@Article{info:doi/10.2196/63166,
author="Lee, Sol-Hee
and Kim, Jiae
and Kim, Han-Joon",
title="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",
journal="J Med Internet Res",
year="2025",
month="Feb",
day="13",
volume="27",
pages="e63166",
keywords="Parkinson disease; speech therapy; mHealth; home-based training; self-delivered; digital health care; app; feasibility; voice therapy; mobile phone; satisfaction; effectiveness; smartphone; apps; single-arm study; mobility; mobile health; acoustic analysis; self-training",
abstract="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. ",
issn="1438-8871",
doi="10.2196/63166",
url="https://www.jmir.org/2025/1/e63166",
url="https://doi.org/10.2196/63166"
}
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