{"title":"Perceived Algorithmic Care Intensity and Older Adults' Autonomy in Community Smart Care: Mixed Methods Study.","authors":"Xianghui Huang","doi":"10.2196/94559","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>As smart older adult care shifts from basic information support to more continuous algorithm-driven care, concerns have grown about whether such systems support older adults' independence or weaken their sense of autonomy. Although previous research has focused mainly on technology acceptance, less is known about how algorithmic care shapes perceived autonomy and through which psychological pathways this occurs.</p><p><strong>Objective: </strong>This study examined whether perceived algorithmic care intensity reduces older adults' perceived autonomy in community smart care settings, whether decisional substitution and perceived surveillance mediate this relationship, and whether digital literacy moderates these effects.</p><p><strong>Methods: </strong>A 3-stage design was adopted. First, a qualitative prestudy with 15 older adults was conducted to refine the focal constructs and measures. Second, a vignette-based experiment with 233 valid participants tested the effects of algorithmic care intensity on decisional substitution, perceived surveillance, and perceived autonomy. Third, a community-based survey with 298 valid participants examined the moderated mediation model in real-world smart older adult care settings.</p><p><strong>Results: </strong>In study 1, compared with the low-intensity condition, the high-intensity condition significantly increased decisional substitution and perceived surveillance, while reducing perceived autonomy. Indirect effects through decisional substitution (effect=-0.072, 95% CI -0.144 to -0.016) and perceived surveillance (effect=-0.084, 95% CI -0.161 to -0.019) were both significant. In study 2, perceived algorithmic care intensity positively predicted decisional substitution (β=.400, P<.001) and perceived surveillance (β=.440, P<.001), and negatively predicted perceived autonomy (β=-.356, P<.001). The indirect effects through decisional substitution (effect=-0.112, 95% CI -0.172 to -0.065) and perceived surveillance (effect=-0.149, 95% CI -0.215 to -0.093) were significant. Digital literacy significantly weakened the effect of algorithmic care intensity on decisional substitution (β=-.174, P=.002), but not on perceived surveillance (β=-.071, P=.18).</p><p><strong>Conclusions: </strong>Algorithmic care may undermine older adults' perceived autonomy both directly and indirectly through decisional substitution and perceived surveillance. Digital literacy appears to be a selective rather than universal buffer. These findings extend smart older adult care research beyond technology acceptance and clarify the tension between empowerment and control in algorithmic care.</p>","PeriodicalId":36245,"journal":{"name":"JMIR Aging","volume":"9 ","pages":"e94559"},"PeriodicalIF":4.6000,"publicationDate":"2026-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13378906/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Aging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2196/94559","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: As smart older adult care shifts from basic information support to more continuous algorithm-driven care, concerns have grown about whether such systems support older adults' independence or weaken their sense of autonomy. Although previous research has focused mainly on technology acceptance, less is known about how algorithmic care shapes perceived autonomy and through which psychological pathways this occurs.
Objective: This study examined whether perceived algorithmic care intensity reduces older adults' perceived autonomy in community smart care settings, whether decisional substitution and perceived surveillance mediate this relationship, and whether digital literacy moderates these effects.
Methods: A 3-stage design was adopted. First, a qualitative prestudy with 15 older adults was conducted to refine the focal constructs and measures. Second, a vignette-based experiment with 233 valid participants tested the effects of algorithmic care intensity on decisional substitution, perceived surveillance, and perceived autonomy. Third, a community-based survey with 298 valid participants examined the moderated mediation model in real-world smart older adult care settings.
Results: In study 1, compared with the low-intensity condition, the high-intensity condition significantly increased decisional substitution and perceived surveillance, while reducing perceived autonomy. Indirect effects through decisional substitution (effect=-0.072, 95% CI -0.144 to -0.016) and perceived surveillance (effect=-0.084, 95% CI -0.161 to -0.019) were both significant. In study 2, perceived algorithmic care intensity positively predicted decisional substitution (β=.400, P<.001) and perceived surveillance (β=.440, P<.001), and negatively predicted perceived autonomy (β=-.356, P<.001). The indirect effects through decisional substitution (effect=-0.112, 95% CI -0.172 to -0.065) and perceived surveillance (effect=-0.149, 95% CI -0.215 to -0.093) were significant. Digital literacy significantly weakened the effect of algorithmic care intensity on decisional substitution (β=-.174, P=.002), but not on perceived surveillance (β=-.071, P=.18).
Conclusions: Algorithmic care may undermine older adults' perceived autonomy both directly and indirectly through decisional substitution and perceived surveillance. Digital literacy appears to be a selective rather than universal buffer. These findings extend smart older adult care research beyond technology acceptance and clarify the tension between empowerment and control in algorithmic care.
背景:随着智能老年人护理从基本的信息支持转向更持续的算法驱动的护理,人们越来越关注这样的系统是支持老年人的独立性还是削弱他们的自主意识。虽然以前的研究主要集中在技术接受上,但对于算法护理如何塑造感知的自主性以及通过哪些心理途径发生这种情况,人们知之甚少。目的:本研究考察了感知算法护理强度是否会降低老年人在社区智能护理环境中的感知自主性,决策替代和感知监督是否介导了这种关系,以及数字素养是否调节了这些影响。方法:采用三阶段设计。首先,对15名老年人进行了定性预研究,以完善焦点结构和措施。其次,一项有233名有效参与者的基于图像的实验测试了算法关心强度对决策替代、感知监视和感知自治的影响。第三,以社区为基础,对298名有效参与者进行了调查,检验了现实世界智能老年人护理环境中的调节中介模型。结果:在研究1中,与低强度条件相比,高强度条件显著增加了决策替代和感知监视,同时降低了感知自主性。通过决策替代(效应=-0.072,95% CI -0.144至-0.016)和感知监视(效应=-0.084,95% CI -0.161至-0.019)的间接效应均显著。在研究2中,感知算法护理强度正向预测决策替代(β= 0.400, p)。结论:算法护理可能通过决策替代和感知监视直接和间接地破坏老年人的感知自主性。数字素养似乎是一种选择性的缓冲,而不是普遍的缓冲。这些发现将智能老年人护理研究扩展到技术接受之外,并澄清了算法护理中授权和控制之间的紧张关系。