Computers in Human Behavior最新文献

{"title":"Willingness to use home-care robots and views regarding the provision of personal information in Japan: comparison between actual or potential users and robot developers","authors":"Yumi Akuta ,&nbsp;Sayuri Suwa ,&nbsp;Tatsuhito Kamimoto ,&nbsp;Hiroo Ide ,&nbsp;Ayano Inuyama ,&nbsp;Naonori Kodate ,&nbsp;Atsuko Shimamura ,&nbsp;Kieko Iida ,&nbsp;Akiyo Yumoto ,&nbsp;Nana Kawakami ,&nbsp;Sachiho Jitsuisihi ,&nbsp;Mayuko Tsujimura ,&nbsp;Mina Ishimaru ,&nbsp;Satoko Suzuki ,&nbsp;Shunsuke Doi ,&nbsp;Ayano Sakai ,&nbsp;Seiko Iwase ,&nbsp;Wenwei Yu","doi":"10.1016/j.chb.2025.108817","DOIUrl":"10.1016/j.chb.2025.108817","url":null,"abstract":"<div><div>Japan has the world's fastest ageing population. In 2024, people aged 65 and older accounted for 29.3 % of the population. Many of these people require long-term care, and a shortage of 570,000 care workers is projected by 2040. Home-care robots are expected to reduce caregiver burden and support older adults' independence. Widespread adoption requires collaboration among policymakers, healthcare professionals, and the robotics industry to ensure users' dignity and privacy.</div><div>This study surveyed the willingness to use home-care robots and provide personal information from the perspective of actual or potential users (older adults, family caregivers, care staff) and employees of companies developing such robots. A total of 4786 questionnaires were distributed to 6 users groups and 10 companies, yielding 1122 user and 83 developer responses. Data were analyzed using univariate and multivariate regression.</div><div>The findings indicate that actual or potential users’ willingness to use home-care robots was influenced by age, receipt of care, interest in robot-related news, and motivation to contribute to society. In contrast, developers prioritised safety and privacy protection. Both groups were influenced by “openness to using robots” and “openness to use them even during the research and development stage”. Furthermore, 80 % of actual or potential users agreed to share personal information with medical and care professionals, and 40–50 % with development companies, for research and development purposes.</div><div>This study concludes that a collaborative ecosystem involving all stakeholders, aligned with ethical principles and shared interests, is essential for the successful development and implementation of home-care robots.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"174 ","pages":"Article 108817"},"PeriodicalIF":8.9,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145333644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of a robot's agreement (or disagreement) on human-human interpersonal closeness in a two-person decision-making task","authors":"Ting-Han Lin ,&nbsp;Yuval Rubin Kopelman ,&nbsp;Madeline Busse ,&nbsp;Sarah Sebo ,&nbsp;Hadas Erel","doi":"10.1016/j.chb.2025.108807","DOIUrl":"10.1016/j.chb.2025.108807","url":null,"abstract":"<div><div>Robots and artificial agents are becoming increasingly integrated into our lives and show promise in assisting people in decision-making tasks. Despite their advantages, robot-assisted decision-making systems may have negative effects on the relationships between human team members. In this work, we examine the influence of the robot's agreement (or disagreement) on the interpersonal closeness between two participants in a two-person decision-making task. We test the robot's impact in two experiments: Experiment 1 (N = 172, 86 pairs) with a High Anthropomorphism Robot and Experiment 2 (N = 150, 75 pairs) with a Low Anthropomorphism Robot. For both experiments, we use a 2 x 2 study design to examine how the perceived interpersonal closeness between two participants was influenced by two aspects of robot behavior, namely <em>the valence of the robot's feedback</em> (positive feedback or negative feedback) and <em>the treatment of the two participants</em> (equal treatment or unequal treatment). Our results demonstrate that interacting with the High Anthropomorphism Robot led to greater interpersonal closeness between participants when the robot provided positive feedback as opposed to negative feedback. The Low Anthropomorphism Robot had a different and opposite effect: interactions with this robot led to greater interpersonal closeness when the robot's feedback was equal as opposed to unequal and when the robot provided negative feedback as opposed to positive feedback. Our results indicate that robots can shape human-human relationships when indicating their agreement with people's perspectives in two-person decision-making tasks and that the robot's influence depends on its appearance and communication style.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"174 ","pages":"Article 108807"},"PeriodicalIF":8.9,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Political Content Engagement Model: A large-scale analysis of TikTok political video content features and audience engagement","authors":"Zicheng Cheng ,&nbsp;Yanlin Li","doi":"10.1016/j.chb.2025.108808","DOIUrl":"10.1016/j.chb.2025.108808","url":null,"abstract":"<div><div>TikTok has emerged as a prominent platform for political information dissemination, where traditional news organizations, political figures, grassroots organizations, and influencers engage audiences on political and civic issues. However, limited research has systematically examined why politically oriented TikTok videos attract engagement. This study introduces the Political Content Engagement Model (PCEM), which explains how