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Record W4410084506 · doi:10.2196/56028

Online Health Information–Seeking Behaviors Among the Chongqing Population: Cross-Sectional Questionnaire Study

2025· article· en· W4410084506 on OpenAlexvenueno aff
Honghui Rong, Lu Lu, Tian Z. Guo, Qingliu Tao, Yixin Li, Chuanfen Zheng, Fengju Li, D. Yi, Enyu Lei, Ting Luo, Qinghua Yang, Ji-an Chen

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsHealth literacyPopulationLogistic regressionEnvironmental healthMedicineChinaCross-sectional studyDemographicsThe InternetGeographyDemographyHealth careWorld Wide Web

Abstract

fetched live from OpenAlex

Background: With the rapid development of the internet and its widespread use, online health information-seeking (OHIS) has become a popular and important research topic. Various benefits of OHIS are well recognized. However, OHIS seems to be a mixed blessing. Research on OHIS has been reported in Western countries and in high-income regions in eastern China. Studies on the population in the western region of China, such as Chongqing, are still limited. Objective: The aim of the study was to identify the prevalence, common topics, and common methods of health information-seeking and the factors influencing these behaviors among the Chongqing population. Methods: This cross-sectional questionnaire study was conducted from September to October 2021. A web-based questionnaire was sent to users aged 15 years and older in Chongqing using a Chinese web-based survey hosting site (N=14,466). Data on demographics, web-based health information resources, and health topics were collected. Factors that may influence health literacy were assessed using the chi-square test and multivariate logistic regression models. Results: A total of 67.1% (9704/14,466) of the participants displayed OHIS behaviors. Participants who were younger, had a higher educational level, and worked as medical staff or teachers were more likely to engage in OHIS, while those living in rural areas, ethnic minorities, and farmers were less likely to seek health information on the web (P<.01). Among the Chongqing population, the most common topic searched on the internet was health behavior and literacy (87.4%, 8483/9704), and the most popular method of seeking health information on the web was through WeChat (77.0%, 7468/9704). Conclusions: OHIS is prevalent in Chongqing. Further research could be performed based on the influencing factors identified herein and high-priority, effective ways of improving the OHIS behaviors of the Chongqing population.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.115
GPT teacher head0.594
Teacher spread0.479 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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