Predicting Premature Treatment Termination in Inpatient Psychotherapy: A Machine Learning Approach

NCT06042595 | Completed

• 1 other identifier: Dropout-Prediction-2023
• Study Type: observational
• Target: 2,023
• Locations: 0 countries
• Sites: N/A

Brief Summary

The study aims to develop a prediction model of premature treatment termination in psychosomatic hospitals using a machine learning approach.

Conditions

Premature Treatment Termination; Dropout Prediction; Inpatient Psychotherapy; Machine Learning

Outcome Measures

Primary Outcomes (1)

• Premature treatment termination (vs. treatment completion)

  Premature treatment termination will be classified based on the treatment duration. Classification will be made retrospectively for each patient based on the duration of the inpatient treatment and if applicable (duration \< 49 days) on the hospital discharge letter to screen for reasons of the shorter treatment duration.

  Premature treatment termination will be operationalized as a dummy variable. Regular treatment duration is 8 weeks of inpatient psychotherapy. Data will be reported for 7 years of continuous study enrolment (01/2015 - 01/2022).

Interventions

Psychotherapy BEHAVIORAL

Patients treated at the inpatient psychotherapy unit of the University Hospital receive 8 to 10 weeks of multimodal psychotherapeutic treatment. Treatment consists of individual as well as group psychodynamic therapy. Additionally, patients receive an individual combination of music, art, relaxation and body-oriented group therapy. Therapeutic treatment is provided by a multiprofessional, interdisciplinary team of psychotherapists with either a medical or psychology degree, art and music therapists, specialist nurses, social workers, and physiotherapists.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population consists of patients being treated at the inpatient unit of University Hospital Heidelberg, department for psychosomatic medicine.

You may qualify if:

• 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

You may not qualify if:

• bipolar, acute psychotic or substance abuse disorder

Sponsors & Collaborators

• University Hospital Heidelberg: lead

MeSH Terms

Interventions

Psychotherapy

Intervention Hierarchy (Ancestors)

Behavioral Disciplines and Activities

Study Officials

• Ulrike Dinger-Ehrenthal, Prof. Dr.

  Department of Psychosomatic Medicine and Psychotherapy, Medical Faculty, Heinrich-Heine University Düsseldorf

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: August 11, 2023
• First Posted: September 18, 2023
• Study Start: January 1, 2015
• Primary Completion: January 1, 2022
• Study Completion: January 1, 2022
• Last Updated: September 18, 2023

Record last verified: 2023-09

Data Sharing

• IPD Sharing: Will not share