political identity, content features, content sources, and topic issues influence engagement. Using a dataset of 578,420 TikTok videos posted by 9722 elite accounts, we use machine learning and topic modeling to analyze how features such as political party references, issue framing, justification, sentiment, civility, and mobilization appeals affect video engagement. Besides, we investigate differences in engagement patterns between liberal- and conservative-leaning TikTok accounts and differentiate between internal and external engagement behaviors. Across both liberal and conservative accounts, civility level and out-party critique consistently emerge as the most powerful predictors of political TikTok video engagement. Our findings contribute to the field of digital political communication by offering insights into TikTok users’ political engagement behavior on TikTok and how different content strategies drive audience interactions.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"174 ","pages":"Article 108808"},"PeriodicalIF":8.9,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Malicious insider threats in cybersecurity: A fraud triangle and Machiavellian perspective","authors":"Chelsea Idensohn ,&nbsp;Stephen Flowerday ,&nbsp;Karl van der Schyff ,&nbsp;Yi Ting Chua","doi":"10.1016/j.chb.2025.108809","DOIUrl":"10.1016/j.chb.2025.108809","url":null,"abstract":"<div><div>Malicious insiders remain among the most persistent cybersecurity concerns, yet existing frameworks often overlook the psychological predispositions that drive unethical intent. This study examines how Machiavellianism, a dark personality trait characterized by manipulation, strategic self-interest, and moral disengagement, influences the elements of the well-established criminological framework of the Fraud Triangle to shape insider threat intention. Using a sample of 768 full-time U.S.-based employees and partial least squares structural equation modeling (PLS-SEM), the analysis investigates how Machiavellianism affects perceptions of pressure, opportunity, and rationalization. Results reveal that Machiavellianism significantly influences all three constructs, with rationalization emerging as the strongest and most significant pathway to the intention to commit malicious insider behavior. These findings highlight how individuals high in Machiavellianism cognitively justify unethical actions, positioning rationalization as a key psychological mechanism in threat formation. Theoretically, this study extends insider threat literature by demonstrating the relevance of personality traits, specifically Machiavellianism, in shaping key situational perceptions. It advances understanding of the Fraud Triangle by emphasizing justification not merely as a cognitive condition, but as a pivotal mechanism through which individuals justify malicious intent. By integrating a dark personality trait into a situational framework, this study refines our understanding of how insider threats emerge and supports more behaviorally informed approaches to cybersecurity risk modeling.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"174 ","pages":"Article 108809"},"PeriodicalIF":8.9,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Psychological insights into enhanced online learning: Investigating the role of Danmaku interaction and cognitive styles","authors":"Lei Han ,&nbsp;Chunze Xu ,&nbsp;Mengshi Xiao ,&nbsp;Qing Lv ,&nbsp;Li Wang ,&nbsp;Zhong Liu ,&nbsp;Fengqiang Gao ,&nbsp;Yanwei Dang ,&nbsp;Min Jou","doi":"10.1016/j.chb.2025.108802","DOIUrl":"10.1016/j.chb.2025.108802","url":null,"abstract":"<div><div>Danmaku, as an emerging mode of interaction, is widely used in online video learning. It is therefore crucial to understand how Danmaku influences learning experiences. Previous studies found that Danmaku fosters a collaborative atmosphere, enhancing students’ attention and motivation. However, research on how Danmaku affects learners with different cognitive styles remains limited, particularly regarding how matching Danmaku properties with cognitive styles influences outcomes.</div><div>This study addresses these issues through two experiments. By examining the effects of Danmaku presentation style and display area on learning outcomes of learners with different cognitive styles, we found that presentation formats and display areas had significantly different impacts on learning perceptions and cognitive load among field-dependent and field-independent learners.</div><div>The findings underscore the importance of adapting Danmaku settings to accommodate learner differences. They further emphasize the necessity of considering cognitive styles in designing online learning environments and provide recommendations for teaching platforms on how to optimize Danmaku to enhance learning outcomes. The main contributions of this study are as follows.<ul><li><span>1</span><span><div>Reveals how Danmaku presentation and display area influence learners with different cognitive styles.</div></span></li><li><span>2</span><span><div>Extends ternary interactive learning theory to online educational technology.</div></span></li><li><span>3</span><span><div>Offers evidence-based guidelines for optimizing Danmaku features.</div></span></li><li><span>4</span><span><div>Promotes personalized, learner-centered instructional strategies.</div></span></li></ul></div><div><ul><li><span>1</span><span><div>Reveals how Danmaku presentation and display area influence learners with different cognitive styles.</div></span></li><li><span>2</span><span><div>Extends ternary interactive learning theory to online educational technology.