Computers in Human Behavior: Artificial Humans最新文献_第3页

Hey AI: Can you trigger me? A comparison of Text-to-Speech synthesis and human speech in a virtual social stress paradigm 嘿，AI：你能触发我吗？虚拟社会压力范式下文本-语音合成与人类语音的比较

Computers in Human Behavior: Artificial Humans Pub Date : 2026-08-01 Epub Date: 2026-08-04 DOI: 10.1016/j.chbah.2026.100371

Sarah Roßkopf, Leon O.H. Kroczek, Theresa F. Wechsler, Felix Stärz, Matthias Blau, Steven van de Par, Andreas Mühlberger

{"title":"Hey AI: Can you trigger me? A comparison of Text-to-Speech synthesis and human speech in a virtual social stress paradigm","authors":"Sarah Roßkopf, Leon O.H. Kroczek, Theresa F. Wechsler, Felix Stärz, Matthias Blau, Steven van de Par, Andreas Mühlberger","doi":"10.1016/j.chbah.2026.100371","DOIUrl":"10.1016/j.chbah.2026.100371","url":null,"abstract":"<div><div>– While the use of text-to-speech synthesis (TTS) is high, evidence of its effects on presence in VR, for example, is scarce. It also remains unclear, whether virtual interactions using TTS can provoke psychosocial stress and evaluative threat as required for psychological paradigms like the Trier Social Stress Test (TSST) as the experimental gold standard to examine human stress reaction. Using TTS instead of prerecorded human speech (PHS) to auralize the agents in the virtual version (VR-TSST) can be beneficial, e.g. by creating greater freedom and flexibility to react. In a randomized-controlled trial, we compared TTS stimuli to PHS within a VR-TSST. Participants’ heart rate, trapezius muscle activity, and self-reports on stress, presence, and affective state were surveyed. In both speech conditions profound stress reactions were provoked <strong>but no significant modulations by audio were observed. Equivalency testing demonstrated equivalent heart rate increases between audio conditions but only moderate evidence for equivalency of stress and presence ratings was observed. The current findings show that social stress reactions can be provoked with synthetic speech stimuli and point towards comparable effects between TTS and PHS in socio-emotional experiences. This highlights the potential of TTS for use in virtual social interactions.</strong></div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"9 ","pages":"Article 100371"},"PeriodicalIF":0.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148738632","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}

引用次数: 0

Mind the style: Impact of communication style on human-chatbot interaction 注意风格：沟通风格对人-聊天机器人互动的影响

Computers in Human Behavior: Artificial Humans Pub Date : 2026-08-01 Epub Date: 2026-07-31 DOI: 10.1016/j.chbah.2026.100362

Erik Derner, Dalibor Kučera, Aditya Gulati, Robert A. Bagheri, Nuria Oliver

{"title":"Mind the style: Impact of communication style on human-chatbot interaction","authors":"Erik Derner, Dalibor Kučera, Aditya Gulati, Robert A. Bagheri, Nuria Oliver","doi":"10.1016/j.chbah.2026.100362","DOIUrl":"10.1016/j.chbah.2026.100362","url":null,"abstract":"<div><div>Conversational agents increasingly mediate everyday digital interactions, yet the effects of their communication style on user experience and task success remain insufficiently understood. Addressing this gap, we report a between-subject user study in which participants interacted with one of two versions of a chatbot called <span>NAVI</span>, which assisted them in an interactive map-based 2D navigation task. The two chatbot versions were designed to differ primarily in communication style: one used a friendly and supportive tone, while the other used a direct and task-focused tone. We also included a control condition where participants did not interact with a chatbot but received the step-by-step navigation instructions. The friendly chatbot significantly increased users’ communication satisfaction and was associated with higher task success than the direct chatbot. However, participants in the control condition achieved the highest task success overall, suggesting that chatbot interaction may introduce overhead in tasks that can be completed effectively using straightforward instructions. We did not find significant evidence that gender moderated the effects of communication style, although exploratory gender-stratified analyses suggested patterns that warrant further investigation. Finally, we found limited evidence of global linguistic accommodation, with only selective feature-level alignment. These findings suggest that chatbot communication style influences users’ perceptions of conversational agents and may improve performance relative to less supportive chatbot designs, but the overall value of chatbot interaction depends on the task context. The study highlights the need for task-sensitive, transparent and carefully evaluated communication-style choices in conversational-agent design.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"9 ","pages":"Article 100362"},"PeriodicalIF":0.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148738663","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}

