ArticleNIHR open research2023
Patient reported outcomes and recruitment rates following the introduction of principled patient information leaflets (PrinciPILs): Protocol for a meta-analysis.
Article in NIHR open research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Developing evidence-based guidelines for describing potential benefits and harms within patient information leaflets/sheets (PILs) that inform and do not cause harm (PrinciPILs).Health technology assessment (Winchester, England) · 2025Article
- When describing harms and benefits to potential trial participants, participant information leaflets are inadequate.Trials · 2024Article
- Patient reported outcomes and recruitment rates following the introduction of principled patient information leaflets (PrinciPILs): Protocol for a meta-analysis.NIHR open research · 2023Article
- Co-production of guidance and resources to implement principled participant information leaflets (PrinciPILs).NIHR open research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: 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: 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: 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.