</div></span></li><li><span>3</span><span><div>Offers evidence-based guidelines for optimizing Danmaku features.</div></span></li><li><span>4</span><span><div>Promotes personalized, learner-centered instructional strategies.</div></span></li></ul></div><div>Overall, this study demonstrates how Danmaku properties can be effectively leveraged in online learning and provides both theoretical and practical guidance for enhancing learning effectiveness, advancing platform development, and supporting student success.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"174 ","pages":"Article 108802"},"PeriodicalIF":8.9,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145333641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Facial emotion recognition from feature loss media: Human versus machine learning algorithms","authors":"Diwakar Y. Dube ,&nbsp;Mathy Vandhana Sannasi ,&nbsp;Markos Kyritsis ,&nbsp;Stephen R. Gulliver","doi":"10.1016/j.chb.2025.108806","DOIUrl":"10.1016/j.chb.2025.108806","url":null,"abstract":"<div><div>The automatic identification of human emotion, from low-resolution cameras is important for remote monitoring, interactive software, pro-active marketing, and dynamic customer experience management. Even though facial identification and emotion classification are active fields of research, no studies, to the best of our knowledge, have compared the performance of humans and Machine Learning Algorithms (MLAs) when classifying facial emotions from media suffering from systematic feature loss. In this study, we used singular value decomposition to systematically reduce the number of features contained within facial emotion images. Human participants were then asked to identify the facial emotion contained within the onscreen images, where image granularity was varied in a stepwise manner (from low to high). By clicking a button, participants added feature vectors until they were confident that they could categorise the emotion. The results of the human performance trials were compared against those of a Convolutional Neural Network (CNN), which classified facial emotions from the same media images. Findings showed that human participants were able to cope with significantly greater levels of granularity, achieving 85 % accuracy with only three singular image vectors. Humans were also more rapid when classifying happy faces. CNNs are as accurate as humans when given mid- and high-resolution images; with 80 % accuracy at twelve singular image vectors or above. The authors believe that this comparison concerning the differences and limitations of human and MLAs is critical to (i) the effective use of CNN with lower-resolution video, and (ii) the development of useable facial recognition heuristics.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"174 ","pages":"Article 108806"},"PeriodicalIF":8.9,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wealth, digital overuse, and the changing landscape of digital inequality","authors":"Soyoung Park","doi":"10.1016/j.chb.2025.108805","DOIUrl":"10.1016/j.chb.2025.108805","url":null,"abstract":"<div><div>Wealth has long influenced digital inequality by shaping access to and benefits from technologies, yet its role in digital overuse—characterized by perceived dissatisfaction and negative consequences rather than mere screen time—remains underexplored. This study investigates the relationship between income and digital overuse, using data from the 2019–2022 Korean Smartphone Overuse Survey, with 101,625 respondents. Digital overuse is both defined and assessed in terms of self-control failure, behavioral salience, and negative after-effects, analyzed using quantile regression across income percentiles. This study examines whether the unintended consequences of digital engagement, like overuse, are also stratified along socioeconomic lines—just as the benefits of technology have been. To explore this, we test two hypotheses in the context of COVID-19: the Affluence Dependency Hypothesis, which suggests that affluent individuals are more prone to digital overuse due to greater access, and the Resourceful Autonomy Hypothesis, which posits that higher-income individuals are better able to regulate their usage. Results indicate that while affluent individuals exhibited higher overuse during the pandemic, this effect diminished by 2022, suggesting a recovery of control. By extending the discussion of digital inequality beyond access and benefits to include overuse, this study expands the landscape of digital inequalities, revealing a new form of stratification in which economic resources shape not only digital advantages but also the ability to mitigate digital risks.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"174 ","pages":"Article 108805"},"PeriodicalIF":8.9,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A study of danmu: Detecting emotional coherence in music videos through synchronized EEG analysis","authors":"Yuqing Liu ,&nbsp;Bu Zhong ,&nbsp;Jiaxuan Wang ,&nbsp;Yao Song","doi":"10.1016/j.chb.2025.108803","DOIUrl":"10.1016/j.chb.2025.108803","url":null,"abstract":"<div><div>A novel approach is essential to assess viewers' emotional responses to online music videos, as the emotional coherence between perceived and induced reactions has not been thoroughly explored. This research investigates the relationship between perceived and induced emotional responses to music videos through a unique multimodal framework that integrates electroencephalography (EEG) analysis with natural language