Mental disorders are among the leading causes of the global burden of disease and are often associated with severe functional impairment and high societal costs. Psychotherapeutic, psychopharmacological and internet-based mental health interventions have proven to be helpful, but challenges remain, including only moderate response rates, high relapse rates and barriers to accessing mental healthcare. Much of the existing evidence stems from studies conducted in controlled, often standardised settings that only partially reflect real-world conditions, contributing to a ‘scientist-practitioner gap’. Moreover, the mechanisms of change, such as the interaction between treatment intensity, common factors (eg, the therapeutic relationship) and specific intervention techniques, have not been sufficiently investigated. In particular, the relationship of changes in personality functioning (PF) with mental and physical health has not yet been extensively researched.

The PSYMPACT (Psychological Impact Factors of Mental Health Treatments) study will use a longitudinal study design with a naturalistic sample (N 3000) to examine changes in psychopathology, PF and allostatic load in psychotherapeutic, psychopharmacological and internet-based treatments. The aim is to identify factors contributing to improvements and deteriorations in mental and physical health across different settings, including common and specific factors. Additionally, to provide patient perspectives, qualitative interviews will be conducted with individuals with varying levels of severity of mental health problems. Allostatic load will be assessed using repeated hair cortisol measurements. Furthermore, ecological momentary assessment will be used to examine the diurnal variability of PF as well as its more momentary correlates and longer-term outcomes. The central research questions and aims include (1) the assessment of common factors across different treatment settings, (2) associations of specific and common factors with improvements in mental health, including PF, (3 and 4) the importance of treatment intensity and interaction effects with common and specific factors, (5) the association of changes in psychopathology with changes in allostatic load, (6) the trait and state variability of PF, (7) the identification of patients who deteriorate under specific treatments and (8) patients’ perspectives on the effectiveness of different treatment modalities.

Approval was obtained from the Ethics Committee of the Department of Education and Psychology at the Freie Universität Berlin, Germany. Results will be submitted to peer-reviewed specialised journals and presented at national and international conferences.

Before data collection started in November 2024, the study was registered in the German Clinical Trials Register (https://www.drks.de/search/de/trial/DRKS00035560).

Cognitive behavioural therapy (CBT) serves as a first-line treatment for internalising disorders (ID), encompassing depressive, anxiety or obsessive-compulsive disorders. Nonetheless, a substantial proportion of patients do not experience sufficient symptom relief. Recent advances in wearable technology and smartphone integration enable new, ecologically valid approaches to capture dynamic processes in real time. By combining ecological momentary assessment (EMA) with passive sensing of behavioural and physiological information, this project seeks to track daily fluctuations in symptom-associated constructs like affect, emotion regulation (ER) and physical activity. Our central goal is to determine whether dynamic, multimodal markers derived from EMA and passive sensing can predict treatment non-response and illuminate key factors that drive or hinder therapeutic change.

PREACT-digital is a subproject of the Research Unit FOR 5187 (PREACT), a large multicentre observational study in four outpatient clinics. PREACT channels state-of-the-art machine learning techniques identify predictors of non-response to CBT in ID. The study is currently running and will end in June 2026. Patients seeking CBT at one of four participating outpatient clinics are invited to join PREACT-digital. They can take part in (1) a short version with a 14-day EMA and passive sensing phase prior to therapy, or (2) a long version in which the short version’s assessments are extended throughout the therapy. It is estimated that 468 patients take part in PREACT-digital, of which 350 opt for the long version of the study. Participants are provided with a smartwatch and a customised study app. We collect passive data on heart rate, physical activity, sleep and location patterns. EMA assessments cover affect, ER strategies, context and therapeutic agency. Primary outcomes on (non)-response are assessed after 20 therapy sessions and therapy end. We employ predictive and exploratory analyses. Predictive analyses focus on classification of non-response using basic algorithms (ie, logistic regression and gradient boosting) for straightforward interpretability and advanced methods (LSTM, DSEM) to capture complex temporal and hierarchical patterns. Exploratory analyses investigate mechanistic links, examine the interplay of variables over time and analyse change trajectories. Study findings will inform more personalised and ecologically valid approaches to CBT for ID.

The study has received ethical approval from the Institutional Ethics Committee of the Department of Psychology at Humboldt Universität zu Berlin (Approval No. 2021–01) and the Ethics Committee of Charité-Universitätsmedizin Berlin (Approval No. EA1/186/22). Written informed consent will be obtained from all participants prior to enrolment. Results will be disseminated through peer-reviewed journals and presentations at national and international conferences.

DRKS00030915; OSF PREACT: http://osf.io/bcgax; OSF PREACT-digital: https://osf.io/253nb.