ArticleFrontiers in public health2022
Exploring public attitudes toward live-streaming fitness in China: A sentiment and content analysis of China's social media Weibo.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06682663 (Evaluation of the Effect of Live Streaming Exercise on the Improvement of Hepatic Steatosis and Fibrosis in Pregnant Women with MASLD and Its Study Based on the Liver-gut Axis Mechanism.), which is not on this map. Cited by 6 papers.
What it found
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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.
Evaluation of the Effect of Live Streaming Exercise on the Improvement of Hepatic Steatosis and Fibrosis in Pregnant Women with MASLD and Its Study Based on the Liver-gut Axis Mechanism.
Who cites it
6 citing papers in PubMed.
- Obesity Prevention and Reduction in China Using the Social Media Platform WeChat: Scoping Review.Interactive journal of medical research · 2025Review
- Investigating the role of Chinese sports media in shaping young adults' exercise habits through the lens of the health belief model.Frontiers in sports and active living · 2025Article
- Chinese Public Attitudes and Opinions on Health Policies During Public Health Emergencies: Sentiment and Topic Analysis.Journal of medical Internet research · 2024Article
- Being there and being with them: the effects of visibility affordance of online short fitness video on users' intention to cloud fitness.Frontiers in psychology · 2024Article
- What drives Chinese youth to use fitness-related health information on social media? An analysis of intrinsic needs, social media algorithms, and source credibility.Frontiers in public health · 2024Article
- Exploring sources of patient dissatisfaction in mobile health communication: A text analysis based on structural topic model.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: Live-streaming fitness is perceived by the Chinese government as an invaluable means to reduce the prevalence of physical inactivity amid the COVID-19 pandemic. This study aims to investigate the public altitudes of the Chinese people toward live-streaming fitness and provide future health communication strategies on the public promotion of live-streaming fitness accordingly. Methods: This study collected live-streaming fitness-related microblog posts from July 2021 to June 2022 in Weibo, the Chinese equivalent to Twitter. We used the BiLSTM-CNN model to carry out the sentiment analysis, and the structured topic modeling (STM) method to conduct content analysis. Results: This study extracted 114,397 live-streaming fitness-related Weibo posts. Over 80% of the Weibo posts were positive during the period of the study, and over 85% were positive in half of the period. This study finds 8 topics through content analysis, which are fitness during quarantine; cost reduction; online community; celebrity effect; Industry; fitness injuries; live commerce and Zero Covid strategy. Conclusions: It is discovered that the public attitudes toward live-streaming fitness were largely positive. Topics related to celebrity effect (5-11%), fitness injuries (8-16%), live commerce (5-9%) and Zero Covid strategy (16-26%) showed upward trends in negative views of the Chinese people. Specific health communication strategy suggestions are given to target each of the negative topics.
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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.