%0 Journal Article %@ 2292-9495 %I JMIR Publications %V 12 %N %P e64079 %T Best Practice Guide for Reducing Barriers to Video Call–Based Telehealth: Modified Delphi Study Among Health Care Professionals %A Rettinger,Lena %A Aichinger,Lea %A Ertelt-Bach,Veronika %A Huber,Andreas %A Javorszky,Susanne Maria %A Maul,Lukas %A Putz,Peter %A Sargis,Sevan %A Werner,Franz %A Widhalm,Klaus %A Kuhn,Sebastian %+ Research Center Digital Health and Care, FH Campus Wien, University of Applied Sciences Vienna, Favoritenstrasse 226, Vienna, 1100, Austria, 43 6066977 ext 4382, lena.rettinger@fh-campuswien.ac.at %K telehealth %K best practices %K video call %K Delphi study %K health communication %K barriers %K health care professionals %K qualitative interviews %K web-based survey %K physiotherapists %K speech therapists %K language therapists %K dietitians %K midwife %D 2025 %7 26.3.2025 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Telehealth has grown, especially during the COVID-19 pandemic, improving access for those in remote or underserved areas. However, its implementation faces technological, practical, and interpersonal barriers. Objective: The aim of this study was to identify and consolidate best practices for telehealth delivery, specifically for video call sessions, by synthesizing the insights of health care professionals across various disciplines. Methods: We first identified 15 common telehealth barriers from a preceding scoping review. Subsequently, a modified Delphi method was used, involving 9 health care professionals (physiotherapists, speech and language therapists, dietitians, and midwife) with telehealth experience in qualitative interviews and 2 iterative rounds of web-based surveys to form consensus. Results: This study addressed 15 telehealth barriers and identified 105 best practices. Among these, 20 are technology-related and 85 concern health care practices. Emphasis was placed on setting up telehealth environments, ensuring safety, building relationships and trust, using nonmanual methods, and enhancing observation and assessment skills. Best practice recommendations for dealing with patients or caregiver skepticism or lack of telehealth-specific knowledge were developed. Further, approaches for unstable networks and privacy and IT security issues were identified. Areas with fewer best practices were the lack of technology skills or technology access, unreliability of hardware and software, increased workload, and a lack of caregiver support. Conclusions: This guide of best practices serves as an actionable resource for health care providers to navigate the complexities of telehealth. Despite a small participant sample and the potential for profession-specific biases, the findings provide a foundation for improving telehealth services and inform future research for its application and education. %M 40138694 %R 10.2196/64079 %U https://humanfactors.jmir.org/2025/1/e64079 %U https://doi.org/10.2196/64079 %U http://www.ncbi.nlm.nih.gov/pubmed/40138694 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 12 %N %P e60424 %T Enhancing Early Language Disorder Detection in Preschools: Evaluation and Future Directions for the Gades Platform %A Dolón-Poza,María %A Gabaldón-Pérez,Ana-Marta %A Berrezueta-Guzman,Santiago %A López Gracia,David %A Martín-Ruiz,María-Luisa %A Pau De La Cruz,Iván %+ , Technical University of Munich, BildungsCampus 2, Heilbronn, 74076, Germany, 49 15159184710, s.berrezueta@tum.de %K developmental language disorder %K simple language delay %K adaptive screening system %K early childhood education %K pervasive therapy %D 2025 %7 14.3.2025 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Language acquisition is a critical developmental milestone, with notable variability during the first 4 years of life. Developmental language disorder (DLD) often overlaps with other neurodevelopmental disorders or simple language delay (SLD), making early detection challenging, especially for primary caregivers. Objective: We aimed to evaluate the effectiveness of the Gades platform, an adaptive screening tool that enables preschool teachers to identify potential language disorders without direct support from nursery school language therapists (NSLTs). Methods: The study took place in a nursery school and an early childhood educational and psychopedagogical center in Madrid, Spain, involving 218 children aged 6 to 36 months, 24 preschool teachers, and 2 NSLTs. Initially, NSLTs conducted informational sessions to familiarize teachers with DLDs and how to identify them. Following this, the teachers used the Gades platform to conduct language screenings independently, without ongoing support from NSLTs. The Gades platform was enhanced to collect detailed profiles of each child and implemented an adaptive screening model tailored to account for variability in language development. This setup allowed preschool teachers, who are not language experts, to observe and assess language development effectively in natural, unsupervised educational environments. The study assessed the platform’s utility in guiding teachers through these observations and its effectiveness in such settings. Results: Gades identified language difficulties in 19.7% (43/218) of the children, with a higher prevalence in boys (29/218, 13.3%) than in girls (14/218, 6.4%). These challenges were most frequently observed in children aged 15 to 27 months. The platform demonstrated a high accuracy rate of 97.41%, with evaluators largely agreeing with its recommendations. Teachers also found Gades to be user friendly and a valuable tool for supporting language development observations in everyday educational settings. Conclusions: Gades demonstrates potential as a reliable and accessible tool for early detection of language disorders, empowering educators to identify DLD and SLD in the absence of NSLTs. However, further refinement of the platform is required to effectively differentiate between DLD and SLD. By integrating Gades into routine preschool assessments, educators can facilitate timely interventions, bridging gaps in early childhood education and therapy. Trial Registration: Pan-African Clinical Trial Registry (PACTR) PACTR202210657553944; https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=24051 %M 40086469 %R 10.2196/60424 %U https://humanfactors.jmir.org/2025/1/e60424 %U https://doi.org/10.2196/60424 %U http://www.ncbi.nlm.nih.gov/pubmed/40086469 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e63166 %T Smartphone Application–Based Voice and Speech Training Program for Parkinson Disease: Feasibility and Satisfaction Study With a Preliminary Rater-Blinded Single-Arm Pretest and Posttest Design %A Lee,Sol-Hee %A Kim,Jiae %A Kim,Han-Joon %+ Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea, 82 10 7279 7883, movement@snu.ac.kr %K Parkinson disease %K speech therapy %K mHealth %K home-based training %K self-delivered %K digital health care %K app %K feasibility %K voice therapy %K mobile phone %K satisfaction %K effectiveness %K smartphone %K apps %K single-arm study %K mobility %K mobile health %K acoustic analysis %K self-training %D 2025 %7 13.2.