Evidence map›Paper›PMID 39640255›Full record

ArticleInflammatory intestinal diseases

Perceptions and Responses to Diseases among Patients with Inflammatory Bowel Disease: Text Mining Analysis of Posts on a Japanese Patient Community Website.

Eujin Lee, Hiroaki Tsuchiya, Hajime Iida, Katsumasa Nagano, Yoko Murata, Atsuo Maemoto

Abstract read
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Article in Inflammatory intestinal diseases. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Eujin LeeMedical Affairs Division, Janssen Pharmaceutical K.K., Tokyo, Japan.
Hiroaki TsuchiyaMedical Affairs Division, Janssen Pharmaceutical K.K., Tokyo, Japan.
Hajime IidaMedical Affairs Division, Janssen Pharmaceutical K.K., Tokyo, Japan.
Katsumasa NaganoMedical Affairs Division, Janssen Pharmaceutical K.K., Tokyo, Japan.
Yoko MurataMedical Affairs Division, Janssen Pharmaceutical K.K., Tokyo, Japan.
Atsuo MaemotoInflammatory Bowel Disease Center, Sapporo Higashi Tokushukai Hospital, Sapporo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Patients with inflammatory bowel disease (IBD) are increasingly using online platforms to communicate with other patients and healthcare professionals seeking disease-related information and support. Free-text posts on these platforms could provide insights into patients' everyday lives, which could help improve patient care. In this proof-of-concept (POC) study, we applied text mining to extract patient needs from free-text posts on a community forum in Japan, holistically visualized the patients' perceptions and their connections, and explored the patient characteristic-dependent trends in the use of words. Methods: Free-text posts written between May 11, 2020 and May 31, 2022 on the community forum were retrieved and subjected to text mining analysis. Trends in the use of words were extracted from the posts for correspondence and co-occurrence network analyses using KH Coder open-source text mining software. Results: Seventy-four posts were analyzed. Using text mining methods, we successfully extracted and visualized a variety of patient concerns and their connections. The correspondence and co-occurrence analyses revealed patient segment-dependent trends in the use of words. For example, patients with a disease duration of ≤5 years were more likely to use words related to emotions or their desire to change or quit their job, such as "anxiety" and "resignation." Patients with a disease duration of >10 years were more likely to use words showing that they are finding ways to live with or accept their disease, and are getting used to the lifestyle, but some patients continued to experience worsening disease. Conclusions: We found that free-text posts on an IBD community forum can be a useful source of information to capture the wide variety of thoughts of patients. Text mining procedures can help visualize the relative importance of the topics identified from free-text posts. Our findings of this POC study will be useful for generating new hypotheses to better understand and address the needs of patients with IBD.

Indexed as

Community forumCrohn’s diseaseInflammatory bowel diseaseText miningUlcerative colitis

Identifiers

PMID39640255
PMCPMC11620774

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LicenceCC BY-NC
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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.