Proceedings of the ACM on Human-Computer Interaction最新文献

To Recommend or Not to Recommend: Designing and Evaluating AI-Enabled Decision Support for Time-Critical Medical Events. 推荐还是不推荐：为时间关键型医疗事件设计和评估人工智能支持的决策支持。

IF 4.9

Proceedings of the ACM on Human-Computer Interaction Pub Date : 2025-11-01 Epub Date: 2025-10-16 DOI: 10.1145/3757512

Angela Mastrianni, Mary Suhyun Kim, Travis M Sullivan, Genevieve Jayne Sippel, Randall S Burd, Krzysztof Z Gajos, Aleksandra Sarcevic

{"title":"To Recommend or Not to Recommend: Designing and Evaluating AI-Enabled Decision Support for Time-Critical Medical Events.","authors":"Angela Mastrianni, Mary Suhyun Kim, Travis M Sullivan, Genevieve Jayne Sippel, Randall S Burd, Krzysztof Z Gajos, Aleksandra Sarcevic","doi":"10.1145/3757512","DOIUrl":"10.1145/3757512","url":null,"abstract":"AI-enabled decision-support systems aim to help medical providers rapidly make decisions with limited information during medical emergencies. A critical challenge in developing these systems is supporting providers in interpreting the system output to make optimal treatment decisions. In this study, we designed and evaluated an AI-enabled decision-support system to aid providers in treating patients with traumatic injuries. We first conducted user research with physicians to identify and design information types and AI outputs for a decision-support display. We then conducted an online experiment with 35 medical providers from six health systems to evaluate two human-AI interaction strategies: (1) AI information synthesis and (2) AI information and recommendations. We found that providers were more likely to make correct decisions when AI information and recommendations were provided compared to receiving no AI support. We also identified two socio-technical barriers to providing AI recommendations during time-critical medical events: (1) an accuracy-time trade-off in providing recommendations and (2) polarizing perceptions of recommendations between providers. We discuss three implications for developing AI-enabled decision support used in time-critical events, contributing to the limited research on human-AI interaction in this context.","PeriodicalId":36902,"journal":{"name":"Proceedings of the ACM on Human-Computer Interaction","volume":"9 7","pages":""},"PeriodicalIF":4.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12536412/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145348974","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

"Mango Mango, How to Let The Lettuce Dry Without A Spinner?": Exploring User Perceptions of Using An LLM-Based Conversational Assistant Toward Cooking Partner. “芒果芒果，如何让生菜在没有旋转器的情况下变干？”：探索用户使用基于法学硕士的对话助手对烹饪伙伴的看法。

IF 4.9

Proceedings of the ACM on Human-Computer Interaction Pub Date : 2025-11-01 Epub Date: 2025-10-16 DOI: 10.1145/3757442

Szeyi Chan, Jiachen Li, Bingsheng Yao, Amama Mahmood, Chien-Ming Huang, Holly Jimison, Elizabeth D Mynatt, Dakuo Wang

{"title":"\"Mango Mango, How to Let The Lettuce Dry Without A Spinner?\": Exploring User Perceptions of Using An LLM-Based Conversational Assistant Toward Cooking Partner.","authors":"Szeyi Chan, Jiachen Li, Bingsheng Yao, Amama Mahmood, Chien-Ming Huang, Holly Jimison, Elizabeth D Mynatt, Dakuo Wang","doi":"10.1145/3757442","DOIUrl":"10.1145/3757442","url":null,"abstract":"The rapid advancement of Large Language Models (LLMs) has created numerous potentials for integration with conversational assistants (CAs) assisting people in their daily tasks, particularly due to their extensive flexibility. However, users' real-world experiences interacting with these assistants remain unexplored. In this research, we chose cooking, a complex daily task, as a scenario to explore people's successful and unsatisfactory experiences while receiving assistance from an LLM-based CA, Mango Mango. We discovered that participants value the system's ability to offer customized instructions based on context, provide extensive information beyond the recipe, and assist them in dynamic task planning. However, users expect the system to be more adaptive to oral conversation and provide more suggestive responses to keep them actively involved. Recognizing that users began treating our LLM-CA as a personal assistant or even a partner rather than just a recipe-reading tool, we propose five design considerations for future development.","PeriodicalId":36902,"journal":{"name":"Proceedings of the ACM on Human-Computer Interaction","volume":"9 7","pages":""},"PeriodicalIF":4.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13099075/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784020","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