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Up to 75% of patients with Parkinson disease (PD) experience voice and speech impairments, such as breathy phonation and low speech volume, which worsen over time and negatively impact the quality of life. However, given their increasingly limited mobility, face-to-face speech therapy is often inaccessible. Mobile health (mHealth) apps offer accessible and cost-effective alternatives; yet, their application in PD-specific, self-delivered voice therapy remains underexplored. Objective: This study aimed to evaluate the feasibility, adherence, and satisfaction of a self-delivered smartphone app for voice therapy in patients with PD, designed to minimize speech-language pathologist involvement while promoting patient independence. In addition, it seeks to assess the preliminary therapeutic effectiveness of the app in addressing voice and speech problems in this population. Methods: A single-arm, rater-blinded, and pretest and posttest study was conducted between September to November 2023. Patients with PD with voice and speech problems who have no problem with using Android (Google) smartphones were recruited. Participants downloaded the researcher-developed mHealth app on their smartphone and participated in a patient-tailored 5-week home-based speech training program. Each session included 5 stages: breathing, oral motor exercises, loudness, prosody, and functional speaking. The training program consisted of 20 sessions, with participants completing 1 session per day, 4 days per week. Each session lasted approximately 20-30 minutes. Adherence was monitored through app logs, satisfaction was assessed through a phone survey, and therapeutic effectiveness was evaluated using acoustic analysis and auditory-perceptual assessments. Results: Out of 30 patients were initially recruited, but 2 of them withdrew. Out of 25 participants completed all the training sessions while 3 dropped out. The adherence was above 90% in 20 participants (80%, 20/25), 70% to 90% in 4 (16%, 4/25), and below 70% in 4 (16%, 4/25). Satisfaction was 75% (18/24) among the 24 people who participated in the survey. Significant improvements were observed in all acoustic measures: the maximum phonation time increased from 11.15 (SD 5.38) seconds to 14.01 (SD 5.64) seconds (P=.003), and vocal intensity increased from 71.59 (SD 4.39) dB to 73.81 (SD 3.48) dB (P<.001) across both sustained phonation and reading tasks. Voice quality scores on the GRBAS (grade, roughness, breathiness, asthenia, and strain) scale improved significantly (all components P<.001). Furthermore, 58.3% (14/24) of participants reported subjective improvements in their voice. Conclusions: This study demonstrates that home-based, self-training speech therapy delivered through a mHealth app is a feasible solution for patients with PD, suggesting that mHealth apps can serve as a convenient and effective alternative to face-to-face therapy by enhancing accessibility and empowering patients to actively manage their condition. %M 39946689 %R 10.2196/63166 %U https://www.jmir.org/2025/1/e63166 %U https://doi.org/10.2196/63166 %U http://www.ncbi.nlm.nih.gov/pubmed/39946689 %0 Journal Article %@ 2561-6722 %I JMIR Publications %V 8 %N %P e60333 %T Efficacy, Feasibility, and Acceptability of an Emotional Competence Tele-Intervention for Mandarin-Speaking Children Aged 5 to 7 Years With Developmental Language Disorder: Pilot Study With an Interrupted Time-Series Design %A Lu,Hsin-Hui %A Liang,Shih-Yuan %A Huang,Yi-Chia %+ Division of Clinical Psychology, Graduate Institute of Behavioral Sciences, College of Medicine, Chang Gung University, 33302 No 259, Wenhua 1st Rd, Guishan Dist, Taoyuan City, 33302, Taiwan, 886 03 2118800, hsinhuilupsy@gmail.com %K language disorder %K pediatrics %K evidence-based intervention %K telemedicine %K tele-practice %K visual support %K mobile phone %D 2025 %7 11.2.2025 %9 Original Paper %J JMIR Pediatr Parent %G English %X Background: Children with developmental language disorder (DLD) often experience language difficulties that hinder their ability to acquire emotional competence. Poor emotional competence is associated with emotional and behavioral problems in young children. Objective: This research involved two studies focusing on (1) the emotional competence of Mandarin-speaking children aged 5 to 7 years with DLD and (2) the efficacy, feasibility, and acceptability of a tele-intervention designed to enhance their emotional competence in Taiwan. Methods: Five children with DLD from study 1 declined to participate in study 2, the emotional competence tele-intervention, and were excluded from the analysis. We compared the emotional competence of 20 Mandarin-speaking children with DLD to that of 24 children with typical language development (TLD). The children with DLD were, on average, aged 5.79 (SD 0.47) years, whereas the children with TLD were, on average, aged 5.93 (SD 0.31) years. We assessed the children’s emotional competence, nonverbal ability, verbal comprehension, vocabulary acquisition, and expressive language skills. In study 2, all children with DLD included in study 1 engaged in an emotional competence tele-intervention. An interrupted time-series design was used to examine their emotional competence. In total, 20 children with DLD provided data on emotional competence evaluated using the Emotional Lexicon Test. These data were individually collected at 3 time points after study 1 (time 1). These phases included baseline (time 1 to time 2), during the tele-intervention (time 2 to time 3), and follow-up (time 3 to time 4), spanning approximately 18 to 20 weeks from time 1 to time 4. Recruitment, retention, and attendance rates were calculated to evaluate the intervention’s feasibility, and participant mood was evaluated after each session to calculate the intervention’s acceptability. Results: No significant changes in the children’s ability to understand basic or complex emotional terms were observed during the baseline period. However, changes were observed during the tele-intervention period, and these changes remained throughout the follow-up period. With a recruitment rate of 80% (20/25), all participants completed 4 intervention sessions, with retention and attendance rates exceeding 95% (19/20). A total of 90% (18/20) of the participants deemed each session to be acceptable. Conclusions: Mandarin-speaking children aged 5 to 7 years with DLD exhibited lower emotional competence compared with their counterparts with TLD. Tele-interventions are effective in enhancing the emotional competence of children with DLD, demonstrating feasibility and acceptability for these children and their parents in Taiwan. %M 39933173 %R 10.2196/60333 %U https://pediatrics.jmir.org/2025/1/e60333 %U https://doi.org/10.2196/60333 %U http://www.ncbi.nlm.nih.gov/pubmed/39933173 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 12 %N %P e67036 %T Device Failures and Adverse Events Associated With Rhinolaryngoscopes: Analysis of the Manufacturer and User Facility Device Experience (MAUDE) Database %A Chang,Shao-Hsuan %A Chen,Daishi %A Chen,Chi-Sheng %A Zhou,Dong %A Yeh,Lung-Kun %K medical device %K device malfunction %K rhinolaryngoscope %K adverse event %K MAUDE %K Manufacturer and User Facility Device Experience %D 2025 %7 5.2.2025 %9 %J JMIR Hum Factors %G English %X Background: Rhinolaryngoscopes are one of the most widely used tools by otolaryngologists and speech-language pathologists in current clinical practice. However, there is limited data on adverse events associated with or caused by the use of rhinolaryngoscopes. Objective: In this study, we used the Manufacturer and User Facility Device Experience (MAUDE) database with the aim of providing insights that may assist otolaryngologists in better understanding the limitations of these devices and selecting appropriate procedures for their specific clinical setting. Methods: We characterized complications associated with the postmarket use of rhinolaryngoscope devices from the US Food and Drug Administration MAUDE database from 2016 through 2023. Results: A total of 2591 reports were identified, including 2534 device malfunctions, 56 injuries, and 1 death, from 2016 through 2023. The most common device problem with