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Changing Patient and Public Beliefs About Antimicrobials and Antimicrobial Resistance (AMR) Using a Brief Digital Intervention

Background: A key driver of antimicrobial resistance (AMR) is patient demand for unnecessary antibiotics, which is driven by patients’ beliefs about antibiotics and AMR. Few interventions have targeted beliefs to reduce inappropriate demand. Objective: To examine whether a brief, online algorithm-ba...

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Autores principales: Chan, Amy Hai Yan, Horne, Rob, Lycett, Helen, Raebel, Eva, Guitart, Jordi, Wildman, Emilie, Ang, Karen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8045782/
https://www.ncbi.nlm.nih.gov/pubmed/33867978
http://dx.doi.org/10.3389/fphar.2021.608971
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author Chan, Amy Hai Yan
Horne, Rob
Lycett, Helen
Raebel, Eva
Guitart, Jordi
Wildman, Emilie
Ang, Karen
author_facet Chan, Amy Hai Yan
Horne, Rob
Lycett, Helen
Raebel, Eva
Guitart, Jordi
Wildman, Emilie
Ang, Karen
author_sort Chan, Amy Hai Yan
collection PubMed
description Background: A key driver of antimicrobial resistance (AMR) is patient demand for unnecessary antibiotics, which is driven by patients’ beliefs about antibiotics and AMR. Few interventions have targeted beliefs to reduce inappropriate demand. Objective: To examine whether a brief, online algorithm-based intervention can change beliefs that may lead to inappropriate antibiotic demand (i.e. perceptions of antibiotic necessity and lack of concern about antibiotic harm). Design: Pre- and post-intervention study. Participants: Participants were 18 years or older, and residing in the United Kingdom, who self-selected to participate via Amazon mTurk, an online survey plaform, and via research networks. Intervention: Participants were presented with a hypothetical situation of cold and flu symptoms, then exposed to the intervention. The online intervention comprised: 1) a profiling tool identifying individual beliefs (antibiotic necessity, concerns, and knowledge) driving inappropriate antibiotic demand; 2) messages designed to change beliefs and knowledge (i.e. reduce antibiotic necessity, and increase antibiotic concerns and knowledge), and 3) an algorithm linking specific messages to specific beliefs and knowledge. Main measures: The profiling tool was repeated immediately after the intervention and compared with baseline scores to assess change in beliefs. A paired samples t-test was used to determine intervention effect. Key Results: A total of 100 respondents completed the study. A significant change in beliefs relating to inappropriate demand was observed after the intervention, with a reduction in beliefs about antibiotic necessity (t = 7.254; p < 0.0001), an increase in antibiotic concerns (t = −7.214; p < 0.0001), and increases in antibiotic and AMR knowledge (t = −4.651; p < 0.0001). Conclusion: This study is the first to demonstrate that patient beliefs about antibiotics and AMR associated with inappropriate demand can be changed by a brief, tailored online intervention. This has implications for the design of future interventions to reduce unnecessary antimicrobial use.
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spelling pubmed-80457822021-04-15 Changing Patient and Public Beliefs About Antimicrobials and Antimicrobial Resistance (AMR) Using a Brief Digital Intervention Chan, Amy Hai Yan Horne, Rob Lycett, Helen Raebel, Eva Guitart, Jordi Wildman, Emilie Ang, Karen Front Pharmacol Pharmacology Background: A key driver of antimicrobial resistance (AMR) is patient demand for unnecessary antibiotics, which is driven by patients’ beliefs about antibiotics and AMR. Few interventions have targeted beliefs to reduce inappropriate demand. Objective: To examine whether a brief, online algorithm-based intervention can change beliefs that may lead to inappropriate antibiotic demand (i.e. perceptions of antibiotic necessity and lack of concern about antibiotic harm). Design: Pre- and post-intervention study. Participants: Participants were 18 years or older, and residing in the United Kingdom, who self-selected to participate via Amazon mTurk, an online survey plaform, and via research networks. Intervention: Participants were presented with a hypothetical situation of cold and flu symptoms, then exposed to the intervention. The online intervention comprised: 1) a profiling tool identifying individual beliefs (antibiotic necessity, concerns, and knowledge) driving inappropriate antibiotic demand; 2) messages designed to change beliefs and knowledge (i.e. reduce antibiotic necessity, and increase antibiotic concerns and knowledge), and 3) an algorithm linking specific messages to specific beliefs and knowledge. Main measures: The profiling tool was repeated immediately after the intervention and compared with baseline scores to assess change in beliefs. A paired samples t-test was used to determine intervention effect. Key Results: A total of 100 respondents completed the study. A significant change in beliefs relating to inappropriate demand was observed after the intervention, with a reduction in beliefs about antibiotic necessity (t = 7.254; p < 0.0001), an increase in antibiotic concerns (t = −7.214; p < 0.0001), and increases in antibiotic and AMR knowledge (t = −4.651; p < 0.0001). Conclusion: This study is the first to demonstrate that patient beliefs about antibiotics and AMR associated with inappropriate demand can be changed by a brief, tailored online intervention. This has implications for the design of future interventions to reduce unnecessary antimicrobial use. Frontiers Media S.A. 2021-03-31 /pmc/articles/PMC8045782/ /pubmed/33867978 http://dx.doi.org/10.3389/fphar.2021.608971 Text en Copyright © 2021 Chan, Horne, Lycett, Raebel, Guitart, Wildman and Ang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Chan, Amy Hai Yan
Horne, Rob
Lycett, Helen
Raebel, Eva
Guitart, Jordi
Wildman, Emilie
Ang, Karen
Changing Patient and Public Beliefs About Antimicrobials and Antimicrobial Resistance (AMR) Using a Brief Digital Intervention
title Changing Patient and Public Beliefs About Antimicrobials and Antimicrobial Resistance (AMR) Using a Brief Digital Intervention
title_full Changing Patient and Public Beliefs About Antimicrobials and Antimicrobial Resistance (AMR) Using a Brief Digital Intervention
title_fullStr Changing Patient and Public Beliefs About Antimicrobials and Antimicrobial Resistance (AMR) Using a Brief Digital Intervention
title_full_unstemmed Changing Patient and Public Beliefs About Antimicrobials and Antimicrobial Resistance (AMR) Using a Brief Digital Intervention
title_short Changing Patient and Public Beliefs About Antimicrobials and Antimicrobial Resistance (AMR) Using a Brief Digital Intervention
title_sort changing patient and public beliefs about antimicrobials and antimicrobial resistance (amr) using a brief digital intervention
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8045782/
https://www.ncbi.nlm.nih.gov/pubmed/33867978
http://dx.doi.org/10.3389/fphar.2021.608971
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