PURPOSE Language sample analysis (LSA) provides many benefits for assessing, identifying therapy goals, and monitoring the progress of children with language disorders. Despite these widely recognized advantages, previous surveys suggest the declining use of LSA by speech-language pathologists (SLPs). This study aimed to provide updates on clinical LSA use following the recent introduction of two new LSA protocols, namely, the Sampling Utterances and Grammatical Analysis Revised (SUGAR) protocol and the Computerized Language Analysis KIDEVAL program. METHOD Survey data from SLPs practicing in the United States (N = 337) were used to examine rates of LSA use, methods, and protocols. Factors predicting LSA use and reported facilitators and barriers were also examined. RESULTS Results indicated that 60% of SLPs used LSA in the past year. LSA skill level, training, and serving preschool or elementary school children predicted LSA use, whereas workplace, caseload, and years of experience were not significant predictors. Most SLPs reported using self-designed LSA protocols (62%), followed by Systematic Analysis of Language Transcripts (23%) and SUGAR (12%) protocols. SLPs who did not use LSA reported limited time (74%), limited resources (59%), and limited expertise (41%) as barriers and identified additional training on LSA computer programs (52%) and access to automatic speech recognition programs (49%) as facilitators to their adoption of LSA. CONCLUSIONS Reported rates of LSA use and methods were consistent with previous survey findings. This study's findings highlight the ongoing needs for more extensive preprofessional training in LSA.

中文翻译：

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临床语言采样实践的更新：在美国执业的言语语言病理学家调查。


目的 语言样本分析 （LSA） 为评估、确定治疗目标和监测语言障碍儿童的进展提供了许多好处。尽管有这些广为人知的优势，但之前的调查表明，语言病理学家 （SLP） 对 LSA 的使用有所下降。本研究旨在提供临床 LSA 使用的最新信息，继最近引入两种新的 LSA 协议，即采样话语和语法分析修订版 （SUGAR） 协议和计算机化语言分析 KIDEVAL 程序。方法 来自在美国执业的 SLP （N = 337） 的调查数据用于检查 LSA 的使用率、方法和协议。还检查了预测 LSA 使用的因素以及报告的促进因素和障碍。结果 结果表明，60% 的 SLP 在过去一年中使用了 LSA。LSA 技能水平、培训和为学龄前或小学儿童提供服务可预测 LSA 的使用，而工作场所、病例量和经验年限不是重要的预测因素。大多数 SLP 报告使用自行设计的 LSA 方案 （62%），其次是语言转录系统分析 （23%） 和 SUGAR （12%） 方案。不使用 LSA 的 SLP 报告说，时间有限 （74%）、资源有限 （59%） 和专业知识有限 （41%） 是障碍，并认为 LSA 计算机程序的额外培训 （52%） 和获得自动语音识别程序 （49%） 是他们采用 LSA 的促进因素。结论 报告的 LSA 使用率和方法与以前的调查结果一致。本研究的结果突出了对更广泛的 LSA 专业前培训的持续需求。