Assessment Tools Used by Speech and Language Pathologists for Assessment of Childhood Apraxia of Speech
Keywords:
Assessment Tools, Childhood Apraxia of Speech (CAS) , Speech-Language Pathologists (SLPs) , Diagnostic criteria , Speech Disorders , Motor Speech Disorder , Clinical evaluationAbstract
Background: Childhood Apraxia of Speech (CAS) is a motor speech disorder characterized by impaired planning and programming of speech movements, leading to inconsistent errors, disrupted transitions, and abnormal prosody. Accurate diagnosis requires valid, reliable assessment tools, yet evidence on the use of such tools by speech-language pathologists (SLPs) in Pakistan is limited, potentially impacting diagnostic precision and treatment planning. Objective: This study aimed to evaluate the assessment tools used by SLPs for diagnosing CAS, determine the frequency of standardized versus non-standardized tool use, and identify perceived challenges associated with these diagnostic methods. Methods: A descriptive cross-sectional design was used, involving 65 SLPs recruited through purposive sampling from various clinical and academic settings. Data were collected using a structured, expert-validated questionnaire, and analyzed using descriptive statistics and chi-square tests with IBM SPSS version 20. Results: Of the participants, 72.3% were female, 67.7% were aged 23–25 years, and 72.3% had 0–5 years of clinical experience. Non-standardized tools (55.4%) were preferred over formal assessments (44.6%), with DEMSS being the most frequently used standardized tool (44.6% any use). Despite this, 80% believed formal tools are sufficient, and 87.7% found them effective. Key barriers included validity concerns (18.5%) and administrative complexity (13.8%). Conclusion: Although SLPs recognize the value of standardized CAS assessments, informal methods predominate due to practical limitations, underscoring the need for training and culturally adapted diagnostic protocols.
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Copyright (c) 2024 Waleeja Batool, Muhammad Talha Afzal, Amna Rashid, Areesha Shahbaz, Saman Shehzadi, Muhammad Shazaib Khan

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