| アブストラクト | Free-text narratives in vaccine adverse event reports contain symptom descriptions and contextual wording that can be characterized using text mining. However, lexicon-based sentiment scores in medical narratives should be interpreted as vocabulary patterns rather than direct measures of patients' emotional states. We evaluated sex-specific and vaccine-specific patterns in sentiment-scored and emotion-category assignment vocabulary in Vaccine Adverse Event Reporting System (VAERS) narratives for coronavirus disease 2019 (COVID-19), influenza, human papillomavirus (HPV), and measles-mumps-rubella (MMR) vaccines. Public VAERS reports received from 2010 to 2024 were analyzed. VAERSDATA, VAERSVAX, and VAERSSYMPTOMS were linked by VAERS_ID, with duplicate records removed. Report-level AFINN scores were normalized per 100 words. Sensitivity analyses excluded common clinical and symptom-related terms. Effect sizes, 95% confidence intervals, adjusted linear regression models with HC3 robust standard errors, and NRC emotion-category assignment profiles were evaluated. After duplicate handling, 1022460 COVID-19, 148489 influenza, 41212 HPV, and 47459 MMR reports were analyzed. Female-associated reports generally showed slightly lower primary AFINN scores than male-associated reports, although effect sizes were negligible. Excluding clinical and symptom-related terms attenuated or reversed these differences. Adjusted regression models showed only small associations between sex and AFINN scores. NRC analyses demonstrated clearer vaccine-specific than sex-specific vocabulary patterns. VAERS narratives showed only small sex-related differences but distinct vaccine-specific patterns in sentiment-scored and emotion-category assignment vocabulary. These findings should be interpreted as lexicon-derived vocabulary patterns rather than direct measures of psychological responses, vaccine perceptions, or clinical outcomes. |
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| ジャーナル名 | Biological & pharmaceutical bulletin |
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| Pubmed追加日 | 2026/9/27 |
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| 投稿者 | Matsumura, Kae; Horibe, Megumi; Ino, Yoko; Sugishita, Kana; Yamazaki, Tomofumi; Maeno, Moe; Kageyama, Koichi; Ito, Seiichiro; Sato, Mugita; Chikahisa, Mahiro; Kitamura, Mayumi; Iwata, Mari; Iguchi, Kazuhiro; Nakamura, Mitsuhiro |
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| 組織名 | Laboratory of Drug Informatics, Gifu Pharmaceutical University, 1-25-4;Daigaku-Nishi, Gifu 501-1196, Japan.;Department of Nursing, School of Health Sciences, Asahi University, Gifu;501-0296, Japan.;Laboratory of Pharmaceutical Health Care and Promotion, Gifu Pharmaceutical;University, 1-25-4 Daigaku-Nishi, Gifu 501-1196, Japan.;Department of Pharmacy, University of Miyazaki Hospital, 5200 Kihara,;Kiyotake-cho, Miyazaki 889-1692, Japan.;Yanaizu Pharmacy, Gifu 501-6103, Japan.;Laboratory of Community Pharmacy, Gifu Pharmaceutical University, 1-25-4 |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/42802070/ |
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