The Impact of a Digital Artificial Intelligence System on the Monitoring and Self-management of Non-motor Symptoms in People With Parkinson's
试验速览
- 阶段
- 不适用
- 状态
- 撤回
- 入组人数
- 60
- 主要终点
- Patient (and care partner) activation
研究概览
简要总结
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Supportive Care
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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
- •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
排除标准
- •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
结局指标
主要结局
Patient (and care partner) activation
时间窗: Assessed monthly for 12 months
Patient Activation Measure (and caregiver version) will be used to evaluate their confidence, knowledge, and skills at non-motor symptom self-management
次要结局
- Presence of non-motor symptoms(Measured at patients' discretion throughout intervention (12 months))
- Frequency and severity of non-motor symptoms(Measured at baseline, 6, and 12 months)
- Engagement(3, 6, and 12 months)
- Mental well-being(Measured at baseline, 6, and 12 months)
- Clinical safety(Throughout 12 months)
- Short-form self-assessment of functioning and well-being related to Parkinson's disease(Measured at patients' discretion throughout intervention (12 months))
- Long-form self-assessment of functioning and well-being related to Parkinson's disease(Measured at baseline, 6, and 12 months)
- Carer well-being and quality of life(Measured at care partners' discretion throughout intervention (12 months))
- Health status(Measured at baseline, 6, and 12 months)
- Adverse events(Throughout 12 months)
- Quantitative usability(6 and 12 months)
- Acceptability(3, 6, and 12 months)
- Healthcare contacts(Throughout 12 months)
- Technical and implementation issues(Throughout 12 months)
- System use and compliance(Throughout 12 months)
- Costs(Throughout 12 months)
研究者
Edward Meinert, PhD
Associate Professor of eHealth
University of Plymouth