A Risk Taxonomy and Reflection Tool for Large Language Model Adoption in Public Health. 公共卫生中采用大型语言模型的风险分类和反思工具。

IF 4.9

Proceedings of the ACM on Human-Computer Interaction Pub Date : 2025-11-01 Epub Date: 2025-10-16 DOI: 10.1145/3757544

Jiawei Zhou, Amy Z Chen, Darshi Shah, Laura M Schwab-Reese, Munmun DE Choudhury

{"title":"A Risk Taxonomy and Reflection Tool for Large Language Model Adoption in Public Health.","authors":"Jiawei Zhou, Amy Z Chen, Darshi Shah, Laura M Schwab-Reese, Munmun DE Choudhury","doi":"10.1145/3757544","DOIUrl":"10.1145/3757544","url":null,"abstract":"Recent breakthroughs in large language models (LLMs) have generated both interest and concern about their potential adoption as information sources or communication tools across different domains. In public health, where stakes are high and impacts extend across diverse populations, adopting LLMs poses unique challenges that require thorough evaluation. However, structured approaches for assessing potential risks in public health remain under-explored. To address this gap, we conducted focus groups with public health professionals and individuals with lived experience to unpack their concerns, situated across three distinct and critical public health issues that demand high-quality information: infectious disease prevention (vaccines), chronic and wellbeing care (opioid use disorder), and community health and safety (intimate partner violence). We synthesize participants' perspectives into a risk taxonomy, identifying and contextualizing the potential harms LLMs may introduce when positioned alongside traditional health communication. This taxonomy highlights four dimensions of risk to individuals, human-centered care, information ecosystems, and technology accountability. For each dimension, we unpack specific risks and offer example reflection questions to help practitioners adopt a risk-reflexive approach. By summarizing distinctive LLM characteristics and linking them to identified risks, we discuss the need to revisit prior mental models of information behaviors and complement evaluations with external validity and domain expertise through lived experience and real-world practices. Together, this work contributes a shared vocabulary and reflection tool for people in both computing and public health to collaboratively reflect and assess risks in deciding when to employ LLM capabilities (or not) and how to mitigate harm.","PeriodicalId":36902,"journal":{"name":"Proceedings of the ACM on Human-Computer Interaction","volume":"9 7","pages":""},"PeriodicalIF":4.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12916142/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146228858","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

Can you see what I see? Examining the Impact of Smart Glasses on Communication Dynamics in Distributed Emergency Medical Teams. 你能看到我看到的吗？研究智能眼镜对分布式应急医疗队通信动态的影响。

IF 4.9

Proceedings of the ACM on Human-Computer Interaction Pub Date : 2025-11-01 Epub Date: 2025-10-16 DOI: 10.1145/3757565