rhinolaryngoscopes was breakage (n=1058 reports, 40.8%), followed by fluid leaks (n=632 reports, 24.4%). The third most common problem was poor image quality (n=467 reports, 18%). Other device issues included contamination or device reprocessing problems (n=127 reports, 4.9%), material deformation or wear (n=125 reports, 4.8%), and device detachment (n=73 reports, 2.8%). Of the 63 reported adverse events, the most common patient-related adverse event was hemorrhage or bleeding, accounting for 18 reports, with the root causes including material deformation or wear, breakage, wrinkled rubber, or improper operation. Conclusions: Our study offers valuable insights for endoscopists and manufacturers to recognize potential issues and adverse events associated with the use of rhinolaryngoscopes. It emphasizes the need for improving device reliability, training, and procedural protocols to enhance patient safety during diagnostic procedures. %R 10.2196/67036 %U https://humanfactors.jmir.org/2025/1/e67036 %U https://doi.org/10.2196/67036 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e60520 %T Usefulness of Automatic Speech Recognition Assessment of Children With Speech Sound Disorders: Validation Study %A Kim,Do Hyung %A Jeong,Joo Won %A Kang,Dayoung %A Ahn,Taekyung %A Hong,Yeonjung %A Im,Younggon %A Kim,Jaewon %A Kim,Min Jung %A Jang,Dae-Hyun %+ Department of Rehabilitation Medicine, Incheon St Mary’s Hospital, College of Medicine, The Catholic University of Korea, 22 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea, 82 0322806601, dhjangmd@naver.com %K speech sound disorder %K speech recognition software %K speech articulation tests %K speech-language pathology %K child %D 2025 %7 14.1.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Speech sound disorders (SSDs) are common communication challenges in children, typically assessed by speech-language pathologists (SLPs) using standardized tools. However, traditional evaluation methods are time-intensive and prone to variability, raising concerns about reliability. Objective: This study aimed to compare the evaluation outcomes of SLPs and an automatic speech recognition (ASR) model using two standardized SSD assessments in South Korea, evaluating the ASR model’s performance. Methods: A fine-tuned wav2vec 2.0 XLS-R model, pretrained on 436,000 hours of adult voice data spanning 128 languages, was used. The model was further trained on 93.6 minutes of children’s voices with articulation errors to improve error detection. Participants included children referred to the Department of Rehabilitation Medicine at a general hospital in Incheon, South Korea, from August 19, 2022, to June 14, 2023. Two standardized assessments—the Assessment of Phonology and Articulation for Children (APAC) and the Urimal Test of Articulation and Phonology (U-TAP)—were used, with ASR transcriptions compared to SLP transcriptions. Results: This study included 30 children aged 3-7 years who were suspected of having SSDs. The phoneme error rates for the APAC and U-TAP were 8.42% (457/5430) and 8.91% (402/4514), respectively, indicating discrepancies between the ASR model and SLP transcriptions across all phonemes. Consonant error rates were 10.58% (327/3090) and 11.86% (331/2790) for the APAC and U-TAP, respectively. On average, there were 2.60 (SD 1.54) and 3.07 (SD 1.39) discrepancies per child for correctly produced phonemes, and 7.87 (SD 3.66) and 7.57 (SD 4.85) discrepancies per child for incorrectly produced phonemes, based on the APAC and U-TAP, respectively. The correlation between SLPs and the ASR model in terms of the percentage of consonants correct was excellent, with an intraclass correlation coefficient of 0.984 (95% CI 0.953-0.994) and 0.978 (95% CI 0.941-0.990) for the APAC and UTAP, respectively. The z scores between SLPs and ASR showed more pronounced differences with the APAC than the U-TAP, with 8 individuals showing discrepancies in the APAC compared to 2 in the U-TAP. Conclusions: The results demonstrate the potential of the ASR model in assessing children with SSDs. However, its performance varied based on phoneme or word characteristics, highlighting areas for refinement. Future research should include more diverse speech samples, clinical settings, and speech data to strengthen the model’s refinement and ensure broader clinical applicability. %M 39576242 %R 10.2196/60520 %U https://www.jmir.org/2025/1/e60520 %U https://doi.org/10.2196/60520 %U http://www.ncbi.nlm.nih.gov/pubmed/39576242 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e63004 %T Clinical Decision Support Using Speech Signal Analysis: Systematic Scoping Review of Neurological Disorders %A De Silva,Upeka %A Madanian,Samaneh %A Olsen,Sharon %A Templeton,John Michael %A Poellabauer,Christian %A Schneider,Sandra L %A Narayanan,Ajit %A Rubaiat,Rahmina %+ Department of Computer Science and Software Engineering, Auckland University of Technology, 55 Wellesley Street East, Auckland CBD, Auckland 1010, Auckland, 1010, New Zealand, 64 09 9219999 ext 6539, sam.madanian@aut.ac.nz %K digital health %K health informatics %K digital biomarker %K speech analytics %K artificial intelligence %K machine learning %D 2025 %7 13.1.2025 %9 Review %J J Med Internet Res %G English %X Background: Digital biomarkers are increasingly used in clinical decision support for various health conditions. Speech features as digital biomarkers can offer insights into underlying physiological processes due to the complexity of speech production. This process involves respiration, phonation, articulation, and resonance, all of which rely on specific motor systems for the preparation and execution of speech. Deficits in any of these systems can cause changes in speech signal patterns. Increasing efforts are being made to develop speech-based clinical decision support systems. Objective: This systematic scoping review investigated the technological revolution and recent digital clinical speech signal analysis trends to understand the key concepts and research processes from clinical and technical perspectives. Methods: A systematic scoping review was undertaken in 6 databases guided by a set of research questions. Articles that focused on speech signal analysis for clinical decision-making were identified, and the included studies were analyzed quantitatively. A narrower scope of studies investigating neurological diseases were analyzed using qualitative content analysis. Results: A total of 389 articles met the initial eligibility criteria, of which 72 (18.5%) that focused on neurological diseases were included in the qualitative analysis. In the included studies, Parkinson disease, Alzheimer disease, and cognitive disorders were the most frequently investigated conditions. The literature explored the potential of speech feature analysis in diagnosis, differentiating between, assessing the severity and monitoring the treatment of neurological conditions. The common speech tasks used were sustained phonations, diadochokinetic tasks, reading tasks, activity-based tasks, picture descriptions, and prompted speech tasks. From these tasks, conventional speech features (such as fundamental frequency, jitter, and shimmer), advanced digital signal processing–based speech features (such as wavelet transformation–based features), and spectrograms in the form of audio images were analyzed. Traditional machine learning and deep learning approaches were used to build predictive models, whereas statistical analysis assessed variable relationships and reliability of speech features. Model evaluations primarily focused on analytical validations. A significant research gap was identified: the need for a structured research process to guide studies toward