Publication Date

Spring 2024

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Communicative Disorders and Sciences

Advisor

Paul W. Cascella; Pei-Tzu Tsai; Carol Zepecki

Abstract

This research examined 20 speech sound disorder (SSD) treatment apps’ features and costs as related to the feature matching process within speech-language therapy. Methods included the development of a 67-item SSD checklist and sorted into 9 categories, including linguistic levels, speech models, software customization, cost, game types, image types, technical elements, feedback types, and engagement and manipulation. Two independent reviewers applied the checklist to randomly selected contemporary apps available on both iPhones and iPads. App cost was capped at $25. Results indicated that app cost was not a good predictor of feature quantity and contemporary apps had some relevant feature matching characteristics. Nearly all of the apps were easy to manipulate and were engaging consistent with early childhood learning activities. Most relied on articulation word-level practice with easily recognized gender-diverse drawings paired with written text. As well, many had a participation cumulative scoring feature. In contrast, fewer apps included auditory discrimination, phonological processes, traditional (VanRiper) linguistic levels, customization, or software analysis of children’s pronunciation skills. As well, fewer apps had space for clinicians to add their own notes, overtly race-diverse images, app developer troubleshooting access, public education materials, or software that enabled multiple children to use the app at the same time. Some, though not a majority, allowed children to record their own voices for immediate playback. Results are discussed as related to the app feature mapping process that clinicians often embed into clinical services.

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