Academic Primary Care, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
Psychology and Neuroscience, University of Westminster, London, UK.
BMJ Open. 2024 May 27;14(5):e081416. doi: 10.1136/bmjopen-2023-081416.
Fatigue is prevalent across a wide range of medical conditions and can be debilitating and distressing. It is likely that fatigue is experienced differently according to the underlying aetiology, but this is poorly understood. Digital health technologies present a promising approach to give new insights into fatigue.The aim of this study is to use digital health technologies, real-time self-reports and qualitative interview data to investigate how fatigue is experienced over time in participants with myeloma, long COVID, heart failure and in controls without problematic fatigue. Objectives are to understand which sensed parameters add value to the characterisation of fatigue and to determine whether study processes are feasible, acceptable and scalable.
An ecological momentary assessment study will be carried out over 2 or 4 weeks (participant defined). Individuals with fatigue relating to myeloma (n=10), heart failure (n=10), long COVID (n=10) and controls without problematic fatigue or a study condition (n=10) will be recruited. ECG patches will measure heart rate variability, respiratory rate, body temperature, activity and posture. A wearable bracelet accompanied by environment beacons will measure physical activity, sleep and room location within the home. Self-reports of mental and physical fatigue will be collected via smartphone app four times daily and on-demand. Validated fatigue and affect questionnaires will be completed at baseline and at 2 weeks. End-of-study interviews will investigate experiences of fatigue and study participation. A feedback session will be offered to participants to discuss their data.Data will be analysed using multilevel modelling and machine learning. Interviews and feedback sessions will be analysed using content or thematic analyses.
This study was approved by the East of England-Cambridge East Research Ethics Committee (22/EE/0261). The results will be disseminated in peer-reviewed journals and at international conferences.
NCT05622669.
疲劳在广泛的医疗条件下普遍存在，可能会使人虚弱和痛苦。根据潜在的病因，疲劳的体验可能不同，但这一点理解得很差。数字健康技术为深入了解疲劳提供了一种有前途的方法。本研究旨在使用数字健康技术、实时自我报告和定性访谈数据，调查骨髓瘤、长新冠、心力衰竭患者和无疲劳问题的对照组参与者随时间推移的疲劳感。目的是了解哪些感知参数对疲劳特征有价值，并确定研究过程是否可行、可接受和可扩展。
将进行为期 2 或 4 周（由参与者定义）的生态瞬时评估研究。将招募与骨髓瘤（n=10）、心力衰竭（n=10）、长新冠（n=10）和无疲劳问题或研究条件的对照组（n=10）相关的疲劳患者。心电图贴片将测量心率变异性、呼吸频率、体温、活动和姿势。带有环境信标的可穿戴手链将测量身体活动、睡眠和家庭内的房间位置。智能手机应用程序将每天四次和按需收集精神和身体疲劳的自我报告。基线和 2 周时将完成经过验证的疲劳和情感问卷。结束时的访谈将调查疲劳和研究参与的体验。将为参与者提供一个反馈会议，以讨论他们的数据。
将使用多层次建模和机器学习分析数据。将使用内容或主题分析分析访谈和反馈会议。
这项研究已获得东英格兰剑桥东部研究伦理委员会的批准（22/EE/0261）。结果将在同行评议的期刊和国际会议上发表。
NCT05622669。
