FROM AUTHOR]

This study investigates the effects of humanoid robot appearance, emotional expression, and interaction skills on the uncanny valley phenomenon among university students using the social humanoid robot (SHR) Ameca. Two fundamental studies were conducted within a university setting: Study 1 assessed student expectations of SHRs in a hallway environment, emphasizing the need for robots to integrate seamlessly and engage effectively in social interactions; Study 2 compared the humanlikeness of three humanoid robots, ROMAN, ROBIN, and EMAH (employing the EMAH robotic system implemented on Ameca). The initial findings from corridor interactions highlighted a diverse range of human responses, from engagement and curiosity to indifference and unease. Additionally, the online survey revealed significant insights into expected non-verbal communication skills, continuous learning, and comfort levels during hallway conversations with robots. Notably, certain humanoid robots evoked stronger emotional reactions, hinting at varying degrees of humanlikeness and the influence of interaction quality. The EMAH system was frequently ranked as most humanlike before the study, while post-study perceptions indicated a shift, with EMAH and ROMAN showing significant changes in perceived humanlikeness, suggesting a re-evaluation by participants influenced by their interactive experiences. This research advances our understanding of the uncanny valley phenomenon and the role of humanoid design in enhancing human–robot interaction, marking the first direct comparison between the most advanced, humanlike research robots. [ABSTRACT FROM AUTHOR]

Although video affective content analysis has great potential in many applications, it has not been thoroughly studied due to limited datasets. In this article, we construct a large-scale video affective dataset with danmu (VAD). It consists of 19,267 elaborately segmented video clips from user-generated videos. The VAD dataset is annotated by the crowdsourcing platform with discrete valence, arousal, and primary emotions, as well as the comparison of valence and arousal between two consecutive video clips. Unlike previous datasets, including only video clips, our proposed dataset also provides danmu, which is the real-time comment from users as they watch a video. Danmu provides extra information for video affective content analysis. As a preliminary assessment of the usability of our dataset, an analysis of inter-annotator consistency for each label is conducted using weighted Fleiss’ Kappa, regular Fleiss’ Kappa, intraclass correlation coefficient, and percent consensus. Besides, we also perform a statistical analysis of labels and danmu. Finally, video affective content analysis is conducted on our dataset and three typical methods (i.e., TFN, MulT, and MISA) are leveraged to provide benchmarks. We also demonstrate that danmu can significantly improve the performance of the video affective content analysis task on some labels. Our dataset is available for research purposes. [ABSTRACT FROM AUTHOR]

This exploratory laboratory study analyzes emotional responses to two types of populist strategies on social media platforms. We focus on emotional responses to content expressing ordinariness (on Instagram) and victimhood (on TikTok), where the content creator is a right-wing populist leader who is unfavorably perceived by the respondents in the study. Thus, the study critically tests the effectiveness of de-demonization strategies used by populist leaders to diversify the electorate. The research employs a combination of facial expressions analysis and two self-report measures of emotions to investigate the emotional responses elicited by populist strategies in individuals belonging to an out-group. Additionally, we examine the interrelation between psychophysiological measures and self-reported emotions. In doing so, the study makes a methodological contribution by advancing our understanding of emotional response processes and the methodologies employed to measure emotional responses. The results reveal positive and negative emotional responses, challenging the prevailing emphasis on negative emotions in response to out-group communication. However, the facial expressions and the self-reported emotions do not correlate. Our interpretation underscores the role of cognitive reasoning processes in differentiating emotional responses to political out-group social media content. [ABSTRACT FROM AUTHOR]

Effective collaboration within teams relies significantly on emotion regulation, a process vital for managing and navigating emotional responses. Various methods have been employed to measure emotional responses in team contexts, including self-report questionnaires, behavioral coding, and physiological measures. This review paper aims to summarize studies conducted in teamwork contexts that measured team members' emotional responses, with a particular focus on the methods used. The findings from these studies can lead to identification of emotion regulation strategies and can lead to effective interventions to improve team performance in future. The core question guiding this review is: What are effective measures in capturing individuals' emotional responses in team dynamics? Using a scoping review, the study aims to answer three research questions (RQs): 1: What was the distribution over time of the studies that examined team members' emotional responses and/or regulation of emotions in team dynamic? 2: What type(s) of data were collected, and what are the theories used in these studies? 3: What are the advantages and challenges of each type of measurement on emotional responses in team dynamics? The synthesis of the findings suggests that multimodal data, combining various measures such as physiological data, observations, and self-reports, offer a promising approach to capturing emotions in teamwork contexts. Furthermore, combining multimodal data can benefit capturing individual and inter-personal regulation, including self-, co-, and social emotion regulation in teamwork. This paper highlights the importance of integrating multiple measurement methods and provides insights into the advantages and challenges associated with each approach. [ABSTRACT FROM AUTHOR]

Anthropomorphized robots are increasingly integrated into human social life, playing vital roles across various fields. This study aimed to elucidate the neural dynamics underlying users' perceptual and emotional responses to robots with varying levels of anthropomorphism. We investigated event-related potentials (ERPs) and event-related spectral perturbations (ERSPs) elicited while participants viewed, perceived, and rated the affection of robots with low (L-AR), medium (M-AR), and high (H-AR) levels of anthropomorphism. EEG data were recorded from 42 participants. Results revealed that H-AR induced a more negative N1 and increased frontal theta power, but decreased P2 in early time windows. Conversely, M-AR and L-AR elicited larger P2 compared to H-AR. In later time windows, M-AR generated greater late positive potential (LPP) and enhanced parietal-occipital theta oscillations than H-AR and L-AR. These findings suggest distinct neural processing phases: early feature detection and selective attention allocation, followed by later affective appraisal. Early detection of facial form and animacy, with P2 reflecting higher-order visual processing, appeared to correlate with anthropomorphism levels. This research advances the understanding of emotional processing in anthropomorphic robot design and provides valuable insights for robot designers and manufacturers regarding emotional and feature design, evaluation, and promotion of anthropomorphic robots. [ABSTRACT FROM AUTHOR]