potential technological intervention in clinical settings. To address this, a research framework was proposed that adapts a design science research methodology to guide research studies systematically. Conclusions: The findings highlight how data science techniques can enhance speech signal analysis to support clinical decision-making. By combining knowledge from clinical practice, speech science, and data science within a structured research framework, future research may achieve greater clinical relevance. %M 39804693 %R 10.2196/63004 %U https://www.jmir.org/2025/1/e63004 %U https://doi.org/10.2196/63004 %U http://www.ncbi.nlm.nih.gov/pubmed/39804693 %0 Journal Article %@ 2561-7605 %I JMIR Publications %V 7 %N %P e54655 %T Investigating Acoustic and Psycholinguistic Predictors of Cognitive Impairment in Older Adults: Modeling Study %A Badal,Varsha D %A Reinen,Jenna M %A Twamley,Elizabeth W %A Lee,Ellen E %A Fellows,Robert P %A Bilal,Erhan %A Depp,Colin A %+ IBM Research, 1101 Kitchawan Rd, Yorktown Heights, NY, United States, 1 9149453000, ebilal@us.ibm.com %K acoustic %K psycholinguistic %K speech %K speech marker %K speech markers %K cognitive impairment %K CI %K mild cognitive impairment %K MCI %K cognitive disability %K cognitive restriction %K cognitive limitation %K machine learning %K ML %K artificial intelligence %K AI %K algorithm %K algorithms %K predictive model %K predictive models %K predictive analytics %K predictive system %K practical model %K practical models %K early warning %K early detection %K NLP %K natural language processing %K Alzheimer %K dementia %K neurological decline %K neurocognition %K neurocognitive disorder %D 2024 %7 16.9.2024 %9 Original Paper %J JMIR Aging %G English %X Background: About one-third of older adults aged 65 years and older often have mild cognitive impairment or dementia. Acoustic and psycho-linguistic features derived from conversation may be of great diagnostic value because speech involves verbal memory and cognitive and neuromuscular processes. The relative decline in these processes, however, may not be linear and remains understudied. Objective: This study aims to establish associations between cognitive abilities and various attributes of speech and natural language production. To date, the majority of research has been cross-sectional, relying mostly on data from structured interactions and restricted to textual versus acoustic analyses. Methods: In a sample of 71 older (mean age 83.3, SD 7.0 years) community-dwelling adults who completed qualitative interviews and cognitive testing, we investigated the performance of both acoustic and psycholinguistic features associated with cognitive deficits contemporaneously and at a 1-2 years follow up (mean follow-up time 512.3, SD 84.5 days). Results: Combined acoustic and psycholinguistic features achieved high performance (F1-scores 0.73-0.86) and sensitivity (up to 0.90) in estimating cognitive deficits across multiple domains. Performance remained high when acoustic and psycholinguistic features were used to predict follow-up cognitive performance. The psycholinguistic features that were most successful at classifying high cognitive impairment reflected vocabulary richness, the quantity of speech produced, and the fragmentation of speech, whereas the analogous top-ranked acoustic features reflected breathing and nonverbal vocalizations such as giggles or laughter. Conclusions: These results suggest that both acoustic and psycholinguistic features extracted from qualitative interviews may be reliable markers of cognitive deficits in late life. %M 39283659 %R 10.2196/54655 %U https://aging.jmir.org/2024/1/e54655 %U https://doi.org/10.2196/54655 %U http://www.ncbi.nlm.nih.gov/pubmed/39283659 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 10 %N %P e42739 %T Patient Satisfaction With Speech Recognition in the Exam Room: Exploratory Survey %A Sippel,Jeffrey %A Podhajsky,Tim %A Lin,Chen-Tan %+ Department of Internal Medicine, University of Colorado School of Medicine, 12700 E 19th Avenue, RC2, Room 9C03, Box C272, Aurora, CO, 80045, United States, 1 303 724 4075, jeffrey.sippel@cuanschutz.edu %K speech recognition %K exam room %K primary care %K general practitioner %K satisfaction %K survey %K perception %K opinion %K speech %K voice %K eHealth %K digital health %K health technology %K communication technology %D 2023 %7 5.4.2023 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Medical speech recognition technology uses a microphone and computer software to transcribe the spoken word into text and is not typically used in outpatient clinical exam rooms. Patient perceptions regarding speech recognition in the exam room (SRIER) are therefore unknown. Objective: This study aims to characterize patient perceptions of SRIER by administering a survey to consecutive patients scheduled for acute, chronic, and wellness care in three outpatient clinic sites. Methods: We used a microphone and medical speech recognition software to complete the “assessment and plan” portion of the after-visit summary in the patient’s presence, immediately printed the after-visit summary, and then administered a 4-question exploratory survey to 65 consecutive patients in internal medicine and pulmonary medicine clinics at an academic medical center and a community family practice clinic in 2021 to characterize patient perceptions of SRIER. All questions were completed by all participants. Results: When compared to patients’ recollection of usual care (visits with no microphone and an after-visit summary without an “assessment and plan”), 86% (n=56) of respondents agreed or strongly agreed that their provider addressed their concerns better, and 73% (n=48) agreed or strongly agreed that they understood their provider’s advice better. A total of 99% (n=64) of respondents agreed or strongly agreed that a printed after-visit summary including the “assessment and plan” was helpful. By comparing the “agree” and “strongly agree” responses to the neutral responses, we found that patients felt that clinicians using SRIER addressed their concerns better (P<.001), they understood their clinician’s advice better (P<.001), and receiving a paper summary was helpful (P<.001). Patients were likely to recommend a provider using a microphone based on the Net Promoter Score of 58. Conclusions: This survey suggests patients have a very positive perception of speech recognition use in the exam room. %M 37018039 %R 10.2196/42739 %U https://humanfactors.jmir.org/2023/1/e42739 %U https://doi.org/10.2196/42739 %U http://www.ncbi.nlm.nih.gov/pubmed/37018039 %0 Journal Article %@ 2369-3762 %I JMIR Publications %V 8 %N 2 %P e34042 %T Digital Health and Learning in Speech-Language Pathology, Phoniatrics, and Otolaryngology: Survey Study for Designing a Digital Learning Toolbox App %A Lin,Yuchen %A Lemos,Martin %A Neuschaefer-Rube,Christiane %+ Clinic for Phoniatrics, Pedaudiology & Communication Disorders, University Hospital and Medical Faculty, Rheinisch-Westfaelische Technische Hochschule Aachen, Pauwelsstrasse 30, Aachen, 52074, Germany, 49 241 80 88954, yuchen.lin@rwth-aachen.de %K digital learning %K mLearning %K mHealth %K speech-language pathology %K phoniatrics %K otolaryngology %K communication disorders %K mobile phone %D 2022 %7 27.4.2022 %9 Original Paper %J JMIR Med Educ %G English %X Background: The digital age has introduced opportunities and challenges for clinical education and practice caused by infinite incoming information and novel technologies for health. In the interdisciplinary field of communication sciences and disorders (CSD), engagement with digital topics has emerged slower than in other health fields, and effective strategies for