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Trait mindfulness is often conceptualized to comprise multiple facets such as attention to and acceptance of present-moment experiences. State mindfulness however is mostly conceptualized as unidimensional. As research on trait mindfulness indicates that differentiating aspects of mindfulness deepens our understanding of its associations with well-being, we tested the presence of four facets at both, the trait and the state level: acting with awareness, nonjudgmental acceptance, present-moment attention, and nonreactivity. Via an experience-sampling technology, 70 participants (aged 20–30 years, 50% female) reported their state mindfulness six times a day for several days. In multiple multilevel confirmatory factor analyses, three of the four facets were corroborated at both levels of analysis. The final three-factor model including acting with awareness, nonjudgmental acceptance, and present-moment attention was superior to a one-factor model implying that state mindfulness can be conceptualized as multidimensional. A multidimensional state assessment will likely be informative for future research questions.

IntroductionCognitive 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.Methods and analysisPREACT-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.Ethics and disseminationThe 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.Trial registration numberDRKS00030915; OSF PREACT: http://osf.io/bcgax; OSF PREACT-digital: https://osf.io/253nb.

Background Internet-based interventions (IBIs) are a low-threshold treatment for individuals with depression. However, comparisons of IBI against unstandardized care-as-usual (CAU) are scarce. Moreover, little evidence is available if IBI has an add-on effect for individuals already receiving an evidence-based treatment such as antidepressants and/or psychotherapy. Method This parallel, two-arm RCT (1:1 allocation ratio, simple randomization) examines the effectiveness of a therapist-guided cognitive-behavioral IBI compared to unstandardized CAU in a self-selected sample of adults (≥ 18 years). Eligible individuals reported (a) mild (BDI-II score ≥ 14) to moderately severe (PHQ-9 ≤ 19) symptoms of depression, (b) no acute suicidal ideations, (c) no acute or lifetime (hypo-)mania and/or symptoms of psychosis. We assigned eligible individuals to an intervention (INT) arm or an unstandardized CAU-arm (i.e., we imposed no restrictions on what individuals were allowed to do in the 8-week waiting period). Individuals in the INT-arm got access to a 7-module CBT-based IBI. The primary endpoint is depressive symptom load 9 to 11 weeks after randomization. Secondary endpoints included anxiety, self-efficacy, and perceived social support. We report effects for the entire sample ( N  = 1899), as well as for individuals using the IBI as a stand-alone intervention ( n  = 1408) or as an add-on to antidepressants ( n  = 367), psychotherapy ( n  = 73), or antidepressants and psychotherapy ( n  = 51). Patients entered the trial with these concurrent treatments (i.e., they were not randomly assigned). Results Concerning all randomized individuals, 62.5% of individuals in the INT-arm accessed all treatment modules within 11 weeks. Individuals assigned to the INT-arm reported significantly lower depressive symptoms (PHQ-9: − 2.5, 95% CI [− 2.9, − 2.0], d  =  − 0.7; BDI-II: − 5.3, 95% CI [− 6.5, − 4.1], d  =  − 0.8) and higher rates of  ≥ 50% symptom improvements (PHQ-9: 38.5% vs. 14.3%; BDI-II: 44.6% vs. 14.8%) compared to individuals assigned to the CAU-arm. Secondary outcomes also favored INT over CAU, with effect sizes ranging from | d |= 0.18 (social support) to 0.62 (anxiety). Rates of deterioration (PHQ-9: 4.1%; BDI-II: 3.4%) and self-reported side effects (10.5%) were low in the INT-arm. Similar patterns emerged for all strata. However, the between-arm differences failed to reach significance within the strata of individuals using the IBI as an add-on to psychotherapy. Conclusion Our results show that providing interested adults access to the therapist-guided, cognitive-behavioral IBI under investigation is associated with improved mental health outcomes, whether individuals use the IBI as a stand-alone or add-on intervention to another evidence-based treatment. This finding aligns with available studies indicating that IBIs should be considered a low-threshold treatment option for individuals with depression. Trial registration The trial was registered at the Deutsches Studienregister (Trial-Registriation Number/DRKS-ID: DRKS00021106, Date: 25.06.2020).

IntroductionMental 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.Methods and analysisThe 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.Ethics and disseminationApproval 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.Registration detailsBefore data collection started in November 2024, the study was registered in the German Clinical Trials Register (https://www.drks.de/search/de/trial/DRKS00035560).

Background Reproductive mood disorders indicate that within-person variation in depressive symptoms across the menstrual cycle can be related to ovarian hormone changes. Until now, such cycle-related symptom changes have been measured once daily, even though depression research indicates systematic diurnal changes in symptoms. Further, previous research often focused on aggregated depression scores. This study examined whether three daily assessments of depressive symptoms follow similar trajectories across the menstrual cycle and investigated within-person cyclical fluctuation of all individual symptoms and the aggregated score. Methods 77 naturally-cycling participants (35 with and 42 without depressive disorder) provided three daily ratings of depressive symptoms across one menstrual cycle to evaluate individual and summarized symptoms. Results Reliability estimates (w) of the three diurnal measurements ranged from 0.56 to 0.78. Cyclicity showed statistically significant interindividual differences for all symptoms, and individual symptoms differed significantly from each other in their magnitude of cyclicity. Limitations Only one menstrual cycle was assessed to reduce participant burden. Further, ovulation testing dates were based on self-reported cycle lengths, and only LH (luteinizing hormone) peaks were tested without subsequent progesterone rises. Conclusions The results highlight the need for a symptom-specific approach to assess individual variance in cyclicity of depressive symptoms. Reliability for one daily assessment can be improved by using the afternoon value, a sum score for depressiveness, or multiple items per symptom. Furthermore, this study emphasizes, that depressive symptoms can systematically change across the menstrual cycle, and it is, therefore, important to include it in depression research. Exploring female-specific risk factors of depression will enable the development of person-tailored treatments. Trial registration The study was preregistered at ClinicalTrials.gov (NCT04086316) with the first registration on 27/08/2019.

The Center of Epidemiologic Studies Depression Scale (CES-D) is a commonly used self-report scale to measure depressive symptoms in the general population. In the present study, the Dutch version of the CES-D was administered to a sample of 837 Dutch-speaking adults of Belgium to examine the factor structure of the scale. Using confirmatory factory analysis (CFA), four first-order models and two second-order models were tested, and the second-order factor model with three pairs of correlated error terms provided the best fit to the data. Second, five socio-demographic variables (age, gender, education level, relation status, and family history of depression) were included as covariates to the second-order factor model to explore the associations between background characteristics and the latent factor depression using a multiple indicators and multiple causes (MIMIC) approach. Age had a significantly negative effect on depression, but the effect was not substantial. Female gender, lower education level, being single or widowed, and having a family history of depression were found to be significant predictors of higher levels of depression symptomatology. Finally, percentile norms on the CES-D raw scores were provided for subgroups of gender by education level for the general Dutch-speaking adult population of Belgium.

Contextual factors shape emotion regulation (ER). The intensity of emotional stimuli may be such a contextual factor that influences the selection and moderates the effectiveness of ER strategies in reducing negative affect (NA). Prior research has shown that, on average, when emotional stimuli were more intense, distraction was selected over reappraisal (and vice versa). This pattern was previously shown to be adaptive as the preferred strategies were more efficient in the respective contexts. Here, we investigated whether stressor intensity predicted strategy use and effectiveness in similar ways in daily life. We examined five ER strategies (reappraisal, reflection, acceptance, distraction, and rumination) in relation to the intensity of everyday stressors, using two waves of experience-sampling data ( N  = 156). In accordance with our hypotheses, reappraisal, reflection, and acceptance were used less, and rumination was used more, when stressors were more intense. Moreover, results suggested that distraction was more effective, and rumination more detrimental the higher the stressor intensity. Against our hypotheses, distraction did not covary with stressor intensity, and there was no evidence that reappraisal, reflection, and acceptance were more effective at lower levels of stressor intensity. Instead, when examined individually, reflection and reappraisal (like distraction) were more effective at higher levels of stressor intensity. In sum, stressor intensity predicted ER selection and moderated strategy effectiveness, but the results also point to a more complex ER strategy use in daily life than in the laboratory.

