Browse Items (16488 total)
Sort by:
-
Emotionally Adaptive AI Companions for Supporting Routine Management in Autistic Adolescents
Autistic Adolescents usually experience difficulties in the management of emotions, routine transitions and social cue interpretation. Many existing tools that aim to fill in the gap are often non-personalise, static or lack real-time responsiveness in handling these challenges. This study conceptualises and empirically validates a prototype of an emotionally adaptive AI companion that focuses on reducing stress due to routine transition, emotional regulation and social cue interpretation while increasing personalised management by providing contextual support. A quasi-experimental, mixed methods design is adopted. The core of this system conducts facial multimodal emotion recognition through facial expression and simulated voice tone using transfer learning across three CNN architectures (ResNet-18, MobileNetV2, and EfficientNet-B0) as comparison tests. The resulting emotion output is feeds into a contextual engine for real-time personalised interventions which can also be continuously improved through critical feedback-in-the-loop control architecture based on caregiver logs. The key model trade-offs are validated, the findings established that ResNet18 possesses the highest accuracy of 48%, EfficientNet-B0 with a superior F1 Score of 0.31 and MobileNetV2 proves to be efficient but slightly lower performance compared to other architectures. Simulated user feedback validation resulted in high preliminary acceptability, as high as 87.5% acceptability for an intervention like 'Reassurance'. This validated the utility of this responsive system. This transfer-learning based, multi-modal pipeline is robust. The results of the comparative analysis uncovered a very profound and instructive trade-off between the complexity of models, their efficiency, and performance metrics relating to accuracy versus the F1-score. 2026 IEEE. -
Emotional needs of women post-rescue from sex trafficking in India
Sex trafficking has persisted a social crime that maintains its status despite being unlawful. Since it prevails, there is a need to investigate it to understand the effects and consequences of the same on the survivors. The current study aims to understand the emotional needs of survivors post-rescue from sex trafficking living in aftercare homes in India and to look into survivors suggestions post-rescue to NGOs, society, family, government and police. It included ten survivors from sex trafficking, ages between 18 to 24years old. They are emerging adults who have experienced sex trafficking for at least one year, regardless of whether trafficking happened in childhood, adolescence or early adulthood, rescued one to five years ago. The researcher used a phenomenological approach. Thematic analysis was employed to identify themes within the data collected from the participants. Findings revealed that survivors had got a better life after the rescue, and they need acceptance, respect, understanding, and they need to develop trust on people around them. They still have many challenges post-rescue such as lack of education and job opportunities. They need guidance to start a new life. Mostly, sex trafficking survivors need safety and protection. 2019, 2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Emotional Maturity and Self-Perception Among Adolescents Living With HIVNeed for Life-Skills Intervention
Among Adolescents Living With HIV (hereby referred to as ALWH), emotional maturity and self-perception gain importance because they play a decisive role in the overall development into adulthood. This study examines the relationship between self-perception and emotional maturity among ALWH. The sample comprised of 92 male and female ALWH, aged 13 to 18 years. Self-Perception Questionnaire and Emotional Maturity Scale were the tools used. Descriptive and inferential statistics were used for analysis. Correlation analysis showed a negative moderate relationship between Physical Competence and Global Self-Worth dimensions of self-perception and emotional maturity, with regression analysis confirming their predictive abilities. Discussions are focused on the relevance of the findings in terms of a need for a psychosocial life-skills intervention for the population. The Author(s) 2019. -
Emotional Landscape of Social Media: Exploring Sentiment Patterns
Sentiment analysis, a pivotal research area, involves exploring emotions, attitudes, and evaluations prevalent in diverse public spheres. In the contemporary era, individuals extensively share their perspectives on various subjects through social media platforms. Twitter has emerged as a prominent microblogging site, facilitating users to express opinions and insights globally. However, disrespectful or unfair comments have prompted specific platforms to restrict user comments, highlighting the need to foster productive discourse on social media. This study addresses this imperative by analyzing sentiments using data from Twitter. This work employed various deep learning algorithms and methods to classify elements as negative or positive. The Sentiment140 dataset, sourced from Twitter, serves as the training data for the models to identify the most accurate classification approach. By delving into sentiment analysis on Twitter, the study contributes to a better understanding of the nuances of online expressions. It aims to enhance the overall quality of discourse in social media. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Emotional intelligence, job satisfaction and psychological well-being among nurses in a tertiary care hospital
Background: Emotional intelligence helps in preservation of mental health because of their effective emotional regulation skills. Objectives: We aimed to evaluate the impact of emotional intelligence on nurses job satisfaction and psychological well-being. Methods: This cross-sectional study was conducted in a tertiary hospital and included 120 nurses. Wong and Law Emotional Intelligence Scale, Psychological General Well-being scale and Job Satisfaction Survey questionnaires were used. Results: The study showed a low positive correlation between emotional intelligence and psychological wellbeing (r=0.313) and a low correlation between emotional intelligence and job satisfaction (r= 0.122). The emotional intelligence was significantly correlated to their psychological well-being (9.8%). Conclusion: Nurses with higher emotional intelligence experience greater psychological well-being. We did not find a link between emotional intelligence and job satisfaction. Implementing interventions to enhance emotional intelligence in nurses is crucial for improving psychological well-being and reducing burnout risk. The Author(s). 2024. -
Emotional Intelligence as a Predictor of Police Operational Stress: A Pilot Study
The present study examined the relationship between police operational stress and emotional intelligence. The study also observed the difference in operational stress and emotional intelligence concerning gender, rank, education, and marital status. The sample included 80 police officers from Bangalore, India. The operational police stress questionnaire developed by McCreary and Thompson (2006) and emotional intelligence scale developed by Hyde et al. (2002) were used to measure police operational stress and emotional intelligence, respectively. Independent sample t-test and Cohens d indicated that differences in gender, rank, education, and marital status had no significant effect on police operational stress. Gender differences had a significant effect on the emotional intelligence factors, empathy, and self-motivation. Differences in rank had a significant effect on empathy, self-motivation, emotional stability, managing relationships, integrity, value orientation, and commitment. Differences in marital status had a significant effect on value orientation. Correlation analysis showed that operational stress had a significant negative relationship with emotional intelligence and its factors such as self-motivation, emotional stability, value orientation, and altruistic behavior. Regression analysis showed emotional intelligence and its factor, emotional stability, as significant predictors of police operational stress. 2021, Society for Police and Criminal Psychology. -
-
Emotional intelligence and work life balance of women IT professional in Bangalore /
Adarsh Journal of Management Research, Vol.7, Issue 2, pp.241-253, ISSN No: 0974-7028. -
Emotional intelligence and self esteem in cannabis abusers
This study was taken up to investigate emotional intelligence and self esteem in cannabis abusers. Cross sectional hospital based study, Study is based on a sample of 200 individuals. 100 Cannabis dependent, diagnosed based on DSM-IV TR was selected from two different hospitals in north India. 100 healthy matched subjects constituted the control group. Assessment was done using MINI, General Health Questionnaire, Indian Adaptation of Emotional Intelligence Scale and Rosenberg Self Esteem Scale. Significant differences were seen in Emotional Intelligence between the Cannabis dependent group and normal control group. The cannabis dependent groups scored significantly low on emotional intelligence in comparison with control group. Further, cannabis dependent group scored significantly lower on score of self esteem than the normal control group. Relationship between emotional intelligence and self esteem was found to be positively correlated. Our study suggests an association between low emotional intelligence, low self esteem and cannabis dependence and the prevention and treatment of cannabis dependence should lay focus on these factors. Journal of the Indian Academy of Applied Psychology. -
-
Emotional Intelligence and General Well-Being Among Middle Aged People
International Journal of Research in Social Sciences, Vol-2 (4), pp. 454-471. ISSN-2249-2496 -
Emotional Intelligence and Cross-Cultural Adaptation of Indian Students in the Context of Interstate Education
India is known for its cultural diversity based on several factors, such as language, religion, race, and customs. In India, people used to move from one place to another for various purposes, and this was particularly the case with students in pursuit of education. In such situations, cross-cultural adaptation is one of the factors that facilitate their adjustment to new cultures and surroundings. Cross-cultural adaptation is needed when a person has to live in a different cultural setting than their own native place. Being sensitive to others emotions is essential when one lives in a new place. Emotional intelligence helps in that way and influences cross-cultural adaptation. Therefore, the present study was intended to explore the influence of emotional intelligence on cross-cultural adaptation. As many as 332 students, aged 17 to 29, who moved to another state for education, participated in the study. Emotional Intelligence Scale and Cross-Cultural Adjustment Scale were used for data collection. The components of emotional intelligence, such as self-emotional appraisal (SEA) and others emotional appraisal (OEA), were found to significantly influence expatriate adjustment. Furthermore, SEA and OEA have also influenced cultural novelty and the use of emotions (UOE). Students from rural areas were found to have more cross-cultural adaptation in the presence of their friends company compared to urban dwellers. In summary, the current study emphasizes the importance of higher emotional intelligence for better cross-cultural adaptation. 2025 Common Ground Research Networks. All rights reserved. -
