Machine Learning-based Classification of Symptom Clusters and Online CBT

Wuhan Mental Health Centre

Status: Enrolling

Conditions: Depression and Anxiety Symptom

Treatments: Other: control group; Behavioral: problem solving therapy

Study type: Interventional

Funder types: Other

Identifiers

NCT06350201

KY2024.0124.02

Details and patient eligibility

About

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.

Enrollment: 380 estimated patients

Sex: All

Ages: 18 to 64 years old

Volunteers: No Healthy Volunteers

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.

Trial design

Primary purpose: Supportive Care

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Double Blind

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380 participants in 2 patient groups, including a placebo group

8 weeks Problem-solving therapy

Experimental group

Description:

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.

Treatment:

Behavioral: problem solving therapy

treatment as usual

Placebo Comparator group

Description:

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

Treatment:

Other: control group