Apraxia world

Hair, Adam; Monroe, Penelope; Ahmed, Beena; Ballard, Kirrie J.; Gutierrez‐Osuna, Ricardo

doi:10.1145/3202185.3202733

Cited by 40 publications

(8 citation statements)

References 35 publications

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“…A possible explanation for the low scores regarding how well apps were able to achieve participant engagement might be the lack of human-centered theory-driven approaches [40,41]. Although prior studies on speech therapy mobile apps targeting children have used theory-driven or co-design approaches to improve engagement in therapy [42][43][44], this is lacking in the design of apps targeting adults with speech-language therapy. In particular, the apps should be tailored to suit individuals' treatment goals and demographics with a high level of attention to human factors [45] to achieve optimal outcomes.…”

Section: Principal Findingsmentioning

confidence: 99%

Mobile Apps for Speech-Language Therapy in Adults With Communication Disorders: Review of Content and Quality (Preprint)

Vaezipour¹,

Campbell²,

Theodoros³

et al. 2020

Preprint

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BACKGROUND Worldwide, more than 75% of people with acquired brain injury (ABI) experience communication disorders. Communication disorders are impairments in the ability to communicate effectively, that is, sending, receiving, processing, and comprehending verbal and nonverbal concepts and symbols. Such disorders may have enduring impacts on employment, social participation, and quality of life. Technology-enabled interventions such as mobile apps have the potential to increase the reach of speech-language therapy to treat communication disorders. However, ensuring that apps are evidence-based and of high quality is critical for facilitating safe and effective treatment for adults with communication disorders. OBJECTIVE The aim of this review is to identify mobile apps that are currently widely available to adults with communication disorders for speech-language therapy and to assess their content and quality using the validated Mobile App Rating Scale (MARS). METHODS Google Play Store, Apple App Store, and webpages were searched to identify mobile apps for speech-language therapy. Apps were included in the review if they were designed for the treatment of adult communication disorders after ABI, were in English, and were either free or for purchase. Certified speech-language pathologists used the MARS to assess the quality of the apps. RESULTS From a total of 2680 apps identified from Google Play Store, Apple App Store, and web searches, 2.61% (70/2680) apps met the eligibility criteria for inclusion. Overall, 61% (43/70) were available for download on the iPhone Operating System (iOS) platform, 20% (14/70) on the Android platform, and 19% (13/70) on both iOS and Android platforms. A content analysis of the apps revealed 43 apps for language, 17 apps for speech, 8 apps for cognitive communication, 6 apps for voice, and 5 apps for oromotor function or numeracy. The overall MARS mean score was 3.7 out of 5, SD 0.6, ranging between 2.1 and 4.5, with functionality being the highest-scored subscale (4.3, SD 0.6), followed by aesthetics (3.8, SD 0.8), information (3.4, SD 0.6), and engagement (3.3, SD 0.6). The top 5 apps were Naming Therapy (4.6/5), Speech Flipbook Standard (4.6/5), Number Therapy (4.5/5), Answering Therapy, and Constant Therapy (4.4/5). CONCLUSIONS To our knowledge, this is the first study to systematically identify and evaluate a broad range of mobile apps for speech-language therapy for adults with communication disorders after sustaining ABI. We found a lack of interactive and engaging elements in the apps, a critical factor in sustaining self-managed speech-language therapy. More evidence-based apps with a focus on human factors, user experience, and a patient-led design approach are required to enhance effectiveness and long-term use.

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Section: Principal Findingsmentioning

confidence: 99%

Mobile Apps for Speech-Language Therapy in Adults With Communication Disorders: Review of Content and Quality (Preprint)

Vaezipour¹,

Campbell²,

Theodoros³

et al. 2020

Preprint

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“…Text entry [9,38,67,71,82,85,93] Application control [22,90,92] Speech analysis [26,36,52,68,72] Spoken output [28,31,66,77] Conversational Agents [33,43,45,48,55,61,96] Probes [18,74] Domains Education [22,43,52,61,68,77] Health & Well-being [26,28,36,71,72,92,94] Transportation [33,38,55,67,90] Gaming [18,26,36,52,66,…”

