Machine Learning-based Classification of Symptom Clusters and Online CBT
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: problem solving therapy, control group.
- Who it may be relevant to
- Registry conditions: Depression and Anxiety Symptom. Basic parameters: 18 years — 64 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Machine Learning-based Classification of Symptom Clusters and Matched Online Cognitive Behavior Intervention for Depression Symptom and Anxiety Symptom
Overview
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.
Interventions
- Behavioral problem solving therapy
Problem-solving therapy-based holistic emotion management interventions matched to individual symptoms - Other control group
Routine psychological care and guidance on mood management
Primary outcome measures
- The Patient Health Questionnaire (PHQ-9) [Time frame: Baseline, week 1, week 2, week 3, week 4, week 5, week 6, week 7, week 8, week 12, week 20, week 32]
- GAD-7 [Time frame: Baseline, week 1, week 2, week 3, week 4, week 5, week 6, week 7, week 8, week 12, week 20, week 32]
Secondary outcome measures (3)
- PSQI [Time frame: Baseline, week 1, week 4, week 6, week 8, week 12, week 20, week 32]
- WHODAS 2.0 [Time frame: Baseline, week 1, week 4, week 6, week 8, week 12, week 20, week 32]
- EQ-5D-5L [Time frame: Baseline, week 1, week 4, week 6, week 8, week 12, week 20, week 32]
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:
- They are receiving psychological therapy during an interview for any mental health issue;
- currently acutely suicidal or have attempted suicide in the past 2 months, as indicated by PHQ-9 item 9;
- 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.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Double blind
- Primary purpose
- Supportive care
Study locations
China · 1 center
- Renmin Hospital of Wuhan University — Wuhan
Identifiers
NCT: NCT06350201 · KY2024.0124.02