International Journal of Human-Computer Studies最新文献

{"title":"Natural manipulation of virtual reality: The effects of kinesthetic gloves with force feedback on user performance and experience for accurate 3D object manipulation","authors":"Zhenxing Li,&nbsp;Oğuz 'Oz' Buruk,&nbsp;Mila Bujić,&nbsp;Bojan Kerouš,&nbsp;Juho Hamari","doi":"10.1016/j.ijhcs.2025.103507","DOIUrl":"10.1016/j.ijhcs.2025.103507","url":null,"abstract":"<div><div>One of the challenges facing virtual reality (VR) is the pursuit of efficient and natural object manipulation, required by many applications, such as computer-aided medical diagnosis, surgery planning and industrial prototyping. Current hand-based three-dimensional (3D) manipulation allows users to interact with virtual objects intuitively, enabled primarily by using motion controllers with single-point interaction. There are promising avenues to increase naturalness of interaction through kinesthetic gloves that provide finger-based multipoint interaction with force feedback. These novel gloves could have more potential for 3D object manipulation in VR, however, their practical usability in this field remains largely unexplored. This study compared the glove-based VR interfaces (with/without force feedback) with the traditional controller-based VR interface in accurate movement and rotation tasks. The results demonstrated the strengths of finger-based multipoint interaction provided by kinesthetic gloves in accurate 3D manipulation, in terms of task completion time, accuracy, perceived workload and user preference. Additionally, the experiment identified that force feedback from kinesthetic gloves surprisingly did not benefit user task performance and even negatively affected rotation accuracy. However, it was perceived as valuable for object rotation that required complicated finger movement and coordination.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"199 ","pages":"Article 103507"},"PeriodicalIF":5.3,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explaining AI weaknesses improves human–AI performance in a dynamic control task","authors":"Tobias Rieger ,&nbsp;Hanna Schindler ,&nbsp;Linda Onnasch ,&nbsp;Eileen Roesler","doi":"10.1016/j.ijhcs.2025.103505","DOIUrl":"10.1016/j.ijhcs.2025.103505","url":null,"abstract":"<div><div>AI-based decision support is increasingly implemented to support operators in dynamic control tasks. While these systems continuously improve, to truly achieve human–system synergy, one must also study humans’ system understanding and behavior. Accordingly, we investigated the impact of explainability instructions regarding a specific system weakness on performance and trust in two experiments (with higher task demands in Experiment 2). Participants performed a dynamic control task with support from either an explainable AI (XAI, information on a system weakness), a non-explainable AI (nonXAI, no information on system weakness), or without support (manual, only in Experiment 2). Results show that participants with XAI support outperformed those in the nonXAI group, particularly in situations where the AI actually erred. Notably, informing users of system weaknesses did not affect trust once they had interacted with the system. In addition, Experiment 2 showed the general benefit of decision support over working manually under higher task demands. These findings suggest that AI support can enhance performance in complex tasks and that providing information on potential system weaknesses aids in managing system errors and resource allocation without compromising trust.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"199 ","pages":"Article 103505"},"PeriodicalIF":5.3,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards empathic medical conversation in Narrative Medicine: A visualization approach based on intelligence augmentation","authors":"Hua Ma ,&nbsp;Effie Lai-Chong Law ,&nbsp;Xu Sun ,&nbsp;Weili Yang ,&nbsp;Xiangjian He ,&nbsp;Glyn Lawson ,&nbsp;Huizhong Zheng ,&nbsp;Qingfeng Wang ,&nbsp;Qiang Li ,&nbsp;Xiaoru Yuan","doi":"10.1016/j.ijhcs.2025.103506","DOIUrl":"10.1016/j.ijhcs.2025.103506","url":null,"abstract":"<div><div>Empathic medical conversation is central to patient-centered care within Narrative Medicine. However, difficulties, such as physicians’ limited empathic capabilities and lack of time, impede the practice. Research on real-time, on-site empathic medical exchanges has been limited in exploring technology to assist and enhance physicians’ capabilities. This paper proposed the Empathic Opportunity Perception and Distinction (EOPD) framework for building physician-AI collaboration based on Intelligence Augmentation (IA) for empathic conversations. The EOPD integrates two multi-modal machine learning (ML) models based on facial and verbal cues, presenting a physician-AI interaction framework and three distinctive visualization components: emotional reference, opportunity reminding and keyword collection, and situation understanding. To assess EOPD's effectiveness and gauge physicians’ and patients’ receptiveness, a prototype system named EMVIS (<strong><em>EM</em></strong><em>otional</em> <strong><em>VIS</em></strong><em>ualization</em>) was designed and developed. Results from