Eric E Kaczor, Manohar Golleru, Daniel C Carter, Orian B Painter, Kyle J Kelleran, Joshua J Lynch, Brian M Clemency, Lora A Cavuoto, Peter R Chai
{"title":"Detecting Ethanol Intoxication and Impairment Using Wearable Biosensors.","authors":"Eric E Kaczor, Manohar Golleru, Daniel C Carter, Orian B Painter, Kyle J Kelleran, Joshua J Lynch, Brian M Clemency, Lora A Cavuoto, Peter R Chai","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Reliable objective measures of a person's intoxication and impairment from alcohol consumption are not readily available to the public. Wearable biosensors have the potential to provide a ubiquitous on-demand tool to deliver this kind of objective assessment in real world settings. This study evaluated the feasibility of assessing ethanol intoxication in N=28 healthy participants in a police academy's intoxication lab using wrist-worn biosensors to continuously measure heart rate, skin temperature, electrodermal activity, and accelerometry. Participants consumed ad hoc standard alcoholic drinks in a controlled setting and had regular breath alcohol content assessments and underwent standard field sobriety testing. The analysis showed statistically significant changes in each physiologic parameter between the sober and intoxicated periods. An XGBoost model was applied to this data producing machine learning algorithms to identify impairment with an accuracy as high as 0.80. These results demonstrate that it is feasible to assess ethanol intoxication using wrist-worn biosensors.</p>","PeriodicalId":74512,"journal":{"name":"Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences","volume":"2026 ","pages":"3532-3542"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12805382/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145999934","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}
{"title":"What Are You Craving? Using Wearables to Distinguish Food and Drug Cravings During Treatment with Extended-Release Buprenorphine.","authors":"Pravitha Ramanand, Premananda Indic, Nirzari Kapadia, Powell Graham, Stephanie Carreiro","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Craving, or the subjective, strong desire to use a substance, is a central factor in addiction, and part of the diagnostic criteria for substance use disorders (SUDs). Cravings can also occur for other triggers such as food, and cravings for food and drugs have been found to activate distinct neural pathways in the brain. Recently, physiologic signals from wearable devices have been applied to digitally detect cravings in patients with SUDs. But to date, no studies have explored digital detection of cravings by subtype. We collected continuous physiologic sensor data from N = 12 participants with opioid use disorder (OUD), treated with extended-release buprenorphine (BUP-XR). Data were analyzed to assess whether sensor signals carried differential information that could distinguish between food-, drug- and mixed-craving types. Accelerometer, heart rate and heart rate variability features significantly differed between drug, food and mixed trigger cravings. Cross validated models trained with these features distinguished each type of craving with area under ROC curve ranging from 75%-80%. These findings support the ability of wearable sensor-based digital biomarkers to distinguish craving subtypes in individuals with OUD.</p>","PeriodicalId":74512,"journal":{"name":"Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences","volume":"2026 ","pages":"3976-3985"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12834459/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146069285","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}
James R Heldridge, Angie N Benda, Joel S Elson, Sam T Hunter
{"title":"From Automation to Collaboration: A Systematic Review of AI Use in Assessment Across Critical Infrastructure Sectors.","authors":"James R Heldridge, Angie N Benda, Joel S Elson, Sam T Hunter","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Assessments are used to help gather and analyze information to inform processes and outcomes and are rapidly being reshaped by AI. This systematic review investigates where, why, and when AI is used across the assessment life-cycle and further considers its core functions, design elements, and the ways users engage with them Thirty-eight peer-reviewed studies met our inclusion criteria, each embedding artificial intelligence directly into the assessment process. Together, government facilities and healthcare settings accounted for more than 70% of all documented use cases. Across sectors, the prevailing role of AI was that of a digital assistant, streamlining knowledge capture and evaluation supporting assessment in its role as an expert with a focus on goal-oriented collaboration. These patterns illuminate both the breadth of adoption and the potential of AI as an augmentative partner, offering a roadmap for future assessment design and research.</p>","PeriodicalId":74512,"journal":{"name":"Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences","volume":"2026 ","pages":"464-473"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13047582/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625026","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}
J S Elson, Erin M Kearns, Callie Vitro, Tin Nguyen, Ryan Schuetzler
