Reducing Loneliness and Improving Social Support among Older Adults through Different Modalities of Personal Voice Assistants.

IF 2.1 Q3 GERIATRICS & GERONTOLOGY
Valerie K Jones, Changmin Yan, Marcia Y Shade, Julie Blaskewicz Boron, Zhengxu Yan, Hyeon Jung Heselton, Kate Johnson, Victoria Dube
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引用次数: 0

Abstract

This study examines the potential of AI-powered personal voice assistants (PVAs) in reducing loneliness and increasing social support among older adults. With the aging population rapidly expanding, innovative solutions are essential. Prior research has indicated the effectiveness of various interactive communication technologies (ICTs) in mitigating loneliness, but studies focusing on PVAs, particularly considering their modality (audio vs. video), are limited. This research aims to fill this gap by evaluating how voice assistants, in both audio and video formats, influence perceived loneliness and social support. This study examined the impact of voice assistant technology (VAT) interventions, both audio-based (A-VAT) and video-based (V-VAT), on perceived loneliness and social support among 34 older adults living alone. Over three months, participants engaged with Amazon Alexa™ PVA through daily routines for at least 30 min. Using a hybrid natural language processing framework, interactions were analyzed. The results showed reductions in loneliness (Z = -2.99, p < 0.01; pre-study loneliness mean = 1.85, SD = 0.61; post-study loneliness mean = 1.65, SD = 0.57), increases in social support post intervention (Z = -2.23, p < 0.05; pre-study social support mean = 5.44, SD = 1.05; post-study loneliness mean = 5.65, SD = 1.20), and a correlation between increased social support and loneliness reduction when the two conditions are combined (ρ = -0.39, p < 0.05). In addition, V-VAT was more effective than A-VAT in reducing loneliness (U = 85.50, p < 0.05) and increasing social support (U = 95, p < 0.05). However, no significant correlation between changes in perceived social support and changes in perceived loneliness was observed in either intervention condition (V-VAT condition: ρ = -0.24, p = 0.37; A-VAT condition: ρ = -0.46, p = 0.06). This study's findings could significantly contribute to developing targeted interventions for improving the well-being of aging adults, addressing a critical global issue.

通过个人语音助理的不同模式减少老年人的孤独感并改善他们的社会支持。
本研究探讨了人工智能驱动的个人语音助手(PVA)在减少老年人孤独感和增加社会支持方面的潜力。随着老龄化人口的迅速增长,创新的解决方案至关重要。先前的研究表明,各种互动交流技术(ICTs)在减轻孤独感方面都很有效,但以个人语音助理为重点的研究,特别是考虑到其模式(音频与视频)的研究却很有限。本研究旨在通过评估音频和视频格式的语音助手如何影响孤独感和社会支持来填补这一空白。本研究考察了语音助理技术(VAT)干预措施对 34 名独居老年人感知到的孤独感和社会支持的影响,包括基于音频的(A-VAT)和基于视频的(V-VAT)。在三个月的时间里,参与者通过日常活动与亚马逊 Alexa™ PVA 进行了至少 30 分钟的互动。使用混合自然语言处理框架对互动进行了分析。结果显示,孤独感减少(Z = -2.99,p < 0.01;研究前孤独感平均值 = 1.85,SD = 0.61;研究后孤独感平均值 = 1.65,SD = 0.57),干预后社会支持增加(Z = -2.23,p < 0.05;研究前社会支持平均值 = 5.44,SD = 1.05;研究后孤独感平均值 = 5.65,SD = 1.20),当两种情况合并时,社会支持的增加与孤独感的减少之间存在相关性(ρ = -0.39,p < 0.05)。此外,在减少孤独感(U = 85.50,p < 0.05)和增加社会支持(U = 95,p < 0.05)方面,V-VAT 比 A-VAT 更有效。然而,在任何一种干预条件下,感知到的社会支持的变化与感知到的孤独感的变化之间都没有观察到明显的相关性(V-VAT 条件:ρ = -0.24,p = 0.37;A-VAT 条件:ρ = -0.46,p = 0.06)。这项研究的结果将大大有助于制定有针对性的干预措施,以改善老龄成年人的福祉,从而解决这一至关重要的全球性问题。
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
Geriatrics
Geriatrics 医学-老年医学
CiteScore
3.30
自引率
0.00%
发文量
115
审稿时长
20.03 days
期刊介绍: • Geriatric biology • Geriatric health services research • Geriatric medicine research • Geriatric neurology, stroke, cognition and oncology • Geriatric surgery • Geriatric physical functioning, physical health and activity • Geriatric psychiatry and psychology • Geriatric nutrition • Geriatric epidemiology • Geriatric rehabilitation
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