| Title | Understanding patterns of fatigue in health and disease: protocol for an ecological momentary assessment study using digital technologies. |
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| Type | Journal article |
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| Authors | Adam, Rosalind, Lotankar, Yojana, Sas, Corina, Powell, Daniel, Martinez, Veronica, Green, Stephen, Cooper, Jonathan, Bradbury, Katherine, Sive, Jonathan and Hill, Derek L. |
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| Abstract | Introduction: 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.Methods and analysisAn 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.Ethics and disseminationThis 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.Trial registration numberNCT05622669. |
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| Keywords | Fatigue |
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| information technology |
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| Heart Failure |
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| myeloma |
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| Patient Reported Outcome Measures |
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| Post-Acute Covid-19 Syndrome |
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| Humans |
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| Multiple Myeloma |
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| Research Design |
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| Self Report |
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| Ecological Momentary Assessment |
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| Wearable Electronic Devices |
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| COVID-19 |
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| SARS-CoV-2 |
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| Digital Technology |
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| Article number | e081416 |
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| Journal | BMJ Open |
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| Journal citation | 14 (5) |
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| ISSN | 2044-6055 |
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| Year | 2024 |
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| Publisher | BMJ |
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| Publisher's version | License CC BY 4.0 File Access Level Open (open metadata and files) |
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| Digital Object Identifier (DOI) | https://doi.org/10.1136/bmjopen-2023-081416 |
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| PubMed ID | 38802273 |
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| Publication dates |
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| Published online | 27 May 2024 |
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| Published in print | 01 May 2024 |
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| Project | SCAF/18/02 |
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| EP/W003228/1 |
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| Funder | Chief Scientist Office |
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| EPSRC |
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| License | CC BY |
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| File |  bmjopen-2023-081416.pdf |
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