Understanding Cancer Survivorship Care Needs Using Amazon Reviews: Content Analysis, Algorithm Development, and Validation Study

Our results demonstrate the potential of Amazon consumer reviews as a novel data source for identifying persistent symptoms, concerns, and self-management strategies among cancer survivors. This corpus, along with the baseline natural language processing models developed for named entity recognition and text classification, lays the groundwork for future methodological advancements in cancer survivorship research. Importantly, insights from this study could be evaluated against established clinical guidelines for symptom management in cancer survivorship care. By revealing the feasibility of using consumer-generated data for mining survivorship-related experiences, this study offers a promising foundation for future research and argumentation analysis aimed at improving long-term outcomes and support for cancer survivors.

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Publication Details

Journal
JMIR Cancer
Published
2025-05-19
DOI
https://doi.org/10.2196/71102
Primary Topic
Mental Health via Writing
Type
article
Field-Weighted Citation Impact
0.00
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article

Understanding Cancer Survivorship Care Needs Using Amazon Reviews: Content Analysis, Algorithm Development, and Validation Study

Heling Jia, Ming Jun Huang, Heidi Dowst, Jungwei Fan et al.
JMIR Cancer
Mental Health via Writing
article

Understanding Cancer Survivorship Care Needs Using Amazon Reviews: Content Analysis, Algorithm Development, and Validation Study

Heling Jia, Ming Jun Huang, Heidi Dowst, Jungwei Fan, Hoda Badr, Tracy NH. Harrison, Liwei Wang, Rui Zhang, Rui Li, Hongfang Liu, Qiuhao Lu
article en

Abstract

Our results demonstrate the potential of Amazon consumer reviews as a novel data source for identifying persistent symptoms, concerns, and self-management strategies among cancer survivors. This corpus, along with the baseline natural language processing models developed for named entity recognition and text classification, lays the groundwork for future methodological advancements in cancer survivorship research. Importantly, insights from this study could be evaluated against established clinical guidelines for symptom management in cancer survivorship care. By revealing the feasibility of using consumer-generated data for mining survivorship-related experiences, this study offers a promising foundation for future research and argumentation analysis aimed at improving long-term outcomes and support for cancer survivors.

JMIR CancerVol. 11
Thomas Jefferson University (US), Baylor College of Medicine (US), Twin Cities Orthopedics (US), Mayo Clinic in Florida (US), The University of Texas Health Science Center (US), The University of Texas Health Science Center at Houston (US)
Openalex Percentile: Top 88%
Mental Health via Writing
DOIOpen Access PDFOpenAlex
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