Drawing upon evolutionary explanations of emotions and social appraisal theory, the present study investigated the emotional and behavioral responses exhibited by residents of Varosha during their visits to this specific dark tourism destination located in Famagusta, North Cyprus. To accomplish this objective, a qualitative research design was employed, involving interviews conducted with a select group of these residents. For data collection, a semi-structured questionnaire was developed. Utilizing a grounded theory approach, the researchers proposed a framework that delineates four sequential stages encompassing background emotions, pre-visit emotions, emotions experienced during the visit, and subsequent behavioral outcomes. Furthermore, various external factors prevalent within society that influence the emotional and behavioral outcomes of the residents were also identified. The findings of this study demonstrated that dark tourism sites possess the potential to symbolize notions of peace, hope, and interdependent relationships, and serve as a vehicle for educating future generations about past acts of inhumanity. [ABSTRACT FROM AUTHOR]

This study compared two virtual reality (VR) interaction modes and assessed differences in characteristics, namely usability, emotional responses, flow experience, technology acceptance, activity effectiveness, preference, and satisfaction, aiming to gain insights for proposing design suggestions. The two types of VR interaction examined were freeform creativity, which enabled users to autonomously explore and create using the Gravity Sketch drawing program, and goal-directed training, which involved structured task completion by using a VR dumbbell exercise program developed with Unity. This study involved 33 participants and revealed three key findings. First, both VR modes exhibited excellent results in terms of flow experience, technology acceptance, preference, and satisfaction and evoked strong positive emotions. They also demonstrated shared VR advantages, including overcoming screen constraints and facilitating three-dimensional spatial activities. Second, compared with goal-directed training, freeform creativity elicited greater levels of pleasure, evoked more intense emotional responses, and demonstrated superior performance across related indicators. Third, in terms of usability, goal-directed training surpassed freeform creativity, particularly in overall responsiveness, simplicity, and clarity of information presentation, and learnability, underscoring the importance of enhancing usability for complex tasks in VR application design. These findings offer valuable insights for crafting more appealing, practical, and user-friendly VR systems in the future. [ABSTRACT FROM AUTHOR]

Abstract Pu'er crude tea (PCT), the initial raw material for making Pu'er tea, is favored because of unique flavor and health effects. Emotional response is helpful to explain consumers’ choice of different flavors of tea. This study aims to clarify the key floral volatiles of PCT and their emotional impact on people. Twenty‐nine compounds were identified as the key volatiles from 237 volatiles, which formed the flowery aroma of PCT. Linalool, geraniol, nonanal, and methyl salicylate were more abundant in the PCT, they evoked the top five emotions (mild, wild, aggressive, tame, bored). Methyl salicylate contributed most to the wild emotion in the two mixed samples (B10 and B14), and it may contribute positively to the health effects of tea, such as refreshing and anti‐inflammatory. This study provided a preliminary research idea for exploring the relationship between tea aroma and human emotions and its potential role in human health.

Electromyography (EMG), galvanic skin responses (GSR), and electrocardiogram (ECG) tools have been used to investigate emotional responses to marketing stimuli, encompassing advertisements, product packaging, and brand logos. However, despite the widespread application of EMG, GSR, and ECG tools in neuromarketing research, a comprehensive synthesis of their collective impact remains conspicuously absent. Addressing this gap is the primary goal of the present review paper, which systematically scrutinizes recent studies employing EMG, GSR, and ECG to assess emotional responses to marketing stimuli. Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, relevant articles were meticulously extracted from the Scopus database, spanning the years 2009 to 2022, including twenty articles for detailed analysis. The outcomes of this review underscore the unique insights offered by these tools into emotional reactions, emphasizing that their collective utilization can afford a more comprehensive understanding of these intricate processes. This propels advancements in comprehending the pivotal role of emotions in consumer behavior and serves as a guidepost for future research directions in this burgeoning field. Ultimately, this paper aims to furnish a broad understanding and detailed insights into the current trends within neuromarketing research, specifically employing EMG, GSR, and ECG tools.

Neuromarketing is an emerging interdisciplinary field that merges neuroscience with marketing to explore the cognitive processes driving consumer behavior. By employing neuroimaging techniques, such as fMRI, EEG, and eye-tracking, neuromarketing offers deeper insights into how consumers respond to marketing stimuli at a subconscious level. This paper aims to provide a comprehensive analysis of neuromarketing's role in understanding consumer choices, focusing on how cognitive and emotional responses influence decision-making. Traditional marketing approaches often rely on consumer self-reports, which may not capture the full complexity of human behavior. Neuromarketing bridges this gap by revealing unconscious preferences and biases that shape purchasing decisions. This paper examines key neuromarketing tools, methodologies, and their applications in diverse industries, such as retail, advertising, and branding. Additionally, it addresses the ethical concerns surrounding the use of brain data for marketing purposes, particularly issues of privacy and consumer manipulation. The findings from various studies illustrate how marketers can leverage cognitive insights to create more effective campaigns that resonate emotionally with target audiences. By understanding how consumers process information and make choices, businesses can optimize their strategies to align better with consumer needs and preferences. However, the paper also highlights the limitations of neuromarketing, including the high cost of technology and the need for further research to refine its techniques. Ultimately, neuromarketing presents a valuable opportunity for marketers to enhance their understanding of consumer behavior, but it must be employed responsibly and ethically. [ABSTRACT FROM AUTHOR]

