Enhancing Emotional Intelligence in Cybersecurity: A Quantitative Study on Generative AI's Impact

What is the impact of AI in the market? The global AI market is projected to expand at a "staggering compound annual growth rate (CAGR) of 37.3% from 2023 to 2030 and is expected to reach $1.8 trillion by 2030" (Nagraj, 2023). PwC estimates that "AI could contribute up to $15.7 trillion to the global economy in 2030, more than the current output of China and India combined." This includes "$6.6 trillion from increased productivity and $9.1 trillion from consumption-side effects." Additionally, AI is expected to have a profound impact on brand storytelling (Nagraj, 2023). The 2023 Forbes article "Improving Collaboration" emphasizes how AI is revolutionizing teamwork and organizational communication. It discusses how generative AI, integrated into advanced collaborative tools, enhances virtual meetings by improving interaction quality, optimizing workflows, and automating routine tasks for teams spread across different locations. Furthermore, AI's impact on productivity is highlighted through examples like Microsoft’s Copilot for IT, which utilizes enterprise data and real-time user context to deliver customized, AI-driven solutions. This integration allows for seamless content creation, collaboration, and task automation tailored to specific business needs. In the context of hybrid work challenges, such as remote employees feeling disconnected and delays in issue resolution, AI-powered virtual assistants play a crucial role. These assistants aggregate information from various sources, promptly address queries, and resolve issues, thereby fostering better connectivity and efficiency among team members. Overall, AI's ability to automate mundane tasks like meeting transcriptions and note-taking liberates employees to focus on more creative and collaborative aspects of their work. The article underscores AI's potential to transform teamwork and organizational communication, paving the way for a more productive and innovative workplace culture.

Artificial intelligence usage in the communication field is of strategic importance. However, most communication practitioners and academicians have not noticed the gains in momentum substantially artificial intelligence. Through communication journals, this study aims to examine how artificial intelligence is used, its effects, and how important it is in communication. This study was designed as a content analysis and bibliometric analysis study. The sample of this study is AI-based articles in Web of Science Q1 indices communication journals. It selected and examined the first sixteen journals in communication keyword search based on SCImago Journal & Country Rank. This study revealed artificial intelligence usage in the communication industry and field, in addition to AI's impact and significance and AI-based technologies in communication. It was found that the most used method for artificial intelligence-based articles in communication journals was the semi-structured interview method. It is seen that common keywords in AI-based articles and communication journals are announced as human-machine communication, machine learning, artificial agent, artificial intelligence, bias, and social media concepts. In this study, a positive correlation between communication science and artificial intelligence technologies was observed. This study contributes to new studies on artificial intelligence, communication, the impacts of artificial intelligence on communication, new communication technologies, generative AI, human-machine communication, and other related areas.

This study aims to produce empirical insights into how students in Chinese higher vocational colleges view and use generative AI in EFL learning. This quantitative study uses the technology acceptance model (TAM) to analyze EFL learners' attitudes, intentions, and behaviors about utilizing generative AI in EFL learning with Structural Equation Modelling. 911 English as a foreign language(EFL) learners completed a questionnaire measuring personal innovativeness, perceived ease of use, perceived usefulness, attitude, behavioral intention, and actual use. Structural equation modeling investigations show that Perceived Ease of Use does not directly predict learners' attitudes but can impact them through the full mediator Perceived Usefulness. Positive attitudes towards generative AI and personal innovativeness are associated with increased behavioral intention. Behavior intention predicts the actual application of generative AI in English learning. This study demonstrates the effectiveness of generative AI as a language-learning tool for EFL learners, promoting personalized and sustainable learning.

In an era where generative AI (GenAI) is reshaping industries, public understanding of this phenomenon remains limited. This study addresses this gap by analyzing public beliefs about GenAI using the Technology Acceptance Model and Diffusion of Innovations Theory as frameworks. We adopted a big-data approach, utilizing machine-learning techniques to analyze 21,817 public comments extracted from an initial set of 32,707 on 44 YouTube videos discussing GenAI. Our investigation surfaced six pivotal themes: concerns over job and economic impacts, GenAI's potential to revolutionize problem-solving, its perceived shortcomings in creativity and emotional intelligence, the proliferation of misinformation, existential risks, and privacy decay. Emotion analysis showed that negative emotions dominated at 58.46%, including anger (22.85%) and disgust (17.26%). Sentiment analysis echoed this negativity, with 70% negative. The triangulation of thematic, emotional, and sentiment analyses highlighted a polarized public stance: recognition of GenAI's transformative potential is tempered by significant concerns about its implications. The findings offer actionable insights for engineering managers and policymakers. Strategies such as awareness-building, transparency, public engagement, balanced communication, governance, and human-centered development can address polarization and build trust. Ongoing research into public opinion remains essential for aligning technological advancements with societal expectations and acceptance.

