Better Risk Perception Via Patient Similarity to Control Hyperglycemia and Sustained by Telemonitoring

NCT06607497 | Active Not Recruiting

• 1 other identifier: 2024-2281
• Study Type: interventional
• Target: 360
• Locations: 1 country
• Sites: 1

Brief Summary

Background: Diabetes significantly raises the likelihood of complications, thereby increasing the risk of diabetes-related mortality, particularly due to vascular complications. It is vital to address this rising trend of mortality, by enhancing awareness of diabetes complications to improve risk perception and ultimately reduce mortality rates. Managing diabetes effectively requires interventions addressing both risk communication and monitoring, helping patients better understand and make informed decisions about their health. Objectives: The primary aim is to evaluate and compare the effectiveness of combined risk communication session using an AI module (PERDICT.AI) and home-based diabetes monitoring (PTEC-DM) versus a standalone risk communication session in improving health outcomes (risk perception, medication adherence, self-care activities and glycaemic control) among poorly controlled diabetes patients. Secondary aims are to explore participants' views and experiences of risk communication session using PERDICT.AI, PTEC-DM and usual care and clinician' views on utility of the new approach to improve risk perception. Methods: A mixed-method study design will be employed to conduct a multi-arm randomized controlled trial across four of the SingHealth Polyclinics cluster (Pasir Ris, Eunos, Sengkang, Tampines North). Patient participants will be randomly allocated in a 1:1:1 ratio to one of the three arms. Arm 1 will receive risk communication session using PERDICT.AI and home-based diabetes monitoring using PTEC-DM alongside usual care. Arm 2 participants will undergo a standalone risk communication session using PERDICT.AI with usual care while arm 3 will serve as the control group with usual care. A total of 360 (120 in each group) participants will be enrolled by simple randomization. Eligible patient must be of age between 36 and 65 years with HbA1c \>8.0% within the last 6 months. Significance of the study: Findings from the study may add evidence to the scientific knowledge of using these approaches to improve risk perception and recommend development of similar interventions.

Conditions

Diabetes Mellitus, Type 2

Outcome Measures

Primary Outcomes (5)

• Risk Perception Survey-Diabetes Mellitus (RPS-DM)

  The RPS-DM consists of 31 questions. The first section assesses risk knowledge (5 items scored on 3-point scale with 1 point for each correct answer; higher score indicates greater knowledge of the risk of getting diabetes complications). The remaining 26 items comprise 5 subscales which can be described as: perceived personal control (4 items scored on 4-point scale); worry (2 items scored on 4-point scale), optimistic bias (2 items scored on 4-point scale); personal disease risk (9 items scored on a 4-point scale; indicates degree of own perceived risk of getting 9 diseases or conditions, plus additional question about whether they have ever had the condition, scored yes/no with 1 point added for yes response); and environmental risk (9 items scored on a 4-point scale). The composite risk perception is the average of the 26 items in the main questionnaire; higher scores indicate greater comparative perceived risk.

  through study completion, an average of 12 to 16 months

• Health related Quality of life

  Change in the scores using EQ-5D-5L questionnaire; The EQ-5D-5L tool comprises five dimensions, each describing a different aspect of health: mobility, self-care, usual activities, pain/ discomfort and anxiety/ depression. Each dimension has five response levels (no problems, slight problems, moderate problems, severe problems, unable to/ extreme problems). The proportion of patients reporting each level of problem on each dimension of the EQ-5D will be determined through study completion and compared. EQ VAS (Visual Analogue Scale) provides a quantitative measure of the patient's perception of their overall health. The EQ VAS records the respondent's overall current health on a vertical scale (0-100), where the endpoints are labelled '0-The worst health you can imagine' and '100-The best health you can imagine'.

  through study completion, an average of 12 to 16 months

• Medication adherence

  Change in the scores using five item Medication Adherence Report Scale (MARS-5); MARS-5 score was calculated by summing the numeric score (range 1-5) from each question for out of 25 (range 5-25). A higher score indicates better adherence.