accessing, managing, and focusing on digital resources are greatly needed. Objective: We aimed to conceptualize and investigate preferences of stakeholders regarding a digital learning toolbox, an app containing a library of current resources for CSD. This cross-sectional survey study conducted in German-speaking countries investigated professional and student perceptions and preferences regarding such an app’s features, functions, content, and associated concerns. Methods: An open web-based survey was disseminated to professionals and students in the field of CSD, including speech-language pathologists (SLPs; German: Logopäd*innen), speech-language pathology students, phoniatricians, otolaryngologists, and medical students. Insights into preferences and perceptions across professions, generations, and years of experience regarding a proposed app were investigated. Results: Of the 164 participants, an overwhelming majority (n=162, 98.8%) indicated readiness to use such an app, and most participants (n=159, 96.9%) perceived the proposed app to be helpful. Participants positively rated app functions that would increase utility (eg, tutorial, quality rating function, filters based on content or topic, and digital format); however, they had varied opinions regarding an app community feature. Regarding app settings, most participants rated the option to share digital resources through social media links (144/164, 87.8%), receive and manage push notifications (130/164, 79.3%), and report technical issues (160/164, 97.6%) positively. However, significant variance was noted across professions (H3=8.006; P=.046) and generations (H3=9.309; P=.03) regarding a username-password function, with SLPs indicating greater perceived usefulness in comparison to speech-language pathology students (P=.045), as was demonstrated by Generation X versus Generation Z (P=.04). Participants perceived a range of clinical topics to be important; however, significant variance was observed across professions, between physicians and SLPs regarding the topic of diagnostics (H3=9.098; P=.03) and therapy (H3=21.236; P<.001). Concerns included technical challenges, data protection, quality of the included resources, and sustainability of the proposed app. Conclusions: This investigation demonstrated that professionals and students show initial readiness to engage in the co-design and use of an interdisciplinary digital learning toolbox app. Specifically, this app could support effective access, sharing, evaluation, and knowledge management in a digital age of rapid change. Formalized digital skills education in the field of CSD is just a part of the solution. It will be crucial to explore flexible, adaptive strategies collaboratively for managing digital resources and tools to optimize targeted selection and use of relevant, high-quality evidence in a world of bewildering data. %M 35475980 %R 10.2196/34042 %U https://mededu.jmir.org/2022/2/e34042 %U https://doi.org/10.2196/34042 %U http://www.ncbi.nlm.nih.gov/pubmed/35475980 %0 Journal Article %@ 2369-2529 %I JMIR Publications %V 9 %N 1 %P e31502 %T Patient Outcomes and Lessons Learned From Treating Patients With Severe COVID-19 at a Long-term Acute Care Hospital: Single-Center Retrospective Study %A Grevelding,Pete %A Hrdlicka,Henry Charles %A Holland,Steve %A Cullen,Lorraine %A Meyer,Amanda %A Connors,Catherine %A Cooper,Darielle %A Greco,Allison %+ Milne Institute for Healthcare Innovation, Gaylord Specialty Healthcare, 50 Gaylord Farm Road, Wallingford, CT, 06492, United States, 1 203 741 3386, pgrevelding@gaylord.org %K COVID-19 %K SARS-CoV-2 %K post–COVID-19 %K subacute COVID-19 %K postacute care %K long-term acute care hospital %K pulmonary %K speech therapy %K speech-language pathology %K rehabilitation %K physical therapy %K occupational therapy %K respiratory therapy %D 2022 %7 10.2.2022 %9 Original Paper %J JMIR Rehabil Assist Technol %G English %X Background: With the continuation of the COVID-19 pandemic, shifting active COVID-19 care from short-term acute care hospitals (STACHs) to long-term acute care hospitals (LTACHs) could decrease STACH census during critical stages of the pandemic and maximize limited resources. Objective: This study aimed to describe the characteristics, clinical management, and patient outcomes during and after the acute COVID-19 phase in an LTACH in the Northeastern United States. Methods: This was a single-center group comparative retrospective analysis of the electronic medical records of patients treated for COVID-19–related impairments from March 19, 2020, through August 14, 2020, and a reference population of medically complex patients discharged between December 1, 2019, and February 29, 2020. This study was conducted to evaluate patient outcomes in response to the holistic treatment approach of the facility. Results: Of the 127 total COVID-19 admissions, 118 patients were discharged by the data cutoff. At admission, 29.9% (38/127) of patients tested positive for SARS-CoV-2 infection. The mean age of the COVID-19 cohort was lower than that of the reference cohort (63.3, 95% CI 61.1-65.4 vs 65.5, 95% CI 63.2-67.8 years; P=.04). There were similar proportions of males and females between cohorts (P=.38); however, the proportion of non-White/non-Caucasian patients was higher in the COVID-19 cohort than in the reference cohort (odds ratio 2.79, 95% CI 1.5-5.2; P=.001). The mean length of stay in the COVID-19 cohort was similar to that in the reference cohort (25.5, 95% CI 23.2-27.9 vs 29.9, 95% CI 24.7-35.2 days; P=.84). Interestingly, a positive correlation between patient age and length of stay was observed in the COVID-19 cohort (r2=0.05; P=.02), but not in the reference cohort. Ambulation assistance scores improved in both the reference and COVID-19 cohorts from admission to discharge (P<.001). However, the mean assistance score was greater in the COVID-19 cohort than in the reference cohort at discharge (4.9, 95% CI 4.6-5.3 vs 4.1, 95% CI 3.7-4.7; P=.001). Similarly, the mean change in gait distance was greater in the COVID-19 cohort than in the reference cohort (221.1, 95% CI 163.2-279.2 vs 146.4, 95% CI 85.6-207.3 feet; P<.001). Of the 16 patients mechanically ventilated at admission, 94% (15/16) were weaned before discharge (mean 11.3 days). Of the 75 patients admitted with a restricted diet, 75% (56/75) were discharged on a regular diet. Conclusions: The majority of patients treated at the LTACH for severe COVID-19 and related complications benefited from coordinated care and rehabilitation. In comparison to the reference cohort, patients treated for COVID-19 were discharged with greater improvements in ambulation distance and assistance needs during a similar length of stay. These findings indicate that other patients with COVID-19 would benefit from care in an LTACH. %M 35023835 %R 10.2196/31502 %U https://rehab.jmir.org/2022/1/e31502 %U https://doi.org/10.2196/31502 %U http://www.ncbi.nlm.nih.gov/pubmed/35023835 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 1 %P e35080 %T Coproducing Knowledge of the Implementation of Complex Digital Health Interventions for Adults with Acquired Brain Injury and their Communication Partners: Protocol for a Mixed Methods Study %A Miao,Melissa %A Power,Emma %A Rietdijk,Rachael %A Debono,Deborah %A Brunner,Melissa %A Salomon,Alexander %A Mcculloch,Ben %A Wright,Meg Rebecca %A Welsh,Monica %A Tremblay,Bastian %A Rixon,Caleb %A Williams,Liz %A Morrow,Rosemary %A Evain,Jean-Christophe %A Togher,Leanne %+ University of Technology Sydney, 100 Broadway, Ultimo, Sydney, 2007, Australia, 61 295147348, melissa.miao@uts.edu.au %K priority setting %K public involvement %K implementation science %K internet interventions %K acquired brain injury %K delivery of health care %K caregivers %K speech-language pathology %K brain injury %K mobile phone %D 2022 %7 10.1.