Arabic Fluency Assessment: Procedures for Assessing Stuttering in Arabic Preschool Children

The primary aim of this thesis was to screen school-aged (4+) children for two separate types of fluency issues and to distinguish both groups from fluent children. The two fluency issues are Word-Finding Difficulty (WFD) and other speech disfluencies (primarily stuttering). The cohort examined consisted of children who spoke Arabic and English. We first designed a phonological assessment procedure that can equitably test Arabic and English children, called the Arabic English non-word repetition task (AEN_NWR). Riley’s Stuttering Severity Instrument (SSI) is the standard way of assessing fluency for speakers of English. There is no standardized version of SSI for Arabic speakers. Hence, we designed a scheme to measure disfluency symptoms in Arabic speech (Arabic fluency assessment). The scheme recognizes that Arabic and English differ at all language levels (lexically, phonologically and syntactically). After the children with WFD had been separated from those with stuttering, our second aim was to develop and deliver appropriate interventions for the different cohorts. Specifically, we aimed to develop treatments for the children with WFD using short procedures that are suitable for conducting in schools. Children who stutter are referred to SLTs to receive the appropriate type of intervention. To treat WFD, another set of non-word materials was designed to include phonemic patterns not used in the speaker’s native language that are required if that speaker uses another targeted language (e.g. phonemic patterns that occur in English, but not Arabic). The goal was to use these materials in an intervention to train phonemic sequences that are not used in the child’s additional language such as the phonemic patterns that occur in English, but not Arabic. The hypothesis is that a native Arabic speaker learning English would be expected to struggle on those phonotactic patterns not used in Arabic that are required for English. In addition to the screening and intervention protocols designed, self-report procedures are desirable to assess speech fluency when time for testing is limited. To that end, the last chapter discussed the importance of designing a fluency questionnaire that can assess fluency in the entire population of speakers. Together with the AEN_NWR, the brief self-report instrument forms a package of assessment procedures that facilitate screening of speech disfluencies in Arabic children (aged 4+) when they first enter school. The seven chapters, described in more detail below, together constitute a package that achieves the aims of identifying speech problems in children using Arabic and/or English and offering intervention to treat WFD

Factors affecting judgment accuracy when scoring children's responses to non-word repetition stimuli in real time

Background: Non-word repetition (NWR) tests are an important way speech and language therapists (SaLTs) assess language development. NWR tests are often scored whilst participants make their responses (i.e., in real time) in clinical and research reports (documented here via a secondary analysis of a published systematic review). / Aims: The main aim was to determine the extent to which real-time coding of NWR stimuli at the whole-item level (as correct/incorrect) was predicted by models that had varying levels of detail provided from phonemic transcriptions using several linear mixed method (LMM) models. / Methods & Procedures: Live scores and recordings of responses on the universal non-word repetition (UNWR) test were available for 146 children aged between 3 and 6 years where the sample included all children starting in five UK schools in one year or two consecutive years. Transcriptions were made of responses to two-syllable NWR stimuli for all children and these were checked for reliability within and between transcribers. Signal detection analysis showed that consonants were missed when judgments were made live. Statistical comparisons of the discrepancies between target stimuli and transcriptions of children's responses were then made and these were regressed against live score accuracy. Six LMM models (three normalized: 1a, 2a, 3a; and three non-normalized: 1b, 2b, 3b) were examined to identify which model(s) best captured the data variance. Errors on consonants for live scores were determined by comparison with the transcriptions in the following ways (the dependent variables for each pair of models): (1) consonants alone; (2) substitutions, deletions and insertions of consonants identified after automatic alignment of live and transcribed materials; and (3) as with (2) but where substitutions were coded further as place, manner and voicing errors. / Outcomes & Results: The normalized model that coded consonants in non-words as ‘incorrect’ at the level of substitutions, deletions and insertions (2b) provided the best fit to the real-time coding responses in terms of marginal R2, Akaike's information criterion (AIC) and Bayesian information criterion (BIC) statistics. / Conclusions & Implications: Errors that occur on consonants when non-word stimuli are scored in real time are characterized solely by the substitution, deletion and insertion measure. It is important to know that such errors arise when real-time judgments are made because NWR tasks are used to assess and diagnose several cognitive–linguistic impairments. One broader implication of the results is that future work could automate the analysis procedures to provide the required information objectively and quickly without having to transcribe data