Emotional Intelligence and Cross-Cultural Adaptation of Indian Students in the Context of Interstate Education
India is known for its cultural diversity based on several factors, such as language, religion, race, and customs. In India, people used to move from one place to another for various purposes, and this was particularly the case with students in pursuit of education. In such situations, cross-cultural adaptation is one of the factors that facilitate their adjustment to new cultures and surroundings. Cross-cultural adaptation is needed when a person has to live in a different cultural setting than their own native place. Being sensitive to others emotions is essential when one lives in a new place. Emotional intelligence helps in that way and influences cross-cultural adaptation. Therefore, the present study was intended to explore the influence of emotional intelligence on cross-cultural adaptation. As many as 332 students, aged 17 to 29, who moved to another state for education, participated in the study. Emotional Intelligence Scale and Cross-Cultural Adjustment Scale were used for data collection. The components of emotional intelligence, such as self-emotional appraisal (SEA) and others emotional appraisal (OEA), were found to significantly influence expatriate adjustment. Furthermore, SEA and OEA have also influenced cultural novelty and the use of emotions (UOE). Students from rural areas were found to have more cross-cultural adaptation in the presence of their friends company compared to urban dwellers. In summary, the current study emphasizes the importance of higher emotional intelligence for better cross-cultural adaptation. 2025 Common Ground Research Networks. All rights reserved. -
Emotional Inhibition and Personality as Predictors of Anxiety and Depression in Young Adults
Purpose: Anxiety and depression have been major contributors to the global burden of disease, and the impact has been exacerbated following the COVID-19 pandemic. Therefore, the aim of this study was to understand the association between emotional suppression and the introverted-extraverted dimension of personality in young people and anxiety and depression. Method: Participants were 152 Indian females between the age group of 18-25 years who provided basic demographic details and completed three questionnaires via a google form. Findings: Results described a significant negative correlation of anxiety r (152) = .500, p <0.01and depression r(152)=.471, p <0.01 with emotional inhibition. There was also a significant positive correlation of anxiety r (152) = .288,p < 0.01 and depression r(152)= .288, p <0.01 with personality. While Emotional inhibition emerged as a significant negative predictor of anxiety (R2= .250) as well as of depression (R2=.222), personality (R2=.243) emerged as a significant predictor of depression. Conclusion/Value: Contrary to popular belief, the results of this study suggest that anxiety and depression are inversely related to emotional inhibition. It restores the complexity of emotions and the need to investigate their role in various pathologies. These findings provide an initial basis for further investigation into the role of emotional expression and suppression in the Indian population. 2024 RJ4All. -
Emotional Dysregulation and Emerging Psychopathology in Adolescents
[No abstract available] -
Emotional Abuse and the Pandemic in India: Implications for Policy, Research, and Practice
During the COVID-19 outbreak, cases of violence and abuse have increased significantly around the world, necessitating a reevaluation of our relation-ships. Both violence and abuse seek to control and instill fear in the individ-ual, gradually disrupting their overall well-being. Emotional abuse does not receive the same level of attention and social response as other forms of abuse due to its subtle nature. Its effects are as harmful as physical and sexual abuse, with serious consequences for the mental health of individual and their families. The COVID-19 pandemic has brought to light the importance of mental health. With the imposition of lockdown in India, the number of helplines for domestic violence and abuse has skyrocketed. Abuse experien-ces can be seen to be bidirectional; women are not alone in such instances. Many cases, however, go unreported and never reach formal institutions. The National Family Health Survey (2019-2021) reveals the current state of Indian health and nutrition, but emotional abuse (also referred to inter-changeably in this article as emotional violence) only includes responses from women and is no longer included under spousal violence in the most recent edition. This article also includes recommendations and attempts to highlight existing shortcomings in addressing the issue of emotional violence. The articles cited in this article were obtained from electronic databases. Other secondary data sources mentioned include newspaper articles, magazines, census reports, and periodicals. 2024 Springer Publishing Company. -
Emotion-Aware Sign Language Recognition Using CNN and UNET Architectures
