Multimodal Identification of Depressive Symptoms in the Elderly
ConditionDepression
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age60-100
SponsorWuhan Mental Health Centre
About this trial
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.
Eligibility criteria
Qualifiers
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.
Disqualifiers
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.
Trial design
Treatments tested in this trial
- data collection
Treatment groups
2,000 Participants
are divided into 2 treatment groupsSponsors and collaborators
Source ClinicalTrials.gov