Computers in Human Behavior最新文献

{"title":"Mapping the symptom structure of internet gaming disorder among adolescents: Insights from network and Bayesian graph analyses","authors":"Firoj Al-Mamun ,&nbsp;Moneerah Mohammad ALmerab ,&nbsp;Mohammed A. Mamun","doi":"10.1016/j.chb.2025.108890","DOIUrl":"10.1016/j.chb.2025.108890","url":null,"abstract":"<div><div>Internet Gaming Disorder (IGD) has become an emerging public health concern among adolescents, particularly in low-resource setting. Despite growing international interest, little is known about how IGD symptoms interact and reinforce one another in these contexts. This study aimed to elucidate the symptom structure of IGD among Bangladeshi adolescents. Specifically, to (i) estimate the undirected network structure of IGD symptoms, (ii) identify central and predictable symptoms, (iii) examine gender-based differences in network structure, and (iv) explore directional symptom pathways using Bayesian Directed Acyclic Graphs (DAGs). A cross-sectional survey was conducted among 1030 secondary school students in northern Bangladesh. Data were collected using the nine-item Internet Gaming Disorder Scale–Short Form (IGDS9-SF), while both regularized partial correlation networks and DAGs were estimated to examine symptom associations and potential directional pathways. Subgroup comparisons by gender were conducted using the Network Comparison Test (NCT). The undirected network revealed strong conditional associations among core IGD symptoms, particularly between <em>Preoccupation</em>, <em>Tolerance</em>, and <em>Withdrawal</em>. Centrality analyses identified <em>Give Up Activities</em>, <em>Withdrawal</em>, and <em>Preoccupation</em> as the most structurally important symptoms, and predictability estimates indicated strong local symptom connectivity. The NCT showed no significant differences in network structure or global strength between males and females. DAG analysis highlighted <em>Withdrawal</em> as a likely initiating symptom, with strong probable directional paths toward <em>Tolerance</em>, <em>Loss of Control</em>, and <em>Continued Use</em>. These findings provide symptom-level insights into IGD's psychopathological structure and offer guidance for targeted, school-based mental health interventions in resource-constrained settings.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"177 ","pages":"Article 108890"},"PeriodicalIF":8.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737243","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":"From facial expressions to academic performance: Affective computing reveals the serial mediating roles of emotional valence and self-regulated learning","authors":"Ruchang Miao ,&nbsp;Peijia Yang ,&nbsp;Shuna Li ,&nbsp;Kaizhen Kong ,&nbsp;Xiangting Wang","doi":"10.1016/j.chb.2025.108902","DOIUrl":"10.1016/j.chb.2025.108902","url":null,"abstract":"<div><div>The rapid advancement of technology in education has drawn increased scholarly attention to the role of affective factors in student development. Although prior research has primarily examined the relationship between affective strategies and academic achievement, limited attention has been paid to the dynamic quantification of affective processes and their underlying mechanisms. This study employed affective computing technology to analyze students’ facial expressions, captured by live classroom cameras, on a frame-by-frame basis. The analysis quantified temporal fluctuations in emotional valence and examined the distribution patterns of positive, neutral, and negative emotions during classroom learning. Participants were 183 college students who were recorded during class and completed a questionnaire. The results revealed significant positive correlations among affective strategies, emotional valence, self-regulated learning (SRL), and academic performance. Furthermore, chain mediation analysis demonstrated that affective strategies predicted academic performance only indirectly through the serial mediation of emotional valence and SRL, with no significant direct effect being observed. Notably, emotional valence did not exhibit an independent mediating effect, underscoring its role as part of a sequential psychological mechanism rather than a standalone pathway.By extending the application of Achievement Emotions Theory (AET) to the context of Ideological and Political Theory Courses, this study addresses several limitations inherent in traditional self-report methods through the use of affective computing. The findings provide preliminary empirical support for designing personalized interventions in these specific courses and highlight the potential of affective computing to advance the development of intelligent educational technologies.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"177 ","pages":"Article 108902"},"PeriodicalIF":8.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884552","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":"Bridging or broadening Gaps? AI-Assisted professional writing among native and non-native English Writers","authors":"Inyoung Shin ,&nbsp;Hyesun Choung ,&nbsp;Mina Choi","doi":"10.1016/j.chb.2025.108897","DOIUrl":"10.1016/j.chb.2025.108897","url":null,"abstract":"<div><div>This study examines how AI influences existing differences in professional writing between native and non-native English writers (NEWs and NNEWs) in the United States, reflecting individuals’ task-related proficiency and language-based social positioning. We compare how these two groups integrate AI-generated content into their writing and include writing self-efficacy as a moderator to examine whether perceived task proficiency shapes the differences in AI use between the two groups. We also test an underlying social-psychological mechanism by examining the mediating role of perceived superiority: the extent to which participants judged the AI-generated text as better than their own writing. In an online experiment, 327 NEWs and NNEWs were recruited to write a job application cover letter for a hypothetical scenario. Participants were randomly assigned to receive AI-generated content written at either a simple or advanced lexical level and were asked to revise their letter as they chose, potentially incorporating the AI-generated content. Using natural language processing techniques, we measured the extent to which participants integrated AI-generated content. Findings show that NNEWs favored simpler content, while NEWs tended to incorporate advanced content. This difference was pronounced among those with lower writing self-efficacy. However, the perceived superiority of AI-generated text did not explain this pattern. These findings show that while AI can support lower-skilled groups in specific tasks, sociolinguistic gaps still remain even with AI-assistance. We conclude by calling for AI training frameworks that scaffold learning to address both proficiency gaps and social constraints.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"177 ","pages":"Article 108897"},"PeriodicalIF":8.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884555","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":"Personalizing explanations in AI-based decisions: The effects of personalization and (mis)aligning with individual preferences","authors":"Richard Uth ,&nbsp;Nelli Niemitz ,&nbsp;Isabel Valera ,&nbsp;Markus Langer","doi":"10.1016/j.chb.2025.108854","DOIUrl":"10.1016/j.chb.2025.108854","url":null,"abstract":"<div><div>The increasing reliance on AI-based decision-making in high-stakes contexts underscores the need for transparency and justice. Here, negative outcomes drive individuals affected by AI-based decisions to seek actionable explanations that enable them to realize what they can do to achieve a better future outcome. However, actionability is subjective, varying across individuals and contexts. Personalization of explanations has been proposed to address this variability, but insights on personalized explanation processes, their potential, and challenges are scarce. This paper investigates the impact of personalization and (mis)alignment with individual needs and preferences in explanations for AI-based decisions through an experimental online study simulating denied loan applications. In a within-participants design (<em>N</em> <span><math><mo>=</mo></math></span> 255), participants ranked the actionability of decision-relevant features and experienced five explanation conditions: personalized directive explanations based on the most, second most, or least actionable feature (as ranked by participants); a non-personalized directive explanation highlighting a random feature; and no explanation. In line with justice theory, our results show that any explanation was better than none, and that personalized explanations led to more favorable reactions than non-personalized explanations, enhancing perceptions of justice and attractiveness of the bank. Closer alignment with preferences had only small positive effects, mainly for attractiveness. These findings highlight that even simple ranking-based approaches can make explanations more effective and accessible without requiring technical expertise while cautioning against offering superficial control. This study provides insights into the effects of ranking-based personalization, informing the design of explainability tailored to diverse user needs and addressing ethical and practical considerations in personalization.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"177 ","pages":"Article 108854"},"PeriodicalIF":8.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685065","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":"Association between school phone restriction policies and adolescents’ cyberbullying, gambling, and substance use behaviors","authors":"Szu-Chia Chen ,&nbsp;Tzu-Fu Huang ,&nbsp;Kevin Chang ,&nbsp;Fong-Ching Chang ,&nbsp;Shawn C. Chiang ,&nbsp;Chiung-Hui Chiu ,&nbsp;Ping-Hung Chen ,&nbsp;Nae-Fang Miao ,&nbsp;Hung-Yi Chuang","doi":"10.1016/j.chb.2025.108898","DOIUrl":"10.1016/j.chb.2025.108898","url":null,"abstract":"<div><h3>Background</h3><div>Adolescents are increasingly exposed to online risks in the digital era, yet few studies have examined how school phone restriction policies relate to these risks. This study aimed to investigate the association between school phone restriction policies and adolescents’ online risk exposure and engagement in online risk behaviors, including cyberbullying, online gambling, and substance use.</div></div><div><h3>Methods</h3><div>A cross-sectional survey was conducted in 2022 among 3158 high school students from 35 schools in Taiwan. Students reported their perceptions of school phone restriction policies, online risk exposure, and engagement in risk behaviors. Generalized estimating equation (GEE) models were used to examine these relationships.</div></div><div><h3>Results</h3><div>Compared with students who reported that their schools had phone restriction policies, those who perceived their schools as lacking such policies reported greater online risk exposure (i.e., longer smartphone use time, more frequent risky loot box engagement, and greater online marketing exposure) and higher rates of risk behaviors (i.e., cyberbullying, online gambling, and alcohol and tobacco use). GEE multivariate analyses indicated that perceiving schools as having no phone restriction policies was significantly associated with greater online risk exposure. Furthermore, students who perceived an absence of phone restriction policies and reported higher online risk exposure were more likely to engage in risk behaviors.