Evidence map›Paper›PMID 37828723›Full record

ArticleClinical and translational science2023

uConsent: Addressing the gap in measuring understanding of informed consent in clinical research.

Richard F Ittenbach, J William Gaynor, Jenny M Dorich, Nancy B Burnham, Guixia Huang, Madisen T Harvey, Jeremy J Corsmo

Abstract read
In one paragraph

Article in Clinical and translational science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Richard F IttenbachDivision of Biostatistics and Epidemiology, Cincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA.ORCID 0000-0002-7914-4298
J William GaynorDivision of Cardiothoracic Surgery, Department of Surgery, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID 0000-0001-7955-5604
Jenny M DorichDivision of Patient Services, Cincinnati Children's Hospital and Department of Orthopedic Surgery, University of Cincinnati College of Medicine, Ohio, Cincinnati, USA.ORCID 0000-0002-4522-9533
Nancy B BurnhamDivision of Cardiothoracic Surgery, Department of Surgery, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID 0009-0001-9038-2297
Guixia HuangDivision of Biostatistics and Epidemiology, Cincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA.ORCID 0000-0002-2754-9410
Madisen T HarveyDivision of Cardiothoracic Surgery, Department of Surgery, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Jeremy J CorsmoResearch Administration, Kennedy Krieger Institute, Baltimore, Maryland, USA.ORCID 0000-0003-2904-5467

Funding

LCenter for Clinical and Translational Science and TrainingUL1TR001425 · NCATS · UNIVERSITY OF CINCINNATI · PI MEINZEN-DERR, JAREEN, STRAWN, JEFFREY ROBERT · 2015 to 2024
$37.5M
NCATS NIH HHS UL1 TR001425
6 · The paper itself

Abstract

The purpose of this study was to establish the technical merit, feasibility, and generalizability of a new measure of understanding of informed consent for use with clinical research participants. A total of 109 teens/young adults at a large, pediatric medical center completed the consenting process of a hypothetical biobanking study. Data were analyzed using a combination of classical and modern theory analytic methods to produce a final set of 19 items referred to as the uConsent scale. A requirement of the scale was that each item mapped directly onto one or more of the Basic Elements of Informed Consent from the 2018 Final Rule. Descriptive statistics were computed for each item as well as the scale as a whole. Partial credit (Rasch) logistic modeling was then used to generate difficulty/endorsability estimates for each item. The final, 19-item uConsent scale was derived using inferential methods to yield a set of items that ranged across difficulty levels (-3.02 to 3.10 logits) with a range of point-measure correlations (0.12 to 0.50), within-range item- and model-fit statistics, varying item types mapped to both Bloom's Taxonomy of Learning and required regulatory components of the 2018 Final Rule. Median coverage rate for the uConsent scale was 95% for the 25 randomly selected studies from ClinicalTrials.gov. The uConsent scale may be used as an effective measure of informed consent when measuring and documenting participant understanding in clinical research studies today.

Indexed as

Biological Specimen BanksInformed ConsentAdolescentChildHumansPsychometricsReproducibility of ResultsSurveys and QuestionnairesYoung Adult

Identifiers

PMID37828723
PMCPMC10719467

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.