Cited by 197Digital Mental Health InterventionsAnxiety, Depression, Psychometrics, Treatment, Cognitive ProcessesPsychotherapy Techniques and Applications

Towards integrating personalized feedback research into clinical practice: Development of the Trier Treatment Navigator (TTN)

Lutz, Wolfgang, Rubel, Julian A., Schwartz, Brian, Schilling, Viola, Deisenhofer, Anne-Katharina·2019·Behaviour Research and Therapy

Abstract

In this study, a computer-based feedback, decision and clinical problem-solving system for clinical practice will be described - the Trier Treatment Navigator (TTN). The paper deals with the underlying research concepts related to personalized pre-treatment recommendations for drop-out risk and optimal treatment strategy selection as well as personalized adaptive recommendations during treatment. The development sample consisted of 1234 patients treated with cognitive behavioral therapy (CBT). Modern statistical machine learning techniques were used to develop personalized recommendations. Drop-out analyses resulted in seven significant predictors explaining 12.0% of variance. The prediction of optimal treatment strategies resulted in differential prediction models substantially improving effect sizes and reliable improvement rates. The dynamic failure boundary reliably identified patients with a higher risk for no improvement or deterioration and indicated the usage of clinical problem-solving tools in risk areas. The probability to be reliably improved for patients identified as at risk for treatment failure was about half of the probability for other patients (35% vs. 62.15%; χ 2df=1 = 82.77, p < .001). Results related to the computer-based feedback system are discussed with regard to the implication for clinical applications as well as clinical training and future research possibilities.

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Crossref · 10.1016/j.brat.2019.103438

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Authors
Lutz, W., Rubel, J. A., Schwartz, B., Schilling, V., & Deisenhofer, A.-K.
Affiliations
Universität Trier (DE)
Corresponding author
Lutz, Wolfgang
Venue
Behaviour Research and Therapy
Publisher
Elsevier BV
Published
2019-09
Volume
120
Pages
103438
ISSN
0005-7967 (ISSN-L)
OpenAlex
W2956805281
Cited by
196
References
54
Citations by year
2026: 18 · 2025: 26 · 2024: 39 · 2023: 25 · 2022: 22 · 2021: 34 · 2020: 25 · 2019: 7
FWCI
24.91
Type
journal article
Language
en
Open access
closed
Locations
  • Behaviour Research and Therapy (publishedVersion)
  • PubMed (publishedVersion)
Funders
Deutsche Forschungsgemeinschaft (LU 660/8-1, LU 660/10-1)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
  • Social Sciences › Psychology › Clinical Psychology › Psychotherapy Techniques and Applications
Keywords
personalized feedback, cognitive behavioral therapy, treatment strategy selection, clinical problem solving, computer-based decision support, treatment failure prediction, clinical teaching, machine learning prediction models
MeSH terms
Clinical Decision-Making, Machine Learning, Adjustment Disorders, Adolescent, Adult, Aged, Anxiety Disorders, Mental Disorders, Feedback, Female, Humans, Male, Middle Aged, Patient Dropouts, Personality Disorders, Problem Solving, Surveys and Questionnaires, Stress Disorders, Post-Traumatic, Cognitive Behavioral Therapy, Mood Disorders, Decision Support Systems, Clinical, Young Adult, Precision Medicine

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