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: The Social Brain Toolkit, conceived and developed in partnership with stakeholders, is a novel suite of web-based communication interventions for people with brain injury and their communication partners. To support effective implementation, the developers of the Social Brain Toolkit have collaborated with people with brain injury, communication partners, clinicians, and individuals with digital health implementation experience to coproduce new implementation knowledge. In recognition of the equal value of experiential and academic knowledge, both types of knowledge are included in this study protocol, with input from stakeholder coauthors. Objective: This study aims to collaborate with stakeholders to prioritize theoretically based implementation targets for the Social Brain Toolkit, understand the nature of these priorities, and develop targeted implementation strategies to address these priorities, in order to support the Social Brain Toolkit’s implementation. Methods: Theoretically underpinned by the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework of digital health implementation, a maximum variation sample (N=35) of stakeholders coproduced knowledge of the implementation of the Social Brain Toolkit. People with brain injury (n=10), communication partners (n=11), and clinicians (n=5) participated in an initial web-based prioritization survey based on the NASSS framework. Survey completion was facilitated by plain English explanations and accessible captioned videos developed through 3 rounds of piloting. A speech-language pathologist also assisted stakeholders with brain injury to participate in the survey via video teleconference. Participants subsequently elaborated on their identified priorities via 7 web-based focus groups, in which researchers and stakeholders exchanged stakeholder perspectives and research evidence from a concurrent systematic review. Stakeholders were supported to engage in focus groups through the use of visual supports and plain English explanations. Additionally, individuals with experience in digital health implementation (n=9) responded to the prioritization survey questions via individual interview. The results will be deductively analyzed in relation to the NASSS framework in a coauthorship process with people with brain injury, communication partners, and clinicians. Results: Ethical approval was received from the University of Technology Sydney Health and Medical Research Ethics Committee (ETH20-5466) on December 15, 2020. Data were collected from April 13 to November 18, 2021. Data analysis is currently underway, with results expected for publication in mid-2022. Conclusions: In this study, researchers supported individuals with living experience of acquired brain injury, of communicating with or clinically supporting someone post injury, and of digital health implementation, to directly access and leverage the latest implementation research evidence and theory. With this support, stakeholders were able to prioritize implementation research targets, develop targeted implementation solutions, and coauthor and publish new implementation findings. The results will be used to optimize the implementation of 3 real-world, evidence-based interventions and thus improve the outcomes of people with brain injury and their communication partners. International Registered Report Identifier (IRRID): DERR1-10.2196/35080 %M 35006082 %R 10.2196/35080 %U https://www.researchprotocols.org/2022/1/e35080 %U https://doi.org/10.2196/35080 %U http://www.ncbi.nlm.nih.gov/pubmed/35006082 %0 Journal Article %@ 2369-2529 %I JMIR Publications %V 9 %N 1 %P e29249 %T Speech and Language Practitioners’ Experiences of Commercially Available Voice-Assisted Technology: Web-Based Survey Study %A Kulkarni,Pranav %A Duffy,Orla %A Synnott,Jonathan %A Kernohan,W George %A McNaney,Roisin %+ Action Lab, Department of Human Centred Computing, Monash University, 7 Innovation Walk, Clayton, 3168, Australia, 61 0444511615, pranav.kulkarni1@monash.edu %K speech and language therapy %K voice-assisted technology %K professional practice %K rehabilitation %K speech therapy %K health technology %K mobile phone %D 2022 %7 5.1.2022 %9 Original Paper %J JMIR Rehabil Assist Technol %G English %X Background: Speech and language therapy involves the identification, assessment, and treatment of children and adults who have difficulties with communication, eating, drinking, and swallowing. Globally, pressing needs outstrip the availability of qualified practitioners who, of necessity, focus on individuals with advanced needs. The potential of voice-assisted technology (VAT) to assist people with speech impairments is an emerging area of research but empirical work exploring its professional adoption is limited. Objective: This study aims to explore the professional experiences of speech and language therapists (SaLTs) using VAT with their clients to identify the potential applications and barriers to VAT adoption and thereby inform future directions of research. Methods: A 23-question survey was distributed to the SaLTs from the United Kingdom using a web-based platform, eliciting both checkbox and free-text responses, to questions on perceptions and any use experiences of VAT. Data were analyzed descriptively with content analysis of free text, providing context to their specific experiences of using VAT in practice, including barriers and opportunities for future use. Results: A total of 230 UK-based professionals fully completed the survey; most were technologically competent and were aware of commercial VATs (such as Alexa and Google Assistant). However, only 49 (21.3%) SaLTs had used VAT with their clients and described 57 use cases. They reported using VAT with 10 different client groups, such as people with dysarthria and users of augmentative and alternative communication technologies. Of these, almost half (28/57, 49%) used the technology to assist their clients with day-to-day tasks, such as web browsing, setting up reminders, sending messages, and playing music. Many respondents (21/57, 37%) also reported using the technology to improve client speech, to facilitate speech practice at home, and to enhance articulation and volume. Most reported a positive impact of VAT use, stating improved independence (22/57, 39%), accessibility (6/57, 10%), and confidence (5/57, 8%). Some respondents reported increased client communication (5/57, 9%) and sociability (3/57, 5%). Reasons given for not using VAT in practice included lack of opportunity (131/181, 72.4%) and training (63/181, 34.8%). Most respondents (154/181, 85.1%) indicated that they would like to try VAT in the future, stating that it could have a positive impact on their clients’ speech, independence, and confidence. Conclusions: VAT is used by some UK-based SaLTs to enable communication tasks at home with their clients. However, its wider adoption may be limited by a lack of professional opportunity. Looking forward, additional benefits are promised, as the data show a level of engagement, empowerment, and the possibility of achieving therapeutic outcomes in communication impairment. The disparate responses suggest that this area is ripe for the development of evidence-based clinical practice, starting with a clear definition, outcome measurement, and professional standardization. %M 34989694 %R 10.2196/29249 %U https://rehab.jmir.org/2022/1/e29249 %U https://doi.org/10.2196/29249 %U http://www.ncbi.nlm.nih.gov/pubmed/34989694 %0 Journal Article %@ 2369-3762 %I JMIR