Females Are More Sensitive to Opponent's Emotional Feedback: Evidence From Event-Related Potentials

Loneliness and its associated factors among university students during late stage of COVID-19 pandemic: An online cross-sectional study

BACKGROUND

The COVID-19 pandemic resulted in a number of psychosocial and emotional catastrophes, including loneliness. The associated lockdowns, reduced social support, and insufficiently perceived interactions are expected to heighten the level of loneliness during the pandemic. However, there is a dearth of evidence regarding the level of loneliness and what correlates with loneliness among university students in Africa, particularly in Ethiopia.

OBJECTIVES

The general objective of this study was to assess the prevalence and associated factors of loneliness among university students during the COVID-19 pandemic in Ethiopia.

METHODS

A cross-sectional study was undertaken. An online data collection tool was distributed to voluntary undergraduate university students. The sampling technique used was snowball sampling. Students were requested to pass the online data collection tool to at least one of their friends to ease data collection. SPSS version 26.0 was used for data analysis. Both descriptive and inferential statistics were used to report the results. Binary logistic regression was used to identify factors associated with loneliness. A P-value less than 0.2 was used to screen variables for the multivariable analysis, and a P-value less than 0.05 was used to declare significance in the final multivariable logistic regression.

RESULT

A total of 426 study participants responded. Out of the total, 62.9% were males, and 37.1% attended fields related to health. Over three-fourths (76.5%) of the study participants encountered loneliness. Females (adjusted odds ratio (AOR): 1.75; 95% confidence interval (CI): 1.01, 3.04), non-health-related departments (AOR: 1.94; 95% CI: 1.17, 3.35), ever encountering sexual harassment (AOR: 3.32; 95% CI: 1.46, 7.53), sleeping problems (AOR: 2.13; 95% CI: 1.06, 4.30), perceived stress (AOR: 6.40; 95% CI: 1.85, 22.19) and poor social support (AOR: 3.13; 95% CI: 1.10, 8.87) were significantly associated with loneliness.

CONCLUSION AND RECOMMENDATION

A significant proportion of students were victims of loneliness during the COVID-19 pandemic. Being female, working in non-health-related fields, having sleeping problems, encountering sexual harassment, perceived stress, and poor social support were significantly associated with loneliness. Interventions to reduce loneliness should focus on related psychosocial support to reduce stress, sleeping disturbances, and poor social support. A special focus should also be given to female students.

Characteristics and influencing factors of early childhood teachers’ work stress and burnout: A comparative study between China, Ghana, and Pakistan

Introduction

Many studies have documented the stress and burnout experienced by early childhood teachers. However, few have focused on comparisons among countries, particularly developing ones. Meanwhile, female teachers, who are more sensitive and tend to provide emotional responses, are often overlooked as a major force of emotional involvement. This study examined the similarities and differences of early childhood teachers’ stress, burnout, and gender in China, Ghana, and Pakistan.

Methods

This study adopted a cross-sectional design. The participants included 945 preschool and lower primary school teachers recruited from Zhejiang Province in China, the Ashanti Region in Ghana, and Punjab, Pakistan. The analyses were conducted using structural equation modeling. First, the study estimated all parameters separately and without constraints between the groups for all models. Second, the study compared the latent mean difference and of stressors and burnout between teachers’ personal and job characteristics. Third, a structural equation model was used to assess the relationship between teachers’ stressors and burnout.

Results

Across the three countries, female teachers are more stressed out, with higher emotional demands and work-family conflicts, and are more prone to burnout with a greater level of emotional exhaustion and a lower level of personal accomplishments than their male counterparts are. Moreover, Chinese teachers were found to be the most stressed-out group with the highest level of burnout. In comparison to teachers in China and Pakistan, early childhood teachers in Ghana possess the lowest level of emotional demands. With the lowest level of emotional exhaustion and the highest level of personal accomplishments, Pakistani teachers were unlikely to experience burnout.

Discussion

This study comparatively analyzed the characteristics of stress and burnout among ECTs in different cultural settings and educational systems in three developing countries (China, Ghana, and Pakistan), and revealed workplace characteristics and circumstances for ECTs. In addition, this study takes gender as the main influencing factor and explores its effect on ECTs’ stress and burnout, and it highlights and verifies "emotionality" in ECTs' profession. As a result, policymakers and stakeholders in different countries may be encouraged to improve ECE quality and the well-being of ECTs.

