Evidence map›Paper›PMID 41191632›Full record

ArticlePloS one2025

Sentiment analysis of cancer screening in Chinese social media: Qualitative studies based on machine learning.

Qi Zhou, Lingling Qian, Luyu Wu, Haiqian Wu, Junwei Ye, Qinrou Yu, Xiangnan Gu, Yueli Zhu

Abstract read
In one paragraph

Article in PloS one, 2025. 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. Observational
  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

8 authors.

Qi ZhouIntegrated Traditional and Western Medicine Hospital of Linping District, Hangzhou, Zhejiang Province, China.
Lingling QianTongji zhejiang college, Huzhou, Zhejiang Province, China.
Luyu WuFengyang College, Shanxi Medical University, Fengyang, Shanxi Province, China.
Haiqian WuHuZhou Normal University, Hangzhou, Zhejiang Province, China.
Junwei YeIntegrated Traditional and Western Medicine Hospital of Linping District, Hangzhou, Zhejiang Province, China.
Qinrou YuNursing department, Hangzhou normal university, Hangzhou, Zhejiang Province, China.
Xiangnan GuZhejiang University, Hangzhou, Zhejiang Province, China.
Yueli ZhuIntegrated Traditional and Western Medicine Hospital of Linping District, Hangzhou, Zhejiang Province, China.ORCID https://orcid.org/0009-0005-1867-4315

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeExplore public perceptions and sentiments about cancer screening on social media. The dissemination of misinformation and negative attitudes continue to impede the access of many individuals with perceived risk to cancer screening services despite their awareness of the necessity and concept of early cancer screening.

methodsThis study was divided into five steps: data collection, data cleaning, data standardization, sentiment analysis, and content analysis.

resultsThis study analyzed 796 social media comments (53,151 words) from Weibo, Zhihu, and Xiaohongshu to explore public sentiments toward cancer screening. Seven emotion categories emerged: good, happy, surprise, anger, disgust, fear, and sadness. Positive emotions reflected trust in physicians, financial support, and perceived screening effectiveness, whereas negative emotions reflected fear of cancer, stigma, and procrastination.

conclusionThe findings of this study include the development of health communication strategies, the promotion of public screening participation, and the improvement of nursing personalization and emotional sensitivity. These findings highlight barriers and facilitators for cancer screening promotion in China and inform targeted nursing communication strategies.

Indexed as

Early Detection of CancerMachine LearningNeoplasmsSocial MediaAdultChinaEmotionsFemaleHumansMaleMiddle AgedQualitative Research

Identifiers

PMID41191632
PMCPMC12588461

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.