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Development of a New Voice Assessment Tool: Persian Adductor Laryngeal Dystonia-Vocal Symptoms Scale Publisher Pubmed



Hosseinifar S ; Ahmadi A ; Faham M ; Ebadi A ; Shahramnia M ; Firouzifar M
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Source: Journal of Voice Published:2025


Abstract

Introduction: In the current research, the development of a new Persian scale designed to assess the voice symptoms and their impacts on communicative participation of patients with adductor laryngeal dystonia (AdLD). Methods: The research was conducted in two phases: 1. items were generated, and the scale was developed. 2. The patients with AdLD and primary muscle tension dysphonia (P-MTD) completed the Persian adductor laryngeal dystonia-vocal symptoms scale (PAdLD-VSS) to establish validity (content, convergent, construct) and reliability (test-retest and internal consistency). After the primary development of the PAdLD-VSS, ten participants with AdLD were asked to complete the AdLD-VSS to perform item analysis. Then, 94 patients with AdLD and P-MTD comprised the sample for this research, with each group consisting of 47 participants. Results: Except for two items, all the items had an acceptable content validity ratio. Corrected item-total correlation analysis led to the elimination of 13 items. A moderate value was observed for the convergent validity between total scores of PAdLD-VSS and voice activity and participation profile-Persian (r = 0.532, P = 0.02). The evidence of clinical validity was proved by the higher total scores of PAdLD-VSS in participants with AdLD compared to those with P-MTD (df = 92, P < 0.001). Internal consistency value was satisfactory (α = 0.77, P < 0.001). Test-retest reliability was also obtained to be of a high value (intraclass correlation coefficient = 0.90, P < 0.001). Conclusion: The PAdLD-VSS is a tool with satisfactory reliability and validity values. Performing research on a larger sample size and the association of the scores of PAdLD-VSS with other types of assessment is suggested. © 2025 The Voice Foundation. Published by Elsevier Inc. All rights reserved. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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