A clinical training model for students: intensive treatment of stuttering using prolonged speech

• Autor(a) principal: Georgieva,Dobrinka
• Data de Publicação: 2018
• Outros Autores: Stoilova,Rositsa
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: CoDAS
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2317-17822018000500306
• topic: Student Training; Stuttering; Adult; Intensive Treatment; Prolonged Speech

ABSTRACT Purpose This study describes a practical model for improving the quality of Speech-Language Pathology (SLP) education on a clinical setting in a Bulgarian University. During this study, adults who stutter (AWS) received intensive treatment (IT) to increase fluent speech. The intensive treatment was delivered by students trained in the SLP Master’s degree program “Logopedics Management in Fluency and Voice Disorders”. Methods The La Trobe University intensive program of prolonged speech was implemented. SLP students were trained and delivered the IT for AWS, under supervision in all stages. The treatment followed a clinical modeling pattern. Results The primary outcomes were measured according to (i) percent of syllables stuttered (%SS) within and outside the stuttering research center of the university; (ii) self-reported inventory scores; and (iii) speech naturalness score evaluations from pre-treatment, immediately following treatment, 11 months post-treatment, and 18 months after the intensive treatment using stutter-free speech samples. The outcomes were reported for the overall IT program delivered by the SLP Master students. Conclusion The treatment delivered by students can ensure objective speech outcomes. The evidence-based practice model allowed students to develop and master specific clinical skills in establishing fluent speech by applying a prolonged speech technique. During the IT experience, students began to incorporate elements of evidence-based practice (EBP), clinical expertise, and consider values held by AWS. After four outcome-sessions, the AWS developed self-consciousness about the quality of their prolonged speech during controlled fluent patterns. The participants produced objective speech fluency data and statistically significant differences before and immediately after the IT regarding %SS and overall speech naturalness.