Zhan Zhang, Enze Bai, Yincao Xu, Kathleen Adelgais, Mustafa Ozkaynak

{"title":"Can you see what I see? Examining the Impact of Smart Glasses on Communication Dynamics in Distributed Emergency Medical Teams.","authors":"Zhan Zhang, Enze Bai, Yincao Xu, Kathleen Adelgais, Mustafa Ozkaynak","doi":"10.1145/3757565","DOIUrl":"10.1145/3757565","url":null,"abstract":"Effective communication is critical for emergency medical teams, especially when distributed providers must collaborate under high-stakes conditions to deliver timely, life-saving care. Traditional communication tools such as radios and phones, while commonly used, are limited to audio-only exchanges-often resulting in misunderstandings, communication breakdowns, and delays in treatment. This study explores the use of smart glasses as an alternative communication tool in prehospital emergency care and examines how their use influences communication dynamics between prehospital providers (e.g., paramedics) and remote emergency physicians, compared to traditional methods (radio and phone). Through simulation-based testing, we found that smart glasses reduced communication breakdowns and facilitated more in-depth, context-rich discussions about patient care. Both EMS providers and physicians viewed the smart glass technology as a promising solution for enabling multimodal communication (e.g., visual, auditory, gestures, text). However, we also identified several challenges associated with its use in near-realistic simulation environments, including the need for overhearing capabilities, issues with visual alignment and motion-induced discomfort, extended interaction times, and concerns around autonomy and privacy. We conclude with a discussion of the design and practical implications of these findings.","PeriodicalId":36902,"journal":{"name":"Proceedings of the ACM on Human-Computer Interaction","volume":"9 7","pages":"CSCW384"},"PeriodicalIF":4.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13001593/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147500064","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

Large Language Model Agents for Improving Engagement with Behavior Change Interventions: Application to Digital Mindfulness. 改善行为改变干预的大型语言模型代理：在数字正念中的应用。

IF 4.9

Proceedings of the ACM on Human-Computer Interaction Pub Date : 2025-11-01 Epub Date: 2025-10-16 DOI: 10.1145/3757619

Harsh Kumar, Suhyeon Yoo, Angela Zavaleta Bernuy, Jiakai Shi, Huayin Luo, Joseph Jay Williams, Anastasia Kuzminykh, Ashton Anderson, Rachel Kornfield

{"title":"Large Language Model Agents for Improving Engagement with Behavior Change Interventions: Application to Digital Mindfulness.","authors":"Harsh Kumar, Suhyeon Yoo, Angela Zavaleta Bernuy, Jiakai Shi, Huayin Luo, Joseph Jay Williams, Anastasia Kuzminykh, Ashton Anderson, Rachel Kornfield","doi":"10.1145/3757619","DOIUrl":"10.1145/3757619","url":null,"abstract":"Although engagement in self-directed wellness exercises typically declines over time, integrating social support such as coaching can sustain it. However, traditional forms of support are often inaccessible due to the high costs and complex coordination. Large Language Models (LLMs) show promise in providing human-like dialogues that could emulate social support. Yet, in-depth, in situ investigations of LLMs to support behavior change remain underexplored. We conducted two randomized experiments to assess the impact of LLM agents on user engagement with mindfulness exercises. First, a single-session study, involved 502 crowdworkers; second, a three-week study, included 54 participants. We explored two types of LLM agents: one providing information and another facilitating self-reflection. Both agents enhanced users' intentions to practice mindfulness. However, only the information-providing LLM agent, featuring a friendly persona, significantly improved engagement with the exercises. Our findings suggest that specific LLM agents may bridge the social support gap in digital health interventions.","PeriodicalId":36902,"journal":{"name":"Proceedings of the ACM on Human-Computer Interaction","volume":"9 7","pages":""},"PeriodicalIF":4.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12945337/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147327558","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

Bridging Ontologies of Neurological Conditions: Towards Patient-centered Data Practices in Digital Phenotyping Research and Design. 神经系统疾病的桥梁本体：在数字表型研究和设计中以患者为中心的数据实践。

IF 4.9

Proceedings of the ACM on Human-Computer Interaction Pub Date : 2025-11-01 Epub Date: 2025-10-16 DOI: 10.1145/3757562