Objective: This study provides an empirical analysis of the link between Generative AI (GenAI) adoption and business performance in UK firms, with a specific focus on the mediating effects of operational efficiency and product innovation. Methodology: Grounded in the Resource-Based View (RBV) and the Technology-Organization-Environment (TOE) framework, a conceptual model was developed and tested. Data were collected via a cross-sectional survey of 312 senior managers across diverse UK industries. The data were analysed using partial least squares structural equation modeling (PLS-SEM). Findings: The results indicate a significant positive direct relationship between GenAI adoption and business performance. Both operational efficiency and product innovation were found to be significant partial mediators, with product innovation exhibiting a stronger mediating effect. Key drivers of adoption included technological competence, top management support, and competitive pressure, while regulatory uncertainty was a significant barrier. Implications: The findings offer robust evidence for policymakers and business leaders, positioning GenAI not just as a tool for cost reduction but as a strategic lever for growth, primarily through enhanced innovation. The study underscores the need for sustained investment in technological infrastructure and workforce skills. Originality/Value: This research is one of the first large-scale quantitative studies to empirically validate the mediating pathways through which GenAI influences business performance, providing nuanced, context-specific insights for the UK market.

As generative artificial intelligence tools like ChatGPT become increasingly integrated into educational environments, understanding their impact on critical thinking is crucial. Despite growing concerns about AI's potential to diminish students' independent reasoning, there is a lack of research tools specifically designed to evaluate students' perceptions of AI's cognitive capabilities. To address this gap, this study introduces the Perceived Critical Thinking Disposition of Generative Artificial Intelligence (PCTD-GAI) scale, aimed at measuring how students perceive generative AI’s (GAI) six critical thinking dispositions (reasoning, access to justice, search for evidence, search for truth, open-mindedness, and systematicity). While this study validates the scale using ChatGPT, the instrument is adaptable for evaluating other generative AI tools, supporting broader research in AI-driven learning environments, to assess not only how students engage with AI, but also how their reliance on AI may affect their cognitive development and self-regulated learning skills in digital education. To develop and validate the PCTD-GAI scale, the Marmara Critical Thinking Dispositions Scale (MCTDS) was adapted, ensuring relevance to AI assessment while maintaining conceptual robustness. A quantitative cross-sectional study was conducted with 931 university students from Portugal and Poland, employing exploratory and confirmatory factor analyses (EFA & CFA) to assess the scale’s validity and reliability. The results demonstrate that the PCTD-GAI effectively captures students’ perceptions of ChatGPT’s critical thinking dispositions across six key dimensions. Findings indicate moderately positive perceptions across both countries, with Portuguese students consistently rating ChatGPT marginally higher across domains and showing less response variability, suggesting greater consensus. Notably, perceptions were most neutral in the "truth-seeking" domain, while systematicity received the highest ratings, reflecting ChatGPT’s perceived systematic capabilities among students. These findings have significant implications for e-learning and AI-driven education. The PCTD-GAI scale enables educators to track students’ evolving AI literacy and develop targeted interventions that promote critical AI engagement rather than passive reliance on AI-generated content. Moreover, this research advances the field of e-learning by offering an empirical basis for integrating AI assessment into digital learning strategies, ensuring that AI serves as a cognitive tool rather than a substitute for independent reasoning. The validated PCTD-GAI scale provides a reliable, scalable method for assessing students’ perceptions of AI's cognitive capabilities, supporting evidence-based AI pedagogy, and guiding institutional policies on AI integration in education.

Objective The current literature on Generative Artificial Intelligence (GenAI) in tertiary settings primarily focuses on the risk it poses to academic integrity, and ways to reduce or remove GenAI use in assessments. As psychology graduates enter a workforce where GenAI is present, educators need to prepare students to use GenAI responsibly. This scoping review aims to assess the current state of knowledge in tertiary psychology regarding opportunities for integrating GenAI into assessment methods. Method A comprehensive literature search identified four studies for inclusion. These were published in Australia, Canada, Switzerland, and the United States, and included two quantitative case studies, a mixed-method case study, and a pedagogical case study. Results Three themes were generated: 1) GenAI can be used as an effective psychology tutor, 2) GenAI can be used for authentic assessment in undergraduate psychology, and 3) Critiquing GenAI as a form of assessment can enhance student learning and AI literacy. Conclusions Only four studies were identified, but all indicate that GenAI can be meaningfully incorporated into psychology assessments. However, this is an underdeveloped area and ongoing research with a particular focus on developing evidence-based assessment methods which adapt to the evolving GenAI landscape is needed.

