Literature DB >> 32208006

Use of an Online Crowdsourcing Platform to Assess Patient Comprehension of Radiology Reports and Colloquialisms.

Joshua K Cho1, Hanna M Zafar1, Tessa S Cook1.   

Abstract

OBJECTIVE. The purpose of this study was to use an online crowdsourcing platform to assess patient comprehension of five radiology reporting templates and radiology colloquialisms. MATERIALS AND METHODS. In this cross-sectional study, participants were surveyed as patient surrogates using a crowdsourcing platform. Two tasks were completed within two 48-hour time periods. For the first crowdsourcing task, each participant was randomly assigned a set of radiology reports in a constructed reporting template and subsequently tested for comprehension. For the second crowdsourcing task, each participant was randomly assigned a radiology colloquialism and asked to indicate whether the phrase indicated a normal, abnormal, or ambivalent finding. RESULTS. A total of 203 participants enrolled for the first task and 1166 for the second within 48 hours of task publication. The payment totaled $31.96. Of 812 radiology reports read, 384 (47%) were correctly interpreted by the patient surrogates. Patient surrogates had higher rates of comprehension of reports written in the patient summary (57%, p < 0.001) and traditional unstructured in combination with patient summary (51%, p = 0.004) formats than in the traditional unstructured format (40%). Most of the patient surrogates (114/203 [56%]) expressed a preference for receiving a full radiology report via an electronic patient portal. Several radiology colloquialisms with modifiers such as "low," "underdistended," and "decompressed" had low rates of comprehension. CONCLUSION. Use of the crowdsourcing platform is an expeditious, cost-effective, and customizable tool for surveying laypeople in sentiment- or task-based research. Patient summaries can help increase patient comprehension of radiology reports. Radiology colloquialisms are likely to be misunderstood by patients.

Entities:  

Keywords:  cancer; crowdsourcing; follow-up; informatics; patient portal; radiology report

Mesh:

Year:  2020        PMID: 32208006     DOI: 10.2214/AJR.19.22202

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  2 in total

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Authors:  Mohammad Alarifi; Timothy Patrick; Abdulrahman Jabour; Min Wu; Jake Luo
Journal:  Int J Environ Res Public Health       Date:  2020-05-22       Impact factor: 3.390

2.  When text simplification is not enough: could a graph-based visualization facilitate consumers' comprehension of dietary supplement information?

Authors:  Xing He; Rui Zhang; Jordan Alpert; Sicheng Zhou; Terrence J Adam; Aantaki Raisa; Yifan Peng; Hansi Zhang; Yi Guo; Jiang Bian
Journal:  JAMIA Open       Date:  2021-04-04
  2 in total

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