Section: References Themesmentioning

confidence: 99%

“…It also helped the learners by demonstrating the correct pronunciation with lip animations. Hair et al [36] presented a third remote therapy tool. They used a Wizard-of-Oz trial to compare the potential for improving engagement with therapy through the use of a mobile game to motivate practice.…”

Section: Speech Analysismentioning

confidence: 99%

“…A software agent calls the player to help them, a game mechanic that could be incorporated with any number of narrative driven games. By building upon mechanics of vocal analysis such as those used in the Karaoke game SLIONS [68] or the various speech therapy tools [26,36] (which naturally lend themselves to personalised models on a personal device) in combination with the more complex text-to-speech generation provides opportunities for more complex, deeper, and emotive interactions through CUIs motivated by gaming principles and narratives.…”

Section: Gamesmentioning

confidence: 99%

“…Explicitly De-coupling the CUI from the rest of the interaction can also be explored to take advantage of the unused modality for complimentary, but distinct tasks. For example a speech therapy task can be lightly coupled to a platform game [36], and furthering interaction research on this path could involve the use of techniques for pro-active CUIs [61] combined with greater awareness of context and ongoing use to initiate parallel activities of the user's choosing (for example language learning) when the opportunity presents itself.…”

Section: Multi-modality In Cuismentioning

confidence: 99%

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Conversational User Interfaces on Mobile Devices

Jaber

2020

Proceedings of the 2nd Conference on Conversational User Interfaces

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Conversational User Interfaces (CUI) on mobile devices are the most accessible and widespread examples of voice-based interaction in the wild. This paper presents a survey of mobile conversation user interface research since the commercial deployment of Apple's Siri, the first readily available consumer CUI. We present and discuss Text Entry & Typing, Application Control, Speech Analysis, Conversational Agents, Spoken Output, & Probes as the prevalent themes of research in this area. We also discuss this body of work in relation to the domains of Health & Well-being, Education, Games, and Transportation. We conclude this paper with a discussion on Multi-modal CUIs, Conversational Repair, and the implications for CUIs of greater access to the context of use. CCS CONCEPTS• Computing methodologies → Speech recognition; • Humancentered computing → Interaction techniques; Smartphones; • General and reference → Surveys and overviews.

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Identifying data elements and key features to design a telerehabilitation system for speech and language disorders in children with hearing impairments in Iran: A cross‐sectional study

Ebrahimi,

Zakerabbasali,

Oryadi

et al. 2024

Health Science Reports

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Background and AimsDesigning and implementing telerehabilitation systems would require the identification of data elements to meet disabled people's needs. An in‐depth study on the identification and validation of data elements can help design and implement telerehabilitation systems successfully. Therefore, this study aimed to identify and validate data elements to design a telerehabilitation system for the speech and language disorders of hearing‐impaired children in Iran.MethodsThis descriptive cross‐sectional study was conducted in three steps including literature review, focused group discussion, and Delphi technique implementation to extract and validate data elements. In the first step, the literature on electronic databases was reviewed to extract the data elements of telerehabilitation systems, and nine studies were selected based on the inclusion criteria. In the second step, a focused group discussion was held to review and classify the extracted data elements. Finally, the Delphi technique was employed to validate the drafted data elements.ResultsIn total, 352 data elements were extracted from the literature review. Finally, 102 data elements in 10 categories (Demographic and Clinical information of the disabled person, Clinical history, Demographic information of the provider, Customization of exercises, Reminders, Online and offline counseling, and training, Reporting, Key features of the system, Evaluation of the progress of the disabled person) were classified and validated by experts as essential data elements to design a telerehabilitation system for the speech and language disorders of hearing‐impaired children.ConclusionsThe necessary data elements were proposed as the foundations to design a telerehabilitation system for the speech and language disorders of hearing‐impaired children. These data elements help design and implement telerehabilitation systems successfully so that such systems can easily be provided for children with hearing disabilities.

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Apraxia world

Cited by 40 publications

References 35 publications

Mobile Apps for Speech-Language Therapy in Adults With Communication Disorders: Review of Content and Quality (Preprint)

Mobile Apps for Speech-Language Therapy in Adults With Communication Disorders: Review of Content and Quality (Preprint)

Conversational User Interfaces on Mobile Devices

Identifying data elements and key features to design a telerehabilitation system for speech and language disorders in children with hearing impairments in Iran: A cross‐sectional study

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