Evidence map›Paper›PMID 42331989›Full record

ArticleScientific reports2026

Pain-centered symptom-language co-occurrence networks differ between interstitial cystitis/bladder pain syndrome and fibromyalgia in Reddit patient discourse.

Nobuo Okui, Kenta Ichino, Hisamitu Ide, Kazuhito Matsushita, Yoshihiro Ikehata, Machiko Okui, Shigeo Horie

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Article in Scientific reports, 2026. 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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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Nobuo Okui *Innovative Longevity, Medicine, Juntendo University, Tokyo, 113-8421, Japan. okuinobuo@gmail.com.ORCID http://orcid.org/0000-0001-5894-5283
Kenta Ichino *Innovative Longevity, Medicine, Juntendo University, Tokyo, 113-8421, Japan.
Hisamitu IdeInnovative Longevity, Medicine, Juntendo University, Tokyo, 113-8421, Japan.
Kazuhito MatsushitaInnovative Longevity, Medicine, Juntendo University, Tokyo, 113-8421, Japan.
Yoshihiro IkehataInnovative Longevity, Medicine, Juntendo University, Tokyo, 113-8421, Japan.
Machiko OkuiUrology, Yokosuka Urogynecology and Urology Clinic, Ootaki 2-6, Yokosuka, 238-0008, Kanagawa, Japan.
Shigeo HorieInnovative Longevity, Medicine, Juntendo University, Tokyo, 113-8421, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interstitial cystitis/bladder pain syndrome (IC/BPS) and fibromyalgia (FM) are chronic pain conditions frequently discussed within shared conceptual frameworks such as central sensitization. Despite this conceptual overlap, IC/BPS is clinically characterized by pelvic and urinary symptoms, whereas FM is associated with widespread pain, fatigue, sleep disturbance, and other systemic manifestations. Whether these differences are reflected in the organization of symptom-related language within patient-generated discourse remains insufficiently characterized. Patient-generated text related to IC/BPS and FM was collected from disease-specific Reddit communities using identical retrieval procedures, yielding temporally comparable corpora. A predefined evaluative lexicon was constructed from validated clinical questionnaires together with pain-related, affective, and anatomical vocabulary. Symptom-language co-occurrence networks were analyzed using a three-step framework examining global pain-centered network organization, dense-core topology and community structure, and local pain-centered lexical configurations. Both conditions exhibited pain-centered symptom-language networks. However, the FM network showed a greater concentration of symptom-language terms within the immediate network neighborhood of "pain," whereas the IC/BPS network retained a larger peripheral structure. Dense-core analysis revealed distinct topological organization. The IC/BPS dense core retained partial modular differentiation, whereas the FM dense core formed a highly interconnected structure with minimal residual community organization. At the local level, pain-centered lexical neighborhoods also differed between conditions. In IC/BPS, "pain" was preferentially associated with pelvic, urinary, and sensory terms, whereas in FM it was more frequently associated with whole-body, fatigue-, sleep-, chronicity-, and affect-related vocabulary. These findings indicate that two chronic pain conditions sharing substantial conceptual overlap nevertheless exhibit distinct pain-centered symptom-language topologies within patient-generated discourse. Comparative network analysis of patient-generated language may provide a complementary framework for characterizing disease-specific patterns of symptom-language organization in online health communities.

Indexed as

Cystitis, InterstitialFibromyalgiaLanguageAdultFemaleHumansMaleMiddle AgedSurveys and Questionnaires

Identifiers

PMID42331989
PMCPMC13562692

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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.