Recent research has focused on the effectiveness of Virtual Reality (VR) in games as a more immersive method of interaction. However, there is a lack of robust analysis of the physiological effects between VR and flatscreen (FS) gaming. This paper introduces the first systematic comparison and analysis of emotional and physiological responses to commercially available games in VR and FS environments. To elicit these responses, we first selected four games through a pilot study of 6 participants to cover all four quadrants of the valence-arousal space. Using these games, we recorded the physiological activity, including Blood Volume Pulse and Electrodermal Activity, and self-reported emotions of 33 participants in a user study. Our data analysis revealed that VR gaming elicited more pronounced emotions, higher arousal, increased cognitive load and stress, and lower dominance than FS gaming. The Virtual Reality and Flat Screen (VRFS) dataset, containing over 15 hours of multimodal data comparing FS and VR gaming across different games, is also made publicly available for research purposes. Our analysis provides valuable insights for further investigations into the physiological and emotional effects of VR and FS gaming. [ABSTRACT FROM AUTHOR]

Emotion recognition in conversation (ERC) and emotional response generation (ERG) are two important NLP tasks. ERC aims to detect the utterance-level emotion from a dialogue, while ERG focuses on expressing a desired emotion. Essentially, ERC is a classification task, with its input and output domains being the utterance text and emotion labels, respectively. On the other hand, ERG is a generation task with its input and output domains being the opposite. These two tasks are highly related, but surprisingly, they are addressed independently without making use of their duality in prior works. Therefore, in this article, we propose to solve these two tasks in a dual learning framework. Our contributions are fourfold: (1) We propose a dual learning framework for ERC and ERG. (2) Within the proposed framework, two models can be trained jointly, so that the duality between them can be utilised. (3) Instead of a symmetric framework that deals with two tasks of the same data domain, we propose a dual learning framework that performs on a pair of asymmetric input and output spaces, i.e., the natural language space and the emotion labels. (4) Experiments are conducted on benchmark datasets to demonstrate the effectiveness of our framework. [ABSTRACT FROM AUTHOR]

The view of embodied emotion believes that emotions are the emotions of the body. While emotion-specific patterns of self-reported bodily sensation have been previously reported, the physiological bodily representation across emotions remains to be addressed. The present study aimed to investigate the effectiveness of multi-site bodily electrodermal representations of emotions. A multi-channel electrodermal measurement device was designed to record electrodermal activities from nine body sites (neck, back, chest, bilateral abdomen, bilateral wrist, and bilateral ankle) from thirty-six college students (all male), while they were presented with a series of emotional pictures. Using the integral skin conductance response feature and a random forest classification method, the classification of high and low arousal levels achieved an average classification accuracy of 80.4 ± 8.1%, and the classification of positive, neutral, and negative states reached an average classification accuracy of 76.4 ± 10.2%. The classification models for arousal and valence were found to rely on distinct bodily representations. Meanwhile, the classification results of multi-site measurement were significantly better than single-site results. Our findings for the first time illustrate the bodily electrodermal representations of emotion and suggest the feasibility of affective computing using bodily electrodermal signals. [ABSTRACT FROM AUTHOR]

Emotion causes constitute a pivotal component in the comprehension of emotional conversations. Recently, a new task named Causal Emotion Entailment (CEE) has been proposed to identify the causal utterances for the target emotional utterance in a conversation. Although researchers have achieved some progress in solving this problem, they failed to adequately incorporate speaker characteristics and overlooked the effects of temporal relations in conversation structures. To fill such a research gap to some extent, we propose a novel causal emotion entailment framework, namely MPEG (Multi-Perspective Enhanced Graph attention network). The training of MPEG consists of three stages. First, we utilize a speaker-aware pre-trained model and two attention mechanisms to obtain the utterance representations that incorporate local contexts as well as the speaker and emotional information. Then, these representations are fed into a graph attention network to model the conversation structures and emotional dynamics from both local and global perspectives. Finally, a fully-connected network is implemented to predict the relationships between emotional utterances and causal utterances. Experimental results show that MPEG achieves state-of-the-art performance. [ABSTRACT FROM AUTHOR]

Introduction: Social media platforms such as Twitter and Weibo facilitate both positive and negative communication, including cyberbullying. Empirical evidence has revealed that cyberbullying increases when public crises occur, that such behavior is gendered, and that social media user account verification may deter it. However, the association of gender and verification status with cyberbullying is underexplored. This study aims to address this gap by examining how Weibo users' gender, verification status, and expression of affect and anger in posts influence cyberbullying attitudes. Specifically, it investigates how these factors differ between posts pro- and anti-cyberbullying of COVID-19 cases during the pandemic. Methods: This study utilized social role theory, the Barlett and Gentile Cyberbullying Model, and general strain theory as theoretical frameworks. We applied text classification techniques to identify pro-cyberbullying and anticyberbullying posts on Weibo. Subsequently, we used a standardized mean difference method to compare the emotional content of these posts. Our analysis focused on the prevalence of affective and anger-related expressions, particularly examining variations across gender and verification status of the users. Results: Our text classification identified distinct pro-cyberbullying and anticyberbullying posts. The standardized mean difference analysis revealed that pro-cyberbullying posts contained significantly more emotional content compared to anti-cyberbullying posts. Further, within the pro-cyberbullying category, posts by verified female users exhibited a higher frequency of angerrelated words than those by other users. Discussion: The findings from this study can enhance researchers' algorithms for identifying cyberbullying attitudes, refine the characterization of cyberbullying behavior using real-world social media data through the integration of the mentioned theories, and help government bodies improve their cyberbullying monitoring especially in the context of public health crises. [ABSTRACT FROM AUTHOR]

BackgroundMedical security work for the 2022 Beijing Winter Olympic and Paralympics faced enormous challenges under COVID-19. This study aimed to investigate the mental status of those medical team members to provide a reference for scientifically implementing medical security services for large-scale events.MethodsIn this prospective cohort study, the Patient Health Questionnaire-9, Self-rating Anxiety Scale, General Self-Efficacy Scale, and Psychological Questionnaire for Emergent Events of Public Health (PQEEPH) were administered to 145 members of the medical team. A generalized mixed linear model was used to analyze the impact of work duration, position, on/off rotation, and gender on psychological status.ResultsWork duration significantly impacted depression, anxiety, self-efficacy, and all dimensions of PQEEPH. Women scored higher than men in the PQEEPH dimensions of depression, neurasthenia, fear, and total score. Working status affected the dimensions of depression, neurasthenia, and total score. Deterioration in emotional state became apparent in the fourth week and recovered 1 week after the task concluded, while self-efficacy decreased from beginning to end.ConclusionAll the medical team members experienced emotional deterioration and decreased self-efficacy in medical security tasks. To maintain a medical team’s psychological wellbeing during large-scale activities, rotation times should be set reasonably, and adequate mental health services should be provided.

Abstract The relationship between self-esteem and emotional reactions to receiving comfort has been extensively studied in social and personality psychology, but the results have been inconsistent. Therefore, this study investigated the association between emotional reactions to receiving comfort from friends and self-esteem by examining whether an instability in self-esteem mediates the association between self-esteem levels and comfort effectiveness. Japanese university students (N = 115) read a vignette involving comfort and completed a questionnaire evaluating the emotions they felt when a friend offered comfort. They also completed a daily measure of state self-esteem for 7 days, the perceived self-Esteem instability measure (P-SEI), and the Rosenberg self-esteem scale (RSES). Results were derived using multiple regression analysis. The interaction between P-SEI and RSES predicted gratitude when gender, friendship intimacy, seriousness, and controllability of the scenario were controlled for. The interaction between state self-esteem and instability was not significant. People with stable low self-esteem felt less grateful when comforted than those with unstable self-esteem, but they showed high gratitude and low hostility when comforted by a close friend. Although participants with stable low self-esteem were less impacted by comforted, the comfort provided by close friends induced positive emotions. This study offers a more comprehensive understanding of the correlations between self-esteem and the effectiveness of comfort by concurrently employing different self-esteem measurement tools and revealing the importance of the level and stability of self-esteem.

Abstract Background This research delves into the role of stereotypes and emotional prejudice in behavioral intentions, particularly towards individuals with suicidal tendencies. The study extends the cognitive-affective-behavioral process model, identifying pathways that negative stereotypes use to impact emotional responses and behavioral intentions. Methods A cross-sectional online survey was conducted in South Korea, utilizing the largest Korean online panel (1,623,938 users) to recruit 552 eligible participants (49.1% male, 50.9% female) aged 20 and above with online access and no history of suicide attempts. The survey assessed negative stereotypes, prejudices, and behavioral intentions related to suicidal thoughts, employing specific measurements. Results The findings established the correlation between negative stereotypes and both stigmatized emotional responses and discriminatory intentions. The study uniquely demonstrated that emotional responses act as a bridge between negative stereotypes and behavioral intentions towards suicidal individuals. These findings carry profound implications for health psychology, emphasizing the necessity of modifying attitudes to reduce suicide stigma. It was observed that stereotypical perceptions fuel negative emotions, which in turn provoke various behavioral intentions. Conclusions The study enhances our understanding of the influential role emotional reactions can have in shaping attitudes. It points towards the potential that addressing emotions holds in the stigma process, enabling people to shift their attitudes about stigmatized individuals, thus establishing intervention opportunities for stigma reduction in health psychology.

The relationship between self-esteem and emotional reactions to receiving comfort has been extensively studied in social and personality psychology, but the results have been inconsistent. Therefore, this study investigated the association between emotional reactions to receiving comfort from friends and self-esteem by examining whether an instability in self-esteem mediates the association between self-esteem levels and comfort effectiveness. Japanese university students (N = 115) read a vignette involving comfort and completed a questionnaire evaluating the emotions they felt when a friend offered comfort. They also completed a daily measure of state self-esteem for 7 days, the perceived self-Esteem instability measure (P-SEI), and the Rosenberg self-esteem scale (RSES). Results were derived using multiple regression analysis. The interaction between P-SEI and RSES predicted gratitude when gender, friendship intimacy, seriousness, and controllability of the scenario were controlled for. The interaction between state self-esteem and instability was not significant. People with stable low self-esteem felt less grateful when comforted than those with unstable self-esteem, but they showed high gratitude and low hostility when comforted by a close friend. Although participants with stable low self-esteem were less impacted by comforted, the comfort provided by close friends induced positive emotions. This study offers a more comprehensive understanding of the correlations between self-esteem and the effectiveness of comfort by concurrently employing different self-esteem measurement tools and revealing the importance of the level and stability of self-esteem. [ABSTRACT FROM AUTHOR]

Most NPCs (non-player characters) in the game tend to repeat programmed lines or actions, which can be boring for players who want realistic progression. This paper focuses on the study of intelligent NPCs in games that actively display various emotions and reactions through interactions with players. As a research method, ChatGPT API and customized prompts were used to improve NPC personality and behavior. To enable NPCs to actively perform their given roles in the game, the ChatGPT API and prompts were used to set personality, tone of voice, and action radius, and a web-based chatbot in the form of a game template was implemented using these. Experiment result, the NPC confirmed the possibility of expanding dynamic content by providing quests through various conversations. NPC's emotional changes were reflected in the image in real time, increasing player immersion. When this intelligent NPC is applied to actual games, game quality and immersion are expected to improve. [ABSTRACT FROM AUTHOR]

