Morton CC, Marazita ML, Peter B, Rice ML, Kraft SJ, Barkmeier‐Kraemer J, Balaban C, Phillips M, Schoden J, Maiese D, Hendershot T, Hamilton CM. Tools for standardized data collection: Speech, Language, and Hearing measurement protocols in the PhenX Toolkit.
Ann Hum Genet 2022;
86:45-51. [PMID:
34582045 PMCID:
PMC8725989 DOI:
10.1111/ahg.12447]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 08/16/2021] [Accepted: 08/27/2021] [Indexed: 11/30/2022]
Abstract
The PhenX Toolkit (https://www.phenxtoolkit.org/) is an online catalog of recommended measurement protocols to facilitate cross-study analyses for biomedical research. An expert review panel (ERP) reviewed and updated the PhenX Toolkit Speech and Hearing domain to improve the precision and consistency of speech, language, and hearing disorder phenotypes. A three-member ERP convened in August 2018 to review the measurement protocols in the PhenX Speech and Hearing domain. Aided by three additional experts in voice assessment, vertigo, and stuttering, the ERP updated the 28 protocols to reflect the latest science and technology. ERP recommendations include six new protocols, five updated protocols (from the same source), and one retired protocol. New additions include two voice-related, three hearing-related, and two speech-related protocols. Additions reflect new phone/tablet applications for hearing and language, and clinical evaluations of voice. "Language" was added to the domain name, which is now "Speech, Language, and Hearing," to represent language-related protocols. These protocols can facilitate the assessment of speech, language, and hearing in clinical and population research. Common data elements (i.e., use of the same variables across studies) used by geneticists, otolaryngologists, audiologists, speech-language pathologists, and in other disciplines can lead to cross-study data integration and increased statistical power when studies are combined.
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