Computers in human behavior reports最新文献

{"title":"Does digital grabbing boost affectivity in less empathic users? An interactive approach to affective laterality: Empathy, hand dominance, and action-context shape pleasantness experience","authors":"Sergio C. Torres","doi":"10.1016/j.chbr.2024.100568","DOIUrl":"10.1016/j.chbr.2024.100568","url":null,"abstract":"<div><div>This study investigates the interplay between dispositional empathy and emotional processing during embodied digital interactions. It builds upon the Spatial Affective Interaction (SAI) framework, which integrates neurobehavioral and cognitive perspectives on affective laterality, affective spatialization, and hand-proximity effects. The research particularly focuses on how lateralized manual interactions with emotional images (“emotional grabbing”) affect users’ pleasantness experiences. A sample of 240 right-handed participants used either their dominant right hand or non-dominant left hand to engage with 40 emotional images (20 pleasant and 20 unpleasant) using ipsilateral (same hand-side) or contralateral (opposite hand-side) interactions in a touchscreen environment. Key findings reveal asymmetries in pleasantness experiences that depend on hand dominance, ipsilateral interactions, and empathy levels. Specifically, participants reporting lower empathy associated increased pleasantness after using the dominant right hand to interact with right-positioned pleasant images. Conversely, interactions with left-positioned unpleasant images using the non-dominant left hand were associated with a heightened unpleasantness among low-empathy participants, with the opposite pattern observed in high-empathy individuals. These findings suggest that “emotional grabbing” may enhance sensitivity to emotional content in less empathic individuals, possibly by compensating an impaired activation of the action-observation network (AON), which integrates sensorimotor and empathy processes. The study underscores the relevance of considering hand dominance, emotional valence, and empathy in the future design of embodied digital interactions, to enhance emotional experiences of individuals with explicit empathy deficits.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"17 ","pages":"Article 100568"},"PeriodicalIF":4.9,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does AI adoption redefine financial reporting accuracy, auditing efficiency, and information asymmetry? An integrated model of TOE-TAM-RDT and big data governance","authors":"Saeed Awadh Bin-Nashwan ,&nbsp;Jackie Zhanbiao Li ,&nbsp;HaiChang Jiang ,&nbsp;Anas Rasheed Bajary ,&nbsp;Muhammad M. Ma'aji","doi":"10.1016/j.chbr.2024.100572","DOIUrl":"10.1016/j.chbr.2024.100572","url":null,"abstract":"<div><div>Accounting and auditing firms (AAFs) are experiencing a paradigm shift with the integration of artificial intelligence (AI), which has the potential to revolutionise important areas like fostering financial reporting accuracy, auditing efficiency, and diminishing information asymmetry. Yet, the effectiveness of AI adoption in achieving this goal is not guaranteed. Hence, this study aims to empirically explore what shapes AI adoption among AAFs, and what its potential role is in financial reporting accuracy, auditing efficiency, and information asymmetry. By applying a validated model of TOE-TAM-RDT and analysing using PLS-SEM, we found that AI adoption was shaped by competitive pressure, vendor ecosystem, top management support, relative advantage, AI readiness, and innovation climate. The adoption of AI-driven systems among AAFs exerted a positive impact on financial reporting accuracy, and auditing efficiency, while a negative impact on information asymmetry. Results further reveal a significant moderating effect of big data governance, demonstrating that proper management, quality, and ethical use of data within AAFs can amplify AI adoption benefits, boosting financial reporting accuracy, auditing efficiency, and mitigating information asymmetries between AAFs and stakeholders. These outcomes not only advance scholarly conversations on AI adoption in the financial and accounting landscape but also deliver actionable strategies for stakeholders to maximise AAFs’ benefits from this emerging revolutionary technology.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"17 ","pages":"Article 100572"},"PeriodicalIF":4.9,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Public sentiment and engagement on cybersecurity: Insights from Reddit discussions","authors":"Krishnashree Achuthan ,&nbsp;Sugandh Khobragade ,&nbsp;Robin Kowalski","doi":"10.1016/j.chbr.2024.100573","DOIUrl":"10.1016/j.chbr.2024.100573","url":null,"abstract":"<div><div>Cyber insecurity is recognized amongst the top severe global risks by the World Economic Forum.This study addresses a significant gap in our understanding of the social dynamics of public perception and online discourse related to cybersecurity, with a particular focus on how social media platforms shape and reflect public engagement. We employ sentiment analysis, topic modeling, and zero-shot text classification to analyze 33,893 news and user posts, along with the corresponding 194,591 news and user comments, across five subreddit discussion forums between 2012 and 2022. Through the lens of the Social Amplification of Risk Framework (SARF) and Protection Motivation Theory (PMT), we uncover patterns in topic engagement, emotional responses, community support, and