This study investigates and compares the effects of both subjective and objective soundscapes on visitors' emotional responses and stickiness (i.e. their intention to stay) toward an attraction. Following the soundwalk approach, this study utilizes sound level meters and questionnaires to measure the objective and subjective soundscapes, respectively. The results indicate that subjective soundscape encompasses three dimensions, namely pleasant, unpleasant, and uneventful, which influence visitor stickiness. Moreover, both positive and negative emotions mediate the effects of subjective soundscape on visitors' stickiness. The findings provide insights into the evaluation of soundscapes in visitor attractions and guide their design and management. [ABSTRACT FROM AUTHOR]

Electromyography (EMG), galvanic skin responses (GSR), and electrocardiogram (ECG) tools have been used to investigate emotional responses to marketing stimuli, encompassing advertisements, product packaging, and brand logos. However, despite the widespread application of EMG, GSR, and ECG tools in neuromarketing research, a comprehensive synthesis of their collective impact remains conspicuously absent. Addressing this gap is the primary goal of the present review paper, which systematically scrutinizes recent studies employing EMG, GSR, and ECG to assess emotional responses to marketing stimuli. Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, relevant articles were meticulously extracted from the Scopus database, spanning the years 2009 to 2022, including twenty articles for detailed analysis. The outcomes of this review underscore the unique insights offered by these tools into emotional reactions, emphasizing that their collective utilization can afford a more comprehensive understanding of these intricate processes. This propels advancements in comprehending the pivotal role of emotions in consumer behavior and serves as a guidepost for future research directions in this burgeoning field. Ultimately, this paper aims to furnish a broad understanding and detailed insights into the current trends within neuromarketing research, specifically employing EMG, GSR, and ECG tools. [ABSTRACT FROM AUTHOR]

Mothers who use substances during pregnancy and postpartum may have altered maternal behavior towards their infants, which can have negative consequences on infant social-emotional development. Since maternal substance use has been associated with difficulties in recognizing and responding to infant emotional expressions, investigating mothers' subjective responses to emotional infant stimuli may provide insight into the neural and psychological processes underlying these differences in maternal behavior. In this study, 39 mothers who used substances during the perinatal period and 42 mothers who did not underwent functional magnetic resonance imaging while viewing infant faces and hearing infant cries. Afterwards, they rated the emotional intensity they thought each infant felt ('think'-rating), and how intensely they felt in response to each infant stimulus ('feel'-rating). Mothers who used substances had lower 'feel'-ratings of infant stimuli compared to mothers who did not. Brain regions implicated in affective processing (e.g., insula, inferior frontal gyrus) were less active in response to infant stimuli, and activity in these brain regions statistically predicted maternal substance-use status. Interestingly, 'think'-ratings and activation in brain regions related to cognitive processing (e.g., medial prefrontal cortex) were comparable between the two groups of mothers. Taken together, these results suggest specific neural and psychological processes related to emotional responsivity to infant stimuli may reflect differences in maternal affective processing and may contribute to differences in maternal behavior in mothers who use substances compared to mothers who do not. The findings suggest potential neural targets for increasing maternal emotional responsivity and improving child outcomes. [ABSTRACT FROM AUTHOR]

There is an increasing research interest in emotional responses to climate change and their role in climate action and psycho-social impacts of climate change. At the same time, emotional experience of climate change is multidimensional and influenced by a variety of factors, including the local cultural context. Here, we contribute to the scientific debate about this topic with original qualitycontrolled data from the general populations in Norway (N = 491) and Ireland (N = 485). We investigate the cross-cultural validity and the nomological span of eight distinct emotional responses to climate change - climate anger, climate contempt, climate enthusiasm, climate powerlessness, climate guilt, climate isolation, climate anxiety, and climate sorrow - measured using the recently introduced Inventory of Climate Emotions. We first validate the 8-factor structure of the Norwegian and English language versions of the ICE. Subsequently, we demonstrate a high degree of cross-cultural measurement invariance for these eight climate emotions. Finally, we explore the relationships between these emotional responses and a range of theoretically relevant variables. In this final step, we show that climate emotions are differentially linked to climate change perceptions, support for mitigation policies, socio-demographic factors, feelings of loneliness and alienation, environmental activism, and the willingness to prioritize the natural environment over one's immediate selfinterests. Some of these links are also differentiated by the cultural context. This research presents further evidence for the structural, cross-cultural, and concurrent validity of climate emotions as postulated in the ICE framework. Moreover, it provides tools in the form of validated Norwegian and English language versions of the ICE, the complete R code for the validation analysis, as well as an informed basis for cross-cultural research on emotional responses to climate change. [ABSTRACT FROM AUTHOR]

Adaptive learning technologies often provide students with immediate feedback on task performance. This feedback can elicit various emotional responses, which, in turn, influence learning. Most recent studies capture these emotions by single data streams, contradicting the multi-componential nature of emotion. Therefore, this study investigated 32 university students solving mathematical problems using an adaptive learning technology. Students received immediate feedback on every step in the solution process, after which their physiological, experiential and behavioral responses to this feedback were recorded. Physiological arousal was measured by electrodermal activity, valence was measured by self-reports (experiential), and emotion types were measured by observations of facial expressions (behavioral). Results showed more peaks in electrodermal activity after feedback than was expected based on chance. These responses were comparable in strength after feedback on failure and success. Students’ experiential responses conveyed mostly positive valence after feedback on success and mostly negative valence after feedback on failure. Behavioral observations showed more negative than positive emotion types after feedback on failure and more positive than negative emotion types after feedback on success. These results show that physiological arousal is a valuable objective indicator of emotional responses after immediate feedback but should be accompanied by other data streams in order to understand students’ emotional responses. Both valence and emotion types can be used for this purpose. These outcomes pave the way for designing adaptive learning technologies that take students’ emotions into account. [ABSTRACT FROM AUTHOR]

This exploratory laboratory study analyzes emotional responses to two types of populist strategies on social media platforms. We focus on emotional responses to content expressing ordinariness (on Instagram) and victimhood (on TikTok), where the content creator is a right-wing populist leader who is unfavorably perceived by the respondents in the study. Thus, the study critically tests the effectiveness of de-demonization strategies used by populist leaders to diversify the electorate. The research employs a combination of facial expressions analysis and two self-report measures of emotions to investigate the emotional responses elicited by populist strategies in individuals belonging to an out-group. Additionally, we examine the interrelation between psychophysiological measures and self-reported emotions. In doing so, the study makes a methodological contribution by advancing our understanding of emotional response processes and the methodologies employed to measure emotional responses. The results reveal positive and negative emotional responses, challenging the prevailing emphasis on negative emotions in response to out-group communication. However, the facial expressions and the self-reported emotions do not correlate. Our interpretation underscores the role of cognitive reasoning processes in differentiating emotional responses to political out-group social media content.

