Imperial College London
Alternate

EUR ING Dr Edward A Meinert

Faculty of Medicine, School of Public Health

Honorary Senior Lecturer
 
 
 
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Contact

 

e.meinert14

 
 
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Location

 

Reynolds BuildingCharing Cross Campus

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Summary

 

Publications

Citation

BibTex format

@article{Meinert:2022:10.2196/preprints.40317,
author = {Meinert, E and Milne-Ives, M and Chaudhuri, KR and Harding, T and Whipps, J and Whipps, S and Carrol, C},
doi = {10.2196/preprints.40317},
title = {The impact of a digital artificial intelligence system on the monitoring and self-management of non-motor symptoms in People with Parkinson’s: Proposal for a Phase 1 implementation study (Preprint)},
url = {http://dx.doi.org/10.2196/preprints.40317},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - <sec>                    <title>BACKGROUND</title>                        <p>Non-motor symptoms of Parkinson’s 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 NMS.</p>                </sec>                                <sec>                    <title>OBJECTIVE</title>                        <p>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 NMS, symptom burden, and quality of life of people with Parkinson’s (PwP) and their care partners (CPs). It will also evaluate the usability, acceptability, and potential for adoption of the system for PwP, CPs, and healthcare professionals (HCPs).</p>                </sec>                                <sec>                    <title>METHODS</title>                        <p>A mixed-methods implementation and feasibility study based on the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability framework will be conducted with 60 PwP-CP dyads and their associated HCPs. Participants will be recruited from outpatient clinics at the University Hospitals Plymouth NHS Trust’s Parkinson’s 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. Semi-structured interviews with a subset of participants will gather a more in-depth understanding of users' perspectives and experiences with the system. Repeated measures ANOVA will analyse change over time and thematic analysis will be conducted on qualitative data. The was peer-reviewed by the Parkinson’s UK Non-Drug Approaches grant board, and i
AU  - Meinert,E
AU  - Milne-Ives,M
AU  - Chaudhuri,KR
AU  - Harding,T
AU  - Whipps,J
AU  - Whipps,S
AU  - Carrol,C
DO  - 10.2196/preprints.40317
PY  - 2022///
TI  - The impact of a digital artificial intelligence system on the monitoring and self-management of non-motor symptoms in People with Parkinson’s: Proposal for a Phase 1 implementation study (Preprint)
UR  - http://dx.doi.org/10.2196/preprints.40317
ER  -
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