The Portrayal of Stuttering on YouTube Purpose: The purpose of this study was to explore the portrayal of stuttering on YouTube and gage the popularity and tone of the user-generated comments. Method: A search of stuttering videos on YouTube was conducted and 50 videos were analyzed. A combination of descriptive and inferential statistics were used to ... Article
Article  |   May 01, 2014
The Portrayal of Stuttering on YouTube
Author Affiliations & Notes
  • Joseph Donaher
    The Center For Childhood Communication, The Children's Hospital of Philadelphia, Philadelphia, PA
  • Christina Minkoff
    The Center For Childhood Communication, The Children's Hospital of Philadelphia, Philadelphia, PA
  • Disclosure: Financial: Joseph Donaher and Christina Minkoff have no financial interests to disclose.
    Disclosure: Financial: Joseph Donaher and Christina Minkoff have no financial interests to disclose.×
  • Nonfinancial: Joseph Donaher is the Editor of Perspectives on Fluency and Fluency and Disorders. Christina Minkoff has no nonfinancial interests to disclose.
    Nonfinancial: Joseph Donaher is the Editor of Perspectives on Fluency and Fluency and Disorders. Christina Minkoff has no nonfinancial interests to disclose.×
Article Information
Speech, Voice & Prosodic Disorders / Fluency Disorders / Articles
Article   |   May 01, 2014
The Portrayal of Stuttering on YouTube
SIG 4 Perspectives on Fluency and Fluency Disorders, May 2014, Vol. 24, 20-25. doi:10.1044/ffd24.1.20
SIG 4 Perspectives on Fluency and Fluency Disorders, May 2014, Vol. 24, 20-25. doi:10.1044/ffd24.1.20

Purpose: The purpose of this study was to explore the portrayal of stuttering on YouTube and gage the popularity and tone of the user-generated comments.

Method: A search of stuttering videos on YouTube was conducted and 50 videos were analyzed. A combination of descriptive and inferential statistics were used to explore the following variables: (a) type of video, (b) age of presenter, (c) diagnostic reliability—behaviors, (d) diagnostic reliability—content, and (e) public perception.

Results: Videos were viewed on average 27,494 times with 95% of videos receiving positive ratings by the public. Sixty-four percent of the videos were classified as “poor” to “very poor” clinical examples of stuttering behaviors and 52% were classified as “poor” to “very poor” clinical examples of stuttering content. User-generated comments were characterized more often as negative (28%) than positive (12%) with 34% of the comments being neutral.

Conclusion: The low diagnostic reliability scores and proportion of negative user generated comments suggest that clinicians should remain cautious in using YouTube for clinical purposes related to stuttering.

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