Select or adjust? How information from early treatment stages boosts the prediction of non-response in internet-based depression treatment

Background Internet-based interventions produce comparable effectiveness rates as face-to-face therapy in treating depression. Still, more than half of patients do not respond to treatment. Machine learning (ML) methods could help to overcome these low response rates by predicting therapy outcomes on an individual level and tailoring treatment accordingly. Few studies implemented ML algorithms in internet-based depression treatment using baseline self-report data, but differing results hinder inferences on clinical practicability. This work compares algorithms using features gathered at baseline or early in treatment in their capability to predict non-response to a 6-week online program targeting depression. Methods Our training and test sample encompassed 1270 and 318 individuals, respectively. We trained random forest algorithms on self-report and process features gathered at baseline and after 2 weeks of treatment. Non-responders were defined as participants not fulfilling the criteria for reliable and clinically significant change on PHQ-9 post-treatment. Our benchmark models were logistic regressions trained on baseline PHQ-9 sum or PHQ-9 early change, using 100 iterations of randomly sampled 80/20 train-test-splits. Results Best performances were reached by our models involving early treatment characteristics (recall: 0.75–0.76; AUC: 0.71–0.77). Therapeutic alliance and early symptom change constituted the most important predictors. Models trained on baseline data were not significantly better than our benchmark. Conclusions Fair accuracies were only attainable by involving information from early treatment stages. In-treatment adaptation, instead of a priori selection, might constitute a more feasible approach for improving response when relying on easily accessible self-report features. Implementation trials are needed to determine clinical usefulness

TONI - One for all? Participatory development of a transtheoretic and transdiagnostic online intervention for blended care

Background Internet-based interventions offer a way to meet the high demand for psychological support. However, this setting also has disadvantages, such as the lack of personal contact and the limited ability to respond to crises. Blended care combines Internet-based interventions with face-to-face psychotherapy and merges the benefits of both settings. To ensure the uptake of blended care in routine care, Internet-based interventions need to be suitable for different therapeutic approaches and mental disorders. Objective This paper describes the participatory development process of the Internet-based intervention “TONI” using a common therapeutic language and content on various transdiagnostic topics to be integrated into routine outpatient psychotherapy. Methods To develop this intervention in a participatory manner, we followed the Integrate, Design, Assess, and Share (IDEAS) framework. In a multilevel development process, we used a combination of interviews, focus groups, and proofreading to optimally tailor online modules to routine outpatient psychotherapy. Building on well-established cognitive-behavioral online content, we included expert interviews with psychodynamic (n = 20) and systemic psychotherapists (n = 9) as well as focus groups with psychotherapists of different approaches (n = 10) and persons with lived experience of mental illness (PWLE; n = 10). Results We describe the development process of TONI step-by-step, outlining the specific requirements that therapists from different therapeutic approaches as well as PWLE have and how we implemented them in our intervention. This includes the content and specific exercises in the online modules, aspects of data protection, language, design, and usability. Conclusion Internet-based interventions that use a common therapeutic language and address therapeutic principles across different approaches have the potential to advance digitalization in psychotherapy. Involving psychotherapists and PWLE in intervention development may positively impact acceptance and usage in practice. This study shows how participatory intervention development involving both psychotherapists and PWLE can be carried out

Increasing the effectiveness of psychotherapy in routine care through blended therapy with transdiagnostic online modules (PsyTOM): study protocol for a randomized controlled trial

Background In blended therapy, face-to-face psychotherapy and Internet-based interventions are combined. Blended therapy may be advantageous for patients and psychotherapists. However, most blended interventions focus on cognitive behavioral therapy or single disorders, making them less suitable for routine care settings. Methods In a randomized controlled trial, we will compare blended therapy and face-to-face therapy in routine care. We intend to randomize 1152 patients nested in 231 psychotherapists in a 1:1 ratio. Patients in the blended therapy group will receive access to a therapeutic online intervention (TONI). TONI contains 12 transdiagnostic online modules suited for psychodynamic, cognitive behavioral, and systemic therapy. Psychotherapists decide which modules to assign and how to integrate TONI components into the psychotherapeutic process to tailor treatment to their patients’ specific needs. We will assess patients at baseline, 6 weeks, 12 weeks, and 6 months. Patients enrolled early in the trial will also complete assessments at 12 months. The primary outcomes are depression and anxiety at 6-month post-randomization, as measured by PHQ-8 and GAD-7. The secondary outcomes include satisfaction with life, level of functioning, personality traits and functioning, eating pathology, sexual problems, alcohol/drug use, satisfaction with treatment, negative effects, and mental health care utilization. In addition, we will collect several potential moderators and mediators, including therapeutic alliance, agency, and self-efficacy. Psychotherapists will also report on changes in symptom severity and therapeutic alliance. Qualitative interviews with psychotherapists and patients will shed light on the barriers and benefits of the blended intervention. Furthermore, we will assess significant others of enrolled patients in a sub-study. Discussion The integration of online modules which use a common therapeutic language and address therapeutic principles shared across therapeutic approaches into regular psychotherapy has the potential to improve the effectiveness of psychotherapy and transfer it into everyday life as well help save therapists’ resources and close treatment gaps. A modular and transdiagnostic setup of the blended intervention also enables psychotherapists to tailor their treatment optimally to the needs of their patients

Zur Erinnerung an den verstorbenen Direktor, Herrn Dr. Peter Doetsch

von dem Direktor Joh. HammelrathProgr.-Nr. 52

Grammatisch - stilistische Beiträge zu den prosaischen Schriften des L. Annäus Seneca

von HammelrathText. teilw. dt., teilw. lat.Progr.-Nr. 45

Rede des Direktors, gehalten am 27. Januar 1906

des DirektorsProgr.-Nr. 54