Recruitment

Recruitment Status
Not yet recruiting
Estimated Enrollment
1250

Summary

Conditions
Diabetes Mellitus - Type 2
Type
Interventional
Phase
Not Applicable
Design
Allocation: RandomizedIntervention Model: Parallel AssignmentIntervention Model Description: A pragmatic 2-arm (1:1) randomized controlled trial (RCT) on 1,000 eligible diabetes patients using the Pragmatic Explanatory Continuum Indicator Summary Framework-2 (PRECIS-2) criteria for pragmatic trials. Patients with diabetes will be randomly allocated in a 1:1 ratio to either the intervention or control group. The intervention group will receive the personalized feedback intervention through the personalized and adaptive intervention platform app on a FitBit wearable on top of their usual clinical care for their diabetes condition. The control group will receive the FitBit wearable on top of their usual clinical care for their diabetes condition but will not receive the personalized and adaptive intervention platform.Masking: Triple (Care Provider, Investigator, Outcomes Assessor)Masking Description: Patients will be screened and recruited for the RCT by research coordinators positioned in the SingHealth polyclinics. They will identify eligible patients according to the inclusion and exclusion criteria. Informed consent will be taken and they will be referred to the research coordinators who will randomly assign the patients to the intervention or control arm using a site-specific pre-generated randomization list. A research coordinator will keep custody of the 3 randomization lists (1 for each recruitment site), and assign treatment accordingly to the intervention listed and not be involved in the recruitment or assessment of patients.Primary Purpose: Health Services Research

Participation Requirements

Age
Between 40 years and 120 years
Gender
Both males and females

Description

Traditional healthcare facility-based consultation model of episodic contact in managing chronic disease patients have limited exposure to monitor and intervene patients' lifestyle factors. These factors have been found to be more effective in managing 3H than medication. The proposed adaptive platf...

Traditional healthcare facility-based consultation model of episodic contact in managing chronic disease patients have limited exposure to monitor and intervene patients' lifestyle factors. These factors have been found to be more effective in managing 3H than medication. The proposed adaptive platform will utilize wearable and mobile application technologies which has the ability to continuous track several physiological and lifestyle factors data (e.g. moderate to vigorous active minutes, resting heart rate, sleep hours and quality and dietary habits) Similarly, due to the limited exposure that healthcare workers have with patients under the current consultation model, current health education and intervention tends to be "one size fits all", passive and "top down" knowledge-loading. Patients are expected to change their behavior or to remember health education knowledge after a consultation session. The proposed adaptive platform will be built using educational and behavioral cues obtained from multiple stakeholders (including patients) and multiple data sources with the aim to gather more comprehensive and targeted feedback that is relevant to patients' needs in their management of their 3H condition. As changes in lifestyle factors and habits takes time, the proposed platform can also provide timely and appropriate feedbacks and reminders to patients at a more constant interval as compared to current model of care when advice was only given during consultation follow-up To be able to add healthy years to the life of the current and future seniors,behavioral interventions that are closely studied and carefully implemented without disruption to the daily activity of the seniors is needed to achieve a revolutionary improvement in current primary care management. The investigators will conduct a qualitative study to have a deep and enriched understanding of the types of nudges that are suited for patients with chronic diseases. Through modelling approach using the electronic medical records, the proposed adaptive platform will profile patients into groups and pre-set the nudges that are suitable for them. This allows the investigators to identify patients that have a higher risk of complications of 3H and quickly match the desired nudges to change behavior. The proposed adaptive platform also aims to empower patients by providing patients with automated bite-sized knowledge of their health conditions. Coupled with real-time personalized feedback to their health behaviors, patients will be equipped with the knowledge to take charge of their health using far lesser healthcare manpower and resources. The proposed adaptive platform will be integrated into common mobile wearable which are readily available devices that are widely used by many Singaporeans now. As such it can also be scaled up relatively easily with minimal resources and education. Therefore, the proposed adaptive intervention will improve health outcomes and reduce healthcare utilization. An empowered patient will result in lesser complications and improve health outcomes, resulting in lower patient and caregiver burden, improving quality of life.

Tracking Information

NCT #
NCT04518566
Collaborators
  • National University, Singapore
  • SingHealth Polyclinics
  • Duke-NUS Graduate Medical School
Investigators
Principal Investigator: Lian Leng Low Singhealth Foundation