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数字人工智能系统对帕金森病患者非运动症状监测及自我管理的影响:一项1期实施研究的提案

The Impact of a Digital Artificial Intelligence System on the Monitoring and Self-management of Nonmotor Symptoms in People With Parkinson Disease: Proposal for a Phase 1 Implementation Study.

作者信息

Meinert Edward, Milne-Ives Madison, Chaudhuri K Ray, Harding Tracey, Whipps John, Whipps Susan, Carroll Camille

机构信息

Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom.

Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom.

出版信息

JMIR Res Protoc. 2022 Sep 26;11(9):e40317. doi: 10.2196/40317.

DOI:10.2196/40317
PMID:36155396
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9555326/
Abstract

BACKGROUND

Nonmotor symptoms of Parkinson disease are a major factor of disease burden but are often underreported in clinical appointments. A digital tool has been developed to support the monitoring and management of nonmotor symptoms.

OBJECTIVE

The aim of this study is to establish evidence of the impact of the system on patient confidence, knowledge, and skills for self-management of nonmotor symptoms, symptom burden, and quality of life of people with Parkinson and their care partners. It will also evaluate the usability, acceptability, and potential for adoption of the system for people with Parkinson, care partners, and health care professionals.

METHODS

A mixed methods implementation and feasibility study based on the nonadoption, abandonment, scale-up, spread, and sustainability framework will be conducted with 60 person with Parkinson-care partner dyads and their associated health care professionals. Participants will be recruited from outpatient clinics at the University Hospitals Plymouth NHS Trust Parkinson service. The primary outcome, patient activation, will be measured over the 12-month intervention period; secondary outcomes include the system's impact on health and well-being outcomes, safety, usability, acceptability, engagement, and costs. Semistructured interviews with a subset of participants will gather a more in-depth understanding of user perspectives and experiences with the system. Repeated measures analysis of variance will analyze change over time and thematic analysis will be conducted on qualitative data. The study was peer reviewed by the Parkinson's UK Non-Drug Approaches grant board and is pending ethical approval.

RESULTS

The study won funding in August 2021; data collection is expected to begin in December 2022.

CONCLUSIONS

The study's success criteria will be affirming evidence regarding the system's feasibility, usability and acceptability, no serious safety risks identified, and an observed positive impact on patient activation. Results will be disseminated in academic peer-reviewed journals and in platforms and formats that are accessible to the general public, guided by patient and public collaborators.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05414071; https://clinicaltrials.gov/ct2/show/NCT05414071.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/40317.

摘要

背景

帕金森病的非运动症状是疾病负担的主要因素,但在临床诊疗中常未得到充分报告。已开发出一种数字工具来支持非运动症状的监测和管理。

目的

本研究的目的是证实该系统对帕金森病患者及其护理伙伴在非运动症状自我管理的信心、知识和技能、症状负担以及生活质量方面的影响。它还将评估该系统对帕金森病患者、护理伙伴和医疗保健专业人员的可用性、可接受性及采用潜力。

方法

将基于非采用、放弃、扩大规模、传播和可持续性框架开展一项混合方法实施与可行性研究,研究对象为60对帕金森病患者 - 护理伙伴二元组及其相关医疗保健专业人员。参与者将从普利茅斯大学医院国民保健服务信托基金帕金森病服务门诊招募。主要结局指标,即患者激活度,将在为期12个月的干预期内进行测量;次要结局指标包括该系统对健康和幸福结局、安全性、可用性、可接受性、参与度及成本的影响。对部分参与者进行半结构化访谈,以更深入了解用户对该系统的看法和体验。重复测量方差分析将分析随时间的变化,定性数据将进行主题分析。该研究已由英国帕金森病非药物治疗方法资助委员会进行同行评审,正在等待伦理批准。

结果

该研究于2021年8月获得资助;预计2022年12月开始数据收集。

结论

该研究的成功标准将是确认有关该系统可行性、可用性和可接受性的证据,未发现严重安全风险,以及观察到对患者激活度有积极影响。研究结果将在学术同行评审期刊以及患者和公众合作者指导的、公众可获取的平台和形式上进行传播。

试验注册

ClinicalTrials.gov NCT05414071;https://clinicaltrials.gov/ct2/show/NCT05414071。

国际注册报告识别码(IRRID):PRR1 - 10.2196/40317。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/817f/9555326/05c25c2e1ff3/resprot_v11i9e40317_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/817f/9555326/78f00ee21761/resprot_v11i9e40317_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/817f/9555326/05c25c2e1ff3/resprot_v11i9e40317_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/817f/9555326/78f00ee21761/resprot_v11i9e40317_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/817f/9555326/05c25c2e1ff3/resprot_v11i9e40317_fig2.jpg

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