</div></div><div><h3>Conclusion</h3><div>School phone restriction policies may serve as a protective factor by reducing adolescents’ online risk exposure and limiting their involvement in cyberbullying, online gambling, and substance use.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"177 ","pages":"Article 108898"},"PeriodicalIF":8.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884556","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":"Does transparency matter when an AI system meets performance expectations? An experiment with an online dating site","authors":"Yuan Sun ,&nbsp;Mengqi (Maggie) Liao ,&nbsp;S. Shyam Sundar ,&nbsp;Joseph B. Walther","doi":"10.1016/j.chb.2025.108875","DOIUrl":"10.1016/j.chb.2025.108875","url":null,"abstract":"<div><div>Powered by sophisticated algorithms, artificial intelligence (AI) systems are notorious for being opaque, prompting demands for more algorithmic transparency. However, empirical evidence reveals inconsistent effects of transparency on user trust, suggesting critical boundary conditions. Drawing on the Expectation Confirmation Model and Heuristic-Systematic Model, we propose that the effectiveness of providing algorithmic transparency depends on whether the AI system’s performance meets, exceeds, or falls short of users’ expectations. We tested this through a 3 (Algorithmic transparency: high vs. low vs. absent) × 3 (Expectation confirmation: positive vs. simple vs. negative) between-subjects online experiment (<em>N</em> = 227), in which participants interacted with an online dating site driven by date-matching algorithms. Results revealed that detailed algorithmic explanations enhanced perceived understanding and trust when system performance either exceeded or fell short of expectations, while concise explanations proved more effective when performance met expectations. These findings advance our theoretical understanding of algorithmic transparency and provide practical implications for designing adaptive explainable AI systems that adjust transparency levels based on performance outcomes.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"177 ","pages":"Article 108875"},"PeriodicalIF":8.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610124","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":"Choose to think: Nudging towards privacy informed decisions at the app download stage","authors":"Jennifer Klütsch ,&nbsp;Verena Zimmermann ,&nbsp;Sabine J. Schlittmeier","doi":"10.1016/j.chb.2025.108895","DOIUrl":"10.1016/j.chb.2025.108895","url":null,"abstract":"<div><div>Downloading apps can pose significant privacy risks to users. While users are aware that their data is privacy-sensitive, they often do not read the privacy information provided. To support informed privacy decisions at the app download stage, we evaluated a two-stage nudge intervention in our scenario-based online study with 209 German-speaking Clickworker participants. In Stage 1, we examined whether nudges (color, reminder, social minority, social majority), compared to a control condition, can increase users’ engagement with privacy information in the app store. Once they have decided to engage, we examined how the recommendation of friends (vs. the app store) and the privacy rating (low vs. high) of a hybrid nudge with additional privacy information affected the subsequent download decision in Stage 2. Due to almost perfect separation in Stage 2, Bayesian logistic regressions were conducted. Our results found no evidence that any particular type of nudge increased the likelihood of users to engage with privacy information in Stage 1. Yet, all nudges, including the control condition, led high percentages of participants to click <em>more about data protection</em> (between 48.81% and 64.13%), with the subsequent privacy information in Stage 2 being considered a particularly important decision criterion for them. A “mere-exposure” and “foot-in-the-door” effect in our two-stage approach are discussed as possible explanations. Based on our findings, we derive recommendations for the design of privacy nudges that can be implemented by the app store or personal privacy assistants to promote informed privacy decisions.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"177 ","pages":"Article 108895"},"PeriodicalIF":8.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790367","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":"Negative perceptions of outsourcing to artificial intelligence","authors":"Scott Claessens,&nbsp;Pierce Veitch,&nbsp;Jim A.C. Everett","doi":"10.1016/j.chb.2025.108894","DOIUrl":"10.1016/j.chb.2025.108894","url":null,"abstract":"<div><div>As artificial intelligence (AI) tools become increasingly integrated into daily life, people are beginning to outsource not only professional tasks but also socio-relational ones. Large language models like ChatGPT can generate wedding vows, speeches, and personal messages, raising questions about how individuals who use AI for such tasks are perceived by others. In this paper, we conduct six pre-registered studies with British participants (N = 3935) to understand how people view those who expend less effort by outsourcing tasks to AI in different ways. We highlight a tradeoff between efficiency and inferred moral character, authenticity, and value: outsourcing makes us think more negatively about not only the person and their motivations, but also the outsourced work itself. Importantly, this effect is not uniform. Reduced effort does not consistently lead to domain-general negative character perceptions across all tasks, but has particularly negative effects for outsourcing socio-relational tasks. Our results suggest that reduced effort is important not only because people value time and energy spent, but because expending less effort through outsourcing signals second-order perceptions that people are being less authentic and care less about the task. Our research highlights how relying on AI shapes our perceptions of the user, raising key philosophical questions about efficiency, authenticity, and social ties in a world filled with AI-mediated interactions.