An Online Telepractice Model for the Prevention of Voice Disorders in Vocally Healthy Student Teachers Evaluated by a Smartphone Application This article describes the Global Voice Prevention Model (GVPM) facilitated with student teachers at West Chester University and the VoiceEvalU8 smartphone application (app) used to assess the effectiveness of the GVPM. Twenty-one participants completed 1 of 3 conditions (i.e., in-person GVPM, telepractice GVPM, and control). The in-person and telepractice conditions ... Article
Article  |   June 30, 2017
An Online Telepractice Model for the Prevention of Voice Disorders in Vocally Healthy Student Teachers Evaluated by a Smartphone Application
Author Affiliations & Notes
  • Elizabeth U. Grillo
    Department of Communication Sciences and Disorders, West Chester University, West Chester, PA
  • Disclosures
    Disclosures ×
  • Financial: Elizabeth U. Grillo is an employee of West Chester University and receives a salary. She also receives royalties for online continuing education courses through Northern Speech Services. Research described in this article is funded by the National Institute on Deafness and Other Communication Disorders, R15DC014566.
    Financial: Elizabeth U. Grillo is an employee of West Chester University and receives a salary. She also receives royalties for online continuing education courses through Northern Speech Services. Research described in this article is funded by the National Institute on Deafness and Other Communication Disorders, R15DC014566.×
  • Nonfinancial: Elizabeth U. Grillo is the inventor of the prevention model and the smartphone application. Aspects of the manuscript were presented at the 2016 American Speech-Language-Hearing Association convention.
    Nonfinancial: Elizabeth U. Grillo is the inventor of the prevention model and the smartphone application. Aspects of the manuscript were presented at the 2016 American Speech-Language-Hearing Association convention.×
Article Information
Part 2
Article   |   June 30, 2017
An Online Telepractice Model for the Prevention of Voice Disorders in Vocally Healthy Student Teachers Evaluated by a Smartphone Application
Perspectives of the ASHA Special Interest Groups, June 2017, Vol. 2, 63-78. doi:10.1044/persp2.SIG3.63
History: Received January 14, 2017 , Revised March 31, 2017 , Accepted April 3, 2017
Perspectives of the ASHA Special Interest Groups, June 2017, Vol. 2, 63-78. doi:10.1044/persp2.SIG3.63
History: Received January 14, 2017; Revised March 31, 2017; Accepted April 3, 2017

This article describes the Global Voice Prevention Model (GVPM) facilitated with student teachers at West Chester University and the VoiceEvalU8 smartphone application (app) used to assess the effectiveness of the GVPM. Twenty-one participants completed 1 of 3 conditions (i.e., in-person GVPM, telepractice GVPM, and control). The in-person and telepractice conditions ran for 4 weeks during fall 2016, with 1 week dedicated to vocal education and vocal hygiene and 3 weeks spent in vocal training. The control condition ran for 1 week and included only vocal education and vocal hygiene. The VoiceEvalU8 app was used at pre- and post-condition twice a day for 5 days to record acoustic, perceptual, and aerodynamic voice measures. The study is ongoing; therefore, preliminary acoustic results for fundamental frequency (F0) and jitter% are presented from pre- to post-condition. During spring 2017, the participants were student teaching and using the VoiceEvalU8 app to record the voice measures before and after teaching all day. A new group of participants will be enrolled fall 2017 for selection into 1 of the 3 conditions and then continue on to student teaching spring 2018.

Acknowledgements
The work described in this article is supported by the National Institute on Deafness and Other Communication Disorders, R15DC014566. The author would like to thank the five graduate student clinicians who were involved in training the participants in the in-person and telepractice conditions; Allison Lumbis, Kaeli MacArthur, Natalie McGonigle, Sarah Moreau, and Hannah Symons. The author would also like to thank undergraduate and graduate students who were involved in developing and testing the app and preparing the data for analysis; Elizabeth Fedak, Johannah Hattier, Kaeli MacArthur, Sarah Moreau, Kelly Walsh, and Emily Zborowski. Without student involvement, this work would not be possible.
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