Auditory Processing and Speech Sound Disorders: Behavioral and Electrophysiological Findings

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Pubblicato in:Audiology Research vol. 15, no. 5 (2025), p. 119-137
Autore principale: Drosos Konstantinos
Altri autori: Paris, Vogazianos, Tafiadis Dionysios, Voniati Louiza, Papanicolaou, Alexandra, Panayidou Klea, Thodi Chryssoula
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MDPI AG
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LEADER 00000nab a2200000uu 4500
001 3265831916
003 UK-CbPIL
022 |a 2039-4349 
024 7 |a 10.3390/audiolres15050119  |2 doi 
035 |a 3265831916 
045 2 |b d20250101  |b d20251231 
100 1 |a Drosos Konstantinos  |u School of Sciences, Speech and Language Therapy, European University Cyprus, 2404 Nicosia, Cyprus; l.voniati@euc.ac.cy (L.V.); c.thodi@euc.ac.cy (C.T.) 
245 1 |a Auditory Processing and Speech Sound Disorders: Behavioral and Electrophysiological Findings 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a Background: Children diagnosed with Speech Sound Disorders (SSDs) encounter difficulties in speech perception, especially when listening in the presence of background noise. Recommended protocols for auditory processing evaluation include behavioral linguistic and speech processing tests, as well as objective electrophysiological measures. The present study compared the auditory processing profiles of children with SSD and typically developing (TD) children using a battery of behavioral language and auditory tests combined with auditory evoked responses. Methods: Forty (40) parents of 7–10 years old Greek Cypriot children completed parent questionnaires related to their children’s listening; their children completed an assessment comprising language, phonology, auditory processing, and auditory evoked responses. The experimental group included 24 children with a history of SSDs; the control group consisted of 16 TD children. Results: Three factors significantly differentiated SSD from TD children: Factor 1 (auditory processing screening), Factor 5 (phonological awareness), and Factor 13 (Auditory Brainstem Response—ABR wave V latency). Among these, Factor 1 consistently predicted SSD classification both independently and in combined models, indicating strong ecological and diagnostic relevance. This predictive power suggests real-world listening behaviors are central to SSD differentiation. The significant correlation between Factor 5 and Factor 13 may suggest an interaction between auditory processing at the brainstem level and higher-order phonological manipulation. Conclusions: This research underscores the diagnostic significance of integrating behavioral and physiological metrics through dimensional and predictive methodologies. Factor 1, which focuses on authentic listening environments, was identified as the strongest predictor. These results advocate for the inclusion of ecologically valid listening items in the screening for APD. Poor discrimination of speech in noise imposes discrepancies between incoming auditory information and retained phonological representations, which disrupts the implicit processing mechanisms that align auditory input with phonological representations stored in memory. Speech and language pathologists can incorporate pertinent auditory processing assessment findings to identify potential language-processing challenges and formulate more effective therapeutic intervention strategies. 
651 4 |a Cyprus 
653 |a Comorbidity 
653 |a Language 
653 |a Evoked responses 
653 |a Memory 
653 |a Age 
653 |a Phonological processing 
653 |a Speech-language pathologists 
653 |a Greek language 
653 |a Parent-child relations 
653 |a Phonological awareness 
653 |a Auditory processing 
653 |a Speech disorders 
653 |a Listening 
653 |a Skill development 
653 |a Nervous system 
653 |a Localization 
653 |a Anatomical systems 
653 |a Phonology 
653 |a Speech perception 
653 |a Pattern recognition 
653 |a Sound 
653 |a Auditory brainstem responses 
653 |a Responses 
653 |a Classification 
653 |a Latency 
653 |a Differentiation 
653 |a Discrimination 
653 |a Parents & parenting 
653 |a Children 
653 |a Behavior 
653 |a Manipulation 
653 |a Speech 
653 |a Disorders 
653 |a Noise 
653 |a Consciousness 
653 |a Predictions 
653 |a Medical screening 
653 |a Discrepancies 
700 1 |a Paris, Vogazianos  |u School of Humanities, Social and Education Sciences, Department of Social and Behavioral Sciences, European University Cyprus, 2404 Nicosia, Cyprus; p.vogazianos@euc.ac.cy 
700 1 |a Tafiadis Dionysios  |u Department of Speech and Language Therapy, University of Ioannina, GR-45500 Ioannina, Greece; tafiadis@uoi.gr 
700 1 |a Voniati Louiza  |u School of Sciences, Speech and Language Therapy, European University Cyprus, 2404 Nicosia, Cyprus; l.voniati@euc.ac.cy (L.V.); c.thodi@euc.ac.cy (C.T.) 
700 1 |a Papanicolaou, Alexandra  |u Department of Hearing and Speech Sciences, University of Maryland College Park, College Park, MD 20740, USA 
700 1 |a Panayidou Klea  |u School of Sciences, Speech and Language Therapy, European University Cyprus, 2404 Nicosia, Cyprus; l.voniati@euc.ac.cy (L.V.); c.thodi@euc.ac.cy (C.T.) 
700 1 |a Thodi Chryssoula  |u School of Sciences, Speech and Language Therapy, European University Cyprus, 2404 Nicosia, Cyprus; l.voniati@euc.ac.cy (L.V.); c.thodi@euc.ac.cy (C.T.) 
773 0 |t Audiology Research  |g vol. 15, no. 5 (2025), p. 119-137 
786 0 |d ProQuest  |t Health & Medical Collection 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3265831916/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
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856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3265831916/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch