Machine Learning-based Classification of Symptom Clusters and Online CBT

NCT ID: NCT06350201

Last Updated: 2026-01-08

Basic Information

• Recruitment Status: RECRUITING
• Clinical Phase: NA
• Total Enrollment: 380 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2025-09-01
• Study Completion Date: 2026-12-01

Brief Summary

To breakthrough the bottleneck identified, we will conduct a cross-sectional study to develop a symptom clustering model for depression and anxiety. A wide range of statistical methods as well as machine learning approaches were explored, and a cohesive hierarchical clustering algorithm will be used. After developing the model, a symptom-matched intervention program based on problem solving therapy will be formulated. We are supposed to examine whether its use for personalizing symptom-matched psychological treatment can lead to improved patient outcomes, compared with usual care. This project is expected to provide a new and precise method for the emotion management, which will provide a standardized intervention pathway combining screening with treatment for the management of depression symptom and anxiety symptom. A preciser intervention matched to individual symptoms may provide important insight in improving patient outcome as well as a standardized mood management pathway targeting to the early detection and intervention for community residents.

Conditions

Depression and Anxiety Symptom

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: SUPPORTIVE_CARE
• Blinding Strategy: DOUBLE

Study Groups

8 weeks Problem-solving therapy

Problem-solving therapy imparts problem-solving abilities applicable to participants' daily lives.

Personalized therapies, including brief behavioral treatment of insomnia, mindfulness, and physical exercise suggestions, were tailored to correspond with patients' specific clusters of sadness and anxiety symptoms.

Group Type: EXPERIMENTAL

problem solving therapy

Intervention Type: BEHAVIORAL

Problem-solving therapy-based holistic emotion management interventions matched to individual symptoms

treatment as usual

Care as usual with the PST-PC learning manual and generic information from the same domains (BBTI, mindfulness, and physical activity) included in the intervention group's daily check-ins

Group Type: PLACEBO_COMPARATOR

control group

Intervention Type: OTHER

Routine psychological care and guidance on mood management

Interventions

problem solving therapy

Problem-solving therapy-based holistic emotion management interventions matched to individual symptoms

Intervention Type: BEHAVIORAL

control group

Routine psychological care and guidance on mood management

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Aged between 18 and 64 years. PHQ-9 ≥10 and/or GAD-7 ≥8 at baseline assessment defined as the threshold for caseness.

Exclusion Criteria

• People will be excluded if they meet any of the following criteria:

1. They are receiving psychological therapy during an interview for any mental health issue;

2. currently acutely suicidal or have attempted suicide in the past 2 months, as indicated by PHQ-9 item 9;

3. cognitively impaired or diagnosed with bipolar disorder or psychosis or experiencing psychotic symptoms; d) dependent on alcohol or drugs; e) living with an unstable or acute medical illness that would interfere with trial participation.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 64 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

National Natural Science Foundation of China

OTHER_GOV

Sponsor Role: collaborator

Wuhan Mental Health Centre

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

Renmin Hospital of Wuhan University

Wuhan, , China

Site Status: RECRUITING

Countries

China

Facility Contacts

LI WEN

Role: primary

360668166@qq.com

15807191278

Other Identifiers

KY2024.0124.02

Identifier Type: -

Identifier Source: org_study_id