This paper proposes an AI-based system for the recognition of sign language with the detection of emotions for more expressive communication among speech-impaired and hearing individuals and others. Traditional sign language systems focus mainly on the aspect of hand gestures and neglect the signs for emotions that add meaning and context. In order to overcome the limitation, the project proposes a system that utilizes Convolutional Neural Nets (CNNs) for the recognition of hand signs and UNET for the segmentation of the picture so that the area of the hands can be discriminated from the background. Facial Emotion Recognition (FER) is also incorporated in order to detect signs such as happiness, sadness, or anger. Overall, the parts together constitute a multimodal recognition system that can read signs and emotions and produce more natural and expressive outputs. The paper delves into architecture, dataset challenges, and implementation concepts with publicly available databases such as RWTH-PHOENIX-Weather 2014T. The combined approach can enhance inclusivity and access in learning, communication, and assistive technology. 2025 IEEE. -
Emotion-Aware Sign Language Recognition Using CNN and UNET Architectures
This paper proposes an AI-based system for the recognition of sign language with the detection of emotions for more expressive communication among speech-impaired and hearing individuals and others. Traditional sign language systems focus mainly on the aspect of hand gestures and neglect the signs for emotions that add meaning and context. In order to overcome the limitation, the project proposes a system that utilizes Convolutional Neural Nets (CNNs) for the recognition of hand signs and UNET for the segmentation of the picture so that the area of the hands can be discriminated from the background. Facial Emotion Recognition (FER) is also incorporated in order to detect signs such as happiness, sadness, or anger. Overall, the parts together constitute a multimodal recognition system that can read signs and emotions and produce more natural and expressive outputs. The paper delves into architecture, dataset challenges, and implementation concepts with publicly available databases such as RWTH-PHOENIX-Weather 2014T. The combined approach can enhance inclusivity and access in learning, communication, and assistive technology. 2025 IEEE. -
Emotion Trajectory Analysis and Model Comparison for Hate Speech and Radicalization Detection in Code-Mixed Platforms
The growing presence of multilingual and codemixed content on social media creates major challenges for automated emotion recognition and mental health support. In this work, we introduce an emotion-aware computational framework that processes code-mixed Indian language comments and predicts user emotions with high accuracy, followed by context-aware support suggestions. Our dataset comes from the AI4Bharat IndicNLP corpus [14] and the Dravidian-CodeMix sentiment dataset [15], featuring a variety of multilingual user comments. To maintain linguistic consistency, we translate the raw texts into English using Google Translator and then preprocess them through normalization, tokenization, and stopword removal. We use three advanced transformer-based models, DistilBERT (six emotions), DistilRoBERTa (seven emotions), and RoBERTa GoEmotions (27+ emotions), to categorize the emotions in the comments. We compare predictions across the models and select the most reliable label for each text, which is further verified through manual checks with human annotators. This process results in a curated dataset labeled with emotions and enriched with model provenance. With this dataset, we train a Logistic Regression classifier using TF-IDF features to create an efficient, explainable prediction pipeline. The system classifies emotions and provides tailored suggestions based on emotional states, improving user support in online interactions. Experimental results show the robustness of the pipeline and its ability to adapt to various code-mixed inputs. This study offers an integrated dataset-model-suggestion framework that advances emotion recognition in multilingual contexts and supports the creation of practical emotion-aware digital systems. 2025 IEEE. -
Emotion Regulation and Psychological Well-being as Contributors Towards Mindfulness Among Under-Graduate Students
Emotion regulation is generally described as the ability of an individual not only to manage emotions effectively but also to respond effectively to the emotional experience. It has also been viewed as a crucial aspect for psychological well-being. It is a psychological state which means more than just being free from stress and not having any other psychological disorder reported by the individual. At the same time, students with higher emotion regulation and psychological well-being are expected to be more attentive and able to observe, describe and participate in the present moment, effectively, with non-judgmental awareness, which is in turn defined as mindfulness. Hence, it has been expected that participants with higher emotion regulation and psychological well-being would also report higher levels of mindfulness. Therefore, the present empirical investigation has been conducted with an objective of assessing the level of emotion regulation, psychological well-being and mindfulness among under-graduate students. Additionally, it was also expected that all the said variables would be positively correlated and emotion regulation and psychological well-being would predict mindfulness positively for under-graduate students. For this purpose, ex post facto research design was adopted, and standardized tools pertaining to emotion regulation, psychological well-being and mindfulness were administered on a sample of 104 under-graduate students. The results of correlation statistics revealed that emotional regulation (r=0.27; p<0.01) and psychological well-being (r=0.21; p<0.01) are the positive and significant correlates of mindfulness. Additionally, statistical outcomes of stepwise multiple regression analysis confirm that emotion regulation and psychological well-being are the significant predictors of mindfulness and contribute collectively towards a 11% variance towards the same. 2020, Springer Nature Switzerland AG.