Background: Mental illness in China has traditionally been attributed to physical factors and somatization tendencies, which seldom result in stigma. How has this perception changed after decades of social change? Methods: Based on the Chinese General Social Survey database in 2011, this study constructed a structural equation model to analyze the effects of causal attribution and emotional responses on social distance. The causal attributions include dangerousness, controllability, and responsibility. And the emotional responses encompass negative affect, traditional prejudice, treatment carryover, and exclusionary sentiments. In addition, higher scores indicating greater social distance, whereas a low score reflected stronger emotional responses or a greater degree of internal attribution. Results: The results reported a high level of social distance towards people with mental illness. These findings indicated that emotional responses have a direct impact on social distance. Specifically, when negative affect, traditional prejudice, and exclusionary sentiments increase by one standard deviation, the social distance decreases by 0.497, 0.178, and 0.073 standard deviation, respectively. Conversely, as the level of treatment carryover rises, social distance increases by 0.087. Meanwhile, the causal attribution only exerts a significant indirect effect on social distance by the function of emotional causal responses. Conclusion: The results indicated that the public attributes mental illnesses like depression primarily to psychological issues rather than somatic ones. It suggested widespread stereotypes and public stigma towards people with mental illness in China, as well as an arduous task in anti-stigma. In addition, a targeted way to address public stigma lies in changing the stereotype of people with mental illness.

In this study we explore the impact of multisensory stimuli in virtual reality on users’ emotional responses, addressing a knowledge gap in this rapidly evolving field. Utilizing a range of sensory inputs, including taste, haptics, and smell, in addition to audiovisual cues, this study aims to understand how different combinations of these stimuli affect the users’ emotional experience. Two immersive virtual experiences have been developed for this purpose. One included a scenario to evoke positive emotions through selectively chosen pleasant multisensory stimuli, validated in a focus group. The other sought the contrary: to trigger negative emotions by integrating selected combinations of unpleasant multisensory stimuli, also validated in the same focus group. Through a comparative analysis, our findings revealed significant differences in emotional responses between the groups exposed to positive and negative stimuli combinations. Results indicated that combinations involving haptics and taste were particularly effective in eliciting intense emotions using positive stimuli, but their impact was less significant with negative stimuli. This investigation suggests that a fully multisensory virtual environment integrating positive stimuli might lead to cognitive overload, reducing overall emotional responses. In contrast, environments with negative stimuli could enhance emotional engagement and be more likely to avoid cognitive overload. These findings have important implications for designing emotionally resonant and compelling virtual reality experiences. This research enhances the understanding of sensory integration in virtual reality and its effects on emotional engagement, offering valuable insights for developing more impactful virtual experiences.

Building a human-like dialogue system is a challenging task that requires effective use of context, common sense and personal information. In a conversation, the responder usually analyzes the emotion, intention, and common sense involved in the speaker’s sentence. Based on this analysis, the responder considers both the above-mentioned content and their personal information to formulate a response. Previous work in this area has only focused on one or some aspects, such as emotion, intention, common sense or persona, rather than considering all of them together. To address this issue, we propose a response generation framework called EFCP, which is based on empathy factors, common sense, and persona. This framework simulates a rich dialogue generation process that is rarely seen in previous work. In predicting the type of empathy factors a responder should adopt, we consider both the responder’s personal information and the conversation history. Our experiments show that this method effectively improves the accuracy of prediction. EFCP outperforms the baseline on a variety of automatic metrics and manual metrics, showing its potential for building more effective and human-like dialogue systems.

Exercise is good for health and well-being, yet people experience lapses when trying to adhere to exercise. Self-compassion may help people cope with exercise lapses. Most research on self-compassion and exercise has been conducted with women; men may also benefit from self-compassion. No research has examined whether gender-role schema influences responses to exercise lapses. The authors examined both male and female adult exercisers (N = 220) who reported their self-compassion, recalled an exercise lapse, their reactions to the lapse, and their self-identification of masculinity and femininity. After controlling for self-esteem, age, and lapse importance, self-compassion negatively related to emotional responses (p < .001), rumination (p < .001), extrinsic motivation (p = .004), and positively related to intrinsic motivation (p < .001). Masculinity moderated the relationships between self-compassion and amotivation (p = .006), and identified regulation (p = .01). Self-compassion may be an effective resource for exercisers, especially those who identify as highly masculine. [ABSTRACT FROM AUTHOR]

This study investigates the effects of humanoid robot appearance, emotional expression, and interaction skills on the uncanny valley phenomenon among university students using the social humanoid robot (SHR) Ameca. Two fundamental studies were conducted within a university setting: Study 1 assessed student expectations of SHRs in a hallway environment, emphasizing the need for robots to integrate seamlessly and engage effectively in social interactions; Study 2 compared the humanlikeness of three humanoid robots, ROMAN, ROBIN, and EMAH (employing the EMAH robotic system implemented on Ameca). The initial findings from corridor interactions highlighted a diverse range of human responses, from engagement and curiosity to indifference and unease. Additionally, the online survey revealed significant insights into expected non-verbal communication skills, continuous learning, and comfort levels during hallway conversations with robots. Notably, certain humanoid robots evoked stronger emotional reactions, hinting at varying degrees of humanlikeness and the influence of interaction quality. The EMAH system was frequently ranked as most humanlike before the study, while post-study perceptions indicated a shift, with EMAH and ROMAN showing significant changes in perceived humanlikeness, suggesting a re-evaluation by participants influenced by their interactive experiences. This research advances our understanding of the uncanny valley phenomenon and the role of humanoid design in enhancing human–robot interaction, marking the first direct comparison between the most advanced, humanlike research robots.