Exploring the impact of COVID-19 pandemic on Americans time use related subjective wellbeing

In this study, the most recent American Time Use Surveys containing reported activity-based emotions and sensations information before (10,378 respondents in 2013) and during (6,902 respondents in 2021) the COVID-19 pandemic are used to assess if time use related individuals' subjective wellbeing (SWB) decreased in the pandemic. Given that the coronavirus has been shown to strongly influence activity decisions and social interactions, sequence analysis is applied to find daily time allocation patterns and changes in daily time allocation. Then, those derived daily patterns and other activity-travel factors, as well as social and demographic, temporal, spatial, and other contextual characteristics are added as explanatory variables in regression models of SWB measures. This provides a holistic framework of exploring the direct and indirect effects (via activity-travel schedules) of the recent pandemic on SWB while controlling for contexts such as the life assessments, daily schedule of activities, and living environment. The results show that respondents in the COVID year reported a new time allocation pattern that has a substantial amount of time at home, and they experienced more negative emotions. Three relatively happier daily patterns in 2021 contained substantial amounts of outdoor and indoor activities. In addition, no significant correlation was observed between metropolitan areas and individuals' SWB in 2021. However, comparisons among states show Texas and Florida residents experienced more positive wellbeing presumably due to fewer COVID-related restrictions.

Canabal M, Gutiérrez-Martín L, Lanza-Gutierrez JM, Portela-García M, López-Ongil C. Fear Recognition for Women Using a Reduced Set of Physiological Signals

Emotion recognition is benefitting from the latest research into physiological monitoring and wireless communications, among other remarkable achievements. These technologies can indeed provide solutions to protect vulnerable people in scenarios such as personal assaults, the abuse of children or the elderly, gender violence or sexual aggression. Cyberphysical systems using smart sensors, artificial intelligence and wearable and inconspicuous devices can serve as bodyguards to detect these risky situations (through fear-related emotion detection) and automatically trigger a protection protocol. As expected, these systems should be trained and customized for each user to ensure the best possible performance, which undoubtedly requires a gender perspective. This paper presents a specialized fear recognition system for women based on a reduced set of physiological signals. The architecture proposed is characterized by the usage of three physiological sensors, lightweight binary classification and the conjunction of linear (temporal and frequency) and non-linear features. Moreover, a binary fear mapping strategy between dimensional and discrete emotional information based on emotional self-report data is implemented to avoid emotional bias. The architecture is evaluated using a public multi-modal physiological dataset with two approaches (subject-dependent and subject-independent models) focusing on the female participants. As a result, the proposal outperforms the state-of-the-art in fear recognition, achieving a recognition rate of up to 96.33% for the subject-dependent model.

Emotion Elicitation Under Audiovisual Stimuli Reception: Should Artificial Intelligence Consider the Gender Perspective?

Identification of emotions triggered by different sourced stimuli can be applied to automatic systems that help, relieve or protect vulnerable groups of population. The selection of the best stimuli allows to train these artificial intelligence-based systems in a more efficient and precise manner in order to discern different risky situations, characterized either by panic or fear emotions, in a clear and accurate way. The presented research study has produced a dataset of audiovisual stimuli (UC3M4Safety database) that triggers a complete range of emotions, with a high level of agreement and with a discrete emotional categorization, as well as quantitative categorization in the Pleasure-Arousal-Dominance Affective space. This database is adequate for the machine learning algorithms contained in these automatic systems. Furthermore, this work analyses the effects of gender in the emotion elicitation under audiovisual stimuli, which can help to better design the final solution. Particularly, the focus is set on emotional responses to audiovisual stimuli reproducing situations experienced by women, such as gender-based violence. A statistical study of gender differences in emotional response was carried out on 1332 participants (811 women and 521 men). The average responses per video is around 84 (SD = 22). Data analysis was carried out with RStudio^®.

