Clinical Investigation of NMS Assist

The Impact of a Digital Artificial Intelligence System on the Monitoring and Self-management of Non-motor Symptoms in People With Parkinson's

Parkinson's can cause a wide range of non-motor symptoms (NMS), including pain and problems with mental health, memory and sleep. These affect the quality of life of people with Parkinson's (PwP) and their care partners (CP). If these issues are not recognised and managed quickly, they can result in escalating problems. Many PwP are unsure of the extent and variety of the NMS and how simple adjustments at home could improve them. We have developed a digital system, NMS Assist, to help PwP monitor their non-motor symptoms and develop skills to self-manage them. Such a tool needs to be simple to use, safe and effective. We will ask 60 PwP, CP and members of their Parkinson's healthcare team to use NMS Assist for 12 months, and we will monitor how they use the tool. PwP and CPs will be asked if they feel more knowledgeable and confident to manage their own symptoms whilst being better able to discuss a problem with their healthcare professional. A smaller group of the participants will discuss their experiences in more detail to help pinpoint aspects that work well and those needing adjustment and development. Members of the healthcare team will be asked to assess any improvement in communication with PwP and CPs. It is thought that the use of this system will result in improved quality of life and increased knowledge and confidence for managing symptoms while safely reducing the time spent by health care professionals on manageable non-motor symptoms.

NMS Assist provides a system of linking PwP, CPs, and healthcare providers (HCPs) to monitor and empower self-management of non-motor symptoms through the use of a mobile app and web portal.

The system enables people with Parkinson's and their care partners to complete questionnaires about symptoms and burden and share that information with their care team. They can also access self-help resources and materials about managing non-motor symptoms. Healthcare providers have a dashboard that flags any worsening symptoms or discrepancies between PwP and CP reports, enabling their to prioritise care and quickly see the status of their patients. The system also enables PwP or CPs to request healthcare contact.

Patient Activation Measure (and caregiver version) will be used to evaluate their confidence, knowledge, and skills at non-motor symptom self-management

Measured using the Non-Motor Symptoms Questionnaire (NMSQ), patients tick 'yes' or 'no' for each symptom listed

Measured using the Movement Disorder Society Non-Motor Symptoms Scale (MDS-NMS), where higher scores indicate greater frequency and/or severity

Measured using the short-form Parkinson's Disease Questionnaire (PDQ-8), patients indicate the frequency with which they experience certain issues

Measured using the long-form Parkinson's Disease Questionnaire PDQ-39, patients indicate the frequency with which they experience certain issues

Measured using the Parkinson Disease Questionnaire for care partners; care partners indicate the frequency with which they experience certain issues

Measured using the EQ-5D-5L; higher scores on the EQ-5D-5L descriptive system indicate worse health problems in the specific dimension whereas a high score in the EQ VAS indicates better health on the day of the questionnaire

Measured using the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS); Scores range from 14 to 70 (on the 14 item version) and higher scores indicate greater positive mental wellbeing

Number of PwP-initiated contacts with healthcare team (through the 'request healthcare contact' feature) and the number of HCP-initiated contacts (due to system flagging PwP based on PwP and CP-reported outcomes), recorded by the system

Technical issues identified from the system use data and by participants and process measures relating to service delivery

Data collected via the system about users engagement with the system (e.g. number of times accessed, length of time accessed, features used)

Inclusion Criteria: Willing and able to provide informed consent and comply with intervention requirements 18 years or older Be fluent in English Not resident in a care or nursing home Ambulant Have compatible smartphone/data access Normally under the care of the Parkinson's service in the participating organisation Participant's HCP in the participating organisation consented to participate in the study Exclusion Criteria: Secondary cause of parkinsonism Significant cognitive impairment or a diagnosis of Parkinson's disease dementia Living in residential care facilities Previous involvement in development or testing of the NMS Assist system Significant comorbidity, which in the opinion of the chief investigator would preclude safe participation in the study or protocol compliance (e.g. life expectancy <6 months) In a dependent/unequal relationship with anyone involved in the research or care teams

Data belongs to the study sponsor (the University of Plymouth) and deidentified data will be made available in line with the data sharing policy developed with Parkinson's UK and PPI representatives.

Meinert E, Milne-Ives M, Chaudhuri KR, Harding T, Whipps J, Whipps S, Carroll C. 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. JMIR Res Protoc. 2022 Sep 26;11(9):e40317. doi: 10.2196/40317.