引用次数: 0

How does collaborative prompting behaviour develop and relate to effectiveness in problem-solving with Generative Artificial Intelligence? 协作提示行为如何发展并与生成式人工智能解决问题的有效性相关？

Computers in Human Behavior: Artificial Humans Pub Date : 2026-08-01 Epub Date: 2026-08-22 DOI: 10.1016/j.chbah.2026.100378

Athanasios Christopoulos, Stylianos Mystakidis, Isidoros Perikos, Aikaterini Bourazeri, Andria Michael, Mikko-Jussi Laakso

{"title":"How does collaborative prompting behaviour develop and relate to effectiveness in problem-solving with Generative Artificial Intelligence?","authors":"Athanasios Christopoulos, Stylianos Mystakidis, Isidoros Perikos, Aikaterini Bourazeri, Andria Michael, Mikko-Jussi Laakso","doi":"10.1016/j.chbah.2026.100378","DOIUrl":"10.1016/j.chbah.2026.100378","url":null,"abstract":"<div><div>Research on Generative Artificial Intelligence (GenAI) in education has concentrated on user attitudes and adoption intentions but less is known about how groups actually interact with such tools while solving complex problems. The present study treats prompting as observable, time-resolved, behaviour and investigates how a group's prompting develops and relates to task effectiveness over a collaborative session. Secondary (N = 114) and Higher (N = 57) Education students, working in self-formed groups (N = 45), completed a competitive mystery-solving task with unrestricted access to GenAI tools of their choice. Logged group prompts were coded with a scheme adapted from Bloom's Digital Taxonomy that distinguishes lower-order (Exploration and Action) from higher-order (Creation and Metacognition) cognitive behaviours. Groups produced a modest majority of higher-order prompts and shifted progressively from exploratory toward metacognitive prompting as sessions advanced. A higher proportion of higher-order prompting was associated with greater effectiveness which held even when the total prompt volume was controlled. Prior experience, general attitudes toward AI, and self-reported verification behaviour showed no reliable association with effectiveness. Perceived usefulness and prompting self-efficacy co-varied with success but are interpreted as concurrent correlates. Foregrounding what groups did with the tool and how that behaviour developed over time offers a view on collaborative human-AI interaction that adoption-focused measures alone cannot provide.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"9 ","pages":"Article 100378"},"PeriodicalIF":0.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148843742","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}

引用次数: 0

Generative artificial intelligence (GenAI) use, work outcomes, and the moderating role of GenAI literacy in early organizational adoption 生成人工智能（GenAI）的使用，工作成果，以及GenAI素养在早期组织采用中的调节作用

Computers in Human Behavior: Artificial Humans Pub Date : 2026-08-01 Epub Date: 2026-08-19 DOI: 10.1016/j.chbah.2026.100380

Klara Ida Marienhagen

{"title":"Generative artificial intelligence (GenAI) use, work outcomes, and the moderating role of GenAI literacy in early organizational adoption","authors":"Klara Ida Marienhagen","doi":"10.1016/j.chbah.2026.100380","DOIUrl":"10.1016/j.chbah.2026.100380","url":null,"abstract":"<div><div>Generative artificial intelligence (GenAI) has become increasingly prevalent in organizational work contexts, yet little is known about how employees' early use of GenAI relates to their work experiences before broader organizational transformation occurs. Guided by the challenge–hindrance stress model (CHM) as an interpretive framework, this study examined whether more frequent GenAI use is associated with employees' work outcomes and whether GenAI literacy moderates these associations during a pretransformation phase of organizational GenAI adoption. A cross-sectional quantitative online survey was conducted among administrative employees of a global industrial company shortly before an organization-wide GenAI implementation in early 2025. The sample comprised 1001 employees, most of whom were based in Europe, particularly Germany. Structural equation modeling (SEM) analyses indicated small positive associations between GenAI usage frequency and work engagement as well as quantitative job performance. In addition, GenAI literacy moderated the associations of GenAI usage frequency with qualitative job performance, quantitative job performance, and meaningfulness of work. These findings suggest that in an early, pretransformation phase of organizational GenAI adoption, GenAI use is not uniformly associated with better work outcomes and appears to depend in part on employees’ GenAI literacy. The study highlights the need for an employee-centered approach that considers employee capabilities alongside technological access for successful GenAI adoption in organizations.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"9 ","pages":"Article 100380"},"PeriodicalIF":0.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148843746","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}

