Publishing habits and perceptions of open access publishing and public access amongst clinical and research fellows.

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ID: 77343
2020
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Abstract
Open access (OA) publishing rates have risen dramatically in the biomedical sciences in the past decade. However, few studies have focused on the publishing activities and attitudes of early career researchers. The aim of this study was to examine current publishing activities of clinical and research fellows and their perceptions of OA publishing and public access.This study employed a mixed methods approach. Data on publications authored by Memorial Sloan Kettering Cancer Center fellows between 2013 and 2018 were collected via an in-house author profile system and citation indexes. Journals were categorized according to SHERPA/RoMEO classifications. In-person and telephone interviews were conducted with fifteen fellows to discern their perceptions of OA publishing.The total percentage of fellows' publications that were freely available OA was 28.6%, with a relatively flat rate between 2013 and 2018. Publications with fellows as first authors were significantly more likely to be OA. Fellows cited high article processing charges (APCs) and perceived lack of journal quality or prestige as barriers to OA publishing. Fellows generally expressed support for the National Institutes of Health (NIH) public access policy.While the fellows in this study acknowledged the potential of OA to aid in research dissemination, they also expressed hesitation to publish OA related to confusion surrounding legitimate OA and predatory publications and frustration with APCs. Fellows supported the NIH public access policy and accepted it as part of their research process. Health sciences information professionals could potentially leverage this acceptance of public access to advocate for OA publishing.
Reference Key
ohanlon2020publishingjournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors O'Hanlon, Robin;McSweeney, Jeanine;Stabler, Samuel;
Journal journal of the medical library association : jmla
Year 2020
DOI
10.5195/jmla.2020.751
URL
Keywords
phenotyping collaborative learning differential privacy tensor factorization

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