Patient reported outcomes and recruitment rates following the introduction of principled patient information leaflets (PrinciPILs): Protocol for a meta-analysis.

Communication adverse events harms meta-analysis nocebo placebo recruitment  research ethics

Journal

NIHR open research
ISSN: 2633-4402
Titre abrégé: NIHR Open Res
Pays: England
ID NLM: 9918333281906676

Informations de publication

Date de publication:
2023
Historique:
accepted: 04 04 2023
medline: 26 5 2023
pubmed: 26 5 2023
entrez: 14 8 2024
Statut: epublish

Résumé

The way potential benefits and harms of trial interventions are shared within patient information leaflets (PILs) varies widely and may cause unnecessary harms ("nocebo effects"). The aim of this meta-analysis will be to evaluate the influence on recruitment rates and early effects on patient reported adverse events of principled patient information leaflets (PrinciPILs) compared with standard PILs. Eligible studies will include those that report the effects on recruitment and patient reported adverse events of PrinciPILs compared to standard PILs. We will include in this meta-analysis all the standard PILs in studies within trials (SWATs) of PrinciPILs that were developed as part of the Medical Research Council (MRC) funded PrinciPIL project. By publishing this as a living meta-analysis, we will allow the meta-analysis to be updated with future SWATs of PrinciPILs. We will use the Cochrane Risk of Bias tool to evaluate the risk of bias for each outcome. We will report the total number of studies and participants analysed and the characteristics of included studies (including details of intervention, comparators, outcomes). For dichotomous data, we will calculate the risk difference and the risk ratio (RR) and 95% confidence intervals (CIs). For continuous outcomes we will use weighted mean differences with 95% CIs or standardized mean differences with 95% CIs. We will investigate heterogeneity by visually inspecting the forest plot and by considering the I We will discuss the limitations of the meta-analysis including study risk of bias, inconsistency, heterogeneity, and imprecision. A general interpretation of the results and important implications will be provided. People who take part in randomised trials need to understand the risks as well as the benefits of taking part. Most ‘patient information leaflets’ (PILs) that describe trial treatments include information about harms. Yet only some PILs contain information about potential benefits. This variation is confusing. Also, the over-emphasis on harms can cause “nocebo” effects, which are the harms caused by expecting something bad to happen. To solve these problems, we have developed seven principles that ensure that information about potential benefits and harms in PILs is balanced and consistent. We will now compare PILs that have been developed according to our principles (we call these ‘PrinciPILs’) with PILs that have not been developed with our principles. We will test whether PrinciPILs reduce nocebo effects and improve trial recruitment. Here we have described our plans to test the effect of PrinciPILs in a few trials.

Sections du résumé

Background UNASSIGNED
The way potential benefits and harms of trial interventions are shared within patient information leaflets (PILs) varies widely and may cause unnecessary harms ("nocebo effects"). The aim of this meta-analysis will be to evaluate the influence on recruitment rates and early effects on patient reported adverse events of principled patient information leaflets (PrinciPILs) compared with standard PILs.
Methods UNASSIGNED
Eligible studies will include those that report the effects on recruitment and patient reported adverse events of PrinciPILs compared to standard PILs. We will include in this meta-analysis all the standard PILs in studies within trials (SWATs) of PrinciPILs that were developed as part of the Medical Research Council (MRC) funded PrinciPIL project. By publishing this as a living meta-analysis, we will allow the meta-analysis to be updated with future SWATs of PrinciPILs. We will use the Cochrane Risk of Bias tool to evaluate the risk of bias for each outcome. We will report the total number of studies and participants analysed and the characteristics of included studies (including details of intervention, comparators, outcomes). For dichotomous data, we will calculate the risk difference and the risk ratio (RR) and 95% confidence intervals (CIs). For continuous outcomes we will use weighted mean differences with 95% CIs or standardized mean differences with 95% CIs. We will investigate heterogeneity by visually inspecting the forest plot and by considering the I
Discussion UNASSIGNED
We will discuss the limitations of the meta-analysis including study risk of bias, inconsistency, heterogeneity, and imprecision. A general interpretation of the results and important implications will be provided.
People who take part in randomised trials need to understand the risks as well as the benefits of taking part. Most ‘patient information leaflets’ (PILs) that describe trial treatments include information about harms. Yet only some PILs contain information about potential benefits. This variation is confusing. Also, the over-emphasis on harms can cause “nocebo” effects, which are the harms caused by expecting something bad to happen. To solve these problems, we have developed seven principles that ensure that information about potential benefits and harms in PILs is balanced and consistent. We will now compare PILs that have been developed according to our principles (we call these ‘PrinciPILs’) with PILs that have not been developed with our principles. We will test whether PrinciPILs reduce nocebo effects and improve trial recruitment. Here we have described our plans to test the effect of PrinciPILs in a few trials.

Autres résumés

Type: plain-language-summary (eng)
People who take part in randomised trials need to understand the risks as well as the benefits of taking part. Most ‘patient information leaflets’ (PILs) that describe trial treatments include information about harms. Yet only some PILs contain information about potential benefits. This variation is confusing. Also, the over-emphasis on harms can cause “nocebo” effects, which are the harms caused by expecting something bad to happen. To solve these problems, we have developed seven principles that ensure that information about potential benefits and harms in PILs is balanced and consistent. We will now compare PILs that have been developed according to our principles (we call these ‘PrinciPILs’) with PILs that have not been developed with our principles. We will test whether PrinciPILs reduce nocebo effects and improve trial recruitment. Here we have described our plans to test the effect of PrinciPILs in a few trials.

Identifiants

pubmed: 39139272
doi: 10.3310/nihropenres.13420.1
pmc: PMC11319896
doi:

Types de publication

Journal Article

Langues

eng

Pagination

29

Informations de copyright

Copyright: © 2023 Howick J et al.

Déclaration de conflit d'intérêts

No competing interests were disclosed.

Auteurs

Jeremy Howick (J)

Centre for Trials Research (CTR), College of Biomedical and Life Sciences, Cardiff University, Cardiff, Wales, UK.

Martina Svobodova (M)

Centre for Trials Research (CTR), College of Biomedical and Life Sciences, Cardiff University, Cardiff, Wales, UK.

Shaun Treweek (S)

Health Services Research Unit, University of Aberdeen, Aberdeen, Scotland, UK.

Nina Jacob (N)

Centre for Trials Research (CTR), College of Biomedical and Life Sciences, Cardiff University, Cardiff, Wales, UK.

Katie Gillies (K)

Health Services Research Unit, University of Aberdeen, Aberdeen, Scotland, UK.

Jennifer Bostock (J)

Centre for Trials Research (CTR), College of Biomedical and Life Sciences, Cardiff University, Cardiff, Wales, UK.

Peter Bower (P)

Division of Population Health, Health Services Research & Primary Care, The University of Manchester, Manchester, England, UK.

Adrian Edwards (A)

Division of Population Medicine, School of Medicine, Cardiff University, Cardiff, Wales, UK.

Kerenza Hood (K)

Centre for Trials Research (CTR), College of Biomedical and Life Sciences, Cardiff University, Cardiff, Wales, UK.

Classifications MeSH