processing to examine danmu—user-generated scrolling marquee comments synchronized to specific playback times. Employing a time-synchronized methodology, our deep learning model predicted continuous emotional scores from EEG signals based on danmu sentiment. The findings revealed an over 80 % similarity between the two forms of induced emotional data: EEG-derived emotion curves and danmu sentiment curves across five music videos. We explored periods of divergence by contrasting peak emotional responses during the climaxes of the music, highlighting the significant influence of the multimodal sentiment tone on the alignment between neurophysiological and behavioral emotional trajectories. This study uncovers the coherence between emotion curves derived from EEG and danmu data—a methodology that notably diverges from traditional reliance on self-reports or surveys. The partial consistency observed between perceived and induced emotions, along with the effects of emotional valence and arousal on brain-behavior synchronization, underscores the shared nature of emotions elicited by music videos. Contributing factors include the diversity of emotional experiences and expressions among individuals, as well as the intrinsic rhythmicity within music videos, both of which enhance emotional elicitation.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"174 ","pages":"Article 108803"},"PeriodicalIF":8.9,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145222678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Embracing the Metaverse: User perception and acceptance of the Metaverse in education","authors":"Patricia Baudier ,&nbsp;Tony De Vassoigne ,&nbsp;Mitra Arami ,&nbsp;Arnaud Delannoy ,&nbsp;Rony Germon","doi":"10.1016/j.chb.2025.108804","DOIUrl":"10.1016/j.chb.2025.108804","url":null,"abstract":"<div><div>The COVID-19 crisis accelerated the development of virtual educational tools, including immersive virtual technologies. This study explores the perception and acceptance of Metaverse use in education among individuals with prior experience. A quantitative approach was applied using the METAEDU scale and the Technology Acceptance Model (TAM). As one of the first studies to validate the METAEDU scale, it offers a reliable tool to measure user acceptance. A total of 315 participants were surveyed in January 2024 through a market research platform. Data were analyzed using SmartPLS4 software. Results confirmed: (1) certain METAEDU variables significantly impact perceived ease of use (PEOU) and perceived usefulness (PU); (2) attitude (AT) and creative thinking (CT) influence behavioral intention to use (BITU); (3) PEOU and PU affect AT; and (4) age, gender, and education level act as moderating factors. These findings have important implications for educational institutions adapting to evolving student needs. Validating the METAEDU scale highlights the importance of diverse learning dimensions and provides a robust tool for evaluating the effectiveness and accessibility of Metaverse-based education. Institutions should focus on applications that are both pedagogically valuable and personally engaging for students. <span>Furthermore</span>, demographic differences reveal nuanced variations in adoption, emphasizing the need for customized strategies to support diverse user groups. By understanding these factors, educational organizations can better design and implement virtual learning environments, ultimately enhancing the overall educational experience and fostering greater acceptance of emerging technologies.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"173 ","pages":"Article 108804"},"PeriodicalIF":8.9,"publicationDate":"2025-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Substitution or augmentation? How organisational AI adoption approaches influence the willingness to stay of caregivers","authors":"Li Jiang ,&nbsp;Xuli Wang ,&nbsp;Yuguang Xie ,&nbsp;Junhong Zhu ,&nbsp;Dongxiao Gu","doi":"10.1016/j.chb.2025.108801","DOIUrl":"10.1016/j.chb.2025.108801","url":null,"abstract":"<div><div>In the care sector, the application of artificial intelligence (AI) has become a key strategy to alleviate workforce shortages. However, systematic research is still lacking on the differential effects of different AI adoption approaches on caregivers' willingness to stay and their underlying mechanisms. This study uses job demands-resources theory as basis to develop a dual-path model to explore the differences between AI augmentation and AI substitution in influencing caregivers' willingness to stay. Results of two experiments indicate that AI augmentation has a significantly stronger positive effect on willingness to stay than AI substitution, with the resource gain pathway of ‘self-efficacy–job satisfaction’ playing a partial mediating role. AI substitution also significantly enhances willingness to stay (compared with scenarios without AI), and its effect is mediated by the resource gain and job demand pathways of ‘identity threat–emotional exhaustion’. Additionally, AI learning anxiety significantly weakens the positive effects of both AI adoption approaches, whilst job replacement anxiety only negatively moderates the effect of AI substitution. This study provides a markedly nuanced theoretical perspective for research on organisational AI adoption and offers practical insights into the practical application of AI in the care sector.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"174 ","pages":"Article 108801"},"PeriodicalIF":8.9,"publicationDate":"2025-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}