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电子健康工具评估神经功能,用于研究,在没有神经科医生的情况下 - 系统评价,第一部分(软件)。

eHealth tools to assess the neurological function for research, in absence of the neurologist - a systematic review, part I (software).

机构信息

Department of Sustainable Health, University of Groningen, Campus Fryslân, Wirdumerdijk 34, 8911 CE, Leeuwarden, The Netherlands.

Faculty of Economics and Business, University of Groningen, Groningen, The Netherlands.

出版信息

J Neurol. 2024 Jan;271(1):211-230. doi: 10.1007/s00415-023-12012-6. Epub 2023 Oct 17.

Abstract

BACKGROUND

Neurological disorders remain a worldwide concern due to their increasing prevalence and mortality, combined with the lack of available treatment, in most cases. Exploring protective and risk factors associated with the development of neurological disorders will allow for improving prevention strategies. However, ascertaining neurological outcomes in population-based studies can be both complex and costly. The application of eHealth tools in research may contribute to lowering the costs and increase accessibility. The aim of this systematic review is to map existing eHealth tools assessing neurological signs and/or symptoms for epidemiological research.

METHODS

Four search engines (PubMed, Web of Science, Scopus & EBSCOHost) were used to retrieve articles on the development, validation, or implementation of eHealth tools to assess neurological signs and/or symptoms. The clinical and technical properties of the software tools were summarised. Due to high numbers, only software tools are presented here.

FINDINGS

A total of 42 tools were retrieved. These captured signs and/or symptoms belonging to four neurological domains: cognitive function, motor function, cranial nerves, and gait and coordination. An additional fifth category of composite tools was added. Most of the tools were available in English and were developed for smartphone device, with the remaining tools being available as web-based platforms. Less than half of the captured tools were fully validated, and only approximately half were still active at the time of data collection.

INTERPRETATION

The identified tools often presented limitations either due to language barriers or lack of proper validation. Maintenance and durability of most tools were low. The present mapping exercise offers a detailed guide for epidemiologists to identify the most appropriate eHealth tool for their research.

FUNDING

The current study was funded by a PhD position at the University of Groningen. No additional funding was acquired.

摘要

背景

由于神经障碍的发病率和死亡率不断上升,且在大多数情况下缺乏有效治疗方法,因此神经障碍仍然是全球关注的问题。探索与神经障碍发展相关的保护和风险因素,将有助于改进预防策略。然而,在基于人群的研究中确定神经学结果既复杂又昂贵。在研究中应用电子健康(eHealth)工具可能有助于降低成本和提高可及性。本系统评价的目的是绘制现有的用于流行病学研究的评估神经体征和/或症状的电子健康(eHealth)工具。

方法

使用四个搜索引擎(PubMed、Web of Science、Scopus 和 EBSCOHost)检索有关开发、验证或实施电子健康工具以评估神经体征和/或症状的文章。总结软件工具的临床和技术特性。由于数量较多,此处仅介绍软件工具。

结果

共检索到 42 种工具。这些工具可捕捉属于四个神经领域的体征和/或症状:认知功能、运动功能、颅神经、步态和协调。还添加了第五类综合工具。大多数工具仅提供英文版本,并且为智能手机设备开发,其余工具则作为基于网络的平台提供。所捕获的工具中不到一半得到充分验证,并且在数据收集时只有大约一半仍在使用。

解释

所识别的工具通常由于语言障碍或缺乏适当验证而存在局限性。大多数工具的维护和耐用性都较低。目前的映射工作为流行病学家提供了详细指南,以确定最适合其研究的电子健康工具。

资金

本研究由格罗宁根大学的博士学位资助,没有获得其他资金。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7a3/10770248/b3de453312dd/415_2023_12012_Fig1_HTML.jpg

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