Multivariate identification of disease-specific electrophysiological biomarkers for computerized differential diagnosis, monitoring and long-term assessment of burnout and fatigue - Exploratory study

Recruiting

Conditions: fatigue, depression, burnout

Registration Number: DRKS00032315

Lead Sponsor: Charité - Universitätsmedizin Berlin, Klinik für Pädiatrie mit Schwerpunkt Onkologie und Hämatologie

Brief Summary: Not available

Detailed Description: Not available

Recruitment & Eligibility

Status: Recruiting

Sex: All

Target Recruitment: 192

Inclusion Criteria

Gender: men and women (~50%, ~50%)
All patients will be clinically diagnosed before they can participate in the study
Electrophysiological measurements are performed at rest in untreated patients (diagnosed but not treated)
Clear diagnosis for fatigue, burnout and depression are available (clinical questionnaires, ICD, specialist diagnosis)
Clear definitions of the groups (ICD) + clinical questionnaires
Written consent of the participants
Written consent of the participants for the transfer of pseudonymized data in the context of the documentation.
Capacity to give consent

Exclusion Criteria

Serious physiological or psychiatric pre-existing/co-existing medical condition.
Other pre-existing diseases and health conditions that could interfere with the subject's ability to receive treatment according to the study plan
Participation in other studies to the extent that they interfere with study participation

Study & Design

Study Type: observational

Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
The present study aims at the multifactorial assessment of fatigue, burnout and depression, and investigates various influencing factors associated with fatigue, burnout and depression in order to identify specific electrophysiological biomarkers characteristic of fatigue, burnout and depression, which will contribute to the targeted, inexpensive and effective differential diagnosis and long-term assessment of disease progression. It is envisioned to create an objective, non-invasive tool (computer-aided diagnostic finding) that can be used for clinical prediction and diagnosis of fatigue, burnout, and depression, and grading into severity levels.

Secondary Outcome Measures