Clinical trial NCT06011356: Smart Watch Insights for Prevention of Exacerbations and Enhance Rehabilitation - Movement Study
Official title: Smart Watch Insights for Prevention of Exacerbations and Enhance Rehabilitation - Movement Study
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Cardiovascular Diseases
Non-Alcoholic Fatty Liver Disease
Respiratory Disease
Diabetes
Keywords: Digital health
Smart wearable
Population health
Digital biomarkers
Lead sponsor: Imperial College London
Sponsor class: OTHER
First posted: 2023-08-25
Enrollment: 1000
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: We will recruit study participants from patients registered to the Imperial College Healthcare NHS Trust Care Information Exchange (CIE), a patient-facing electronic health record. Patients on CIE have already provided consent to be approached for NHS research.

Brief summary: Aims of the study:

1. To deliver a scalable wellbeing programme to the local population of Imperial College Healthcare NHS Trust, focusing on movement.
2. To describe the natural history of long-term conditions using digital data from a smartwatch.
3. To identify digital information that is routinely collected by a smart watch that can be used to predict outcomes in patients with long term conditions.
4. To identify factors that determine whether participants engage with and improve in a movement programme.

Adult patients who are registered to the Imperial NHS Care Information Exchange (CIE), an NHS patient-facing electronic health record, are eligible to participate in the study. Participants will receive a smart watch for self-monitoring of their movement and wellbeing and be asked to wear the device as much as possible. They will be asked to download a smartphone application called Connected Life, which displays movement and information on heart rate, breathing and oxygen levels to both the participant and the research team (digital data). Participants will receive secure login details for the Connected Life application from the research team, to ensure data privacy. The research team will look at participants' health records, and attempt to identify associations between the digital data and clinical information. This will allow the research team to identify digital data that predicts the onset and natural history of long term conditions, which may potentially allow for earlier diagnosis for future patients. The primary outcome of the study is the identification of trends in movement based on step-count data recorded by the smartwatch.


Eligibility criteria: Inclusion Criteria:

* Aged over 18 years
* Registered with the patient-facing electronic health record (Care Information Exchange)

Exclusion Criteria:

* Unwilling or unable to provide informed consent
* Arm or wrist injury or condition prohibiting the safe use of a smartwatch
* Any visual impairment preventing the use of the smartwatch or smartphone application.

Primary outcomes:
measure: Step count
timeFrame: 24 months
Secondary outcomes:
measure: Quality of life (EQ-5D-5L)
timeFrame: 24 months
measure: Patient Activation Measure (PAM)
timeFrame: 24 months
Other outcomes:
Locations:
city: London
country: United Kingdom
facility: Imperial College Healthcare NHS Trust
state: United Kingdom (+44)
Study officials:
affiliation: Imperial College Healthcare NHS Trust
name: Nicholas S Peters, MD
role: PRINCIPAL_INVESTIGATOR
References: