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基于语音的数字健康解决方案与新冠病毒相关持续症状监测的协同设计(即将开展的语音研究):一项混合方法研究的方案

Co-Design of a Voice-Based Digital Health Solution to Monitor Persisting Symptoms Related to COVID-19 (UpcomingVoice Study): Protocol for a Mixed Methods Study.

作者信息

Fischer Aurelie, Aguayo Gloria A, Oustric Pauline, Morin Laurent, Larche Jerome, Benoy Charles, Fagherazzi Guy

机构信息

Deep Digital Phenotyping Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.

Université de Lorraine, Nancy, France.

出版信息

JMIR Res Protoc. 2023 Jun 19;12:e46103. doi: 10.2196/46103.

Abstract

BACKGROUND

Between 10% and 20% of people with a COVID-19 infection will develop the so-called long COVID syndrome, which is characterized by fluctuating symptoms. Long COVID has a high impact on the quality of life of affected people, who often feel abandoned by the health care system and are demanding new tools to help them manage their symptoms. New digital monitoring solutions could allow them to visualize the evolution of their symptoms and could be tools to communicate with health care professionals (HCPs). The use of voice and vocal biomarkers could facilitate the accurate and objective monitoring of persisting and fluctuating symptoms. However, to assess the needs and ensure acceptance of this innovative approach by its potential users-people with persisting COVID-19-related symptoms, with or without a long COVID diagnosis, and HCPs involved in long COVID care-it is crucial to include them in the entire development process.

OBJECTIVE

In the UpcomingVoice study, we aimed to define the most relevant aspects of daily life that people with long COVID would like to be improved, assess how the use of voice and vocal biomarkers could be a potential solution to help them, and determine the general specifications and specific items of a digital health solution to monitor long COVID symptoms using vocal biomarkers with its end users.

METHODS

UpcomingVoice is a cross-sectional mixed methods study and consists of a quantitative web-based survey followed by a qualitative phase based on semistructured individual interviews and focus groups. People with long COVID and HCPs in charge of patients with long COVID will be invited to participate in this fully web-based study. The quantitative data collected from the survey will be analyzed using descriptive statistics. Qualitative data from the individual interviews and the focus groups will be transcribed and analyzed using a thematic analysis approach.

RESULTS

The study was approved by the National Research Ethics Committee of Luxembourg (number 202208/04) in August 2022 and started in October 2022 with the launch of the web-based survey. Data collection will be completed in September 2023, and the results will be published in 2024.

CONCLUSIONS

This mixed methods study will identify the needs of people affected by long COVID in their daily lives and describe the main symptoms or problems that would need to be monitored and improved. We will determine how using voice and vocal biomarkers could meet these needs and codevelop a tailored voice-based digital health solution with its future end users. This project will contribute to improving the quality of life and care of people with long COVID. The potential transferability to other diseases will be explored, which will contribute to the deployment of vocal biomarkers in general.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05546918; https://clinicaltrials.gov/ct2/show/NCT05546918.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46103.

摘要

背景

10%至20%的新冠病毒感染患者会发展为所谓的“长新冠”综合征,其症状波动不定。“长新冠”对患者的生活质量有很大影响,患者常常感觉被医疗系统忽视,因此需要新的工具来帮助他们管理症状。新的数字监测解决方案可以让他们直观了解症状的变化,并且可以作为与医护人员沟通的工具。语音和声音生物标志物的使用有助于准确、客观地监测持续存在和波动的症状。然而,为了评估需求并确保这种创新方法被其潜在用户(有或没有“长新冠”诊断的持续存在新冠相关症状的患者以及参与“长新冠”护理的医护人员)接受,将他们纳入整个开发过程至关重要。

目的

在“即将到来的声音”研究中,我们旨在确定“长新冠”患者希望在日常生活中得到改善的最相关方面,评估语音和声音生物标志物的使用如何可能成为帮助他们的潜在解决方案,并与最终用户确定使用声音生物标志物监测“长新冠”症状的数字健康解决方案的一般规格和具体项目。

方法

“即将到来的声音”是一项横断面混合方法研究,包括基于网络的定量调查,随后是基于半结构化个人访谈和焦点小组的定性阶段。将邀请“长新冠”患者和负责“长新冠”患者的医护人员参与这项完全基于网络的研究。从调查中收集的定量数据将使用描述性统计进行分析。来自个人访谈和焦点小组的定性数据将进行转录,并使用主题分析方法进行分析。

结果

该研究于2022年8月获得卢森堡国家研究伦理委员会批准(编号202208/04),并于2022年10月随着基于网络的调查启动而开始。数据收集将于2023年9月完成,结果将于2024年发表。

结论

这项混合方法研究将确定受“长新冠”影响的人在日常生活中的需求,并描述需要监测和改善的主要症状或问题。我们将确定使用语音和声音生物标志物如何满足这些需求,并与未来的最终用户共同开发量身定制的基于语音的数字健康解决方案。该项目将有助于提高“长新冠”患者的生活质量和护理水平。将探索其向其他疾病的潜在可转移性,这将有助于声音生物标志物的普遍应用。

试验注册

ClinicalTrials.gov NCT05546918;https://clinicaltrials.gov/ct2/show/NCT05546918。

国际注册报告识别码(IRRID):DERR1-10.2196/46103。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef43/10337302/3dcc3936f4bb/resprot_v12i1e46103_fig1.jpg

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