Designing a Multimodal and Culturally Relevant Alzheimer Disease and Related Dementia Generative Artificial Intelligence Tool for Black American Informal Caregivers: Cognitive Walk-Through Usability Study.

IF 5 Q1 GERIATRICS & GERONTOLOGY JMIR Aging Pub Date : 2025-01-08 DOI:10.2196/60566
Cristina Bosco, Ege Otenen, John Osorio Torres, Vivian Nguyen, Darshil Chheda, Xinran Peng, Nenette M Jessup, Anna K Himes, Bianca Cureton, Yvonne Lu, Carl V Hill, Hugh C Hendrie, Priscilla A Barnes, Patrick C Shih
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Abstract

Background: Many members of Black American communities, faced with the high prevalence of Alzheimer disease and related dementias (ADRD) within their demographic, find themselves taking on the role of informal caregivers. Despite being the primary individuals responsible for the care of individuals with ADRD, these caregivers often lack sufficient knowledge about ADRD-related health literacy and feel ill-prepared for their caregiving responsibilities. Generative AI has become a new promising technological innovation in the health care domain, particularly for improving health literacy; however, some generative AI developments might lead to increased bias and potential harm toward Black American communities. Therefore, rigorous development of generative AI tools to support the Black American community is needed.

Objective: The goal of this study is to test Lola, a multimodal mobile app, which, by relying on generative AI, facilitates access to ADRD-related health information by enabling speech and text as inputs and providing auditory, textual, and visual outputs.

Methods: To test our mobile app, we used the cognitive walk-through methodology, and we recruited 15 informal ADRD caregivers who were older than 50 years and part of the Black American community living within the region. We asked them to perform 3 tasks on the mobile app (ie, searching for an article on brain health, searching for local events, and finally, searching for opportunities to participate in scientific research in their area), then we recorded their opinions and impressions. The main aspects to be evaluated were the mobile app's usability, accessibility, cultural relevance, and adoption.

Results: Our findings highlight the users' need for a system that enables interaction with different modalities, the need for a system that can provide personalized and culturally and contextually relevant information, and the role of community and physical spaces in increasing the use of Lola.

Conclusions: Our study shows that, when designing for Black American older adults, a multimodal interaction with the generative AI system can allow individuals to choose their own interaction way and style based upon their interaction preferences and external constraints. This flexibility of interaction modes can guarantee an inclusive and engaging generative AI experience.

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为美国黑人非正式照顾者设计一个多模式和文化相关的阿尔茨海默病和相关痴呆生成人工智能工具:认知演练可用性研究。
背景:美国黑人社区的许多成员,面对高患病率的阿尔茨海默病和相关痴呆(ADRD)在他们的人口统计,发现自己承担了非正式照顾者的角色。尽管这些照顾者是负责照顾ADRD患者的主要个体,但他们往往缺乏足够的与ADRD相关的健康知识,并且对自己的照顾责任准备不足。生成式人工智能已成为医疗保健领域一项新的有前途的技术创新,特别是在提高健康素养方面;然而,一些生成式人工智能的发展可能会导致对美国黑人社区的偏见和潜在伤害增加。因此,需要严格开发生成式人工智能工具来支持美国黑人社区。目的:本研究的目的是测试Lola,这是一款多模式移动应用程序,它依靠生成式人工智能,通过支持语音和文本作为输入,并提供听觉、文本和视觉输出,促进了对adrd相关健康信息的访问。方法:为了测试我们的移动应用程序,我们使用了认知演练方法,我们招募了15名年龄在50岁以上的非正式ADRD护理人员,他们是居住在该地区的美国黑人社区的一部分。我们让他们在手机app上完成3个任务(即搜索一篇关于大脑健康的文章,搜索当地的事件,最后搜索参与他们所在地区的科学研究的机会),然后我们记录他们的意见和印象。需要评估的主要方面是手机应用的可用性、可访问性、文化相关性和采用率。结果:我们的研究结果强调了用户对一个能够与不同模式进行交互的系统的需求,对一个能够提供个性化和文化和上下文相关信息的系统的需求,以及社区和物理空间在增加Lola使用中的作用。结论:我们的研究表明,在针对美国黑人老年人的设计中,与生成式AI系统的多模式交互可以让个人根据自己的交互偏好和外部约束选择自己的交互方式和风格。这种交互模式的灵活性可以保证具有包容性和吸引力的生成式人工智能体验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JMIR Aging
JMIR Aging Social Sciences-Health (social science)
CiteScore
6.50
自引率
4.10%
发文量
71
审稿时长
12 weeks
期刊最新文献
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