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Public Perspectives of Using Social Media Data to Improve Adverse Drug Reaction Reporting: A Mixed-Methods Study
INTRODUCTION: Information on suspected adverse drug reactions (ADRs) voluntarily submitted by patients can be a valuable source of information for improving drug safety; however, public awareness of reporting mechanisms remains low. Whilst methods to automatically detect ADR mentions from social med...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8053157/ https://www.ncbi.nlm.nih.gov/pubmed/33582973 http://dx.doi.org/10.1007/s40264-021-01042-6 |
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author | Bulcock, Alexander Hassan, Lamiece Giles, Sally Sanders, Caroline Nenadic, Goran Campbell, Stephen Dixon, Will |
author_facet | Bulcock, Alexander Hassan, Lamiece Giles, Sally Sanders, Caroline Nenadic, Goran Campbell, Stephen Dixon, Will |
author_sort | Bulcock, Alexander |
collection | PubMed |
description | INTRODUCTION: Information on suspected adverse drug reactions (ADRs) voluntarily submitted by patients can be a valuable source of information for improving drug safety; however, public awareness of reporting mechanisms remains low. Whilst methods to automatically detect ADR mentions from social media posts using text mining techniques have been proposed to improve reporting rates, it is unclear how acceptable these would be to social media users. OBJECTIVE: The objective of this study was to explore public opinion about using automated methods to detect and report mentions of ADRs on social media to enhance pharmacovigilance efforts. METHODS: Users of the online health discussion forum HealthUnlocked participated in an online survey (N = 1359) about experiences with ADRs, knowledge of pharmacovigilance methods, and opinions about using automated data mining methods to detect and report ADRs. To further explore responses, five qualitative focus groups were conducted with 20 social media users with long-term health conditions. RESULTS: Participant responses indicated a low awareness of pharmacovigilance methods and ADR reporting. They showed a strong willingness to share health-related social media data about ADRs with researchers and regulators, but were cautious about automated text mining methods of detecting and reporting ADRs. CONCLUSIONS: Social media users value public-facing pharmacovigilance schemes, even if they do not understand the current framework of pharmacovigilance within the UK. Ongoing engagement with users is essential to understand views, share knowledge and respect users’ privacy expectations to optimise future ADR reporting from online health communities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40264-021-01042-6. |
format | Online Article Text |
id | pubmed-8053157 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-80531572021-04-29 Public Perspectives of Using Social Media Data to Improve Adverse Drug Reaction Reporting: A Mixed-Methods Study Bulcock, Alexander Hassan, Lamiece Giles, Sally Sanders, Caroline Nenadic, Goran Campbell, Stephen Dixon, Will Drug Saf Original Research Article INTRODUCTION: Information on suspected adverse drug reactions (ADRs) voluntarily submitted by patients can be a valuable source of information for improving drug safety; however, public awareness of reporting mechanisms remains low. Whilst methods to automatically detect ADR mentions from social media posts using text mining techniques have been proposed to improve reporting rates, it is unclear how acceptable these would be to social media users. OBJECTIVE: The objective of this study was to explore public opinion about using automated methods to detect and report mentions of ADRs on social media to enhance pharmacovigilance efforts. METHODS: Users of the online health discussion forum HealthUnlocked participated in an online survey (N = 1359) about experiences with ADRs, knowledge of pharmacovigilance methods, and opinions about using automated data mining methods to detect and report ADRs. To further explore responses, five qualitative focus groups were conducted with 20 social media users with long-term health conditions. RESULTS: Participant responses indicated a low awareness of pharmacovigilance methods and ADR reporting. They showed a strong willingness to share health-related social media data about ADRs with researchers and regulators, but were cautious about automated text mining methods of detecting and reporting ADRs. CONCLUSIONS: Social media users value public-facing pharmacovigilance schemes, even if they do not understand the current framework of pharmacovigilance within the UK. Ongoing engagement with users is essential to understand views, share knowledge and respect users’ privacy expectations to optimise future ADR reporting from online health communities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40264-021-01042-6. Springer International Publishing 2021-02-13 2021 /pmc/articles/PMC8053157/ /pubmed/33582973 http://dx.doi.org/10.1007/s40264-021-01042-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Original Research Article Bulcock, Alexander Hassan, Lamiece Giles, Sally Sanders, Caroline Nenadic, Goran Campbell, Stephen Dixon, Will Public Perspectives of Using Social Media Data to Improve Adverse Drug Reaction Reporting: A Mixed-Methods Study |
title | Public Perspectives of Using Social Media Data to Improve Adverse Drug Reaction Reporting: A Mixed-Methods Study |
title_full | Public Perspectives of Using Social Media Data to Improve Adverse Drug Reaction Reporting: A Mixed-Methods Study |
title_fullStr | Public Perspectives of Using Social Media Data to Improve Adverse Drug Reaction Reporting: A Mixed-Methods Study |
title_full_unstemmed | Public Perspectives of Using Social Media Data to Improve Adverse Drug Reaction Reporting: A Mixed-Methods Study |
title_short | Public Perspectives of Using Social Media Data to Improve Adverse Drug Reaction Reporting: A Mixed-Methods Study |
title_sort | public perspectives of using social media data to improve adverse drug reaction reporting: a mixed-methods study |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8053157/ https://www.ncbi.nlm.nih.gov/pubmed/33582973 http://dx.doi.org/10.1007/s40264-021-01042-6 |
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