The PsyTAR dataset: From patients generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medications
The “Psychiatric Treatment Adverse Reactions” (PsyTAR) dataset contains patients’ expression of effectiveness and adverse drug events associated with psychiatric medications. The PsyTAR was generated in four phases. In the first phase, a sample of 891 drugs reviews posted by patients on an online he...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019-06-01
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| Series: | Data in Brief |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340919301891 |
| _version_ | 1819148197655740416 |
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| author | Maryam Zolnoori Kin Wah Fung Timothy B. Patrick Paul Fontelo Hadi Kharrazi Anthony Faiola Nilay D. Shah Yi Shuan Shirley Wu Christina E. Eldredge Jake Luo Mike Conway Jiaxi Zhu Soo Kyung Park Kelly Xu Hamideh Moayyed |
| author_facet | Maryam Zolnoori Kin Wah Fung Timothy B. Patrick Paul Fontelo Hadi Kharrazi Anthony Faiola Nilay D. Shah Yi Shuan Shirley Wu Christina E. Eldredge Jake Luo Mike Conway Jiaxi Zhu Soo Kyung Park Kelly Xu Hamideh Moayyed |
| author_sort | Maryam Zolnoori |
| collection | DOAJ |
| description | The “Psychiatric Treatment Adverse Reactions” (PsyTAR) dataset contains patients’ expression of effectiveness and adverse drug events associated with psychiatric medications. The PsyTAR was generated in four phases. In the first phase, a sample of 891 drugs reviews posted by patients on an online healthcare forum, “askapatient.com”, was collected for four psychiatric drugs: Zoloft, Lexapro, Cymbalta, and Effexor XR. For each drug review, patient demographic information, duration of treatment, and satisfaction with the drugs were reported. In the second phase, sentence classification, drug reviews were split to 6009 sentences, and each sentence was labeled for the presence of Adverse Drug Reaction (ADR), Withdrawal Symptoms (WDs), Sign/Symptoms/Illness (SSIs), Drug Indications (DIs), Drug Effectiveness (EF), Drug Infectiveness (INF), and Others (not applicable). In the third phases, entities including ADRs (4813 mentions), WDs (590 mentions), SSIs (1219 mentions), and DIs (792 mentions) were identified and extracted from the sentences. In the four phases, all the identified entities were mapped to the corresponding UMLS Metathesaurus concepts (916) and SNOMED CT concepts (755). In this phase, qualifiers representing severity and persistency of ADRs, WDs, SSIs, and DIs (e.g., mild, short term) were identified. All sentences and identified entities were linked to the original post using IDs (e.g., Zoloft.1, Effexor.29, Cymbalta.31). The PsyTAR dataset can be accessed via Online Supplement #1 under the CC BY 4.0 Data license. The updated versions of the dataset would also be accessible in https://sites.google.com/view/pharmacovigilanceinpsychiatry/home. |
| first_indexed | 2024-12-22T13:41:53Z |
| format | Article |
| id | doaj.art-9f899f61d22d4b148deade57f13dece3 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-12-22T13:41:53Z |
| publishDate | 2019-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-9f899f61d22d4b148deade57f13dece32022-12-21T18:23:54ZengElsevierData in Brief2352-34092019-06-0124The PsyTAR dataset: From patients generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medicationsMaryam Zolnoori0Kin Wah Fung1Timothy B. Patrick2Paul Fontelo3Hadi Kharrazi4Anthony Faiola5Nilay D. Shah6Yi Shuan Shirley Wu7Christina E. Eldredge8Jake Luo9Mike Conway10Jiaxi Zhu11Soo Kyung Park12Kelly Xu13Hamideh Moayyed14Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, United States; Department of Health Informatics & Administration, University of Wisconsin Milwaukee, Milwaukee, WI, United States; Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United States; Corresponding author. Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, United States.Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, United StatesDepartment of Health Informatics & Administration, University of Wisconsin Milwaukee, Milwaukee, WI, United StatesLister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, United StatesDepartment of Health Policy and Management, Johns Hopkins University, Baltimore, MD, United StatesDepartment of Biomedical and Health Information Sciences, University of Illinois at Chicago, Chicago, IL, United StatesDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN, United StatesSchool of Pharmacy, University of Pittsburgh, Pittsburgh, PA, United StatesSchool of Information, University of South Florida, Tampa, FL, United StatesDepartment of Health Informatics & Administration, University of Wisconsin Milwaukee, Milwaukee, WI, United StatesDepartment of Biomedical Informatics, Utah University, Salt Lake City, UT, United StatesEmmes Corporation, Rockville, MD, United StatesDepartment of Epidemiology, Johns Hopkins University, Baltimore, MD, United StatesSchool of Pharmacy, University of Pittsburgh, Pittsburgh, PA, United StatesCollege of Letters and Science, University of Wisconsin Milwaukee, WI, United StatesThe “Psychiatric Treatment Adverse Reactions” (PsyTAR) dataset contains patients’ expression of effectiveness and adverse drug events associated with psychiatric medications. The PsyTAR was generated in four phases. In the first phase, a sample of 891 drugs reviews posted by patients on an online healthcare forum, “askapatient.com”, was collected for four psychiatric drugs: Zoloft, Lexapro, Cymbalta, and Effexor XR. For each drug review, patient demographic information, duration of treatment, and satisfaction with the drugs were reported. In the second phase, sentence classification, drug reviews were split to 6009 sentences, and each sentence was labeled for the presence of Adverse Drug Reaction (ADR), Withdrawal Symptoms (WDs), Sign/Symptoms/Illness (SSIs), Drug Indications (DIs), Drug Effectiveness (EF), Drug Infectiveness (INF), and Others (not applicable). In the third phases, entities including ADRs (4813 mentions), WDs (590 mentions), SSIs (1219 mentions), and DIs (792 mentions) were identified and extracted from the sentences. In the four phases, all the identified entities were mapped to the corresponding UMLS Metathesaurus concepts (916) and SNOMED CT concepts (755). In this phase, qualifiers representing severity and persistency of ADRs, WDs, SSIs, and DIs (e.g., mild, short term) were identified. All sentences and identified entities were linked to the original post using IDs (e.g., Zoloft.1, Effexor.29, Cymbalta.31). The PsyTAR dataset can be accessed via Online Supplement #1 under the CC BY 4.0 Data license. The updated versions of the dataset would also be accessible in https://sites.google.com/view/pharmacovigilanceinpsychiatry/home.http://www.sciencedirect.com/science/article/pii/S2352340919301891 |
| spellingShingle | Maryam Zolnoori Kin Wah Fung Timothy B. Patrick Paul Fontelo Hadi Kharrazi Anthony Faiola Nilay D. Shah Yi Shuan Shirley Wu Christina E. Eldredge Jake Luo Mike Conway Jiaxi Zhu Soo Kyung Park Kelly Xu Hamideh Moayyed The PsyTAR dataset: From patients generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medications Data in Brief |
| title | The PsyTAR dataset: From patients generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medications |
| title_full | The PsyTAR dataset: From patients generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medications |
| title_fullStr | The PsyTAR dataset: From patients generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medications |
| title_full_unstemmed | The PsyTAR dataset: From patients generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medications |
| title_short | The PsyTAR dataset: From patients generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medications |
| title_sort | psytar dataset from patients generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medications |
| url | http://www.sciencedirect.com/science/article/pii/S2352340919301891 |
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