the study demonstrated improvements in physicians’ empathy efforts and perceived empathy performance when using EMVIS, particularly for junior physicians. Physicians and patients held positive attitudes towards EMVIS, with patients expressing a high expectation that EMVIS would improve the physician-patient relationship. The research showed the efficacy of the multi-modal ML models in supporting complex affective empathy and EMVIS in facilitating and complementing empathy concerns. It highlighted the tailored support to junior and senior physicians and emphasized physician-AI collaboration to maintain user autonomy and mitigate potential biases. Future research should explore extensive system applications, tailor visual and interactive support for physicians, and implement adaptive and reflective ML models to improve the effectiveness and efficiency of empathy communications.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"199 ","pages":"Article 103506"},"PeriodicalIF":5.3,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-delay haptic texture display method based on user action information and texture image","authors":"Dapeng Chen ,&nbsp;Yi Ding ,&nbsp;Geng Chen ,&nbsp;Tianyu Fan ,&nbsp;Jia Liu ,&nbsp;Aiguo Song","doi":"10.1016/j.ijhcs.2025.103500","DOIUrl":"10.1016/j.ijhcs.2025.103500","url":null,"abstract":"<div><div>In recent years, tool-mediated vibrotactile display of virtual surface texture has become a hot research topic in the field of haptics. When interacting with a virtual texture, incorporating the user’s interactive behavior into the haptic display process of the texture is an effective means, that can enhance the sense of realism in the interaction. To address the problems of weak generalization ability and low interactive realism in texture modeling and rendering, this paper proposes a haptic rendering model for known textures that varies with action conditions. This model takes texture image and the user’s real-time action information (velocity and normal force) as input. It introduces a self-attention mechanism to assign weights to each feature and combines the previous vibrotactile information to generate corresponding vibrotactile signals. Additionally, we designed a haptic device that integrates a real-time collection of action information and vibrotactile expression capabilities in combination with the 3D Systems Touch device, which together with the haptic rendering model, forms a haptic texture display system. In order to ensure that the system delay is below the perception threshold, this paper further introduced knowledge distillation to optimize the system delay. Based on this, we conducted three user experiments. The results show that our method not only has a certain generalization ability for new textures outside the database, but also can obtain a higher perceptual similarity score. In addition, the delay time of the system we tested is only 29<span><math><mo>∼</mo></math></span>37 ms, which can bring users a more realistic texture perception experience.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"199 ","pages":"Article 103500"},"PeriodicalIF":5.3,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An exploratory study of the relationship between objective game difficulty and subjective game difficulty","authors":"Zhixing Guo,&nbsp;Xiangshi Ren","doi":"10.1016/j.ijhcs.2025.103502","DOIUrl":"10.1016/j.ijhcs.2025.103502","url":null,"abstract":"<div><div>Design issues related to game difficulty in video games have attracted much attention. Although existing studies suggest a discrepancy between subjective game difficulty (SGD) and objective game difficulty (OGD), research exploring this relationship and its impacts on players remains limited. This study investigates whether there is a mismatch between OGD and SGD and their impacts on player enjoyment, engagement, and self-efficacy. A research framework is proposed, accompanied by seven hypotheses for testing. We first determined six dimensions of SGD as a new measuring structure to develop the questionnaire. While OGD is measured by the failure rate, which is a universal method to quantify it. We experimented to validate whether SGDs match OGDs in different OGD conditions in the designed Match-3 game. The three factors of player enjoyment, engagement, and self-efficacy were also measured to assess how the two difficulties affected them. A semi-structured interview was adopted to provide further insight into the experimental results. We found that OGD and SGD only partially match each other and that SGD acts as a mediator between the effects of OGD on player enjoyment, engagement, and self-efficacy. Although preliminary, our findings contribute to a deeper understanding of game difficulty and offer insights for future game difficulty design and human–computer interaction (HCI) research.