This study compared two virtual reality (VR) interaction modes and assessed differences in characteristics, namely usability, emotional responses, flow experience, technology acceptance, activity effectiveness, preference, and satisfaction, aiming to gain insights for proposing design suggestions. The two types of VR interaction examined were freeform creativity, which enabled users to autonomously explore and create using the Gravity Sketch drawing program, and goal-directed training, which involved structured task completion by using a VR dumbbell exercise program developed with Unity. This study involved 33 participants and revealed three key findings. First, both VR modes exhibited excellent results in terms of flow experience, technology acceptance, preference, and satisfaction and evoked strong positive emotions. They also demonstrated shared VR advantages, including overcoming screen constraints and facilitating three-dimensional spatial activities. Second, compared with goal-directed training, freeform creativity elicited greater levels of pleasure, evoked more intense emotional responses, and demonstrated superior performance across related indicators. Third, in terms of usability, goal-directed training surpassed freeform creativity, particularly in overall responsiveness, simplicity, and clarity of information presentation, and learnability, underscoring the importance of enhancing usability for complex tasks in VR application design. These findings offer valuable insights for crafting more appealing, practical, and user-friendly VR systems in the future.

There is an increasing research interest in emotional responses to climate change and their role in climate action and psycho-social impacts of climate change. At the same time, emotional experience of climate change is multidimensional and influenced by a variety of factors, including the local cultural context. Here, we contribute to the scientific debate about this topic with original quality-controlled data from the general populations in Norway (N = 491) and Ireland (N = 485). We investigate the cross-cultural validity and the nomological span of eight distinct emotional responses to climate change - climate anger, climate contempt, climate enthusiasm, climate powerlessness, climate guilt, climate isolation, climate anxiety, and climate sorrow - measured using the recently introduced Inventory of Climate Emotions. We first validate the 8-factor structure of the Norwegian and English language versions of the ICE. Subsequently, we demonstrate a high degree of cross-cultural measurement invariance for these eight climate emotions. Finally, we explore the relationships between these emotional responses and a range of theoretically relevant variables. In this final step, we show that climate emotions are differentially linked to climate change perceptions, support for mitigation policies, socio-demographic factors, feelings of loneliness and alienation, environmental activism, and the willingness to prioritize the natural environment over one’s immediate self-interests. Some of these links are also differentiated by the cultural context. This research presents further evidence for the structural, cross-cultural, and concurrent validity of climate emotions as postulated in the ICE framework. Moreover, it provides tools in the form of validated Norwegian and English language versions of the ICE, the complete R code for the validation analysis, as well as an informed basis for cross-cultural research on emotional responses to climate change.

Adaptive learning technologies often provide students with immediate feedback on task performance. This feedback can elicit various emotional responses, which, in turn, influence learning. Most recent studies capture these emotions by single data streams, contradicting the multi-componential nature of emotion. Therefore, this study investigated 32 university students solving mathematical problems using an adaptive learning technology. Students received immediate feedback on every step in the solution process, after which their physiological, experiential and behavioral responses to this feedback were recorded. Physiological arousal was measured by electrodermal activity, valence was measured by self-reports (experiential), and emotion types were measured by observations of facial expressions (behavioral). Results showed more peaks in electrodermal activity after feedback than was expected based on chance. These responses were comparable in strength after feedback on failure and success. Students’ experiential responses conveyed mostly positive valence after feedback on success and mostly negative valence after feedback on failure. Behavioral observations showed more negative than positive emotion types after feedback on failure and more positive than negative emotion types after feedback on success. These results show that physiological arousal is a valuable objective indicator of emotional responses after immediate feedback but should be accompanied by other data streams in order to understand students’ emotional responses. Both valence and emotion types can be used for this purpose. These outcomes pave the way for designing adaptive learning technologies that take students’ emotions into account.

Electroencephalogram (EEG) variability poses a great challenge to the affective brain-computer interface (aBCI) for practical applications. Most aBCI frameworks have been demonstrated successfully but deliberated on single-day data, which can be realistically susceptible to psychophysiological changes and further hinder the exploration of inter-individual EEG commonality. This study proposes a multiple-day scenario that learns exclusively from diverse EEG correlates of emotional responses on different days (i.e., enriched data diversity) by using a unified independent components analysis framework. Given an eight-day dataset of 10 subjects (i.e., 80 sessions), the results demonstrated that the multiple-day scenario intensified the inter-subject emotion commonality (i.e., the percentage of subjects with the same signature) to a certain extent when considering sufficient cross-day sessions, whereas the most commonly adopted single-day analysis (i.e., diversity-confined) led to session-dependent inferior outcomes. Given the best case, the emotional valence dimension was associated with relatively reproducible frontal beta, central midline gamma, and occipital beta modulations with 30%–40% subject commonality, whereas the arousal counterpart suffered more substantially from EEG variability and barely returned representative signatures. These results suggest that EEG signature representation may be substantially compromised by limited data diversity, impeding the efficacy and generalizability of the aBCI model in real-life settings. [ABSTRACT FROM AUTHOR]