Publications %V 7 %N 4 %P e30873 %T Digital Health and Digital Learning Experiences Across Speech-Language Pathology, Phoniatrics, and Otolaryngology: Interdisciplinary Survey Study %A Lin,Yuchen %A Lemos,Martin %A Neuschaefer-Rube,Christiane %+ Clinic of Phoniatrics, Pedaudiology & Communication Disorders, Medical Faculty, University Hospital Rheinisch-Westfaelische Technische Hochschule Aachen, Pauwelsstraße 30, Aachen, 52074, Germany, 49 0241 80 88954, yuchen.lin@rwth-aachen.de %K digital learning %K e-learning %K speech-language pathology %K phoniatrics %K otolaryngology %K communication disorders %K mobile phone %D 2021 %7 5.11.2021 %9 Original Paper %J JMIR Med Educ %G English %X Background: Advances in digital health and digital learning are transforming the lives of patients, health care providers, and health professional students. In the interdisciplinary field of communication sciences and disorders (CSD), digital uptake and incorporation of digital topics and technologies into clinical training programs has lagged behind other medical fields. There is a need to understand professional and student experiences, opinions, and needs regarding digital health and learning topics so that effective strategies for implementation can be optimized. Objective: This cross-sectional survey study aims to interdisciplinarily investigate professional and student knowledge, use, attitudes, and preferences toward digital health and learning in the German-speaking population. Methods: An open-ended, web-based survey was developed and conducted with professionals and students in CSD including phoniatricians and otolaryngologists, speech-language pathologists (German: Logopäd*innen), medical students, and speech-language pathology students. Differences in knowledge, use, attitudes, and preferences across profession, generation, and years of experience were analyzed. Results: A total of 170 participants completed the survey. Respondents demonstrated greater familiarity with digital learning as opposed to eHealth concepts. Significant differences were noted across profession (P<.001), generation (P=.001), and years of experience (P<.001), which demonstrated that students and younger participants were less familiar with digital health terminology. Professional (P<.001) and generational differences were also found (P=.04) in knowledge of digital therapy tools, though no significant differences were found for digital learning tools. Participants primarily used computers, tablets, and mobile phones; non–eHealth-specific tools (eg, word processing and videoconferencing applications); and digital formats such as videos, web courses, and apps. Many indicated a desire for more interactive platforms, such as virtual reality. Significant differences were found across generations for positive views toward digitalization (P<.001) and across profession for feelings of preparedness (P=.04). Interestingly, across profession (P=.03), generation (P=.006), and years of experience (P=.01), students and younger participants demonstrated greater support for medical certification. Commonly reported areas of concern included technical difficulties, quality and validity of digital materials, data privacy, and social presence. Respondents tended to prefer blended learning, a limited to moderate level of interactivity, and time and space–flexible learning environments (63/170, 37.1%), with a notable proportion still preferring traditional time and space–dependent learning (49/170, 28.8%). Conclusions: This comprehensive investigation into the current state of CSD student and professional opinions and experiences has shown that incorporation of digital topics and skills into academic and professional development curricula will be crucial for ensuring that the field is prepared for the ever-digitalizing health care environment. Deeper empirical investigation into efficacy and acceptance of digital learning and practice strategies and systematic training and practical organizational supports must be planned to ensure adaptive education and practice. %M 34738911 %R 10.2196/30873 %U https://mededu.jmir.org/2021/4/e30873 %U https://doi.org/10.2196/30873 %U http://www.ncbi.nlm.nih.gov/pubmed/34738911 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 10 %P e26305 %T Detecting Parkinson Disease Using a Web-Based Speech Task: Observational Study %A Rahman,Wasifur %A Lee,Sangwu %A Islam,Md Saiful %A Antony,Victor Nikhil %A Ratnu,Harshil %A Ali,Mohammad Rafayet %A Mamun,Abdullah Al %A Wagner,Ellen %A Jensen-Roberts,Stella %A Waddell,Emma %A Myers,Taylor %A Pawlik,Meghan %A Soto,Julia %A Coffey,Madeleine %A Sarkar,Aayush %A Schneider,Ruth %A Tarolli,Christopher %A Lizarraga,Karlo %A Adams,Jamie %A Little,Max A %A Dorsey,E Ray %A Hoque,Ehsan %+ Department of Computer Science, University of Rochester, 250 Hutchinson Rd, Rochester, NY, 14620, United States, 1 5857487677, echowdh2@ur.rochester.edu %K Parkinson’s disease %K speech analysis %K improving access and equity in health care %K mobile phone %D 2021 %7 19.10.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Access to neurological care for Parkinson disease (PD) is a rare privilege for millions of people worldwide, especially in resource-limited countries. In 2013, there were just 1200 neurologists in India for a population of 1.3 billion people; in Africa, the average population per neurologist exceeds 3.3 million people. In contrast, 60,000 people receive a diagnosis of PD every year in the United States alone, and similar patterns of rising PD cases—fueled mostly by environmental pollution and an aging population—can be seen worldwide. The current projection of more than 12 million patients with PD worldwide by 2040 is only part of the picture given that more than 20% of patients with PD remain undiagnosed. Timely diagnosis and frequent assessment are key to ensure timely and appropriate medical intervention, thus improving the quality of life of patients with PD. Objective: In this paper, we propose a web-based framework that can help anyone anywhere around the world record a short speech task and analyze the recorded data to screen for PD. Methods: We collected data from 726 unique participants (PD: 262/726, 36.1% were women; non-PD: 464/726, 63.9% were women; average age 61 years) from all over the United States and beyond. A small portion of the data (approximately 54/726, 7.4%) was collected in a laboratory setting to compare the performance of the models trained with noisy home environment data against high-quality laboratory-environment data. The participants were instructed to utter a popular pangram containing all the letters in the English alphabet, “the quick brown fox jumps over the lazy dog.” We extracted both standard acoustic features (mel-frequency cepstral coefficients and jitter and shimmer variants) and deep learning–based embedding features from the speech data. Using these features, we trained several machine learning algorithms. We also applied model interpretation techniques such as Shapley additive explanations to ascertain the importance of each feature in determining the model’s output. Results: We achieved an area under the curve of 0.753 for determining the presence of self-reported PD by modeling the standard acoustic features through the XGBoost—a gradient-boosted decision tree model. Further analysis revealed that the widely used mel-frequency cepstral coefficient features and a subset of previously validated dysphonia features designed for detecting PD from a verbal phonation task (pronouncing “ahh”) influence the model’s decision the most. Conclusions: Our model performed equally well on data collected in a controlled laboratory environment and in the wild across different gender and age groups. Using this tool, we can collect data from almost anyone anywhere with an audio-enabled device and help the participants screen for PD remotely, contributing to equity and access in neurological care. %M 34665148 %R 10.2196/26305 %U https://www.jmir.org/2021/10/e26305 %U https://doi.org/10.2196/26305 %U http://www.ncbi.nlm.nih.gov/pubmed/34665148 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 8 %P e30500 %T Muscular Assessment in Patients With Severe Obstructive Sleep Apnea Syndrome: Protocol for a Case-Control Study %A Borrmann,Paz Francisca %A O'Connor-Reina,Carlos %A Ignacio,Jose M %A Rodriguez Ruiz,Elisa %A Rodriguez Alcala,Laura %A Dzembrovsky,Florencia %A Baptista,Peter %A Garcia Iriarte,Maria T %A Casado Alba,Carlos %A Plaza,Guillermo %+ Otorhinolaryngology Department, Hospital Quironsalud Marbella, Avda Severo Ochoa 22, Marbella (Malaga), Spain, 34 952774200, coconnor@us.es %K myofunctional therapy %K sleep apnea %K sleep disordered breathing %K speech therapy %K phenotype %K sleep %K therapy %K protocol %K muscle %K assessment %K case study %K exercise %K airway %K respiratory %D 2021 %7 6.8.