{"title":"Familiarity with and Attitudes Towards Chatbots: Findings from a Three-Wave National Surveys of U.S. Adults Before and After ChatGPT.","authors":"J S Elson, Erin M Kearns, Callie Vitro, Tin Nguyen, Ryan Schuetzler","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Generative AI technologies like ChatGPT have transformed how people interact with information and services. However, it is unclear (1) what the public knew about chatbots before ChatGPT, (2) how those understandings have evolved, and (3) whether digital divides exist in these understandings. To explore this, we conducted a three-wave national online survey. Wave 1 data were collected just before ChatGPT's 2022 release; Waves 2 and 3 followed one and two years later. Each wave assessed chatbot familiarity (awareness, use, frequency), and Waves 2 and 3 included generative AI. We also measured trust in, support for, and intentions to use chatbots. We analyzed changes over time and examined differences by age, education, and income. Results suggest that people are more familiar with chatbots post-ChatGPT and use of these technologies is associated with more positive attitudes toward them. We further find evidence of digital divides across age and, increasingly, education and income.</p>","PeriodicalId":74512,"journal":{"name":"Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences","volume":"2026 ","pages":"4526-4534"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13047574/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625051","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}
A Erin Bass, Joel S Elson, Erin G Pleggenkuhle-Miles
{"title":"Co-Piloting with GenAI: A Functional Typology of Student-AI Interaction in Business Education.","authors":"A Erin Bass, Joel S Elson, Erin G Pleggenkuhle-Miles","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>To prepare business students for an AI-enabled workforce, educators are increasingly integrating generative AI (GenAI) tools into the classroom. Yet little is known about how students actually use these tools for complex tasks. This study examines how undergraduate students use GenAI during a strategic decision-making activity. We analyzed 167 student prompts using a dual-framework approach: the AI-ICE model to assess cognitive engagement, and an inductively developed typology of GenAI co-pilot roles: Content Generator, Task Executor, Advisor, Thinking Partner, and Role-Shifting. While students demonstrated cognitive range, most used GenAI in limited functional roles. Even when tasks called for strategic thinking, students rarely used GenAI as a collaborator. This disconnect between what students think and how they use GenAI highlights a gap in current instructional practice. Our findings offer a functional typology of student-GenAI interaction and practical insights for designing GenAI-enabled learning experiences in business education.</p>","PeriodicalId":74512,"journal":{"name":"Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences","volume":"2026 ","pages":"4956-4965"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13047563/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625005","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}
Kristy Helscel, Nathaniel Spears, Alex Oberyszyn, Matthew Marquardt, Angela Emerson, Nicholas Leahy, Catherine Quatman-Yates, James Crick
{"title":"Gown, Glove, Gadget: A Qualitative Study Exploring Surgeons' Use of Wearable Devices in the Operating Room.","authors":"Kristy Helscel, Nathaniel Spears, Alex Oberyszyn, Matthew Marquardt, Angela Emerson, Nicholas Leahy, Catherine Quatman-Yates, James Crick","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>This qualitative study explores surgeon experiences using wearable biometric devices in the operating room to support surgeon wellbeing and optimize personal performance. Through semi-structured interviews with attending surgeons and trainees across surgical subspecialties, we identified four themes: (1) increased self-awareness for behavior modification, (2) integration into surgical workflows, (3) challenges with wearable biometric device usability, and (4) future opportunities and broader implications. Participants valued devices that offered intuitive and actionable insights with minimal workflow disruption. However, data complexity and fragmented app ecosystems limited participant engagement. A Strengths, Weaknesses, Opportunities, and Threats (SWOT) framework was used to translate qualitative insights into device implementation considerations. Ethical concerns, especially regarding employee privacy and data governance, were noted as potential barriers. These findings highlight both the promise and pitfalls of integrating these devices into surgical practice and suggest the need for thoughtful design, institutional support, and ethical safeguards to maximize device utility and efficacy.</p>","PeriodicalId":74512,"journal":{"name":"Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences","volume":"59 ","pages":"3717-3726"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13095232/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791628","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}
Tiffany R Glynn, Roger D Dias, Robson J Verly, Conall O'Cleirigh, Peter R Chai
{"title":"Leveraging virtual reality to improve medication adherence among marginalized populations with high-risk chronic health conditions: Proof-of-concept protocol, considerations, and next steps.","authors":"Tiffany R Glynn, Roger D Dias, Robson J Verly, Conall O'Cleirigh, Peter R Chai","doi":"10.24251/hicss.2025.393","DOIUrl":"10.24251/hicss.2025.393","url":null,"abstract":"<p><p>Marginalized populations experience high prevalence of chronic health conditions - many of which require optimal medication adherence to avoid significant consequences for mortality and morbidity. Yet, marginalization and its complex sequelae create barriers for adherence and access to care, creating a cycle of health inequity. Individuals are not fully benefiting from evidence-based behavioral adherence interventions, like \"Life-steps\", potentially due to lack of embedded experiential learning, which is key for individuals experiencing complex barriers to medication adherence. Leveraging interactive artificial intelligence technologies through immersive virtual reality is a promising avenue to bolster behavioral adherence interventions. We present our current proof-of-concept work for \"Life-steps VR\", an integration of such technologies into the empiric behavioral medication adherence intervention. We then discuss our next steps for further refinement and testing of the technology with consideration for equity, democratization, and accessibility of health technologies. We conclude with a discussion of future potential iterations of Life-steps VR.</p>","PeriodicalId":74512,"journal":{"name":"Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12341852/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144850055","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}
