Evidence map›Paper›PMID 38515596›Full record

ArticleFrontiers in public health2024

Public perception on active aging after COVID-19: an unsupervised machine learning analysis of 44,343 posts.

Peipei Chen, Yuwei Jin, Xinfang Ma, Yan Lin

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Peipei ChenSchool of Foreign Language Studies, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Yuwei JinSchool of Foreign Language Studies, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Xinfang MaSchool of Foreign Language Studies, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Yan LinSchool of Foreign Language Studies, Wenzhou Medical University, Wenzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: To analyze public perceptions of active aging in China on mainstream social media platforms to determine whether the "14th Five Year Plan for the Development of the Aging Career and Older Adult Care System" issued by the CPC in 2022 has fully addressed public needs. Methods: The original tweets posted on Weibo between January 1, 2020, and June 30, 2022, containing the words "aging" or "old age" were extracted. A bidirectional encoder representation from transformers (BERT)-based model was used to generate themes related to this perception. A qualitative thematic analysis and an independent review of the theme labels were conducted by the researchers. Results: The findings indicate that public perceptions revolved around four themes: (1) health prevention and protection, (2) convenient living environments, (3) cognitive health and social integration, and (4) protecting the rights and interests of the older adult. Discussion: Our study found that although the Plan aligns with most of these themes, it lacks clear planning for financial security and marital life.

Indexed as

COVID-19Social MediaAgedHumansPublic OpinionSARS-CoV-2Unsupervised Machine Learningactive agingBERTopicpolicy makingpublic perceptiontopic modeling

Identifiers

PMID38515596
PMCPMC10956692

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.