ArticleFrontiers in public health2022
Utilizing Baidu Index to Investigate Seasonality, Spatial Distribution and Public Attention of Dry Eye Diseases in Chinese Mainland.
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. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Research on pollen allergy in Fuzhou, China: from the online public concern surveys to pollen monitoring.Frontiers in public health · 2026Article
- Public Interest in Dry Eye Disease and Its Association With Environmental Parameters in Taiwan: Google Trends Infodemiology Study.JMIR infodemiology · 2025Article
- Dry eye disease seasonal pattern and climatic association in Saudi Arabia using Google Trends.PloS one · 2025Article
- Spatiotemporal distribution of migraine in China: analyses based on baidu index.BMC public health · 2023Article
- Did the COVID-19 pandemic impact urticaria information-seeking behavior in China? A retrospective longitudinal study.Frontiers in public health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To explore the characteristics of spatial-temporal prevalence and public attention of dry eye diseases (DED) through Baidu Index (BI) based on infodemiology method. Methods: The data about BI of DED were collected from Baidu search engine using "Dry eye diseases" as keyword. The spatial and temporal distribution of DED were analyzed through timeseries data decomposition as well as spatial autocorrelation and hotspot detection of BI about DED. The most popular related words and demographic characteristics were recorded to determine the public attention of DED. Results: The trends of BI about DED in Chinese mainland had gradually increased over time with a rapid increase from 2012 to 2014 and in 2018. The results of timeseries decomposition indicated that there was seasonality in the distribution of BI about DED with the peak in winter, especially in northern regions. The geographic distribution demonstrated the search activities of DED was highest in the east of Chinese mainland while lowest in the west. The vast majority of people searching for DED were teenagers (20-29 years), with a predominance of females. Glaucoma, keratitis and conjunctivitis were the diseases most often confused with DED, and the artificial tears were the most common treatment for DED in Chinese mainland according to the BI about DED. Conclusions: The analysis revealed the seasonality, geographic hotspots and public concern of DED through BI in Chinese mainland, which provided new insights into the epidemiology of DED.
Indexed as
Identifiers
What OpenQuestion holds
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.