# Measuring and evaluating participant understanding of consent processes in clinical trials: a systematic review

**Authors:** Saba Faisal, Julia Wade, Jhulia dos Santos, J. Athene Lane, Giles Birchley, Sarah Dawson, Shoba Dawson

PMC · DOI: 10.1186/s13063-026-09582-x · 2026-03-04

## TL;DR

This review examines tools used to assess participant understanding in clinical trial consent processes, finding that most lack strong validation and public involvement.

## Contribution

The study systematically evaluates the psychometric quality and public involvement in tools measuring informed consent understanding.

## Key findings

- Only three tools showed high-quality psychometric properties: DICCQ, PIC, and P-QIC.
- The most used tool, QuIC, had low methodological quality in its psychometric properties.
- Patient and public involvement in tool development was infrequent and limited.

## Abstract

Informed consent (IC) is essential for maintaining participant autonomy in clinical trials by ensuring participants are fully informed. However, inconsistent oversight of spoken information provision and participant comprehension of both written and spoken information can lead to significant gaps in participant understanding and recall of critical trial details. This systematic review (SR) evaluates existing tools or approaches that measure participant understanding during the IC process. It will further focus on the quality of data regarding the validity and reliability of these methods.

Relevant primary studies were identified through searching electronic databases from inception to March 2023. Studies included adults who had undergone the IC process for research. Following screening, data extraction was performed using a customised Microsoft Excel template, focusing on characteristics including validity, reliability, and patient and public involvement in the development of tools/measures used to assess participant understanding. Narrative synthesis was used to descriptively organise and summarise findings across studies, including study characteristics, assessment timing, and types of tools or approaches used, while psychometric properties were evaluated using the COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) framework.

Of the 6526 records screened, 261 studies were retrieved for full-text screening and a total of 148 studies were included in the review. Among these studies, 103 were quantitative, 24 were mixed methods, and 20 were qualitative studies. This SR identified variability across tools/measures and approaches used in clinical trials to measure participant understanding of IC. Only three tools demonstrated high-quality psychometric properties, i.e. the Digitised Informed Consent Comprehension Questionnaire (DICCQ), the Participatory and Informed Consent (PIC) tool, and the Process and Quality of Informed Consent (P-QIC). Notably, the most frequently used tool across studies, the Quality of Informed Consent (QuIC) questionnaire, demonstrated relatively low methodological quality in its reported psychometric properties. In addition, patient and public involvement in the development of these tools was infrequently reported and often limited in scope.

This review highlights a disconnect between psychometric rigour and common practice. It also emphasises the need to strengthen the validation and standardisation of assessment approaches, alongside more consistent and meaningful integration of patient and public perspectives in their development and validation.

PROSPERO ID: CRD42023407715. Version 1.1, published 14 Aug 2025. Version 1.0, published 22 Mar 2023

The online version contains supplementary material available at 10.1186/s13063-026-09582-x.

## Full-text entities

- **Genes:** PPIE (peptidylprolyl isomerase E) [NCBI Gene 10450] {aka CYP-33, CYP33, CypE}
- **Diseases:** P-QIC (MESH:D010335), dementia (MESH:D003704)
- **Chemicals:** BICEP (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12964858/full.md

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Source: https://tomesphere.com/paper/PMC12964858