Prefrontal activation in suicide attempters during decision making with emotional feedback

Emotional feedback, such as faces showing emotions, can influence decision making. Decision making and emotional face processing, mainly mediated by the prefrontal and cingulate cortices, are impaired in suicide attempters. Here, we used functional MRI (fMRI) to study prefrontal activation in suicide attempters during a modified version of the Iowa Gambling Task (IGT) that included emotional face feedback. We randomly distributed the 116 euthymic women (n = 45 suicide attempters, n = 41 affective controls with history of depression without suicide attempt, and n = 30 healthy controls) included in the study in three emotional IGT groups: concordant (safe and risky choices followed by happy and angry faces, respectively), discordant (safe and risky choices followed by angry and happy faces, respectively), and neutral condition (safe and risky choices followed by neutral faces). Considering the two IGT phases (ambiguous and risky), we then analyzed five regions of interest during the risky vs. safe choices: orbitofrontal (OFC), anterior cingulate (ACC), ventrolateral (VLPFC), medial (MPFC) and dorsal prefrontal (DPFC) cortices. We found: (1) impaired decision making and increased DPFC and OFC activation in suicide attempters vs. controls in the discordant condition during the risky phase; (2) reduced VLPFC activation in suicide attempters in the concordant condition during the ambiguous phase; and (3) decreased OFC, ACC and DPFC activation in both control groups in the concordant condition during the ambiguous phase. Suicide attempters showed prefrontal alterations during reward-learning decision making with emotional feedback. Suicide attempters may guide their decisions to avoid social negative feedback despite the expected outcome.

How do different kinds of incidental emotions influence risk decision making?

Incidental emotions, which are irrelevant to the ongoing decision, play a significant role in decision-making processes. In this study, we investigated the influence of specific incidental emotions on behavioral, psychological, and electrophysiological responses during the process of decision making. Participants finished a forced-choice gambling task, during which incidental emotions (anger/fear/happiness) were elicited by recalling emotional experiences. Behavioral and event-related potential (ERP) data were recorded in the experiment. Behavioral results showed that risk preference was weaker in the fearful condition than in the angry and happy conditions, but emotional feelings to outcome feedback were not influenced by incidental emotions. The feedback-related negativity (FRN) amplitude was larger in the fearful condition than in the angry, happy, and neutral conditions for large outcomes, whereas there was no difference between the four conditions for small outcomes. In addition, the influence of outcome magnitude (small/large) on the P3 amplitude was stronger in the fearful condition than in the angry, happy, and neutral conditions. We suggest that incidental fear elicits risk-avoidant behavior (manifested in behavioral choices), stronger motivation (manifested in the FRN amplitude) and cognitive resources (manifested in the P3 amplitude) for risky outcomes of decision making unconsciously (indicated by unchanged subjective emotional experiences). The current findings have expanded our understanding of the role of specific incidental emotions in decision making.

Gender Identification of Human Cortical 3-D Morphology Using Hierarchical Sparsity

Difference exists widely in cognition, behavior and psychopathology between males and females, while the underlying neurobiology is still unclear. As brain structure is the fundament of its function, getting insight into structural brain may help us to better understand the functional mechanism of gender difference. Previous structural studies of gender difference in Magnetic Resonance Imaging (MRI) usually focused on gray matter (GM) concentration and structural connectivity (SC), leaving cortical morphology not characterized properly. In this study a large dataset is used to explore whether cortical three-dimensional (3-D) morphology can offer enough discriminative morphological features to effectively identify gender. Data of all available healthy controls (N = 1113) from the Human Connectome Project (HCP) were utilized. We suggested a multivariate pattern analysis method called Hierarchical Sparse Representation Classifier (HSRC) and got an accuracy of 96.77% for gender identification. Permutation tests were used to testify the reliability of gender discrimination (p < 0.001). Cortical 3-D morphological features within the frontal lobe were found the most important contributors to gender difference of human brain morphology. Moreover, we investigated gender discriminative ability of cortical 3-D morphology in predefined Anatomical Automatic Labeling (AAL) and Resting-State Networks (RSN) templates, and found the superior frontal gyrus the most discriminative in AAL and the default mode network the most discriminative in RSN. Gender difference of surface-based morphology was also discussed. The frontal lobe, as well as the default mode network, was widely reported of gender difference in previous structural and functional MRI studies, which suggested that morphology indeed affect human brain function. Our study indicates that gender can be identified on individual level by using cortical 3-D morphology and offers a new approach for structural MRI research, as well as highlights the importance of gender balance in brain imaging studies.