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Myofunctional therapy is currently a reasonable therapeutic option to treat obstructive sleep apnea-hypopnea syndrome (OSAHS). This therapy is based on performing regular exercises of the upper airway muscles to increase their tone and prevent their collapse. Over the past decade, there has been an increasing number of publications in this area; however, to our knowledge, there are no studies focused on patients who can most benefit from this therapy. Objective: This protocol describes a case-control clinical trial aimed at determining the muscular features of patients recently diagnosed with severe OSAHS compared with those of healthy controls. Methods: Patients meeting set criteria will be sequentially enrolled up to a sample size of 40. Twenty patients who meet the inclusion criteria for controls will also be evaluated. Patients will be examined by a qualified phonoaudiologist who will take biometric measurements and administer the Expanded Protocol of Orofacial Myofunctional Evaluation with Scores (OMES), Friedman Staging System, Epworth Sleepiness Scale, and Pittsburgh Sleep Quality Index questionnaires. Measures of upper airway muscle tone will also be performed using the Iowa Oral Performance Instrument and tongue digital spoon devices. Evaluation will be recorded and reevaluated by a second specialist to determine concordance between observers. Results: A total of 60 patients will be enrolled. Both the group with severe OSAHS (40 patients) and the control group (20 subjects) will be assessed for differences between upper airway muscle tone and OMES questionnaire responses. Conclusions: This study will help to determine muscle patterns in patients with severe OSAHS and can be used to fill the gap currently present in the assessment of patients suitable to be treated with myofunctional therapy. Trial Registration: ISRCTN Registry ISRCTN12596010; https://www.isrctn.com/ISRCTN12596010 International Registered Report Identifier (IRRID): PRR1-10.2196/30500 %M 34115605 %R 10.2196/30500 %U https://www.researchprotocols.org/2021/8/e30500 %U https://doi.org/10.2196/30500 %U http://www.ncbi.nlm.nih.gov/pubmed/34115605 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 7 %P e30621 %T Implementation and Effects of an Information Technology–Based Intervention to Support Speech and Language Therapy Among Stroke Patients With Aphasia: Protocol for a Virtual Randomized Controlled Trial %A Kim,Esther S %A Laird,Laura %A Wilson,Carlee %A Bieg,Till %A Mildner,Philip %A Möller,Sebastian %A Schatz,Raimund %A Schwarz,Stephanie %A Spang,Robert %A Voigt-Antons,Jan-Niklas %A Rochon,Elizabeth %+ Department of Communication Sciences and Disorders, Faculty of Rehabilitation Medicine, University of Alberta, 2-70 Corbett Hall, Edmonton, AB, T6G 2G4, Canada, 1 780 248 1542, esther.kim@ualberta.ca %K aphasia %K rehabilitation %K speech-language pathology %K app-based therapy %K user-centered design %K mHealth %K adaptive software %D 2021 %7 2.7.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Mobile app–based therapies are increasingly being employed by speech-language pathologists in the rehabilitation of people with aphasia as adjuncts or substitutes for traditional in-person therapy approaches. These apps can increase the intensity of treatment and have resulted in meaningful outcomes across several domains. Objective: VoiceAdapt is a mobile therapy app designed with user and stakeholder feedback within a user-centered design framework. VoiceAdapt uses two evidence-based lexical retrieval treatments to help people with aphasia in improving their naming abilities through interactions with the app. The purpose of the randomized controlled trial (RCT) proposed here is to examine the feasibility and clinical efficacy of training with VoiceAdapt on the language and communication outcomes of people with aphasia. Methods: A multicenter RCT is being conducted at two locations within Canada. A total of 80 people with aphasia will be recruited to participate in a two-arm, waitlist-controlled, crossover group RCT. After baseline assessment, participants will be randomized into an intervention group or a waitlist control group. The intervention group participants will engage in 5 weeks of training with the app, followed by posttreatment and follow-up assessments after an additional 5 weeks. Those in the waitlist control group will have no training for 5 weeks; this is followed by pretreatment assessment, training for 5 weeks, and posttreatment assessment. All trial procedures are being conducted remotely given the COVID-19 pandemic. Results: Recruitment of participants started in September 2020, and the study is expected to be completed by March 2022. Publication of results is expected within 6 months of study completion. Conclusions: The results of the RCT will provide information on evidence-based practice using technology-based solutions to treat aphasia. If positive results are obtained from this RCT, the VoiceAdapt app can be recommended as an efficacious means of improving lexical retrieval and communicative functioning in people with aphasia in an easily accessible and a cost-effective manner. Moreover, the implementation of this RCT through remote assessment and delivery can provide information to therapists on telerehabilitation practices and monitoring of app-based home therapy programs. Trial Registration: ClinicalTrials.gov NCT04108364; https://clinicaltrials.gov/ct2/show/NCT04108364 International Registered Report Identifier (IRRID): DERR1-10.2196/30621 %M 34255727 %R 10.2196/30621 %U https://www.researchprotocols.org/2021/7/e30621 %U https://doi.org/10.2196/30621 %U http://www.ncbi.nlm.nih.gov/pubmed/34255727 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 10 %P e18858 %T Mobile Apps for Speech-Language Therapy in Adults With Communication Disorders: Review of Content and Quality %A Vaezipour,Atiyeh %A Campbell,Jessica %A Theodoros,Deborah %A Russell,Trevor %+ RECOVER Injury Research Centre, Faculty of Health and Behavioural Sciences, The University of Queensland, 288 Herston Road, Brisbane, 4006, Australia, 61 7 3365 5560, a.vaezipour@uq.edu.au %K communication disorders %K speech therapy %K language therapy %K ergonomics %K rehabilitation %K mobile health %K mHealth %D 2020 %7 29.10.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X 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. %M 33118953 %R 10.2196/18858 %U http://mhealth.jmir.org/2020/10/e18858/ %U https://doi.org/10.2196/18858 %U http://www.ncbi.nlm.nih.gov/pubmed/33118953