引用次数: 0

Erratum regarding corrections related to Ethical approval and informed consent in articles published in [Computers in Human Behavior: Artificial Humans 7C (2026)] 关于发表在[计算机与人类行为：人造人7C(2026)]上的文章中有关伦理批准和知情同意的更正的勘误

Computers in Human Behavior: Artificial Humans Pub Date : 2026-08-01 Epub Date: 2026-07-23 DOI: 10.1016/j.chbah.2026.100355

引用次数: 0

Friends, lovers, and companions: A systematic scoping review of empirical evidence on human-AI relationships 朋友、爱人和同伴：对人类与人工智能关系的经验证据进行系统的范围审查

Computers in Human Behavior: Artificial Humans Pub Date : 2026-08-01 Epub Date: 2026-08-19 DOI: 10.1016/j.chbah.2026.100384

Valerie A. Lapointe, Franklin Calazana, Simon Dubé, Regina-Maria Neppel, Sasha Blum, David Lafortune

{"title":"Friends, lovers, and companions: A systematic scoping review of empirical evidence on human-AI relationships","authors":"Valerie A. Lapointe, Franklin Calazana, Simon Dubé, Regina-Maria Neppel, Sasha Blum, David Lafortune","doi":"10.1016/j.chbah.2026.100384","DOIUrl":"10.1016/j.chbah.2026.100384","url":null,"abstract":"<div><div>The rapid popularization of artificial intelligence (AI) conversational agents (CAs) has sparked growing scientific and public interest in the nature and consequences of human-AI relationships. However, what we empirically know about these relationships and their social effects remains scattered. This scoping review consolidates the study designs and methodological approaches in the current literature on human-AI relationships, as well as the AI systems and populations studied, their focus areas, and key empirical findings. Following JBI methodology, three databases (Scopus, PubMed, PsycINFO) were searched in September 2025, supplemented by Google Scholar, arXiv, and reference list screening to maximize coverage. Of the 2280 papers initially identified, 89 met the inclusion criteria and were independently extracted by two reviewers. The literature is mostly characterized by qualitative and correlational designs, with many studies focusing on the AI companion platform Replika. Studies were organized around three thematic orientations: mechanisms underlying engagement, relational experiences with CAs, and psychosocial effects. Qualitative data suggest that loneliness was a frequently reported motivator for CA use, and users often reported perceived benefits, including reduced loneliness, emotional support, and improved social confidence, as well as positive erotic and relational experiences. However, quantitative experimental and longitudinal evidence remains limited and mixed, and the effects of AI companionship appear contingent on individual characteristics, contextual conditions, and patterns of use rather than being uniform across users. Longitudinal experimental research, greater diversity in the platforms and populations investigated, and regular systematic syntheses of evidence are needed to advance science on human-AI relationships.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"9 ","pages":"Article 100384"},"PeriodicalIF":0.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148843748","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}

引用次数: 0

Artificial intelligence as a training tool in clinical psychology: A comparison of text-based and avatar simulations 人工智能作为临床心理学的训练工具：基于文本和虚拟形象模拟的比较

Computers in Human Behavior: Artificial Humans Pub Date : 2026-08-01 Epub Date: 2026-08-19 DOI: 10.1016/j.chbah.2026.100383

