Turning Patients’ Open-Ended Narratives of Chronic Pain Into Quantitative Measures: Natural Language Processing Study
Although our small sample size limits the generalizability of these findings, the results provide preliminary evidence that NLP can be used to quantify the subjective experience of chronic pain and may hold promise for clinical applications.
Authors
- Paul Geha (ORCID: https://orcid.org/0000-0002-0537-7216)
- John D. Markman (ORCID: https://orcid.org/0000-0001-6296-8998)
- Zhengwu Zhang (ORCID: https://orcid.org/0000-0002-9047-8838)
- Chadi G. Abdallah (ORCID: https://orcid.org/0000-0001-5783-6181)
- Anika Tahsin (ORCID: https://orcid.org/0009-0008-6680-9570)
- Jennifer S. Gewandter (ORCID: https://orcid.org/0000-0001-7938-6775)
- Guillermo Cecchi (ORCID: https://orcid.org/0000-0003-1013-8348)
- Raquel Norel (ORCID: https://orcid.org/0000-0001-7737-4172)
- Zhiyao Duan (ORCID: https://orcid.org/0000-0002-8334-9974)
Institutions
- University of North Carolina at Chapel Hill (US)
- IBM (United States) (US)
- Baylor College of Medicine (US)
- Chestnut Hill College (US)
- Alliance for Safe Kids (US)
- University of Rochester (US)
Publication Details
- Journal
- JMIR Human Factors
- Published
- 2025-11-25
- DOI
- https://doi.org/10.2196/80269
- Primary Topic
- Mental Health via Writing
- Type
- article
- Field-Weighted Citation Impact
- 0.00