Depression and Anxiety Symptom
Conditions
Keywords
machine learning approach, CBT, PST, depression, anxiety
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.
Interventions
BEHAVIORALproblem solving therapy
Problem-solving therapy-based holistic emotion management interventions matched to individual symptoms
OTHERcontrol group
Routine psychological care and guidance on mood management
Sponsors
Wuhan Mental Health Centre
National Natural Science Foundation of China
Renmin Hospital of Wuhan University
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SUPPORTIVE_CARE
Masking
DOUBLE (Subject, Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
18 Years to 64 Years
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| The Patient Health Questionnaire (PHQ-9) | 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 | Baseline, week 1, week 2, week 3, week 4, week 5, week 6, week 7, week 8, week 12, week 20, week 32 |
Secondary
| Measure | Time frame |
|---|---|
| PSQI | Baseline, week 1, week 4, week 6, week 8, week 12, week 20, week 32 |
| WHODAS 2.0 | Baseline, week 1, week 4, week 6, week 8, week 12, week 20, week 32 |
| EQ-5D-5L | Baseline, week 1, week 4, week 6, week 8, week 12, week 20, week 32 |
Countries
China
Outcome results
None listed