the interplay of sentiment and comment types. Our findings reveal a complex landscape of public engagement with cybersecurity news, characterized by high interest in government surveillance, cyber warfare, and software vulnerabilities. Comments vary across topics, with technical advice dominating discussions, while skepticism and concern are prevalent in privacy-related areas. Community reactions tend towards critical engagement, with comments expressing concern, disappointment, and anger receiving high upvotes. Post sentiment weakly correlates with comment types, where more negative posts elicit increased expressions of concern, anger, and skepticism. The community's dynamic engagement with cybersecurity issues underscores the need for tailored communication strategies that acknowledge both emotional responses and the desire for practical solutions. This study contributes to an understanding of public engagement with cybersecurity issues on social media while offering insights for stakeholders seeking to foster informed, resilient, and engaged online communities.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"17 ","pages":"Article 100573"},"PeriodicalIF":4.9,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synthetic and natural face identity processing share common mechanisms","authors":"Kim Uittenhove ,&nbsp;Hatef Otroshi Shahreza ,&nbsp;Sébastien Marcel ,&nbsp;Meike Ramon","doi":"10.1016/j.chbr.2024.100563","DOIUrl":"10.1016/j.chbr.2024.100563","url":null,"abstract":"<div><div>Recent developments in generative AI offer the means to create synthetic identities, or deepfakes, at scale. As deepfake faces and voices become indistinguishable from real ones, they are considered as promising alternatives for research and development to enhance fairness and protect humans' rights to privacy. Notwithstanding these efforts and intentions, a basic question remains unanswered: Are natural faces and facial deepfakes perceived and remembered in the same way? Using images created via professional photography on the one hand, and a state-of-the-art generative model on the other, we investigated the most studied process of face cognition: perceptual matching and discrimination of facial identity. Our results demonstrate that identity discrimination of natural <em>and</em> synthetic faces is governed by the same underlying perceptual mechanisms: objective stimulus similarity and observers’ ability level. These findings provide empirical support both for the societal risks associated with deepfakes, while also underscoring the utility of synthetic identities for research and development.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"17 ","pages":"Article 100563"},"PeriodicalIF":4.9,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143146926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Zoom fatigue in review: A meta-analytical examination of videoconferencing fatigue's antecedents","authors":"David Beyea ,&nbsp;Chaeyun Lim ,&nbsp;Alex Lover ,&nbsp;Maxwell Foxman ,&nbsp;Rabindra Ratan ,&nbsp;Alex Leith","doi":"10.1016/j.chbr.2024.100571","DOIUrl":"10.1016/j.chbr.2024.100571","url":null,"abstract":"<div><div>As videoconferencing increasingly integrates with modern life, becoming a regular part of work, education, and socialization, the adverse outcomes of increased usage have become a concern to researchers. Multiple scholars have examined Videoconference Fatigue (VF) to identify the causes of this new phenomenon. However, research has revealed conflicting findings regarding the causes of VF, highlighting the need for a meta-analysis. The present study uses quantitative meta-analysis techniques to examine 56 VF antecedents across 38 quantitative studies to examine the extent antecedent variables may affect VF. We collected quantitative studies on VF from Google Scholar, Web of Science, and PsychINFO. The present study organizes and examines the antecedents using two conceptualizations of VF (Bailenson, 2021; Li &amp; Yee, 2022) and the Zoom Exhaustion and Fatigue (ZEF) scale (Fauv ille et al., 2021). We observed the largest effects on VF within the psychological factors category (<em>r</em> = 0.24, <em>k</em> = 28), with “feeling trapped” (<em>r</em> = 0.33, <em>k</em> = 5) being the largest predictor among uncategorized variables. The results for this study provide a map forward for research concerning negative facets of videoconferencing.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"17 ","pages":"Article 100571"},"PeriodicalIF":4.9,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ChatGPT in higher education - A Student's perspective","authors":"Ahmed Shuhaiber,&nbsp;Mohammad Amin Kuhail,&nbsp;Sinan Salman","doi":"10.1016/j.chbr.2024.100565","DOIUrl":"10.1016/j.chbr.2024.100565","url":null,"abstract":"<div><div>The purpose of this study is to assess the impact of factors influencing students' adoption of ChatGPT within the context of higher education. With the rapid expansion of its user base and its increasing utilization across various fields, there is a pressing need to comprehensively explore students' interactions and experiences with this innovative technology, a topic largely unaddressed in existing literature. This paper aims to identify the factors contributing to ChatGPT's rapid proliferation and to highlight its potential for reshaping higher education. To achieve our research objective, we extend the Unified Theory of Acceptance and Use of Technology (UTAUT2) with a