Evidence map›Paper›PMID 36747557›Full record

ArticleHeliyon2023

Public perception on 'healthy ageing' in the past decade: An unsupervised machine learning of 63,809 Twitter posts.

Qin Xiang Ng, Dawn Yi Xin Lee, Chun En Yau, Yu Liang Lim, Tau Ming Liew

Abstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

5 authors.

Qin Xiang NgHealth Services Research Unit, Singapore General Hospital, Singapore, 168582, Singapore.
Dawn Yi Xin LeeSchool of Medicine, Dentistry and Nursing, University of Glasgow, Glasgow, G12 8QQ, United Kingdom.
Chun En YauNUS Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117597, Singapore.
Yu Liang LimMOH Holdings Pte Ltd, 1 Maritime Square, Singapore, 099253, Singapore.
Tau Ming LiewDepartment of Psychiatry, Singapore General Hospital, Singapore, 169608, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The World Health Organization (WHO) started the initiative on healthy ageing from 2016 to 2020, which has now continued into the United Nations (UN) Decade of Healthy Ageing 2021-2030. Research into healthy ageing and healthy ageing communities have emphasized that the concept of healthy ageing encompasses a plurality of views and has multiple dimensions. Anchored in a transdisciplinary approach, the present report thus aimed to investigate public perceptions of healthy ageing via a deep analysis of social media posts on Twitter. Original tweets, containing the terms "Healthy Ageing" OR "healthy aging" OR "healthyageing" OR "healthyaging", and posted in English between 1 January 2012 and 30 June 2022 were extracted. Bidirectional Encoder Representations from Transformers (BERT) Named Entity Recognition was applied to select for individual users. Topic modelling, specifically BERTopic was used to generate interpretable topics and descriptions pertaining to the concept of healthy ageing. Subsequently, manual thematic analysis was performed by the study investigators, with independent reviews of the topic labels and themes. A total of 63,809 unique tweets were analyzed and clustered semantically into 16 topics. The public perception of healthy ageing could be broadly grouped into three themes: (1) healthy diet and lifestyle, (2) maintaining normal bodily functions and (3) preventive care. While most perceptions dovetail WHO's definition, there are some points regarding skin appearances, beauty and aging that should be closely considered in the design of initiatives in the UN Decade of Healthy Ageing and beyond.

Indexed as

AgeismBERTHealthy ageingPublic perceptionTopic modelling

Identifiers

PMID36747557
PMCPMC9898637

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.