F32 F33 F31 F92.0
Conditions
Interventions
Sponsors
Eligibility
Inclusion criteria
Inclusion criteria: 1. Patients with a previous or current diagnosis of a depressive disorder according to the ICD-10 /ICD-11/DSM-5 criteria: a) Depressive episode (ICD-10: F32.x / ICD-11: 6A70.x, 6A7Z / DSM-5: F32.x) b) Recurrent depressive disorder (ICD-10: F33.x / ICD-11: 6A71.x / DSM-5: F33.x) c) Bipolar affective disorder (ICD-10: F31.x / ICD-11: 6A6Z, 6A60.x / DSM-5: F31.x) d) Depressive conduct disorder (ICD-10: F92.0) 2. Age between 13 and 65 years. 3. The patient has sufficient verbal and cognitive abilities to understand and answer questions asked during the assessments.
Exclusion criteria
Exclusion criteria: 1. Insufficient knowledge of German that hinder the understanding of the questions and instructions 2. Acute suicidality 3. Comorbidities classified according to ICD-10 as: a) F0 Organic, including symptomatic, mental disorders b) F1 Mental and behavioural disorders due to psychoactive substance use (with the exception of the diagnosis F1x.1 – Harmful use) c) F2 Schizophrenia and delusional disorders (with the exception of the diagnosis F21: schizotypal disorder) d) F84 Pervasive developmental disorders 4. History of severe somatic or neurological disease (e.g. tumor disease) with current influence on brain function 5. Learning disorder with effect on reading ability 6. A medical history of somatic/neurological disease affecting the brain, which is the primary explanation for the psychological symptoms. 7. Learning disability or intellectual disability (IQ < 70)
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| The central aim of the present study project is the empirical extraction of predictors as well as the development of a psychometric instrument for risk estimation of the onset of depression, taking into account biopsychosocial risk and protective factors and psychopathological aspects. | — |
Secondary
| Measure | Time frame |
|---|---|
| 1) The multifactorial genesis of depression is based on various etiopathogenetic, psychopathological, and psychosocial factors that can be explored using “DEEP-IN” and allow for a specific description of depressive prodromal symptoms. Predictive models are to be extracted based on this. 2) The “DEEP-IN” questionnaire battery has sufficient retest reliability and validity. 3) The “DEEP-IN” early detection inventory enables the characterization and clustering of specific prodromal courses of depression and the development of a predictive model for forecasting the individual later onset of depression. | — |
Countries
Germany
Contacts
LVR-Klinikum Düsseldorf, Kliniken der Heinrich-Heine-Universität Düsseldorf