quantitative approach. We collected data from a sample of 283 university students in the United Arab Emirates, employing a convenience sampling method. Our findings reveal significant impacts of students' trust, effort expectancy, performance expectancy, and hedonic motivation on their attitudes towards ChatGPT. Additionally, perceived risks and attitude towards ChatGPT significantly influence students' intentions to sustain its usage for educational purposes. Intriguingly, social influences were found to have no significant impact on students' intentions to engage with this AI-based chatbot. These findings have practical implications for the integration of ChatGPT in higher education. Educators and institutions should focus on building trust and enhancing students' perception of effort, performance, and hedonic aspects related to ChatGPT. Addressing perceived risks and fostering a positive attitude can promote sustained usage for educational purposes. This study contributes to the existing literature by shedding light on students' reception of ChatGPT in higher education, an underexplored area. The extension of UTAUT2 and the quantitative analysis provide a comprehensive framework for understanding the factors influencing students' attitudes and intentions regarding this technology. The findings offer valuable insights into the potential transformation of higher education through the adoption of AI-based chatbots like ChatGPT.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"17 ","pages":"Article 100565"},"PeriodicalIF":4.9,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Agreement between self-reported and objectively measured smartphone use among adolescents and adults","authors":"Kimberly M. Molaib ,&nbsp;Xiaoran Sun ,&nbsp;Nilam Ram ,&nbsp;Byron Reeves ,&nbsp;Thomas N. Robinson","doi":"10.1016/j.chbr.2024.100569","DOIUrl":"10.1016/j.chbr.2024.100569","url":null,"abstract":"<div><div>Almost everything we think we know about the prevalence, correlates, risks, and benefits of smartphone use is based on individuals’ self-reported estimates of use. Addressing the need for research on digital recall accuracy among adolescents and parents and for specific types of app use, in this study, we compared self-reports of past-month smartphone use and continuous objective digital trace data of smartphone use provided by 41 adolescents (M_age = 15.5, SD = 1.3, age range = 13–17 years, 56% female) and 40 parents of adolescents (M_age = 45.5, SD = 6.3, 75% mothers). Intraclass correlation coefficients (ICCs) between self-reported and objective measures of total daily use were moderate for adolescents (ICC = .65) and poor for adults (ICC = .18). Consistency between self-reported and objective use of particular types of apps varied widely, with ICCs ranging from .25 (games) to .73 (social media) among adolescents and from .26 (texting and YouTube) to .79 (games) among adults. Evidence did not support a recency bias in subjective estimates. These findings, along with prior research in other samples, make a strong case that it is time to abandon the use of self-report measures of smartphone use in research on its effects.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"17 ","pages":"Article 100569"},"PeriodicalIF":4.9,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing the play of sport and action-adventure game genres on heart rate and heart rate variability","authors":"Sarah C. Cregan ,&nbsp;Adam J. Toth ,&nbsp;Mark J. Campbell","doi":"10.1016/j.chbr.2024.100567","DOIUrl":"10.1016/j.chbr.2024.100567","url":null,"abstract":"<div><div>The ability to cope with stress is imperative for performance in competitive gaming, yet there is a lack of research examining the impact of gaming and esports participation on physiological stress. One way to measure physiological stress is via heart rate variability (HRV). The current literature examining HRV during competitive gaming is limited, with most studies focusing on multiplayer online battle arena games. To better understand the physiological demands of gaming, investigation into the stress imposed on players during gameplay of various game genres is required. In this study, we compared the physiological stress incurred on players who played either a competitive (sports) or a non-competitive (action-adventure) video game. Forty participants played either a sports or action-adventure game, whilst having their heart rate and heart rate variability monitored. Results showed that, compared to a pre-gaming baseline, playing either game increased heart rate, lowered RR intervals, and reduced both vagally mediated time and frequency domain vmHRV. Playing the sport game for 10 min induced higher heart rate and lower RR intervals compared to playing the action-adventure game. However, 10 min of game play was not enough to identify meaningful differences in vmHRV based on game genre played. These findings advance our understanding of the impact of video gaming on heart rate and heart rate variability, providing a useful method for coaches and players to index player stress and recovery.