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Abstract
Scalability of Meta-Research on Patient-Authored Publications: You Can Do a Lot With a Bot
Current Medical Research and Opinion, Vol.39(Supplement 1), pp.S33-S33
Annual Meeting of the International Society for Medical Publication Professionals, 19th (Washington DC, United States, 24-Apr-2023–26-Apr-2023)
2023
Abstract
Objective: As patient authorship increases, publication professionals may face increasing responsibilities in identifying, guiding, and measuring the output of patient authors. Meta-research on patient-authored publications could help publication professionals meet these responsibilities. This research is feasible, but challenging to scale. Our objective was to develop a bot to enable scalability of meta-research on patient-authored publications.
Methods: To enable the bot to rapidly extract relevant text from PubMed’s data fields, we developed Natural Language Processing algorithms, which leveraged pre-trained Name Entity Recognition models (ScispaCy models). We tested the bot on a dataset of patient-authored publications, identified via PubMed’s advanced affiliation search function (final search: 01/09/2023). We automated the bot’s interactions with other databases and data-visualization software.
Results: Scalability was possible. The bot analyzed the complete dataset of patient-authored publications (N¼604). Data extraction efficiency was 66-fold faster than existing methods (e.g. analysis of 100 publications: with bot ¼12 min; without bot ¼10–13 h). Data were successfully extracted for characteristics of patient-authored publications (e.g. number, publication type, disease area, language, accessibility, retractions) and patient authors (e.g. name, country, author order). Bot use and automated linkages enabled patient author diversity evaluation (e.g. gender estimation, country, income), as well as rapid, interactive, and dashboard-style data visualizations.
Conclusions: Scalability of meta-research on patient authorship is possible. The bot can analyze larger datasets with greater efficiency than the original methods used to pioneer this area of research. Publication professionals can use evidence-based insights gained from scalable meta-research to better understand the rapidly emerging field of patient-authored publications and to support patient author partnerships.
Details
- Title
- Scalability of Meta-Research on Patient-Authored Publications: You Can Do a Lot With a Bot
- Authors
- Bella Yang (Author) - Envision Pharma GroupDawn Lobban (Author) - Envision Pharma GroupKaren Woolley (Author) - University of the Sunshine Coast, Queensland, School of Health and Sport Sciences - Legacy
- Publication details
- Current Medical Research and Opinion, Vol.39(Supplement 1), pp.S33-S33
- Conference details
- Annual Meeting of the International Society for Medical Publication Professionals, 19th (Washington DC, United States, 24-Apr-2023–26-Apr-2023)
- Publisher
- Taylor & Francis
- Date published
- 2023
- DOI
- 10.1080/03007995.2023.2194075
- ISSN
- 1473-4877; 0300-7995
- Copyright note
- 2023 International Society for Medical Publication Professionals (ISMPP). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
- Organisation Unit
- Faculty of Science, Health, Education and Engineering; University of the Sunshine Coast, Queensland; School of Health and Sport Sciences - Legacy
- Language
- English
- Record Identifier
- 99966898302621
- Output Type
- Abstract
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- Web Of Science research areas
- Medicine, Research & Experimental