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"199 ","pages":"Article 103502"},"PeriodicalIF":5.3,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143680828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and evaluation of AR-based adaptive human-computer interaction cognitive training","authors":"Man Chu ,&nbsp;Jing Qu ,&nbsp;Tan Zou ,&nbsp;Qinbiao Li ,&nbsp;Lingguo Bu ,&nbsp;Yiran Shen","doi":"10.1016/j.ijhcs.2025.103504","DOIUrl":"10.1016/j.ijhcs.2025.103504","url":null,"abstract":"<div><div>As human-computer interaction (HCI) technology advances, the use of augmented reality (AR) in cognitive training is becoming more prevalent. However, traditional training methods often apply a one-size-fits-all approach, failing to accommodate the varied training needs of individuals with different cognitive levels. Additionally, most HCI systems use subjective questionnaires for evaluation, which can be influenced by the subjects' emotional and mental states. To overcome these challenges, this study developed an AR-based adaptive HCI cognitive training system that dynamically adjusts task difficulty based on real-time user performance. We used multi-source data to empirically validate the effectiveness of adaptive HCI in cognitive training. Specifically, we recorded functional Near-Infrared Spectroscopy (fNIRS) data, movement data, task performance, and subjective feedback from 22 elderly participants, dividing them into two groups—low cognitive group and normal cognitive group. The results showed that the system exerted a significant influence on brain functional connectivity (FC) associated with cognition, movement, and vision. Changes in FC may highlight the benefits of adaptive HCI training strategies. Furthermore, participants with normal cognitive abilities significantly outperformed their low cognitive counterparts in task performance. In conclusion, this study designed and evaluated an AR-based adaptive HCI cognitive training system that ensures personalized training. It demonstrated the feasibility of adaptive HCI strategies in cognitive rehabilitation by incorporating physiological and behavioral data, thereby enhancing the precision of quantitative assessments for HCI systems.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"199 ","pages":"Article 103504"},"PeriodicalIF":5.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143680827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of user feedback in enhancing understanding and trust in counterfactual explanations for explainable AI","authors":"Muhammad Suffian ,&nbsp;Ulrike Kuhl ,&nbsp;Alessandro Bogliolo ,&nbsp;Jose M. Alonso-Moral","doi":"10.1016/j.ijhcs.2025.103484","DOIUrl":"10.1016/j.ijhcs.2025.103484","url":null,"abstract":"<div><div>Counterfactual explanations (CEs) have emerged as a viable solution for generating comprehensible explanations in the context of explainable artificial intelligence (XAI). A CE provides actionable information to users on how to achieve the desired outcome from a machine learning (ML) model with minimal modifications to the input. XAI is crucial for improving transparency and reliability in AI systems, especially for meeting regulations like the General Data Protection Regulation (GDPR) or the European AI Act. However, the integration of CEs into XAI frameworks and their effectiveness in enhancing user trust and cognitive learning remains uncertain and requires further research. We have developed a user study to face this challenge with two user input-driven counterfactual generation XAI approaches: (i) User Feedback-based Counterfactual Explanation (UFCE) and (ii) Diverse Counterfactual Explanation (DiCE). They are integrated within a game-inspired online platform that enables direct comparisons between them. We compared the task performance, understanding, satisfaction, and trust between control and experimental groups, with a total of 101 participants. After curating the collected data, we had 70 users (24 in the control group) who successfully completed the experiment. Participants in the experimental group received explanations generated by UFCE or DiCE. Findings show that explanations generated by UFCE improve users’ learning experiences, resulting in better task performance, comprehension, satisfaction, and trust. Moreover, participants who interacted with UFCE exhibited significantly higher reliance on suggestions than those who interacted with DiCE, what was supported by statistical validation. These results highlight the significance of human-centered XAI methods and promote meaningful cognitive engagement for users. Furthermore, the game-inspired platform is implemented as open-source to promote Open Science, and it is made publicly available along with data collected in the user study to support further investigations and to ensure reproducibility of reported results.