{"title":"TrialView: An AI-powered Visual Analytics System for Temporal Event Data in Clinical Trials.","authors":"Zuotian Li, Xiang Liu, Zelei Cheng, Yingjie Chen, Wanzhu Tu, Jing Su","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Randomized controlled trials (RCT) are the gold standards for evaluating the efficacy and safety of therapeutic interventions in human subjects. In addition to the pre-specified endpoints, trial participants' experience reveals the time course of the intervention. Few analytical tools exist to summarize and visualize the individual experience of trial participants. Visual analytics allows integrative examination of temporal event patterns of patient experience, thus generating insights for better care decisions. Towards this end, we introduce TrialView, an information system that combines graph artificial intelligence (AI) and visual analytics to enhance the dissemination of trial data. TrialView offers four distinct yet interconnected views: Individual, Cohort, Progression, and Statistics, enabling an interactive exploration of individual and group-level data. The TrialView system is a general-purpose analytical tool for a broad class of clinical trials. The system is powered by graph AI, knowledge-guided clustering, explanatory modeling, and graph-based agglomeration algorithms. We demonstrate the system's effectiveness in analyzing temporal event data through a case study.</p>","PeriodicalId":74512,"journal":{"name":"Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences","volume":"2024 ","pages":"1169-1178"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11052597/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140873957","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}
Tiffany R Glynn, Simran S Khanna, Mohammad Adrian Hasdianda, Jeremiah Tom, Krishna Ventakasubramanian, Arlen Dumas, Conall O'Cleirigh, Charlotte E Goldfine, Peter R Chai
{"title":"Informing Acceptability and Feasibility of Digital Phenotyping for Personalized HIV Prevention among Marginalized Populations Presenting to the Emergency Department.","authors":"Tiffany R Glynn, Simran S Khanna, Mohammad Adrian Hasdianda, Jeremiah Tom, Krishna Ventakasubramanian, Arlen Dumas, Conall O'Cleirigh, Charlotte E Goldfine, Peter R Chai","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>For marginalized populations with ongoing HIV epidemics, alternative methods are needed for understanding the complexities of HIV risk and delivering prevention interventions. Due to lack of engagement in ambulatory care, such groups have high utilization of drop-in care. Therefore, emergency departments represent a location with those at highest risk for HIV and in highest need of novel prevention methods. Digital phenotyping via data collected from smartphones and other wearable sensors could provide the innovative vehicle for examining complex HIV risk and assist in delivering personalized prevention interventions. However, there is paucity in exploring if such methods are an option. This study aimed to fill this gap via a cross-sectional psychosocial assessment with a sample of N=85 emergency department patients with HIV risk. Findings demonstrate that although potentially feasible, acceptability of digital phenotyping is questionable. Technology-assisted HIV prevention needs to be designed with the target community and address key ethical considerations.</p>","PeriodicalId":74512,"journal":{"name":"Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences","volume":"57 ","pages":"3192-3200"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10774708/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139405603","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}
{"title":"Comparing Social Media Communities using Functional Data Analysis.","authors":"Xiaoxia Champon, Jasser Jasser, Chathura Jayalath, Ivan Garibay, Wiliam Rand, Ozlem Garibay","doi":"10.24251/hicss.2024.501","DOIUrl":"10.24251/hicss.2024.501","url":null,"abstract":"<p><p>Various social media communities can lead conversations in entirely divergent directions, shaping the nature of information shared on these platforms. Deliberate disinformation and manipulated messages, disseminated both within and beyond these communities, hold the potential to reshape public opinion on a broader scale. A constructive analysis that delves into the disparities between these opposing groups could prove invaluable in discerning the pathways through which information flows. Our research examines the temporal dynamics of social media groups, assessing their behavior through metrics such as time dependent post and retweets. Using functional data analysis, we investigate Tweets related to incidents like the Skripal/Novichok case and the Bucha Crimes. Our goal is to quantify the disparities between these communities and uncover the strategies employed by each group to promote specific campaigns. Our preliminary findings shed new light on the mechanics of information dissemination, offering insights that may inform decisions about optimal response times.</p>","PeriodicalId":74512,"journal":{"name":"Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences","volume":"2024 ","pages":"4162-4171"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12715765/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145806669","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}