We are offering an enthusiastic and motivated PhD student the exciting opportunity to join our international renowned team. This project will be the first to use wearable technology (WT) to objectively and continuously quantify activity, mobility and sleep patterns in people with Parkinson’s with delirium over prolonged periods.
Background Parkinson’s disease is the second most common neurodegenerative disease. People with Parkinson’s disease may be at increased risk of delirium. Delirium is an acute neuropsychiatric syndrome associated with altered levels of consciousness, confusion and impaired attention. Delirium in Parkinson’s has been poorly defined in previous studies and has overlapping symptoms with Parkinson’s and Parkinson’s dementia, such as experiencing sleep-wake disturbance, hallucinations and delusions; this may have underestimated the prevalence. Delirium is associated with poorer outcomes including falls, cognitive decline and mortality. As delirium is preventable in a third of cases, early diagnosis could lead to improved outcomes for patients. However, a growing body of evidence in the field has highlighted the urgent need of accurately diagnosing delirium in Parkinson’s and monitoring its fluctuations over prolonged periods.
Project The use of WT provides a unique opportunity to objectively and continuously quantify clinically relevant digital outcomes. As part of this multidisciplinary study, participants with Parkinson’s disease will be assessed with WT in hospital and again at home to compare their activity levels in the two environments. This will be collected concurrently with standardised delirium assessments. Data will be recorded continuously with an accelerometry-based WT. This will enable the student to segment and extract activity-based data. Novel metrics will also be developed using night-time WT data. The metrics developed will aid the accurate and timely diagnosis of delirium and delirium subtypes in Parkinson’s disease. Identification of delirium and Parkinson’s subtypes will allow for stratification of patients in future clinical trials to prevent or manage delirium.
Supervision and support This interdisciplinary project combines expertise in the fields of psychology (Dr Rachael Lawson) and clinical geriatrics (Dr Alison Yarnall), with engineering applied to wearable technology (Dr Silvia Del Din) and mathematical and statistical modelling (Professor Jian Shi). The PhD student will therefore develop interdisciplinary skills across these areas as part of this translational medicine project. The student will be trained in Parkinson’s disease, delirium diagnosis, clinical data collection and more generally on how develop clinical research studies. Training will also be given in wearable technology methodologies, feature extraction and novel metric development. Furthermore, with support from supervisors quantitative and statistical skills will be developed to develop innovative models. The student will be supported by our research groups. This includes peer support from current PhD students and post-doctoral researchers. As part of the research groups, they will have specific training in presentation skills and communicating scientific research to the public. The student will be supported to go to national and international conference to present their work, and will have the opportunity to develop leadership skills within the research group.
Dr Rachael Lawson https://www.ncl.ac.uk/caru/staff/profile/rachaellawson.html#background Dr Silvia Del Din https://www.ncl.ac.uk/caru/staff/profile/silviadel-din.html#background Dr Alison Yarnall https://www.ncl.ac.uk/caru/staff/profile/alisonyarnall.html#background Professor Jian Shi https://www.ncl.ac.uk/maths-physics/staff/profile/jianshi.html#background Website: https://research.ncl.ac.uk/bam/ Twitter: @BAM_Reseach
Contact Dr Rachael Lawson [Email Address Removed] for more information.
Benefits of being in the DiMeN DTP:
This project is part of the Discovery Medicine North Doctoral Training Partnership (DiMeN DTP), a diverse community of PhD students across the North of England researching the major health problems facing the world today. Our partner institutions (Universities of Leeds, Liverpool, Newcastle and Sheffield) are internationally recognised as centres of research excellence and can offer you access to state-of the-art facilities to deliver high impact research.
We are very proud of our student-centred ethos and committed to supporting you throughout your PhD. As part of the DTP, we offer bespoke training in key skills sought after in early career researchers, as well as opportunities to broaden your career horizons in a range of non-academic sectors.
Being funded by the MRC means you can access additional funding for research placements, international training opportunities or internships in science policy, science communication and beyond. See how our current DiMeN students have benefited from this funding here: http://www.dimen.org.uk/overview/student-profiles/flexible-supplement-awards
Further information on the programme can be found on our website: http://www.dimen.org.uk/
Studentships are fully funded by the Medical Research Council (MRC) for 3.5yrs. Includes: - Stipend at national UKRI standard rate - Tuition fees - Research training and support grant (RTSG) - Travel allowance
Studentships commence: 1st October 2020.
To qualify, you must be a UK or EU citizen who has been resident in the UK/EU for 3 years prior to commencement. Applicants must have obtained, or be about to obtain, at least a 2.1 honours degree (or equivalent) in a relevant subject. All applications are scored blindly based on merit. Please read additional guidance here: https://goo.gl/8YfJf8
Lawson, R. A., McDonald, C., & Burn, D. J. (2019). Defining delirium in idiopathic Parkinson's disease: A systematic review. Parkinsonism & related disorders, 64, 29-39.
Del Din, S., Galna, B., Godfrey, A., Bekkers, E. M., Pelosin, E., Nieuwhof, F., ... & Rochester, L. (2017). Analysis of free-living gait in older adults with and without Parkinson’s disease and with and without a history of falls: identifying generic and disease-specific characteristics. The Journals of Gerontology: Series A, 74(4), 500-506.