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"199 ","pages":"Article 103484"},"PeriodicalIF":5.3,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143680818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Building confidence in the metaverse: Implementation and evaluation of a multi-user virtual reality application for overcoming fear of public speaking","authors":"Teemu H. Laine ,&nbsp;Woohyun Lee ,&nbsp;Jiyoung Moon ,&nbsp;Eunha Kim","doi":"10.1016/j.ijhcs.2025.103487","DOIUrl":"10.1016/j.ijhcs.2025.103487","url":null,"abstract":"<div><div>Fear of public speaking is a social anxiety disorder that causes individuals to fear speaking in front of crowds, significantly impacting their education, work, and psychological wellbeing. Immersive virtual reality (VR) has emerged as a potential tool for addressing this fear by simulating public-speaking scenarios in a controlled environment. However, previous VR solutions for public-speaking anxiety have been single-user and lacked multimodal data collection. This study proposed Ready Player Speak, a novel multi-user VR exposure therapy application designed for people who experience fear of public speaking, incorporating data collection through questionnaires and sensors. We evaluated Ready Player Speak in a mixed-method user study with 32 young adult participants who delivered interactive speeches in front of an audience comprising human- and computer-controlled avatars. Participants completed pre- and post-test questionnaires and were interviewed at the end. The user study results indicated that Ready Player Speak felt realistic, and most participants experienced a sense of spatial presence. However, the realism of the avatars and their appropriateness were criticized. Nevertheless, Ready Player Speak had a statistically significant lowering effect on the fear of public speaking experienced by the participants, indicating its potential as a tool for addressing this fear. Based on the evaluation results and our experiences with the development of Ready Player Speak, we presented 12 lessons learned. This study’s findings can inform researchers and developers seeking to harness multi-user VR exposure therapy for fear of public speaking and other psychology interventions.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"199 ","pages":"Article 103487"},"PeriodicalIF":5.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How do people evaluate the accuracy of video posts when a warning indicates they were generated by AI?","authors":"Yuya Shibuya,&nbsp;Tomoka Nakazato,&nbsp;Soichiro Takagi","doi":"10.1016/j.ijhcs.2025.103485","DOIUrl":"10.1016/j.ijhcs.2025.103485","url":null,"abstract":"<div><div>Given the rise of concerns about Generative Artificial Intelligence (GenAI) powered misinformation, major platforms like Google, Meta, and TikTok have implemented new policies to warn users of AI-generated content. However, we have not fully understood the impacts of such user interface designs that disclose AI made content on user perceptions. This study investigates how people assess the accuracy of video content when they are warned that it is created by GenAI. We conducted an online experiment in the U.S. (14,930 observations), showing half of the participants warning messages about AI before and after they viewed a mockup of true and false video content on social media, while the other half only viewed the same videos without the warning message. The results indicated that the warning message had an impact on the ability to discern between true and false content only among those who had a positive perception of AI. On the contrary, those with a negative perception of AI tended to perceive all AI-made video posts, including those not containing false information, as less accurate when they knew that a GenAI created the videos. These results indicated the limitations of merely relying on simple warnings to mitigate GenAI-based misinformation. Future research on continuous investigations on designing interfaces that go beyond simple warnings is needed.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"199 ","pages":"Article 103485"},"PeriodicalIF":5.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143680816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of attention-demanding task-based technique on reorientation in virtual reality","authors":"Jieun Lee ,&nbsp;Aya Ataya ,&nbsp;SeungJun Kim","doi":"10.1016/j.ijhcs.2025.103501","DOIUrl":"10.1016/j.ijhcs.2025.103501","url":null,"abstract":"<div><div>Reorientation techniques in virtual reality (VR) enable users to explore virtual spaces that are larger than the physical spaces within limited physical spaces. Increasing the rotation gain, which alters the user's orientation between physical and virtual spaces, enables users to navigate a larger virtual space. However, as a significant rotation gain may disrupt the user's sense of presence and cause discomfort, it is used at limited values. To address this issue, we propose an attention-demanding task-based reorientation technique that leverages the human perceptual phenomenon of inattentional blindness. We design attention-demanding tasks that require users to focus on specific types of attention (visual, mental, and physical) and verify that tasks are effective in demanding the intended attention type. In addition, we measure the user noticeability, presence, and VR sickness. The results show that users are less likely to notice reorientation during attention-demanding tasks than during tasks without specific attentional demands, which also avoids undesired effects such as presence degradation and increased VR sickness. Our findings suggest VR content design guidelines for seamlessly integrating reorientation techniques into VR interactive scenarios, thereby increasing the opportunities for reorienting users in virtual environments.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"199 ","pages":"Article 103501"},"PeriodicalIF":5.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}