Why are some cases not on track? An item analysis of the Assessment for Signal Cases during inpatient psychotherapy

Probst, Thomas and Kleinstaeuber, Maria and Lambert, Michael J. and Tritt, Karin and Pieh, Christoph and Loew, Thomas H. and Dahlbender, Reiner W. and Delgadillo, Jaime (2020) Why are some cases not on track? An item analysis of the Assessment for Signal Cases during inpatient psychotherapy. CLINICAL PSYCHOLOGY & PSYCHOTHERAPY, 27 (4). pp. 559-566. ISSN 1063-3995, 1099-0879

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Abstract

Within the Routine Outcome Monitoring system "OQ-Analyst," the questionnaire "Assessment for Signal Cases" (ASC) supports therapists in detecting potential reasons for not-on-track trajectories. Factor analysis and a machine learning algorithm (LASSO with 10-fold cross-validation) were applied, and potential predictors of not-on-track classifications were tested using logistic multilevel modeling methods. The factor analysis revealed a shortened (30 items) version of the ASC with good internal consistency (alpha= 0.72-0.89) and excellent predictive value (area under the curve = 0.98; positive predictive value = 0.95; negative predictive value = 0.94). Item-level analyses showed that interpersonal problems captured by specific ASC items (not feeling able to speak about problems with family members; feeling rejected or betrayed) are the most important predictors of not-on-track trajectories. It should be considered that our results are based on analyses of ASC items only. Our findings need to be replicated in future studies including other potential predictors of not-on-track trajectories (e.g., changes in medication, specific therapeutic techniques, or treatment adherence), which were not measured this study.

Item Type: Article
Uncontrolled Keywords: CLINICAL SUPPORT TOOLS; EXPECTED RECOVERY CURVES; PROGRESS FEEDBACK; TREATMENT FAILURE; PATIENT PROGRESS; SOCIAL SUPPORT; LIFE EVENTS; RISK; CLIENTS; THERAPISTS; Assessment for Signal Cases; progress feedback; psychotherapy; routine outcome monitoring
Subjects: 600 Technology > 610 Medical sciences Medicine
Divisions: Medicine > Abteilung für Psychosomatische Medizin
Depositing User: Dr. Gernot Deinzer
Date Deposited: 19 Mar 2021 08:16
Last Modified: 19 Mar 2021 08:16
URI: https://pred.uni-regensburg.de/id/eprint/44271

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