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Conflicts of Interest Publication Disclosures: Descriptive Study. 利益冲突出版披露:描述性研究。
JMIR data Pub Date : 2024-01-01 Epub Date: 2024-10-31 DOI: 10.2196/57779
S Scott Graham, Jade Shiva, Nandini Sharma, Joshua B Barbour, Zoltan P Majdik, Justin F Rousseau
{"title":"Conflicts of Interest Publication Disclosures: Descriptive Study.","authors":"S Scott Graham, Jade Shiva, Nandini Sharma, Joshua B Barbour, Zoltan P Majdik, Justin F Rousseau","doi":"10.2196/57779","DOIUrl":"10.2196/57779","url":null,"abstract":"<p><strong>Background: </strong>Multiple lines of prior research have documented that author conflicts of interest (COI) can compromise the integrity of the biomedical research enterprise. However, continuing research that would investigate why, how, and in what circumstances COI is most risky is stymied by the difficulty in accessing disclosure statements, which are not widely represented in available databases.</p><p><strong>Objective: </strong>In this study, we describe a new open access dataset of COI disclosures extracted from published biomedical journals articles.</p><p><strong>Methods: </strong>To develop the dataset, we used ClinCalc's Top 300 drugs lists for 2017 and 2018 to identify 319 of the most commonly used drugs. Search strategies for each product were developed using the National Library of Medicine's Medical Subject Headings browser and deployed using the eUtilities API in April 2021. We identified the 150 most relevant articles for each product and extracted COI disclosure statements from PubMed, PubMed Central, or retrieved articles as necessary.</p><p><strong>Results: </strong>Conflicts of Interest PublicatiON Disclosures (COIPonD) is a new dataset that captures author-reported COI disclosures for biomedical research articles published in a wide range of journals and subspecialties. COIPonD captures author-reported disclosure information (including lack of disclosure) for over 38,000 PubMed-indexed articles published between 1949 and 2022. The collected articles are indexed by discussed drug products with a focus on the 319 most commonly used drugs in the United States.</p><p><strong>Conclusions: </strong>COIPonD should accelerate research efforts to understand the effects of COI on the biomedical research enterprise. In particular, this dataset should facilitate new studies of COI effects across disciplines and subspecialties.</p>","PeriodicalId":520971,"journal":{"name":"JMIR data","volume":"5 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12323890/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144791769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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