New research examines accessibility of clinical trial information
New research from UMSI reveals that efforts to improve public access to clinical trial information may be overshadowed by a lack of readability. In a recent paper, principally authored by PhD student Danny T.Y. Wu and published in the Journal of the American Medical Informatics Association, trial descriptions were found to be less comprehensible than clinician notes used for internal communication among medical professionals.
In this paper, the authors measured readability with algorithms that examine document length, sentence length, vocabulary size, vocabulary coverage and reading difficulty based on comparisons to online health articles and medical textbooks.
They found that trial descriptions on ClinicalTrials.gov, a federal registry aimed at informing the general public about clinical trial studies, required on average 18 years of education to properly read and understand.
The results were incongruent with the website’s mission of providing easy access to clinical trial information that is readily understandable by the public, the researchers noted. They suggest potential methods for improving the readability of ClinicalTrials.gov such as shortening sentences, including more terms found in a basic medical dictionary, or providing more consumer-oriented descriptions (e.g., using “chickenpox virus” rather than “varicella zoster virus.”)
“The registry’s potential for facilitating information dissemination and participant recruitment could be limited if the public, with varying literacy levels, are unable to read and properly understand the descriptions of the trials,” the researchers noted in the paper. “Thus, it is important to investigate the readability of trial descriptions available at ClinicalTrials.gov to ensure that the study information can be effectively conveyed to a wide audience with varying literacy.”
“Assessing the readability of clinicaltrials.gov” Danny TY Wu; David A Hanauer; Qiaozhu Mei; Patricia M Clark; Lawrence C An; Joshua Proulx; Qing T Zeng; VG Vinod Vydiswaran; Kevyn Collins-Thompson; Kai Zheng
Journal of the American Medical Informatics Association 2015; doi: 10.1093/jamia/ocv062
The full article can be found here: http://jamia.oxfordjournals.org/content/jaminfo/early/2015/08/08/jamia.ocv062.full.pdf?ijkey=uBfPq3knlHRzbpe&keytype=ref