The purpose of this study is to identify the latent profiles of Chinese adolescents' family (parent–adolescent and sibling) relationships prior to and during the COVID-19 pandemic, as well as associations between those profiles and adolescents' emotional and behavioral responses. A total of 2,305 adolescents from China aged between 10 and 18 years completed measures of parent–adolescent relationships, sibling relationships, and emotional and behavioral responses during the pandemic. Four profiles of family relationships were identified via latent profile analysis and categorized as Cohesive-Decline, Mild-Decline, Conflictual-Stable, and Indifferent-Stable. Adolescents with a Conflictual-Stable profile reported more emotional and behavioral responses compared to the other profiles. In contrast, adolescents with a Cohesive-Decline profile exhibited fewer emotional responses compared to the other profiles. Adolescents with a Mild-Decline profile had fewer emotional responses than those with an Indifferent-Stable profile. These results shed light on the patterns and consequences of family relationships during the COVID-19 pandemic and have substantial implications for interventions involving family relationships in the context of regular epidemic prevention and control. [ABSTRACT FROM AUTHOR]

The purpose of this research is to understand the conceptualizations and emotional responses produced by diversities in thirteen teacher trainers of the Primary Education Pedagogy degree, of a Chilean university with an important trajectory in teacher training in the Metropolitan Region, the national capital. A qualitative approach was used through semi-structured and projective interviews. The data were analyzed following the data analysis spiral proposed by Creswell (2013). It is concluded that the trainers have a descriptive representation of diversity that that does not consider inequalities, discriminations, or conflicts. Regarding their emotional responses about diversity, they positively value the possibility of new learning and an epistemic openness that generates multiple challenges. They also express not being prepared to deal with diversity in the pedagogical space, discomfort regarding certain diversities and an epistemic tension toward the concept of diversity and the classifications that may cause discrimination. [ABSTRACT FROM AUTHOR]

Background: Despite the many roles spoken language interpreters play, there is little evidence exploring the assumed roles and their corresponding emotional impact when working with refugees in health and human services. Methods: Using Constructivist Grounded Theory, our team explored the experiences of 11 interpreters who had undergone migration to the United States to understand the roles they identify with and how those roles intersect with their emotional responses to clients' stories, trauma, and shared experiences. Findings: Our findings indicate that interpreters embody diverse roles and exhibit a spectrum of emotional responses, including being a "voice," a "cultural broker," an "advocate," and "being human." These roles were linked to emotional responses ranging from workplace stress, empathy, and emotional toll to growth and satisfaction. Conclusions: Our field needs to address interpreters' emotional needs and advocate for work environments that value inclusivity and the recognition of interpreters as vital members of the therapeutic alliance. [ABSTRACT FROM AUTHOR]

Abstract With the development of intelligent agents pursuing humanisation, artificial intelligence must consider emotion, the most basic spiritual need in human interaction. Traditional emotional dialogue systems usually use an external emotional dictionary to select appropriate emotional words to add to the response or concatenate emotional tags and semantic features in the decoding step to generate appropriate responses. However, selecting emotional words from a fixed emotional dictionary may result in loss of the diversity and consistency of the response. We propose a semantic and emotion‐based dual latent variable generation model (Dual‐LVG) for dialogue systems, which is able to generate appropriate emotional responses without an emotional dictionary. Different from previous work, the conditional variational autoencoder (CVAE) adopts the standard transformer structure. Then, Dual‐LVG regularises the CVAE latent space by introducing a dual latent space of semantics and emotion. The content diversity and emotional accuracy of the generated responses are improved by learning emotion and semantic features respectively. Moreover, the average attention mechanism is adopted to better extract semantic features at the sequence level, and the semi‐supervised attention mechanism is used in the decoding step to strengthen the fusion of emotional features of the model. Experimental results show that Dual‐LVG can successfully achieve the effect of generating different content by controlling emotional factors.

Anthropomorphized robots are increasingly integrated into human social life, playing vital roles across various fields. This study aimed to elucidate the neural dynamics underlying users’ perceptual and emotional responses to robots with varying levels of anthropomorphism. We investigated event-related potentials (ERPs) and event-related spectral perturbations (ERSPs) elicited while participants viewed, perceived, and rated the affection of robots with low (L-AR), medium (M-AR), and high (H-AR) levels of anthropomorphism. EEG data were recorded from 42 participants. Results revealed that H-AR induced a more negative N1 and increased frontal theta power, but decreased P2 in early time windows. Conversely, M-AR and L-AR elicited larger P2 compared to H-AR. In later time windows, M-AR generated greater late positive potential (LPP) and enhanced parietal-occipital theta oscillations than H-AR and L-AR. These findings suggest distinct neural processing phases: early feature detection and selective attention allocation, followed by later affective appraisal. Early detection of facial form and animacy, with P2 reflecting higher-order visual processing, appeared to correlate with anthropomorphism levels. This research advances the understanding of emotional processing in anthropomorphic robot design and provides valuable insights for robot designers and manufacturers regarding emotional and feature design, evaluation, and promotion of anthropomorphic robots.

During the early stages of the coronavirus pandemic, consumers faced challenges related to obtaining household items due to shortages and limitations in shopping. Researchers from the University of Tennessee conducted a national, web-based consumer survey of 300 consumers in late April 2020 to better understand consumer behavior, shopping patterns, and demand shifts for goods and services. Major findings demonstrate that consumers have increased shopping for essential products from brick-and-mortar national chains, avoided brick-and-mortar small businesses, and have chosen to shop more by themselves, often choosing to forgo spending from across all product categories, compared to prior to the pandemic. Additionally, results indicate that lower levels of positive emotions and active resilience are responsible for higher levels of shopping frequency. Additionally, lower levels of passive resilience and optimism are associated with increases in co-shopping behaviors. Findings from this study provide insight into the changes among consumers during trying times and the influence of consumers’ emotions and individual characteristics in helping to explain these changes in family resource management and mental health, as well as consumer resilience amidst changing macroeconomic conditions.