ArticleJMIR aging2019
Exploring Older Adults' Beliefs About the Use of Intelligent Assistants for Consumer Health Information Management: A Participatory Design Study.
Article in JMIR aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Reducing Loneliness and Social Isolation of Older Adults Through Voice Assistants: Literature Review and Bibliometric Analysis.Journal of medical Internet research · 2024Pooled it
- Home-Based Cognitive Intervention for Healthy Older Adults Through Asking Robots Questions: Randomized Controlled Trial.JMIR aging · 2024Trial
- Dialoguing with algorithms: experiences of generative AI use in navigating complex health decisions among older adults with multimorbidity: a qualitative study.BMC health services research · 2026Article
- A Multimodal Conversational Chatbot for Emotional Support and Daily Assistance in Older Adults: Design, Development and Pilot Usability Evaluation.Healthcare (Basel, Switzerland) · 2026Article
- Article
- Exploring the application of generative artificial intelligence in nursing: a cross-sectional study.Frontiers in public health · 2026Article
- Article
- Engagement of Older Adults in the Design, Implementation, and Evaluation of Artificial Intelligence Systems for Aging: A Scoping Review.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025Article
- Review
- Voice Assistants for Mental Health Services: Designing Dialogues with Homebound Older Adults.DIS. Designing Interactive Systems (Conference) · 2024Article
- Patient Perspectives on the Use of Artificial Intelligence in Health Care: A Scoping Review.Journal of patient-centered research and reviews · 2024Article
- Qualitative Analysis of Conversational Chatbots to Alleviate Loneliness in Older Adults as a Strategy for Emotional Health.Healthcare (Basel, Switzerland) · 2023Article
- Co-design of the Transgender Health Information Resource: Web-Based Participatory Design.Journal of participatory medicine · 2023Article
- Article
- "It's Kind of Like Code-Switching": Black Older Adults' Experiences with a Voice Assistant for Health Information Seeking.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2022Article
- Comparing Older and Younger Adults Perceptions of Voice and Text-based Search for Consumer Health Information Tasks.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- A Question of Access: Exploring the Perceived Benefits and Barriers of Intelligent Voice Assistants for Improving Access to Consumer Health Resources Among Low-Income Older Adults.Gerontology & geriatric medicineArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntelligent assistants (IAs), also known as intelligent agents, use artificial intelligence to help users achieve a goal or complete a task. IAs represent a potential solution for providing older adults with individualized assistance at home, for example, to reduce social isolation, serve as memory aids, or help with disease management. However, to design IAs for health that are beneficial and accepted by older adults, it is important to understand their beliefs about IAs, how they would like to interact with IAs for consumer health, and how they desire to integrate IAs into their homes.
objectiveWe explore older adults' mental models and beliefs about IAs, the tasks they want IAs to support, and how they would like to interact with IAs for consumer health. For the purpose of this study, we focus on IAs in the context of consumer health information management and search.
methodsWe present findings from an exploratory, qualitative study that investigated older adults' perspectives of IAs that aid with consumer health information search and management tasks. Eighteen older adults participated in a multiphase, participatory design workshop in which we engaged them in discussion, brainstorming, and design activities that helped us identify their current challenges managing and finding health information at home. We also explored their beliefs and ideas for an IA to assist them with consumer health tasks. We used participatory design activities to identify areas in which they felt IAs might be useful, but also to uncover the reasoning behind the ideas they presented. Discussions were audio-recorded and later transcribed. We compiled design artifacts collected during the study to supplement researcher transcripts and notes. Thematic analysis was used to analyze data.
resultsWe found that participants saw IAs as potentially useful for providing recommendations, facilitating collaboration between themselves and other caregivers, and for alerts of serious illness. However, they also desired familiar and natural interactions with IAs (eg, using voice) that could, if need be, provide fluid and unconstrained interactions, reason about their symptoms, and provide information or advice. Other participants discussed the need for flexible IAs that could be used by those with low technical resources or skills.
conclusionsFrom our findings, we present a discussion of three key components of participants' mental models, including the people, behaviors, and interactions they described that were important for IAs for consumer health information management and seeking. We then discuss the role of access, transparency, caregivers, and autonomy in design for addressing participants' concerns about privacy and trust as well as its role in assisting others that may interact with an IA on the older adults' behalf. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1145/3240925.3240972.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.