ArticleDigital health
Artificial intelligence development and subjective well-being of older adults: Evidence from the China longitudinal aging social survey.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: With the intensification of population aging, the subjective well-being of older adults has become a topic of social concern. Meanwhile, artificial intelligence (AI) is penetrating various fields of society and transforming the living environment of older adults. However, research on the association between AI and the subjective well-being of older adults remains relatively scarce, and this study aims to explore the relationship between AI development and their subjective well-being. Methods: Based on the data from the China Longitudinal Aging Social Survey (CLASS), this study uses a two-way fixed effects model to examine the association between AI development and the subjective well-being of older adults. For robustness checks, it employs methods including double machine learning (DML), instrumental variable approach, variable replacement, addition of control variables, and adjustment of clustering levels. Results: (1) AI development is positively correlated with the subjective well-being of older adults. (2) Older adults' use of elderly care services and their social participation are the channels through which AI development is associated with improved subjective well-being among older adults. (3) The digital literacy of older adults plays a positive moderating role. (4) The positive association between AI development and subjective well-being is significantly larger in magnitude for the old-old group than for the young-old group. Conclusion: This study provides robust empirical evidence for a positive association between AI development and the subjective well-being of older adults. Based on this, efforts should be made to promote the in-depth integration of AI with elderly care services, expand AI-enabled channels for social participation, launch initiatives to improve older adults' digital literacy, and refine policy safeguards for AI-assisted elderly support.
Indexed as
Identifiers
What OpenQuestion holds
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.