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Proceedings Paper

Are improved rater reliability results associated with faster reaction times after rater training for judgments of laryngeal mucus?
Author(s): Heather Shaw Bonilha; Amy Dawson; Katlyn McGrattan
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Paper Abstract

Mucus aggregation on the vocal folds, a common complaint amongst persons with voice disorders, has been visually rated on four parameters: type, pooling, thickness, and location. Rater training is used to improve the reliability and accuracy of these ratings. The goal of this study was to evaluate the effect of training on rater reliability, accuracy and response time. Two raters scored mucus aggregation from 120 stroboscopic exams after a brief introductory session and again after a thorough training session. Reliability and accuracy were calculated in percent agreement. Two-tail paired t-tests were used to assess differences in reaction time for ratings before and after training. Inter-rater reliability improved from 79% pre-training to 92% post-training. Intra-rater reliability improved from 77% to 91% for Rater 1 and 80% to 88% for Rater 2 following training. Accuracy improved from 80% to 96% for Rater 1 and 76% to 95% for Rater 2 from pre- to post-training. Reaction time decreased for both raters (p=0.025). These findings further our understanding of observer performance on judgments of laryngeal mucus. These results suggest that rater training increases reliability and accuracy while decreasing reaction time. Future studies should assess the relationship of these judgments and voice changes.

Paper Details

Date Published: 22 February 2012
PDF: 8 pages
Proc. SPIE 8318, Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment, 83180Z (22 February 2012); doi: 10.1117/12.913338
Show Author Affiliations
Heather Shaw Bonilha, Medical Univ. of South Carolina (United States)
Amy Dawson, Medical Univ. of South Carolina (United States)
Katlyn McGrattan, Medical Univ. of South Carolina (United States)


Published in SPIE Proceedings Vol. 8318:
Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment
Craig K. Abbey; Claudia R. Mello-Thoms, Editor(s)

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