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"17 ","pages":"Article 100567"},"PeriodicalIF":4.9,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-directed writing development across computer/AI-based tasks: Unraveling the traces on L2 writing outcomes, growth mindfulness, and grammatical knowledge","authors":"Alaa Aladini ,&nbsp;Sayed M. Ismail ,&nbsp;Mohamad Ahmad Saleem Khasawneh ,&nbsp;Goodarz Shakibaei","doi":"10.1016/j.chbr.2024.100566","DOIUrl":"10.1016/j.chbr.2024.100566","url":null,"abstract":"<div><div>As technology continues to reshape the educational landscape, understanding how autonomous engagement with AI-driven platforms influences second language (L2) acquisition is increasingly important. This study examined the impact of self-directed writing development through computer- and AI-based tasks on L2 writing outcomes, growth mindfulness, and grammatical knowledge. The research was conducted in three private English institutes in Ahvaz, Iran, involving 561 intermediate-level EFL learners that were selected using a convenience sampling method. Using a quasi-experimental design, participants were divided into two groups: an experimental group (EG) of 276 students, which engaged in self-directed AI-based writing tasks, and a control group (CG) of 285 students, which followed traditional writing instruction. Quantitative data were gathered through pre- and post-tests measuring writing proficiency, growth mindfulness, and grammatical accuracy. Additionally, qualitative data were collected through interviews and questionnaires administered to the EG to assess their attitudes toward AI-based learning. The results indicated that the EG significantly outperformed the CG in writing outcomes and grammatical accuracy. Moreover, the EG demonstrated greater growth in mindfulness, with participants showing increased awareness of their writing processes and enhanced self-regulation strategies. Interviews and questionnaires revealed that participants in the EG held positive attitudes toward AI-based tasks, emphasizing increased engagement, autonomy, enjoyment, motivation, personalized learning, critical thinking, self-efficacy, time management, and collaboration in their English learning development. These findings underscore the potential of AI-based tasks in fostering both linguistic competence and metacognitive skills in L2 learners. The study provides valuable insights into the role of AI technologies in promoting independent learning and calls for further exploration of AI-based interventions in writing education.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"17 ","pages":"Article 100566"},"PeriodicalIF":4.9,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SC-PA: A spot-checking model based on Stackelberg game theory for improving peer assessment","authors":"Jia Xu (许嘉) ,&nbsp;Panyuan Yang (杨攀原) ,&nbsp;Teng Xiao (肖腾) ,&nbsp;Pin Lv (吕品) ,&nbsp;Minghe Yu (于明鹤) ,&nbsp;Ge Yu (于戈)","doi":"10.1016/j.chbr.2024.100556","DOIUrl":"10.1016/j.chbr.2024.100556","url":null,"abstract":"<div><div>During a peer assessment activity in teaching practices, students may not have sufficient motivation to review their peers’ submissions, which makes the peer assessment results questionable. To this end, this paper proposes a novel spot-checking based peer assessment model, named SC-PA, to improve students’ motivation in peer assessment. In SC-PA, a peer assessment activity is modeled as a Stackelberg game, where the teacher acts as the leader and the students are followers. Submissions spot-checked and graded by teachers are treated as review resources, which are allocated among students based on their review reliabilities. In particular, to ensure the utilities of both of the teachers and students, an algorithm that computes the optimal allocation plan for review resources is carefully designed based on Stackelberg equilibrium. Then, different from the classical spot-checking model, the spot-checking probability status of each student which is determined by the allocation plan is shown to the student. Such a difference intuitively puts pressure on students to be spot-checked by teachers, so as to give full play to the role of spot-checking in enhancing students’ motivation in carefully grading their peers’ submissions. To the best of our knowledge, this is the first attempt to treat a spot-checking based peer assessment as a Stackelberg game and utilize the gaming confrontations between teachers and students to improve the students’ motivation in peer assessment. An empirical study involving 271 students from two computer science courses and lasting approximately one year was conducted to investigate the accuracy of peer assessment, as well as the incentive and learning perception of students in peer assessment. Significant findings from the empirical study and a comparison with baselines include: by showing students the spot-checking probabilities, the students’ motivation in carefully grading their peers’ submissions and the fairness of peer assessment are both apparently enhanced; compared with the best baseline, the accuracy of the SC-PA model for peer assessment is improved by 44.1%; although the accuracy of peer assessment can be improved by increasing the number of review resources, the performance gain may become insignificant when the number of resources exceeds a certain limit in real teaching practices; and most students believe that their assessment ability can be effectively improved after multiple peer assessment activities. In conclusion, the SC-PA model successfully enhances students’ motivation for peer assessment, and improves their performance in terms of the assessment accuracy, self-determination, and self-efficacy</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"17 ","pages":"Article 100556"},"PeriodicalIF":4.9,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}