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Patient Expectations of Assigned Treatments Impact Strength of Randomised Control Trials

Patient engagement with treatments potentially poses problems for interpreting the results and meaning of Randomised Control Trials (RCTs). If patients are assigned to treatments that do, or do not, match their expectations, and this impacts their motivation to engage with that treatment, it will af...

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Detalles Bibliográficos
Autores principales: Truzoli, Roberto, Reed, Phil, Osborne, Lisa A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8247438/
https://www.ncbi.nlm.nih.gov/pubmed/34222273
http://dx.doi.org/10.3389/fmed.2021.648403
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author Truzoli, Roberto
Reed, Phil
Osborne, Lisa A.
author_facet Truzoli, Roberto
Reed, Phil
Osborne, Lisa A.
author_sort Truzoli, Roberto
collection PubMed
description Patient engagement with treatments potentially poses problems for interpreting the results and meaning of Randomised Control Trials (RCTs). If patients are assigned to treatments that do, or do not, match their expectations, and this impacts their motivation to engage with that treatment, it will affect the distribution of outcomes. In turn, this will impact the obtained power and error rates of RCTs. Simple Monto Carlo simulations demonstrate that these patient variables affect sample variance, and sample kurtosis. These effects reduce the power of RCTs, and may lead to false negatives, even when the randomisation process works, and equally distributes those with positive and negative views about a treatment to a trial arm.
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spelling pubmed-82474382021-07-02 Patient Expectations of Assigned Treatments Impact Strength of Randomised Control Trials Truzoli, Roberto Reed, Phil Osborne, Lisa A. Front Med (Lausanne) Medicine Patient engagement with treatments potentially poses problems for interpreting the results and meaning of Randomised Control Trials (RCTs). If patients are assigned to treatments that do, or do not, match their expectations, and this impacts their motivation to engage with that treatment, it will affect the distribution of outcomes. In turn, this will impact the obtained power and error rates of RCTs. Simple Monto Carlo simulations demonstrate that these patient variables affect sample variance, and sample kurtosis. These effects reduce the power of RCTs, and may lead to false negatives, even when the randomisation process works, and equally distributes those with positive and negative views about a treatment to a trial arm. Frontiers Media S.A. 2021-06-17 /pmc/articles/PMC8247438/ /pubmed/34222273 http://dx.doi.org/10.3389/fmed.2021.648403 Text en Copyright © 2021 Truzoli, Reed and Osborne. 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 Medicine
Truzoli, Roberto
Reed, Phil
Osborne, Lisa A.
Patient Expectations of Assigned Treatments Impact Strength of Randomised Control Trials
title Patient Expectations of Assigned Treatments Impact Strength of Randomised Control Trials
title_full Patient Expectations of Assigned Treatments Impact Strength of Randomised Control Trials
title_fullStr Patient Expectations of Assigned Treatments Impact Strength of Randomised Control Trials
title_full_unstemmed Patient Expectations of Assigned Treatments Impact Strength of Randomised Control Trials
title_short Patient Expectations of Assigned Treatments Impact Strength of Randomised Control Trials
title_sort patient expectations of assigned treatments impact strength of randomised control trials
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8247438/
https://www.ncbi.nlm.nih.gov/pubmed/34222273
http://dx.doi.org/10.3389/fmed.2021.648403
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