Past research has shown a positive association between education and well-being. Much of this research has focused on the cognitive component of well-being (i.e., life satisfaction) as outcome. On the other hand, the affective component, that is, how often and intensively people experience positive affect (PA) and negative affect (NA) in their everyday lives, has received far less attention. Therefore, we examined the association between education and PA and NA in everyday life, with a particular focus on affective experiences at the sub-facet level (based on a structure of NA with multiple factors). We used data from a nationally representative sample (N = 1647) of the German Socioeconomic Panel Innovation Sample (SOEP-IS), employing the Day Reconstruction Method (DRM) to capture affective experiences of everyday activities. Multilevel structural equation models revealed that (1) education was not related to PA, but (2) was positively associated with two sub-facets of NA (mourning/worries and loneliness/boredom); (3) income might in part explain the association between education and NA; (4) education does not particularly seem to serve as a resource in times of unemployment or retirement (i.e., there were no interactions between education and unemployment/retirement regarding well-being) In essence, higher educated people reported fewer negative emotions in everyday life than their lower educated counterparts, but not more positive emotions. The findings underline that different facets of NA, in addition to life satisfaction, are relevant variables related to education and should receive more attention in order to gain a more comprehensive understanding of non-monetary correlates of education. (DIPF/Orig.).

In the last years, there has been a shift from traditional measurements of affective well-being to approaches such as the day reconstruction method (DRM). While the traditional approaches often assess trait level differences in well-being, the DRM allows examining affective dynamics in everyday contexts. The latter may ultimately explain why some people feel more happy than others (e.g., because they experience more gratification during everyday experiences). Even though DRM research has increased in the last years, little is known about the structure of affective well-being in everyday life, and potential structural differences of affect at the within- and between-person level have rarely been considered. We thus thoroughly examined the structure of affective well-being in daily life, using data from a nationally representative sample (N = 2401) of the German Socioeconomic Panel Innovation Sample that were obtained with the DRM. Multilevel structural equation models revealed that (1) affective well-being in daily life cannot be reduced to the two global dimensions positive and negative affect (PA and NA) but that the structure of NA is more nuanced; (2) the emerging subfacets of NA have distinct associations with global indicators of well-being (e.g., life satisfaction); (3) there are structural differences of affective well-being at the within- and between-person level, and (4) the relationships between affect subfacets and activities such as “work” can be opposed at the within- and between-person level. These results show that a more differentiated view on the structure of affect contributes to a better understanding of affective well-being in everyday life.

This study investigates the proposition that micro-level experiences in the realm of stress (e.g., daily stress exposure) are among the building blocks of maladjustment, in particular, depression. Data were collected with experience sampling methods and in the lab. A sample of 202 students who had just entered university participated in a three-wave longitudinal study (October 2012-October 2013). Each wave consisted of the assessment of depressive symptoms and the examination of stressful experiences in daily life by means of experience sampling (70 occasions per wave). Cross-lagged panel models revealed that the perceived intensity of daily stressors, stressed and depressed feelings in daily life, as well as depressed reactions to daily stressors predict an increase in future depressive symptoms in young females but not males. Other cross-lagged effects, particularly from depressive symptoms to stressful experiences in daily life, were not significant. Findings are in line with the stress exposure model according to which stress can cause increases in depressive symptoms. Importantly, this study focused on stressful experiences in daily life. Micro-level experiences thus seem to be among the etiological factors of depression. We discuss consequences of these findings and possibilities to alleviate the burden of depression in individuals and society.