Mobile apps for speech-language therapy in adults with communication disorders: review of content and quality
Open accessPublished version of a preprint
Abstract
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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
User-centered design (UCD) can significantly enhance user engagement and intervention outcomes in technology-based health apps.
“consistent with findings demonstrating that UCD can significantly enhance user engagement and intervention outcomes in technology-based health apps [2755].”
From Outcomes of an App-Based Intervention to Target Naming Among Individuals With Poststroke Aphasia: Virtual Randomized Controlled Trial (2025) · cites this paper as [27]
The Discussion (Principal Findings; page not supplied) suggests that a lack of human-centered approaches might explain low engagement scores. The Conclusions (page not supplied) recommend patient-led co-design and say such apps could potentially improve therapy effectiveness. The review does not demonstrate a significant improvement in engagement or intervention outcomes, and its focus is speech-language therapy apps rather than health apps generally. (LLM, conf=0.86)
Experimental — accuracy not yet measuredA review by Vaezipour et al revealed a general lack of engaging and interactive elements in mobile apps for speech therapy in adults with communication disorders.
“A similar review identifying and evaluating mobile apps for speech therapy in adults with communication disorders (not limited to aphasia) revealed that there was a general lack of engaging and interactive elements in the apps [27].”
From Outcomes of an App-Based Intervention to Target Naming Among Individuals With Poststroke Aphasia: Virtual Randomized Controlled Trial (2025) · cites this paper as [27]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Cicchetti, D. V. (1994) · Psychological Assessment · doi:10.1037/1040-3590.6.4.284 · Cited by 9,349 · cited 1× · see citing works
“The overall MARS score demonstrated a good [33] level of interrater reliability (two-way mixed intraclass correlation coefficient (ICC) 0.”
MethodEstimating the global incidence of traumatic brain injury
Dewan, M. C., Rattani, A., Gupta, S., Baticulon, R. E., Hung, Y., Punchak, M. A., Agrawal, A., Adeleye, A. O., Shrime, M. G., Rubiano, A. M., et al. (2018) · Journal of neurosurgery · doi:10.3171/2017.10.jns17352 · Cited by 3,354 · see citing works
Norman, D. A., & DRAPER, S. W. (1986) · CRC Press eBooks · doi:10.1201/b15703 · Cited by 3,154 · see citing works
Gamification. using game-design elements in non-gaming contexts
Deterding, S., Sicart, M., Nacke, L., O'Hara, K., & Dixon, D. (2011) · CHI '11 Extended Abstracts on Human Factors in Computing Systems · doi:10.1145/1979742.1979575 · Cited by 2,413 · see citing works
Mobile app rating scale: a new tool for assessing the quality of health mobile apps
Stoyanov, S. R., Hides, L., Kavanagh, D. J., Zelenko, O., Tjondronegoro, D., & Mani, M. (2015) · JMIR mHealth and uHealth · doi:10.2196/mhealth.3422 · Cited by 2,233 · see citing works
Preventing stroke: saving lives around the world.
Strong, K. L., Mathers, C., & Bonita, R. (2007) · Lancet Neurology · doi:10.1016/s1474-4422(07)70031-5 · Cited by 1,553 · see citing works
Gamification for health and wellbeing: A systematic review of the literature
Johnson, D., Deterding, S., Kuhn, K.-A., Staneva, A., Stoyanov, S., & Hides, L. (2016) · Internet Interventions · doi:10.1016/j.invent.2016.10.002 · Cited by 1,237 · see citing works
Speech and language therapy for aphasia following stroke
Brady, M. C., Kelly, H., Godwin, J., Enderby, P., & Campbell, P. (2016) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd000425.pub4 · Cited by 1,159 · cited 1× · see citing works
“Evidence supports the delivery of rehabilitation by speech-language pathologists (SLPs) for adults after sustaining ABI to treat language [11], motor speech [12], and social communication skill [13] impairments.”
