Evidence map›Paper›PMID 38649405›Full record

ArticleScientific reports2024

Opportunities and challenges of integrating artificial intelligence in China's elderly care services.

Yongyan Zhao, Jian Li

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Observational
  15. Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yongyan ZhaoSchool of Humanities and Law, Harbin University, Heilongjiang, 150086, China.
Jian LiSchool of Innovation and Entrepreneurship, Harbin University, Heilongjiang, 150086, China. ijian@hrbu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The challenge of elderly care presents a formidable task, demanding the collective attention of governmental bodies and diverse sectors of society. The integration of Artificial Intelligence (AI) into the research and development of Social Elderly Care Service (ECS) has emerged as a dominant trend, holding substantial importance in the establishment of an efficient ECS system. This study aims to serve as a comprehensive reference for the advancement of China's ECS system, achieved through the harmonious integration of a social ECS system with AI capabilities. This paper introduces the fundamental theory of AI, delving into the intricacies of the greyscale model of AI. Furthermore, it provides an overview of the current landscape of elderly care and elder care institutions, offering scientific data and insights to propel further research on AI development and system construction. Through an analysis of the existing research status, the study identifies prevalent issues within the AI-ECS integration, emphasizing pivotal factors influencing the construction of a robust social ECS system. To address these concerns, the study puts forth specific and viable policy recommendations. Notably, the questionnaire's statistics underscore that 83% of the elderly populace would opt for AI-driven solutions in selecting intelligent products, thereby underscoring the pivotal role of AI within the social ECS system. The challenges facing elderly care systems, including demographic shifts, resource constraints, and evolving societal norms, demand innovative solutions for providing efficient and effective care. This study addresses these challenges by exploring the integration of Artificial Intelligence (AI) into Social Elderly Care Services (ECS) in China. By delving into the theory of AI and assessing the existing research status, the study identifies key issues in AI-ECS integration and proposes viable policy recommendations. Insights from stakeholder surveys further highlight the importance of AI-driven solutions in meeting the needs of the elderly population.

Indexed as

Artificial IntelligenceHealth Services for the AgedAgedChinaHumansArtificial intelligenceCommunityService evaluationService systemSocial pension

Identifiers

PMID38649405
PMCPMC11035568

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.