An Empirical Study of Older Adult’s Voice Assistant Use for Health Information Seeking

Author:

Brewer Robin1,Pierce Casey1,Upadhyay Pooja2,Park Leeseul1

Affiliation:

1. University of Michigan, Ann Arbor, Michigan, USA

2. Human-Computer Interaction Lab (HCIL), University of Maryland College Park, College Park, MD, USA

Abstract

Although voice assistants are increasingly being adopted by older adults, we lack empirical research on how they interact with these devices for health information seeking. Also, prior work shows how voice assistant responses can provide misleading or inaccurate information and be harmful particularly in health contexts. Because of increased health needs while aging, this paper studies older adult’s (ages 65+) health-related voice assistant interactions. Motivated by a lack of empirical evidence for how older adults approach information seeking with emerging technologies, we first conducted a survey of n = 201 older adults to understand how they engage voice assistants compared to a range of offline and digital sources for health information seeking. Findings show how voice assistants were used for confirmatory health queries, with users showing signs of distrust. As much prior work focuses on perceptions of voice assistant use, we conducted scenario-based interviews with n = 35 older adults to study health-related voice assistant behavior. In interviews, participants engaged with different health topics (flu, migraine, high blood pressure) and scenario types (symptom-driven, behavior-driven) using a voice assistant. Findings show how conversational and human-like expectations with voice assistants lead to information breakdowns between the older adult and voice assistant. This paper contributes a nuanced query-level analysis of older adults’ voice-based health information seeking behaviors. Further, data provide evidence for how query reformulation happens with complex topics in voice-based information seeking. We use our findings to discuss how voice interfaces can better support older adults’ health information seeking behaviors and expectations.

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Human-Computer Interaction

Reference78 articles.

1. 2017. Nearly Half of Americans use Digital Voice Assistants, Mostly on their Smartphones. Technical Report. Pew Research Center. https://www.pewresearch.org/fact-tank/2017/12/12/nearly-half-of-americans-use-digital-voice-assistants-mostly-on-their-smartphones/.

2. 2019. NHS Health Information Available Through Amazon’s Alexa. Technical Report. Department of Health and Social Care. https://www.gov.uk/government/news/nhs-health-information-available-through-amazon-s-alexa.

3. Should I Trust It When I Cannot See It?

4. "Siri Talks at You"

5. Deep evidential regression;Amini Alexander;arXiv preprint arXiv:1910.02600,2019

Cited by 26 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Examining Voice Community Use;ACM Transactions on Computer-Human Interaction;2024-02-05

2. Understanding voice‐based information uncertainty: A case study of health information seeking with voice assistants;Journal of the Association for Information Science and Technology;2023-12-05

3. "I don't know how to help with that" - Learning from Limitations of Modern Conversational Agent Systems in Caregiving Networks;Proceedings of the ACM on Human-Computer Interaction;2023-09-28

4. Understanding the Benefits and Design of Chatbots to Meet the Healthcare Needs of Migrant Workers;Proceedings of the ACM on Human-Computer Interaction;2023-09-28

5. “A Painless Way to Learn:” Designing an Interactive Storytelling Voice User Interface to Engage Older Adults in Informal Health Information Learning;Proceedings of the 5th International Conference on Conversational User Interfaces;2023-07-19

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3