V. El Sawah, A. Bhardwaj, A. Pryke, D. Gamaleldin, J. Nice, C.S. Ang, A.K. Martin

{"title":"Artificial intelligence as a training tool in clinical psychology: A comparison of text-based and avatar simulations","authors":"V. El Sawah, A. Bhardwaj, A. Pryke, D. Gamaleldin, J. Nice, C.S. Ang, A.K. Martin","doi":"10.1016/j.chbah.2026.100383","DOIUrl":"10.1016/j.chbah.2026.100383","url":null,"abstract":"<div><div>Clinical psychology students frequently report feeling underprepared for the interpersonal demands of therapeutic work, highlighting the need for accessible opportunities to practise core counselling skills before seeing real clients. Advances in artificial intelligence (AI) now enable simulated interaction partners that may support early skills development. This study examined postgraduate clinical psychology students' perceptions of two AI-based simulations: a text-based chatbot (ChatGPT) and a voice-based avatar (HeyGen). Twenty-four students completed two brief cognitive-behavioural role-plays (counterbalanced), one with each tool, and provided both quantitative ratings and qualitative feedback on perceived usefulness, skill application, responsiveness and engagement, and perceived skill improvement. Both AI tools were evaluated positively across dimensions. However, the avatar was rated significantly higher than the chatbot for perceived usefulness, skill application, and perceived skill improvement, and qualitative comments highlighted the added value of voice-based interaction for conveying social and emotional cues. These findings suggest that AI-driven simulation may supplement early-stage clinical skills training, with voice-based avatars offering additional benefits. Future work should test whether such simulated interactions translate to objective improvements in real therapeutic performance.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"9 ","pages":"Article 100383"},"PeriodicalIF":0.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148770999","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}

引用次数: 0

Logical consistency as a foundation for emotional persuasion by AI 逻辑一致性是人工智能情感说服的基础

Computers in Human Behavior: Artificial Humans Pub Date : 2026-08-01 Epub Date: 2026-07-23 DOI: 10.1016/j.chbah.2026.100363

Takahiro Tsumura, Kazunori Terada

{"title":"Logical consistency as a foundation for emotional persuasion by AI","authors":"Takahiro Tsumura, Kazunori Terada","doi":"10.1016/j.chbah.2026.100363","DOIUrl":"10.1016/j.chbah.2026.100363","url":null,"abstract":"<div><div>Persuasion can target what people feel they should do as well as what they want to do, yet little is known about how these attitudes respond to logic and emotion in everyday decisions, especially when persuasive messages are produced by AI. We conducted a cross-domain experiment (<span><math><mrow><mi>N</mi><mo>=</mo><mn>197</mn></mrow></math></span>) that manipulated logical consistency (consistent versus inconsistent) and emotional appeal (positive, neutral, negative) in AI-generated persuasive messages. To ensure breadth across contexts, we constructed a pool of 50 candidate issues and selected six systematically varied topics from a two-dimensional space of Individual Value and Social Norm, including medical AI transparency and compulsory voting. Messages were generated via theory-informed prompting and post-edited so that logical structure and emotional wording were varied separately during stimulus construction. Participants completed pre and post measures of belief, normative judgment (Should), and personal preference (Want), along with manipulation checks and measures of trust and empathy toward the agent. Results showed significant Logical Consistency <span><math><mo>×</mo></math></span> Emotional Appeal <span><math><mo>×</mo></math></span> Time interactions for Belief and Should, but not for Want. Belief increased after logically consistent messages with positive or neutral appeals, whereas Should increased only after logically consistent messages with a neutral appeal. Want showed no reliable condition-dependent change. Positive appeals also elicited greater trust than negative appeals. These findings indicate that logical consistency and emotional appeal affect factual belief, normative judgment, personal preference, and trust differently.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"9 ","pages":"Article 100363"},"PeriodicalIF":0.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148636653","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}

引用次数: 0

Corrigendum to “Hey AI: Can you trigger me? A comparison of Text-to-Speech synthesis and human speech in a virtual social stress paradigm: Effects of Text-to-Speech synthesis on VR experience” [Computers in Human Behavior: Artificial Humans 9C (2026) 100371] “嘿，AI：你能触发我吗？”虚拟社会压力范式下的文本-语音合成与人类语音的比较：文本-语音合成对VR体验的影响[j] .计算机与人类行为：人工人类9C(2026) 100371。

Computers in Human Behavior: Artificial Humans Pub Date : 2026-08-01 Epub Date: 2026-09-03 DOI: 10.1016/j.chbah.2026.100390

Sarah Roßkopf, Leon O.H. Kroczek, Theresa F. Wechsler, Felix Stärz, Matthias Blau, Steven van de Par, Andreas Mühlberger

引用次数: 0

Corrigendum to “AI4PCR: Artificial intelligence for practicing conflict resolution” [Computers in Human Behavior: Artificial Humans 1 (1) (2023) 100002] “AI4PCR：用于解决冲突的人工智能”的勘误表[人类行为中的计算机：人工人类1 (1)(2023)100002]

Computers in Human Behavior: Artificial Humans Pub Date : 2026-08-01 Epub Date: 2026-08-20 DOI: 10.1016/j.chbah.2026.100387

Anne Hse, Divya Chaudhary

引用次数: 0