Jianna So, Faye X Yang, Krzysztof Z Gajos, Naveena Karusala, Anoopum S Gupta

{"title":"Bridging Ontologies of Neurological Conditions: Towards Patient-centered Data Practices in Digital Phenotyping Research and Design.","authors":"Jianna So, Faye X Yang, Krzysztof Z Gajos, Naveena Karusala, Anoopum S Gupta","doi":"10.1145/3757562","DOIUrl":"10.1145/3757562","url":null,"abstract":"Amidst the increasing datafication of healthcare, deep digital phenotyping is being explored in clinical research to gather comprehensive data that can improve understanding of neurological conditions. However, participants currently do not have access to this data due to researchers' apprehension around whether such data is interpretable or useful. This study focuses on patient perspectives on the potential of deep digital phenotyping data to benefit people with neurodegenerative diseases, such as ataxias, Parkinson's disease, and multiple system atrophy. We present an interview study (n=12) to understand how people with these conditions currently track their symptoms and how they envision interacting with their deep digital phenotyping data. We describe how participants envision the utility of this deep digital phenotyping data in relation to multiple stages of disease and stakeholders, especially its potential to bridge different and sometimes conflicting understandings of their condition. Looking towards a future in which patients have increased agency over their data and can use it to inform their care, we contribute implications for shaping patient-driven clinical research practices and deep digital phenotyping tools that serve a multiplicity of patient needs.","PeriodicalId":36902,"journal":{"name":"Proceedings of the ACM on Human-Computer Interaction","volume":"9 7","pages":""},"PeriodicalIF":4.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12536435/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145348987","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

Towards a Responsible AI Organizational Maturity Model 构建负责任的人工智能组织成熟度模型

Proceedings of the ACM on Human-Computer Interaction Pub Date : 2025-10-16 DOI: 10.1145/3757514

Amy Heger, Samir Passi, Shipi Dhanorkar, Zoe Kahn, Ruotong Wang, Mihaela Vorvoreanu

{"title":"Towards a Responsible AI Organizational Maturity Model","authors":"Amy Heger, Samir Passi, Shipi Dhanorkar, Zoe Kahn, Ruotong Wang, Mihaela Vorvoreanu","doi":"10.1145/3757514","DOIUrl":"https://doi.org/10.1145/3757514","url":null,"abstract":"Artificial intelligence (AI) holds tremendous potential but also poses consequential risks. Regulation frameworks like the EU AI Act aim to mitigate these risks, yet organizations struggle to understand and operationalize Responsible AI (RAI). We introduce the RAI Organizational Maturity (RAI-OM) framework as an initial step towards a RAI maturity model to highlight the many factors that influence an organization's RAI maturity. Developed through in-depth qualitative interviews and co-design sessions with 90 RAI experts, the RAI-OM framework consists of 24 dimensions grouped into three main categories: Organizational Foundations, Team Approach, and RAI Practices. Our findings also provide further evidence for the interdependent nature of RAI's organizational factors, the import of collaboration for mature RAI, and the need to start RAI early in the AI lifecyle. Researchers and practitioners can use the RAI-OM framework and our research findings to not only understand the different moving parts in RAI's complex organizational machinery, but also address organizational barriers to RAI, unpack the different types of collaborations needed for mature RAI, and support RAI's articulation work and process.","PeriodicalId":36902,"journal":{"name":"Proceedings of the ACM on Human-Computer Interaction","volume":"9 7","pages":"1-33"},"PeriodicalIF":0.0,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147886998","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: 1

Effect of Reward Types on Motivation and Recall in a Geology Game 地质游戏中奖励类型对动机和回忆的影响

Proceedings of the ACM on Human-Computer Interaction Pub Date : 2025-10-05 DOI: 10.1145/3748618

Aisha Darmansjah, Selen Türkay

引用次数: 0

Two-Point Discrimination of Vibrotactile Stimuli on the Forearm MHCI032 前臂振动触觉刺激MHCI032的两点识别

Proceedings of the ACM on Human-Computer Interaction Pub Date : 2025-09-09 DOI: 10.1145/3743721

Jan Willms, Adrien Chaffangeon Caillet, Marco Kurzweg, Katrin Wolf

引用次数: 1

UbiLearn: Supporting English-as-a-Foreign-Language Learners in Reflecting on Conversations Using a Smartwatch MHCI033 ubillearn：帮助英语作为外语的学习者使用智能手表思考对话

Proceedings of the ACM on Human-Computer Interaction Pub Date : 2025-09-09 DOI: 10.1145/3743735

Riku Arakawa, Manami Nakagawa, Hiromu Yakura

引用次数: 2