Status:
COMPLETED
Predicting Premature Treatment Termination in Inpatient Psychotherapy: A Machine Learning Approach
Lead Sponsor:
University Hospital Heidelberg
Conditions:
Premature Treatment Termination
Dropout Prediction
Eligibility:
All Genders
18+ years
Brief Summary
The study aims to develop a prediction model of premature treatment termination in psychosomatic hospitals using a machine learning approach.
Detailed Description
The aim of the study is to identify risk factors that lead to or predict premature treatment termination in psychosomatic hospitals. In the long-term, the study shall help to develop more precise pred...
Eligibility Criteria
Inclusion
- patients of at least 18 years of age
- included in inpatient psychotherapy treatment program in a hospital for psychosomatic medicine
- provided information about admission and discharge date
Exclusion
- bipolar, acute psychotic or substance abuse disorder
Key Trial Info
Start Date :
January 1 2015
Trial Type :
OBSERVATIONAL
Allocation :
ACTUAL
End Date :
January 1 2022
Estimated Enrollment :
2023 Patients enrolled
Trial Details
Trial ID
NCT06042595
Start Date
January 1 2015
End Date
January 1 2022
Last Update
September 18 2023
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