Multimodal Identification of Depressive Symptoms in the Elderly (multimodal)

Wuhan Mental Health Centre

Status

Not yet enrolling

Conditions

Depression

Treatments

Other: data collection

Study type

Observational

Funder types

Other

Identifiers

NCT07112118

KY2025.0115.01

72404094 (Other Grant/Funding Number)

Details and patient eligibility

About

Screening with depression scales alone is subjective, and relying on single-modal data often leads to incomplete identification of symptoms that are easily missed or misdiagnosed. In this study, we first aim to use artificial intelligence to construct a depression symptom recognition model, concatenate multimodal features such as facial expression, audio, text, and postural behavior, and deeply fuse them to construct a multimodal model.

Enrollment

2,000 estimated patients

Sex

All

Ages

60 to 100 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

Elderly individuals aged 60 years or older.
Residents of the community (with residence time of more than 6 months).
Possessing certain reading, writing and comprehension skills, being able to communicate with researchers without obstacles, and being able to independently complete the measurement of various indicators or, although unable to independently fill out the questionnaire, being able to independently make evaluations of the questionnaire items.
Those who have given informed consent.

Exclusion criteria

Those who meet the diagnostic criteria for cognitive impairment (dementia) as stipulated in DSM-5, and/or who suffer from severe physical diseases (such as advanced cancer, cardiovascular and cerebrovascular diseases, etc.).
Those who are undergoing antidepressant treatment.
Elderly individuals who have had suicidal thoughts in any psychological assessment, should be referred to the psychological hotline platform in Wuhan.