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Clinician Perceptions of Phonatory-Respiratory Kinematic Patterns in Primary Muscle Tension Dysphonia
Denise Kim1, Elizabeth D Young2, Robert A Morrison3
1School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Texas; Callier Center for Communication Disorders, Dallas, Texas.
Objectives:
Altered respiratory kinematics are thought to contribute to primary muscle tension dysphonia (pMTD) symptoms such as vocal effort, fatigue, and discomfort. Although speech-language pathologists (SLPs) often comment on respiratory patterns during voice evaluations, it remains unclear which visual-perceptual cues they rely on for clinical decision-making and how accurate these patterns are for identifying patients with pMTD. As such, this study aimed to (1) identify the respiratory patterns SLPs perceive in pMTD and (2) evaluate their diagnostic accuracy in distinguishing pMTD from vocally healthy controls.
Methods:
Forty-six participants (21 pMTD, 25 controls) performed voice tasks varying in intensity and articulatory complexity, while six synchronized cameras captured perilaryngeal-respiratory movements. Five blinded, fellowship-trained SLPs rated breathing normality, severity (0-10), presence of pMTD (Y/N), and confidence (0-10). Open-ended responses were analyzed using natural language processing (NLP) and reflexive content analysis (RCA).
Results:
NLP analysis identified five visual-perceptual respiratory features: abdominal, anterior neck tension, clavicular, thoracic, and suboptimal breathing-none of which reliably distinguished pMTD from vocally healthy controls (average diagnostic accuracy = 60%; d' ≤ 1.04). RCA methods yielded three categories: Observable Features of Movement and Breathing, Perceived Patient Experiences, and Interpreting and Evaluating Data.
Conclusion:
Observable respiratory patterns were inconsistently linked to diagnostic accuracy. Visual observation alone appears insufficient for reliably identifying pMTD, underscoring the need for multimodal physiological approaches to improve diagnostic specificity.
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