It should be noted that phonological disorders among schoolchildren are an intricate issue, which requires multifaceted treatment measures. However, clinical experts primarily utilize only a few of the available options, which makes it important to familiarize them with viable alternative options. The selected article mainly focuses on the complexity approach in regards to phonological treatment among children, which is highly useful to facilitate the utilization of a multitude of pieces of information to expand the overall range of evidence-based options of treatment.
The article begins with characteristics of targets in regard to implicational universals, such as marked and unmarked categories. These include fricatives, affricatives, voiced and voiceless obstruents, nasals, clusters, and others (Storkel 466). In the case of clinical practice, it is important to understand the characteristics of knowledge among children, which include stimulability and accuracy. The complexity approach for the phonological disorders among children “should prioritize selection of (a) late-acquired, (b) implicationally marked, (c) least-knowledge, and (d) nonstimulable targets to produce broad, system-wide change in phonology” (Storkel 469). Although these efforts are likely to increase the time spent on the initial assessment, the complexity treatment can quicken the general treatment process, which means that the given approach is more effective in total.
The implementation of the complexity treatment requires a collection of a large quantity of data, such as stimulability, accuracy, implicational universals, and age of acquisition. The former two are not always a part of a clinician’s regular assessment protocol, and integration of all four categories of data can be challenging (Storkel 469). Therefore, these barriers need to be overcome with the use of a well-coordinated workflow process. In the case of singleton probes, clinicians should select targets by “scoring distortions as correct because the complexity approach prioritizes treatment of substitutions or deletions, rather than distortions” (Storkel 470). However, for singleton stimulability, a clinician should test the latter “for targets with very low accuracy, operationalized as 0%–10% accuracy” (Storkel 470). In the case of cluster probe, every cluster is focused in two words, which is why clinicians should score distortions as correct to identify inaccurate and accurate clusters as well as distorted ones. The cluster stimulability is not mandatory, and thus clinicians “should be cautioned that there is no specific research about testing stimulability of clusters or applying cluster stimulability to select cluster treatment targets” (Storkel 471). The author of the article suggests using the excel spreadsheet designed to calculate and score these assessments.
The complexity approach derives a total score on the basis of stimulability, accuracy, implicational universals, and developmental norms. The complexity treatment only selects individuals with a score of 4 with a possible selection of children with a score between 1 and 3, but the ones with a total score of 0 are not selected (Storkel 473). Children with a total score of 4 are “late acquired, marked based on a high number of relevant implicational universals, of low accuracy, and nonstimulable” (Storkel 473). These groups will require the complexity treatment in order to receive the most effective treatment.
In conclusion, the complexity approach requires an extensive assessment process, which is worthwhile because the treatment process is shortened due to precision and in-depth analysis. The key metrics are stimulability, accuracy, implicational universals, and age of acquisition. The treatment is always recommended for children, who scored 4, which means their phonological issue is nonstimulable, inaccurate, marked based, and late acquired.
Work Cited
Storkel, Holly L. “The Complexity Approach to Phonological Treatment: How to Select Treatment Targets.” Language, Speech, and Hearing Services in Schools, vol. 49, no. 3, 2018, pp. 463-481.