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"177 ","pages":"Article 108894"},"PeriodicalIF":8.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790366","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":"To share or not to share, that is the (moral) question: How moral frames and bystander cues shape health misinformation correction sharing on social media","authors":"Yujie Dong ,&nbsp;Wu Li","doi":"10.1016/j.chb.2025.108900","DOIUrl":"10.1016/j.chb.2025.108900","url":null,"abstract":"<div><div>Moral judgments can play a strong and intrinsic role in guiding correction-sharing decisions. Drawing on the Moral Foundation Theory and the Model of Intuitive Morality and Exemplars, this study examines how moral frames appealing to the care/harm and purity/pollution foundations, along with social media metrics representing proactive bystander cues, influence individuals’ health misinformation correction sharing behaviors on social media, through the mediating roles of personal norms and two moral emotions (i.e., anticipated pride and guilt). A pilot study (<em>N</em> = 96) and a formal experiment (<em>N</em> = 447) were conducted. The findings indicate that both moral frames generally enhanced individuals’ intentions to share corrective information by activating personal norms; however, the magnitude of this effect varied across health topics and levels of social media metrics. Specifically, the care/harm frame demonstrated greater effectiveness in the context of <em>H. pylori</em> infection, independent of social media metrics, whereas the purity/pollution frame elicited stronger responses in the context of secondhand smoke exposure, but only under conditions of high social media metrics. Among the predictors of correction-sharing intention, personal norms emerged as the strongest, followed by anticipated pride, while anticipated guilt did not have a significant effect. Theoretically, the findings advance our understanding of moral appeals and moral judgments in digital health communication. The cognitive component of moral judgements and associated affective components are disentangled. Practically, the findings offer valuable guidance for designing more effective health campaign messages on social media, tailored to resonate with diverse moral foundations and health topics.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"177 ","pages":"Article 108900"},"PeriodicalIF":8.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884553","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":"Game on or gone too far? Executive functioning and implicit sequence learning in problematic vs. recreational gamers","authors":"Krisztina Berta ,&nbsp;Zsuzsanna Viktória Pesthy ,&nbsp;Teodóra Vékony ,&nbsp;Bence Csaba Farkas ,&nbsp;Orsolya Király ,&nbsp;Zsolt Demetrovics ,&nbsp;Dezső Németh ,&nbsp;Bernadette Kun","doi":"10.1016/j.chb.2025.108878","DOIUrl":"10.1016/j.chb.2025.108878","url":null,"abstract":"<div><div>Video gaming often sparks controversy, though negative effects are mainly linked to gaming disorder, not gaming itself. Research shows that gaming disorder correlates with reduced executive functioning and greater reliance on habitual processes, while recreational gaming may relate to enhanced cognitive functions. However, comprehensive comparisons of cognitive profiles across gaming behaviors remain scarce. We aimed to compare the cognitive functioning of non-gamers (NG), recreational gamers (RG), and gaming disorder risk individuals (GDR). Based on the Ten-Item Internet Gaming Disorder Test scores, 114 participants were classified into these three groups. Executive functions were assessed with the Go/No-Go, Counting Span, Digit Span, Card Sorting, 1-back, and 2-back tasks; implicit sequence learning with the Alternating Serial Reaction Time task. Group effects were adjusted for weekly gaming time. The GDR group showed reduced working memory, performing worse on the Digit Span task than the NG group, and worse on the Counting Span task than both NG and RG groups. Conversely, the RG group displayed enhanced attention-related performance compared to the NG group. No group differences emerged in implicit sequence learning. Interaction analyses revealed a negative relationship between implicit sequence learning and inhibitory control/updating across groups, while a positive link between working memory and implicit sequence learning in NG and GDR groups suggests possible compensatory mechanisms. This study underscores that cognitive impairments are linked to gaming disorder rather than gaming time itself, while recreational gaming may offer cognitive benefits. These findings provide insights into the distinct cognitive profiles of recreational gaming and gaming disorder.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"177 ","pages":"Article 108878"},"PeriodicalIF":8.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737241","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}