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NCT Number: NCT07479654

AI-Enabled Frailty Risk Prediction in Adult Congenital Heart Disease

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)

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Key information

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Adults aged 20 years or older.
  • Diagnosed with congenital heart disease by a physician.
  • Able to communicate in Mandarin or Taiwanese, with normal cognitive function.

Exclusion criteria

  • Presence of other congenital anomalies.
  • Currently hospitalized for acute decompensation, or having severe cognitive impairment or psychiatric symptoms that preclude completion of questionnaires.
  • Pregnant individuals.

Treatment and study plan

AI-Based Voice Emotion Detection-Guided Counselling

Behavioral

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

Usual care (control)

Behavioral

Usual Care

Primary outcomes

  1. Depression and Anxiety assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS) Short Form Scales

    Time frame: Baseline, 2 weeks, 1 month, and 3 months after initiation of the intervention

    The PROMIS Depression Short Form evaluates negative mood, feelings of hopelessness, helplessness, and loss of interest.

    The PROMIS Anxiety Short Form assesses emotional distress related to feelings of fear, worry, tension, and hyperarousal.

    Each scale consists of multiple items rated on a 5-point Likert scale (1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Often, 5 = Almost Always) based on the participant's experiences during the past 7 days.

    Raw scores are summed and converted to PROMIS T-scores, standardized to a population mean of 50 with a standard deviation of 10.

    Possible raw score range: 8-40 (for the 8-item short form).

    Higher scores indicate greater levels of depressive or anxiety symptoms (worse outcomes).

Secondary outcomes

  1. Chinese version of the Satisfaction with Life Scale; SWLS

    Time frame: Baseline, 2 weeks, 1 month, and 3 months after initiation of the intervention

    This study used the Chinese version of the Satisfaction With Life Scale (SWLS) (Wu & Yao, 2006), which consists of five items rated on a seven-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Higher total scores indicate greater overall life satisfaction. The scale has been applied in adult patients with congenital heart disease (Liu, Lu, et al., 2024) and demonstrated excellent internal consistency, with a Cronbach's α of 0.93, indicating good reliability of the Chinese version.

  2. Grit-10

    Time frame: Baseline, 2 weeks, 1 month, and 3 months after initiation of the intervention

    Duckworth et al. (2007) proposed the Grit Scale to conceptualize grit as comprising two dimensions: Perseverance of Effort (six items) and Consistency of Interests (six items), yielding a total of 12 items. The overall internal consistency of the original scale was 0.85, with Cronbach's α values of 0.78 for the Perseverance of Effort subscale and 0.84 for the Consistency of Interests subscale, indicating good reliability (Duckworth & Quinn, 2009).

    The Chinese version of the Grit Scale (Grit-10) was adapted from the original 12-item English version and revised to include 10 items loading on two factors. The Passion factor (reverse-coded) includes items such as "I often set a goal but then quickly change it," whereas the Perseverance factor includes items such as "I finish whatever I begin." Responses are rated on a five-point Likert scale ranging from 1 (not at all like me) to 5 (very much like me). Each item is scored from 1 to 5; odd-numbered items are reverse-coded and even-numbere

  3. The Chinese Version of Fatigue Assessment Scale; FAS-C

    Time frame: Baseline, 2 weeks, 1 month, and 3 months after initiation of the intervention

    The Fatigue Assessment Scale-Chinese version (FAS-C) is a self-reported instrument designed to measure subjective fatigue and is particularly suitable for use in populations with chronic illnesses, cardiovascular diseases, and the general adult population (Michielsen et al., 2003). The original FAS consists of 10 items encompassing two domains: physical fatigue and mental fatigue. The Chinese version was developed through a rigorous process of translation, back-translation, and cultural adaptation, and has demonstrated satisfactory psychometric properties, including excellent internal consistency (Cronbach's α = 0.92) and good test-retest reliability (Lee, 2024).

    Each item is rated on a five-point Likert scale ranging from 1 (never) to 5 (always), yielding a total score between 10 and 50, with higher scores indicating greater fatigue severity. The FAS-C is brief and easy to administer, with high sensitivity in distinguishing different levels of fatigue, making it suitable for clinica

Sponsors and collaborators

Lead sponsor

Mackay Memorial Hospital

Other

Registry information

Official study title

Precision Risk Prediction of Symptom Clusters and Frailty With AI-Guided Emotion Detection: A Three-Year Study in Adults With Congenital Heart Disease

Important dates

Study start
2026
Primary completion
2028
Study completion
2028
First posted
Mar 18, 2026
Registry last updated
Mar 18, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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