  through study completion, an average of 12 to 16 months

• Summary of Diabetes Self-care Activities (SDSCA) questionnaire

  SDSCA questionnaire collects data on general diet, specific diet, exercise, blood-glucose testing, foot care, and smoking, using an 8-point Likert-type scale (0-7), which represents the number of days per week when the given self-care activity was performed. Scores are calculated separately for each item and the level of adherence is indicated by the mean score for each dimension.

  through study completion, an average of 12 to 16 months

• Iowa-Netherlands Comparison Orientation Measure (INCOM)

  The INCOM is an 11-item measure of one's tendency to make social comparisons. The scale includes such items as: "I always like to know what others in a similar situation would do." Response choices range from 1 (disagree strongly) to 5 (agree strongly). Higher scores indicate more of a tendency to socially compare.

  baseline enrolment

Secondary Outcomes (3)

• Cost-effectiveness analysis

  through study completion, an average of 12 to 16 months

• Views and experiences of risk communication session using PERDICT.AI, PTEC-DM and usual care

  24-48 weeks

• Exploring clinician' views on utility of combined intervention to improve risk perception

  24-48 weeks

Study Arms (3)

Arm 1

EXPERIMENTAL

In arm 1, participants will attend the risk communication session utilizing AI module (PERDICT.AI) delivered by the study team integrated with Home-based Diabetes Monitoring (PTEC-DM) providing personalized guidance through teleconsultation in addition to usual care. Screen activity of PERDICT.AI will be recorded using a screen capture software. The entire session will be audio recorded.

Other: Intervention using an AI enabled risk communication tool (PERDICT.AI); Other: Telemonitoring with Primary Tech Enhanced Care (PTEC-DM)

Arm 2

EXPERIMENTAL

In arm 2, participants will attend the risk communication session utilising AI module (PERDICT.AI) without PTEC-DM. Screen activity of PERDICT.AI will be recorded using a screen capture software. The entire session will be audio recorded.

Other: Intervention using an AI enabled risk communication tool (PERDICT.AI)

Arm 3

NO INTERVENTION

Arm 3 will be the active control group, receiving only standard care

Interventions

Intervention using an AI enabled risk communication tool (PERDICT.AI) OTHER

Risk communication using PERDICT.AI dynamically communicates an individual's glycemic control, offering a comparative ranking among peers to enhance motivation and awareness. Furthermore, it assesses the risk of potential complications comparing with peer data with exemplary cases to underscore the consequences of suboptimal management. In addition, it will generate personalized recommendations including medication adjustment and personalized health plans.

Arm 1; Arm 2

Telemonitoring with Primary Tech Enhanced Care (PTEC-DM) OTHER

The Primary Tech-Enhanced Care (PTEC) programme focuses on encouraging patients to manage chronic conditions at home through user-friendly kits. The Home Diabetes Monitoring programme (PTEC-DM) enables home-based glucose and blood pressure monitoring once a week using a Bluetooth enabled device. These reading will be securely transmitted to the study team via the app and managed appropriately through teleconsultation. Additionally, participants will receive health nudges, encouragements, and reminders through in-app messages to support their well-being.

Arm 1

Eligibility Criteria

• Age: 36 Years - 65 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Type 2 Diabetes Mellitus on follow-up at the study site for at least 12 months
• Age 36 to 65 years
• At least one HbA1c reading ≥ 8.0% within the last 6 months
• Able to read and speak English

You may not qualify if:

• Not a Singapore citizen or permanent resident
• Pregnant
• End-stage kidney disease or on renal replacement therapy
• Known terminal illness
• Visual and/or hearing impairment
• Cognitive impairment or mental illness
• Unable to provide informed consent

Sponsors & Collaborators

• SingHealth Polyclinics: lead
• AISG Health Grand Challenge: collaborator

Study Sites (1)

SingHealth Polyclinics

Singapore, Singapore, Singapore

Location

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MeSH Terms

Conditions

Diabetes Mellitus, Type 2

Condition Hierarchy (Ancestors)

Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases

Study Officials

• Ngiap Chuan Tan, MMed

  SingHealth Polyclinics

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: SUPPORTIVE CARE
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: September 16, 2024
• First Posted: September 23, 2024
• Study Start: July 15, 2024
• Primary Completion (Estimated): September 30, 2026
• Study Completion (Estimated): September 30, 2026
• Last Updated: April 27, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

SG (1)