BackgroundMethods to support human-centred design
MAGUIRE, M. (2001) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.2001.0503 · Cited by 1,057 · see citing works
A systematic review of gamification in e-Health
Sardi, L., Idri, A., & Fernández‐Alemán, J. L. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.05.011 · Cited by 1,041 · see citing works
The development and evaluation of a survey to measure user engagement
O'Brien, H. L., & Toms, E. G. (2009) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21229 · Cited by 794 · see citing works
Ponsford, J. L., Downing, M. G., Olver, J., Ponsford, M., Acher, R., Carty, M., & Spitz, G. (2014) · Journal of Neurotrauma · doi:10.1089/neu.2013.2997 · Cited by 621 · see citing works
Human factors of complex sociotechnical systems
Carayon, P. (2006) · Applied Ergonomics · doi:10.1016/j.apergo.2006.04.011 · Cited by 617 · see citing works
A Systematic Review of Patient Acceptance of Consumer Health Information Technology
Or, C. K. L., & Karsh, B.-T. (2009) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2888 · Cited by 586 · see citing works
Poststroke Aphasia Frequency, Recovery, and Outcomes: A Systematic Review and Meta-Analysis
Flowers, H. L., Skoretz, S. A., Silver, F. L., Rochon, E. A., Fang, J., Flamand‐Roze, C., & Martino, R. (2016) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2016.03.006 · Cited by 439 · see citing works
Prescribable mHealth apps identified from an overview of systematic reviews
Byambasuren, O., Sanders, S., Beller, E., & Glasziou, P. (2018) · npj Digital Medicine · doi:10.1038/s41746-018-0021-9 · Cited by 291 · see citing works
mHealth and Mobile Medical Apps: A Framework to Assess Risk and Promote Safer Use
Lewis, T., & Wyatt, J. C. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3133 · Cited by 281 · see citing works
Speech and language therapy for aphasia following stroke
Brady, M., Kelly, H., Godwin, J., & Enderby, P. (2012) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd000425.pub3 · Cited by 269 · see citing works
Investigating the Effects of Communication Problems on Caregiver Burden
Savundranayagam, M. Y., Hummert, M. L., & Montgomery, R. J. V. (2005) · The Journals of Gerontology Series B · doi:10.1093/geronb/60.1.s48 · Cited by 243 · see citing works
MacDonald, S. (2017) · Brain Injury · doi:10.1080/02699052.2017.1379613 · Cited by 214 · see citing works
Designing gamification: creating gameful and playful experiences
Deterding, S., Björk, S. L., Nacke, L. E., Dixon, D., & Lawley, E. (2013) · CHI '13 Extended Abstracts on Human Factors in Computing Systems · doi:10.1145/2468356.2479662 · Cited by 192 · see citing works
Sust, P. P., Solans, Ó., Fajardo, J. C., Medina, M., Ródenas, P., Gabaldà, J., García‐Eroles, L., Comella, A., Velasco, C., Ribes, J. S., et al. (2020) · JMIR Public Health and Surveillance · doi:10.2196/19106 · Cited by 186 · see citing works
Semantic Feature Analysis Treatment for Aphasic Word Retrieval Impairments: What’s in a Name?
