AI-Enabled Frailty Risk Prediction in Adult Congenital Heart Disease

Summary

The goal of this three-year mixed-methods observational study with an embedded randomized controlled trial is to develop and validate a frailty risk prediction model and evaluate an artificial intelligence-based voice emotion detection-guided counselling intervention in adults with congenital heart disease (ACHD).

The main questions it aims to answer are:

Are symptom clusters associated with frailty and psychological outcomes in adults with congenital heart disease?

Can symptom clusters and psychosocial factors be used to predict frailty risk over time in ACHD patients?

Does an AI-based voice emotion detection-guided counselling intervention improve psychological outcomes, fatigue, and quality of life among high-risk ACHD patients?

Researchers will compare ACHD patients receiving AI-based voice emotion detection-guided counselling with those receiving usual care to determine whether the intervention reduces depression, anxiety, sleep disturbance, fatigue, and frailty risk, and improves grit and quality of life.

Participants will:

Complete longitudinal assessments of symptom clusters, frailty, and psychological status at baseline and follow-up time points

Participate in qualitative interviews to explore lived experiences related to symptoms and frailty

Receive AI-based voice emotion detection-guided counselling (intervention group only in Year 3)

Conditions

• Adult Congenital Heart Disease
• Symptom Clusters
• Frailty
• Risk Prediction Model
• Artificial Intelligence-Based Voice Emotion Detection

Interventions

BEHAVIORAL

AI-Based Voice Emotion Detection-Guided Counselling

Participants assigned to the intervention arm will receive an artificial intelligence-based voice emotion detection-guided counselling intervention in addition to usual care. The intervention uses voice recordings collected during structured counselling sessions to analyze emotional features, including emotional valence and arousal, through artificial intelligence-based voice emotion detection algorithms. Based on the analyzed emotional profiles, individualized psychological feedback and counselling guidance are provided to support emotional regulation, stress coping, and adaptive self-management. The counselling content is tailored to participants' emotional states and symptom experiences and focuses on reducing psychological distress, improving sleep and fatigue management, enhancing grit, and promoting quality of life. The intervention is delivered by trained healthcare professionals following a standardized protocol, with sessions conducted at predefined intervals during the inter

BEHAVIORAL

Usual Care (Control)

Usual Care

Sponsors & Collaborators

• Mackay Memorial Hospital

  lead OTHER

Study Design

Allocation

RANDOMIZED

Purpose

TREATMENT

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

20 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2026-03-01

Primary Completion

2028-12-31

Completion

2028-12-31