The paradox of self-efficacy and technological dependence: Unraveling generative AI's impact on university students' task completion

In a world increasingly driven by technology, the field of creative content production stands on the initiative of a revolution. This paper explores the cutting-edge advancements in Generative Artificial Intelligence (GAI) & its profound impact on creative content creation. By leveraging the power of neural networks, GAI has the potential to transform how we generate, consume, and interact with creative works across various mediums. The paper begins by explaining the core principles of GAI, simplifying complex concepts for readers. It explores the fascinating world of neural networks, demonstrating how these intricate systems learn and replicate creative patterns and styles similar to human thinking. But the fascination doesn't end there. As the story progresses, the paper reveals the diverse benefits of GAI for creative professionals and enthusiasts alike. From transforming content creation processes to enabling personalized experiences and simplifying automation, the possibilities seem limitless. However, every technological wonder comes with its own set of challenges and considerations. This paper navigates through the ethical maze surrounding GAI, addressing concerns such as prejudices, copyright issues, and the intricate balance between human and artificial creativity. It advocates for responsible and moral practices in the use of GAI, ensuring that this potent tool is employed for the betterment of society. Yet, the most compelling feature lies in the introduction of a groundbreaking innovation: the "Investigate" algorithm. This algorithm, a culmination of advanced techniques including reinforcement learning and evolutionary optimization, promises to enhance GAI's impact by expanding the boundaries of neural network potential even further. It intrigues readers with the promising potential of a future where AI continuously improves itself, leading to the creation of increasingly sophisticated and innovative creative content. In conclusion, this paper calls upon readers to embark on a journey of discovery and innovation, inviting them to explore further into the realm of GAI's impact on creative content production. Through the examination of neural network potential and the moral considerations that come with it, we stand on the threshold of a new era in creativity and innovation.

The emergence of generative AI, particularly language models like ChatGPT, has revolutionized educational practices by enhancing lesson planning and fostering critical thinking. This systematic literature review investigates the application of generative AI in creating effective lesson plans and its broader role in improving the educational process. By synthesizing findings from multiple studies, this research highlights AI's ability to personalize learning, provide adaptive feedback, and simulate real-world scenarios, which collectively promote analytical and reflective thinking among students. Additionally, the integration of ethical considerations in AI-supported education fosters responsible use and critical evaluation of AI systems. Despite its potential, challenges such as ethical dilemmas, dependency on technology, and algorithmic biases remain significant. This study underscores the transformative role of generative AI in modern education, offering practical insights and recommendations for integrating AI tools effectively. The findings contribute to understanding AI's impact on pedagogy, student engagement, and the development of higher-order thinking skills, emphasizing the importance of a balanced approach that aligns AI capabilities with human.

We are confronted with the concept of intelligence every day. Starting with human intelligence to artificial intelligence. Some animals are also attested to be intelligent based on specific problems they solve. We also come across terms such as swarm intelligence, emotional intelligence or even physical intelligence. But there is still a lack of a clear definition of what intelligence actually is and, in particular, how it could be measured. Intelligence tests that provide quantitative information have so far only been available from psychology and only for people. There is a lack of criteria for what makes a system an intelligent system. This became particularly clear with the question of whether generative AI, such as ChatGPT, can be considered intelligent at all. So can intelligence be derived from the cognitive abilities of a system, or is it ultimately decisive how these abilities come about?This paper suggests a definition of the term intelligence and suggests an explanation for what constitutes intelligence and to what extent intelligence is required to gain knowledge. And finally it is questioned whether artificial systems are intelligent and have any knowledge at all.

The objective of this review was to map what is known about nurse manager emotional intelligence in relation to nurse job satisfaction and retention, and the tools used to measure emotional intelligence in this context. As the health care environment responds to the demands of high-quality and low-cost care, nurse managers must ensure that patient care environments are safe, efficient, and effective. Understanding nurse manager emotional intelligence may help organizations improve nurse satisfaction and retention as a strategy for reducing costs. This review considered experimental and quasi-experimental study designs, analytical observational studies, descriptive observational studies, systematic reviews and meta-analyses, qualitative studies, and text and opinion papers. Studies with staff nurses and experiences working with nurse managers were included. Studies that examined emotional intelligence of nurse managers, in any context, related to staff job satisfaction and retention in nursing and/or that discussed tools used to measure nurse managers' emotional intelligence were considered for inclusion. This review followed JBI methodology for scoping reviews. Key information sources searched included CINAHL (EBSCO), Health and Psychosocial Instruments (EBSCO), Scopus (Elsevier), EBSCO Health Source (EBSCO), JBI Database of Systematic Reviews and Implementation Reports (Ovid), ERIC (EBSCO), WorldWideScience (Worldwidescience.com), Wiley Online Library (Onlinelibrary.wiley.com), ProQuest Dissertations and Theses (ProQuest), MedNar (MedNar.com), Google Scholar (GoogleScholar.com), and ScienceDirect (Elsevier). Studies published in English from 1995 to September 2019 were included in the review. Two independent reviewers assessed titles and abstracts against the inclusion criteria. Studies that met the inclusion criteria were retrieved in full and assessed in detail. The data extraction tool was developed by the authors to examine information retrieved. Eight quantitative studies were included, all from the United States. The studies included 232 nurse manager participants and 3731 staff nurse participants from academic and non-academic hospitals. Seven of the eight studies used the Mayer-Salovey-Caruso Emotional Intelligence Test to measure nurse manager emotional intelligence, and one study used the Emotional Quotient Inventory 2.0. Of the eight included studies, six studies showed no significant relationship between emotional intelligence and nurse job satisfaction and/or retention, one revealed a positive correlation, and one revealed both positive and negative correlations. Limited research exists to determine whether nurse manager emotional intelligence plays a role in staff nurse job satisfaction and/or retention. All studies reported a need for further research, as well as the use of differing methodologies and a more diverse nursing population. This review may raise awareness among nurse managers as well as health care organizations about understanding and developing emotional intelligence.

Nursing course is a crucial period where the students need both physical and mentally support to cope up this dynamic transitional period of new independence from their parents. The nursing students have to encounter many problems to make successful adaptation during the life of stress. They cope up the changes in this period of transition in a healthy manner and if not can become a burden to them and put them into risk of negative health behaviors with tendency to be carry into their adulthood. Emotional intelligence and spiritual intelligence together with coping ability are seen to promote better health behavior. A quantitative descriptive study was conducted among 120 undergraduate nursing students who study in two different institutes were chosen through convenient sampling technique. Descriptive and inferential statics like independent t test was used to compare the levels of the Emotional intelligence, spiritual intelligence, coping ability of the nursing students of two institutes in Kannur. It is interpreted that spiritual intelligence can boost positive health behavior and it is associated with emotional intelligence and coping ability and have an important implication for both health practice and policy especially in nursing education institutions. This electronic document on emotional and spiritual intelligence of the nursing students in coping their life transitions was carried out with a view to promote healthy coping style in their professional and personal life by assessing and comparing the levels of emotional intelligence, spiritual intelligence and coping ability of nursing students in Kannur District.This study also emphasized the need for adopting emotional intelligence and spiritual intelligence in maintaining their resiliency throughout their life. Out of the 120 sample, majority of the sample both group one and two 56.66 % in first and 48.33 % in the second group had low levels of Emotional Intelligence, 51.66 % of the first group possess low level of spiritual intelligence whereas the 70% of the second group possess low levels of spiritual intelligence and both the two groups majority (90.66%) of the first group and 85% of the second group have low levels of resiliency or coping ability. Similarly, 73% of the first group and 70% of the second group have low resilience problem based coping ability. In case of emotional based coping ability majority of the first group (71.66%) were medium level of Resilient where as 61.66% of the sample of the second group have low level of resiliency.

This study explored patients’ perceptions of nurses and physicians’ emotional intelligence (EI) and their patient quality of care practices. By understanding EI and the role it plays in nurses and physicians interactions with patients, specialized training, and other initiatives can be developed to help improve the quality of patient care provided. This was a quantitative comparison study and used a survey questionnaires developed from the TEIQUE-SF and HCAHPS surveys to gage patients’ perceptions. The instrument used to analyze patient perceptions consisted of five patient descriptive categories. Of the five descriptive categories presented, only three were used. These three patient characteristic categories were used to determine if patients viewed their nurses and doctors’ EI differently. The study found patients saw their physicians as being more emotionally intelligent than their nurses. The group with the greatest variance when answering the survey was the 75 and older group. This group rated their nurses at a 3.05, but perceived their physicians to have a 3.23 EI rating. Patients in the 45 to 54 and 65 to 74 groups perceived their nurses to be more emotionally intelligent. Even though participants perceived their physicians as being more emotionally intelligent than their nurses, no significant difference existed between nurses and physicians’ EI when all groups were tested using a .05 level of significance.

Background: Emotional Intelligence has made a significant contribution to effective leadership, becoming one of the key characteristics of leaders.Objective: The aim of the present study was to review qualitative and quantitative studies concerning Emotional Intelligence of nurse leaders and the evidence-based composition of their results.Method:A search was performed in the electronic databases (Pubmed, Scopus and CINAHL) for articles, which were published in the period 2000-2017 in English or Greek. Eleven studies met the inclusion criteria, of which 10 were quantitative and one was qualitative.Results:The results suggested that Emotional Intelligence is a useful tool for nurse leaders and contributes decisively to the achievement of effective management in healthcare.Conclusion:It is necessary for nurses to improve their social and emotional skills because of the particular nature of the nursing profession, which places the healthy or weak person at its center.