识别右半球中风后认知沟通障碍的移动健康应用程序:开发和beta测试。

IF 2.2 Q2 HEALTH CARE SCIENCES & SERVICES
mHealth Pub Date : 2025-01-17 eCollection Date: 2025-01-01 DOI:10.21037/mhealth-24-54
Amanda Love, Petrea Cornwell, Ronelle Hewetson, Sebastian Binnewies
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引用次数: 0

摘要

背景:超过50%的右半球(RH)中风住院患者可能存在认知沟通障碍(CCD)。然而,对于语言病理学家(slp)来说,缺乏基于证据的筛查工具来识别这种障碍。我们开发并测试了一种新的移动健康(mHealth)应用程序,用于筛查RH中风后的CCD,即右半球认知通信筛选器(recognition)。方法:RH卒中和slp患者通过Android操作系统进行评估。两组参与者都完成了用户接受度调查。结果:6名RH卒中参与者和3名slp beta测试了recognition。所有RH脑卒中的参与者都报告说,recognition使用起来既简单又愉快。定性内容分析揭示了三个主要主题:测试项目的内容、用户界面和可访问性。slp确定了recognition的几个积极特征,包括基于证据的基础、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导航、图像布局和评分不一致等方面的挑战。结论:recognition是第一个用于RH中风后CCD识别的移动健康应用程序。研究结果表明,通过一些用户界面的改进,recognize有可能为slp提供一种基于证据的工具来筛查RH卒中后的CCD。未来的研究将建立识别的信度和效度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A mHealth application to identify cognitive communication disorder after right hemisphere stroke: development and beta testing.

Background: 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).

Methods: Participants with RH stroke and SLPs evaluated RECOGNISE, accessible via an Android operating system. Both participant groups completed user acceptance surveys.

Results: 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.

Conclusions: 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.

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CiteScore
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