Love Amanda, Cornwell Petrea, Hewetson Ronelle, Binnewies Sebastian
School of Health Sciences and Social Work, Speech Pathology, Griffith University, Gold Coast, Australia.
School of Information and Communication Technology, Griffith University, Gold Coast, Australia.
Mhealth. 2025 Jan 17;11:2. doi: 10.21037/mhealth-24-54. eCollection 2025.
More than 50% of individuals admitted to hospital with a right hemisphere (RH) stroke may present with a cognitive communication disorder (CCD). However, there is a critical absence of evidence-based screening tools available for speech-language pathologists (SLPs) to identify this disorder. We developed and beta tested a new mobile health (mHealth) application to screen for CCD after an RH stroke, the Right Hemisphere Cognitive Communication Screener (RECOGNISE).
Participants with RH stroke and SLPs evaluated RECOGNISE, accessible via an Android operating system. Both participant groups completed user acceptance surveys.
Six participants with RH stroke and three SLPs beta tested RECOGNISE. All participants with RH stroke reported that RECOGNISE was easy and enjoyable to use. Qualitative content analysis revealed three main themes: content of test items, user interface and accessibility. SLPs identified several positive features of RECOGNISE including its evidence-based grounding, capabilities unique to the app and ability to engage patients. User interface issues included challenges with app navigation, layout of images, and scoring inconsistencies.
RECOGNISE is the first mHealth application developed to identify CCD after RH stroke. Findings suggest that with some user interface improvements, RECOGNISE has the potential to offer SLPs with an evidence-based tool to screen for CCD after RH stroke. Future research will establish the reliability and validity of RECOGNISE.
因右半球（RH）中风入院的患者中，超过50%可能会出现认知交流障碍（CCD）。然而，言语语言病理学家（SLP）缺乏用于识别这种障碍的循证筛查工具。我们开发并进行了预测试一种新的移动健康（mHealth）应用程序，即右半球认知交流筛查器（RECOGNISE），用于筛查RH中风后的CCD。
RH中风患者和SLP对可通过安卓操作系统访问的RECOGNISE进行了评估。两个参与组都完成了用户接受度调查。
六名RH中风患者和三名SLP对RECOGNISE进行了预测试。所有RH中风患者都报告说RECOGNISE使用起来简单且有趣。定性内容分析揭示了三个主要主题：测试项目内容、用户界面和可及性。SLP确定了RECOGNISE的几个积极特征，包括其循证基础、该应用程序独有的功能以及吸引患者的能力。用户界面问题包括应用程序导航、图像布局和评分不一致方面的挑战。
RECOGNISE是首个为识别RH中风后的CCD而开发的mHealth应用程序。研究结果表明，通过一些用户界面改进，RECOGNISE有可能为SLP提供一种循证工具，用于筛查RH中风后的CCD。未来的研究将确定RECOGNISE的可靠性和有效性。
