Evidence map›Paper›PMID 41252192›Full record

ArticleJournal of medical Internet research2025

Online Health-Seeking Behaviors and Information Needs Among Patients With Lymphoma in China: Study of Regional and Temporal Trends.

Kaida Ning, Hongfei Gu, Meredith Franklin, Xiaoying Yang, Rong Wei, Zhen Song, Hong Xu, Ling Li Leng, Mengting Liu, Ju Dai and 9 more

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

19 authors.

Kaida Ning *Department of Network Intelligence, Peng Cheng Laboratory, Shenzhen, Guangdong, China.ORCID https://orcid.org/0000-0002-9223-2014
Hongfei Gu *Department of Patient Services, HOUSE086, Beijing, China.ORCID https://orcid.org/0009-0005-7114-0742
Meredith Franklin *Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0003-3802-8829
Xiaoying Yang *Department of Statistics and Mathematical Finance, South China University of Technology, Guangzhou, Guangdong, China.ORCID https://orcid.org/0009-0005-2234-6154
Rong Wei *Institute of Hematology, Peking University People's Hospital, Beijing, China.ORCID https://orcid.org/0009-0009-5727-3767
Zhen Song *Department of Network Intelligence, Peng Cheng Laboratory, Shenzhen, Guangdong, China.ORCID https://orcid.org/0000-0002-3823-2646
Hong XuDepartment of Network Intelligence, Peng Cheng Laboratory, Shenzhen, Guangdong, China.ORCID https://orcid.org/0009-0007-0836-0480
Ling Li LengDepartment of Sociology, Zhejiang University, Hangzhou, Zhejiang, China.ORCID https://orcid.org/0000-0002-1941-3812
Mengting LiuSchool of Biomedical Engineering, Sun Yat-sen University, Shenzhen, Guangdong, China.ORCID https://orcid.org/0000-0003-4972-9006
Ju DaiDepartment of Network Intelligence, Peng Cheng Laboratory, Shenzhen, Guangdong, China.ORCID https://orcid.org/0000-0002-9397-8539
Jin ZhangDepartment of Patient Services, HOUSE086, Beijing, China.ORCID https://orcid.org/0009-0004-0579-0192
Rui ZengDepartment of Network Intelligence, Peng Cheng Laboratory, Shenzhen, Guangdong, China.ORCID https://orcid.org/0000-0001-9688-5875
Yongshuai HouDepartment of Network Intelligence, Peng Cheng Laboratory, Shenzhen, Guangdong, China.ORCID https://orcid.org/0000-0001-6994-8295
Rongjie WangDepartment of Network Intelligence, Peng Cheng Laboratory, Shenzhen, Guangdong, China.ORCID https://orcid.org/0000-0002-8918-5974
Zirong LiuDepartment of Network Intelligence, Peng Cheng Laboratory, Shenzhen, Guangdong, China.ORCID https://orcid.org/0000-0002-1983-0667
Chenyang HuangDepartment of Network Intelligence, Peng Cheng Laboratory, Shenzhen, Guangdong, China.ORCID https://orcid.org/0009-0004-0024-3616
Runfa CaiDepartment of Network Intelligence, Peng Cheng Laboratory, Shenzhen, Guangdong, China.ORCID https://orcid.org/0009-0003-6094-9242
Huiling LiuDepartment of Statistics and Mathematical Finance, South China University of Technology, Guangzhou, Guangdong, China.ORCID https://orcid.org/0000-0002-4671-1006
Li Charlie XiaDepartment of Statistics and Mathematical Finance, South China University of Technology, Guangzhou, Guangdong, China.ORCID https://orcid.org/0000-0003-0868-1923

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth disparities are closely associated with socioeconomic inequalities. Although this relationship is well recognized in the context of traditional health care access, its influence on online health-seeking behaviors such as posting questions on patient forums and seeking peer responses remains poorly understood, particularly in the context of resource-limited regions. Furthermore, it is unclear what types of questions are most frequently asked online and to what extent these questions receive helpful responses.

objectiveThis study aims to examine how socioeconomic status influences online health-seeking behavior by analyzing regional disparities in forum participation and their correlation with economic development. In addition, it aims to identify unmet informational needs among patients with lymphoma through large language model (LLM)-based forum thread classification and expert evaluation of forum responses by using data from the largest online blood cancer forum in China.

methodsWe analyzed over 110,000 patient-initiated forum threads posted between 2012 and 2023, covering all the provinces of mainland China. Regional trends in forum participation rates were examined and correlated with economic development, as measured by gross regional product per capita. Second, an LLM was used to classify the threads into 6 predefined topics based on their semantic content, thereby providing an overview of the topics that users cared about. Additionally, an expert manual review was conducted based on relevance, accuracy, and comprehensiveness to assess whether users' questions were adequately addressed within the forum discussions.

resultsRegional forum participation rates were significantly associated with levels of regional economic development (Wilcoxon rank-sum test; P<.001), with the highest participation rates in the East Coast regions. Participation rates in less-developed regions steadily increased, reflecting the growing public demand for accessible health information. LLM-based analysis revealed that most discussions centered on medical concerns such as interpreting reports and selecting treatment plans across all regions. However, only 37% (117/316) of the user questions received useful responses, underscoring persistent gaps in access to reliable information.

conclusionsTo our knowledge, this study represents the most comprehensive real-world investigation to date of spontaneous online forum participation and information needs among patients with cancer. Our findings highlight the necessity for government and health care providers to implement initiatives such as artificial intelligence-driven information platforms and region-specific health education campaigns to bridge information gaps, reduce regional disparities, and improve patient outcomes across China.

Indexed as

Information Seeking BehaviorInternetLymphomaChinaHumansAIartificial intelligencedigital healthhealth-seeking behaviorlarge language modelonline patient forumregional inequitiessocioeconomic factors

Identifiers

PMID41252192
PMCPMC12673299

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.