Sarah Lennard, Samuel J. Tromans, Robert Taub, Sarah Mitchell, Rohit Shankar
{"title":"SpeechMatch—A novel digital approach to supporting communication for neurodiverse groups","authors":"Sarah Lennard, Samuel J. Tromans, Robert Taub, Sarah Mitchell, Rohit Shankar","doi":"10.1049/htl2.12090","DOIUrl":null,"url":null,"abstract":"<p>Communication can be a challenge for a significant minority of the population. Those with intellectual disability, autism, or Stroke survivors can encounter significant problems and stigma in their communication abilities leading to worse health and social outcomes. SpeechMatch (https://www.speechmatch.com/) is a digital App which is a pragmatic mobile language training platform that teaches individuals to “match” critical components of conversation and looks to provides subjects with immediate visual feedback to shape identification and expression of emotion in speech. While it has been used in autistic people there has been no systematic exploration of its strengths and weaknesses. Further, it's potential to afford improvements in communication to other vulnerable groups such as intellectual disability or Stroke survivors has not been explored. This study looked to understand acceptability from people with intellectual disability and/or autism and those recovering from a stroke on the utility and scope of SpeechMatch using co-production techniques using experts by experience and a mixed methods evaluation. Results across four domains suggest high acceptability levels but highlighting needs for platform capabilities improvement and better user engagement. The study outlines a vital and essential aspect for improving SpeechMatch. It gives a template for evidenced based quality improvement of similar devices.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"11 6","pages":"447-451"},"PeriodicalIF":2.8000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11665792/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Healthcare Technology Letters","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/htl2.12090","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Communication can be a challenge for a significant minority of the population. Those with intellectual disability, autism, or Stroke survivors can encounter significant problems and stigma in their communication abilities leading to worse health and social outcomes. SpeechMatch (https://www.speechmatch.com/) is a digital App which is a pragmatic mobile language training platform that teaches individuals to “match” critical components of conversation and looks to provides subjects with immediate visual feedback to shape identification and expression of emotion in speech. While it has been used in autistic people there has been no systematic exploration of its strengths and weaknesses. Further, it's potential to afford improvements in communication to other vulnerable groups such as intellectual disability or Stroke survivors has not been explored. This study looked to understand acceptability from people with intellectual disability and/or autism and those recovering from a stroke on the utility and scope of SpeechMatch using co-production techniques using experts by experience and a mixed methods evaluation. Results across four domains suggest high acceptability levels but highlighting needs for platform capabilities improvement and better user engagement. The study outlines a vital and essential aspect for improving SpeechMatch. It gives a template for evidenced based quality improvement of similar devices.
期刊介绍:
Healthcare Technology Letters aims to bring together an audience of biomedical and electrical engineers, physical and computer scientists, and mathematicians to enable the exchange of the latest ideas and advances through rapid online publication of original healthcare technology research. Major themes of the journal include (but are not limited to): Major technological/methodological areas: Biomedical signal processing Biomedical imaging and image processing Bioinstrumentation (sensors, wearable technologies, etc) Biomedical informatics Major application areas: Cardiovascular and respiratory systems engineering Neural engineering, neuromuscular systems Rehabilitation engineering Bio-robotics, surgical planning and biomechanics Therapeutic and diagnostic systems, devices and technologies Clinical engineering Healthcare information systems, telemedicine, mHealth.