Boyle, M. (2010) · Topics in Stroke Rehabilitation · doi:10.1310/tsr1706-411 · Cited by 171 · see citing works
Knitza, J., Taşçılar, K., Meßner, E.-M., Meyer, M., Vossen, D., Pulla, A., Bösch, P., Kittler, J., Kleyer, A., Sewerin, P., et al. (2019) · JMIR mhealth and uhealth · doi:10.2196/14991 · Cited by 170 · see citing works
Systematic Review of Mobile Health Applications in Rehabilitation
Nussbaum, R., Kelly, C. J., Quinby, E., Mac, A., Parmanto, B., & Dicianno, B. E. (2018) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2018.07.439 · Cited by 163 · see citing works
Treating naming impairments in aphasia: Findings from a phonological components analysis treatment
Leonard, C., Rochon, E., & Laird, L. (2008) · Aphasiology · doi:10.1080/02687030701831474 · Cited by 150 · see citing works
Ballard, K. J., Wambaugh, J. L., Duffy, J. R., Layfield, C., Maas, E., Mauszycki, S. C., & McNeil, M. R. (2015) · American Journal of Speech-Language Pathology · doi:10.1044/2015_ajslp-14-0118 · Cited by 146 · see citing works
A meta-analysis of word-finding treatments for aphasia
Wisenburn, B., & Mahoney, K. (2009) · Aphasiology · doi:10.1080/02687030902732745 · Cited by 145 · see citing works
Patients' experiences of disruptions associated with post‐stroke dysarthria
Dickson, S., Barbour, R. S., Brady, M., Clark, A. M., & Paton, G. (2008) · International Journal of Language & Communication Disorders · doi:10.1080/13682820701862228 · Cited by 142 · see citing works
Des Roches, C. A., Balachandran, I., Ascenso, E. M., Tripodis, Y., & Kiran, S. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.01015 · Cited by 130 · see citing works
Sprachtherapie für Sprachstörungen nach einem Schlaganfall
(2017) · Sprache · Stimme · Gehör · doi:10.1055/s-0043-106547 · Cited by 128 · see citing works
Struchen, M. A., Pappadis, M. R., Sander, A. M., Burrows, C. S., & Myszka, K. A. (2011) · Journal of Head Trauma Rehabilitation · doi:10.1097/htr.0b013e3182048f7c · Cited by 119 · see citing works
Improved language in chronic aphasia after self-delivered iPad speech therapy
Stark, B. C., & Warburton, E. A. (2018) · Neuropsychological Rehabilitation · doi:10.1080/09602011.2016.1146150 · Cited by 110 · see citing works
A Telerehabilitation Approach for Chronic Aphasia Following Stroke
Choi, Y., Park, H. K., & Paik, N. (2015) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2015.0138 · Cited by 91 · see citing works
Furlong, L., Morris, M., Serry, T., & Erickson, S. (2018) · PLOS ONE · doi:10.1371/journal.pone.0201513 · Cited by 87 · see citing works
Togher, L., Power, E., Tate, R. L., McDonald, S., & Rietdijk, R. (2010) · Aphasiology · doi:10.1080/02687030903422478 · Cited by 83 · see citing works
Finch, E., Copley, A., Cornwell, P., & Kelly, C. M. (2015) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2015.11.005 · Cited by 75 · see citing works
Worrall, L. E., Ryan, B., Hudson, K., Kneebone, I., Simmons‐Mackie, N. N., Khan, A., Hoffmann, T., Power, E., Togher, L., & Rose, M. L. (2016) · Trials · doi:10.1186/s13063-016-1257-9 · Cited by 68 · see citing works
Speech-driven mobile games for speech therapy: User experiences and feasibility
Ahmed, B., Monroe, P., Hair, A., Tan, C. T., Gutierrez-Osuna, R., & Ballard, K. J. (2018) · International Journal of Speech-Language Pathology · doi:10.1080/17549507.2018.1513562 · Cited by 65 · see citing works
Engaging people experiencing communication disability in stroke rehabilitation: a qualitative study
Bright, F. A. S., Kayes, N. M., McPherson, K. M., & Worrall, L. E. (2018) · International Journal of Language & Communication Disorders · doi:10.1111/1460-6984.12409 · Cited by 52 · see citing works
Vaezipour, A., Whelan, B., Wall, K. J., & Theodoros, D. (2019) · Journal of Head Trauma Rehabilitation · doi:10.1097/htr.0000000000000462 · Cited by 47 · see citing works
Self-citationA Telescreening Tool to Detect Aphasia in Patients with Stroke
Choi, Y., Park, H. K., Ahn, K.-H., Son, Y.-J., & Paik, N. (2015) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2014.0207 · Cited by 46 · see citing works
Hair, A., Monroe, P., Ahmed, B., Ballard, K. J., & Gutiérrez‐Osuna, R. (2018) · ACM International Conference on Interaction Design and Children (IDC) · doi:10.1145/3202185.3202733 · Cited by 45 · see citing works
Munsell, M., Oliveira, E. D., Saxena, S., Godlove, J. M., & Kiran, S. (2019) · Journal of Medical Internet Research · doi:10.2196/16286 · Cited by 40 · see citing works
Furlong, L., Morris, M. E., Erickson, S., & Serry, T. A. (2016) · JMIR Research Protocols · doi:10.2196/resprot.6505 · Cited by 31 · see citing works
Human-Centered Design in Practice
Putnam, C., Reiner, A., Ryou, E., Caputo, M., Cheng, J., Allen, M., & Singamaneni, R. (2016) · Journal of Technical Writing and Communication · doi:10.1177/0047281616653491 · Cited by 19 · see citing works
A voice-controlled serious game for the sustained vowel exercise
Lopes, M., Magalhães, J., & Cavaco, S. (2016) · International Conference on Advances in Computer Entertainment Technology (ACE) · doi:10.1145/3001773.3001807 · Cited by 19 · see citing works
Kiran, S. (2016) · Seminars in Speech and Language · doi:10.1055/s-0036-1571358 · Cited by 17 · see citing works
Be Smarter Than Your Phone: A Framework for Using Apps in Clinical Practice
Muñoz, M. L., Hoffman, L. M., & Brimo, D. (2013) · Contemporary Issues in Communication Science and Disorders · doi:10.1044/cicsd_40_f_138 · Cited by 10 · see citing works
Rehabilitation Tool: A Pilot Study On A New Neuropsychological Interactive Training System
Cardullo, S., Gamberini, L., Milan, S., & Mapelli, D. (2015) · Studies in health technology and informatics · doi:10.3233/978-1-61499-595-1-168 · Cited by 8 · see citing works
Kat, L., Schipper, K., Knibbe, J. J., et al. (2010) · BMJ · doi:10.1136/bmj.c808 · Cited by 5 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Du, Y., Choe, S., Vega, J., Liu, Y., & Trujillo, A. (2022) · JMIR Pediatrics and Parenting · doi:10.2196/28661 · Cited by 14 · see citing works
Ericson, C., Latysheva, A., Poirier, S.-È., & Fossard, M. (2025) · Brain Sciences · doi:10.3390/brainsci15020122 · Cited by 7 · see citing works
“There are now numerous software offering therapy activities for PWA [23,24], mostly focusing on word retrieval or a combination of language skills [23,25].”
Kim, E. S., Laird, L., Wilson, C., Stewart, S., Mildner, P., Möller, S., Schatz, R., Spang, R. P., Voigt-Antons, J.-N., & Rochon, E. (2025) · JMIR mHealth and uHealth · doi:10.2196/67711 · Cited by 2 · see citing works
“The app included several features recommended in Vaezipour et al’s [27] review of mobile apps.”
Influential
- Authors
- Vaezipour, A., Campbell, J., Theodoros, D., & Russell, T.
- Affiliations
- The University of Queensland (AU)
- Corresponding author
- Vaezipour, Atiyeh
- Venue
- JMIR mhealth and uhealth
- Publisher
- JMIR Publications Inc.
- Published
- 2020-10-29
- Volume
- 8
- Issue
- 10
- Pages
- e18858
- ISSN
- 2291-5222 (ISSN-L)
- PMC
- PMC7661246
- OpenAlex
- W3095259585
- Cited by
- 65
- References
- 52
- Citations by year
- 2026: 7 · 2025: 16 · 2024: 15 · 2023: 8 · 2022: 9 · 2021: 10
- FWCI
- 1.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR mhealth and uhealth (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Health Professions › Occupational Therapy › Assistive Technology in Communication and Mobility
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Keywords
- mobile application, speech therapy, communication disorders, acquired brain injury, app quality assessment, Mobile App Rating Scale, digital health interventions, speech therapy apps, cognitive communication, voice disorders, oromotor function, app store search, adults with brain injury, app security and privacy
- MeSH terms
- Adult, Communication Disorders, Humans, Language Therapy, Quality of Life, Speech, Mobile Applications
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
