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Prevention of depression is a priority to reduce its global disease burden. Targeting specific risk factors, such as rumination, may improve prevention. Rumination-focused Cognitive Behavioral Therapy (RFCBT) was developed to specifically target depressive rumination. The primary objective of this study was to test whether guided Web-based RFCBT (i-RFCBT) would prevent the incidence of major depression relative to usual care in UK university students. The secondary objective was to test the feasibility and estimated effect sizes of unguided i-RFCBT. To address the primary objective, a phase III randomized controlled trial was designed and powered to compare high risk university students (N=235), selected with elevated worry/rumination, recruited via an open access website in response to circulars within universities and internet advertisements, randomized to receive either guided i-RFCBT (interactive Web-based RFCBT, supported by asynchronous written Web-based support from qualified therapists) or usual care control. To address the secondary objective, participants were also randomized to an adjunct arm of unguided (self-administered) i-RFCBT. The primary outcome was the onset of a major depressive episode over 15 months, assessed with structured diagnostic interviews at 3 (postintervention), 6, and 15 months post randomization, conducted by telephone, blind to the condition. Secondary outcomes of symptoms of depression and anxiety and levels of worry and rumination were self-assessed through questionnaires at baseline and the same follow-up intervals. Participants were randomized to guided i-RFCBT (n=82), unguided i-RFCBT (n=76), or usual care (n=77). Guided i-RFCBT reduced the risk of depression by 34% relative to usual care (hazard ratio [HR] 0.66, 95% CI 0.35 to 1.25; P=.20). Participants with higher levels of baseline stress benefited most from the intervention (HR 0.43, 95% CI 0.21 to 0.87; P=.02). Significant improvements in rumination, worry, and depressive symptoms were found in the short-to-medium term. Of the 6 modules, guided participants completed a mean of 3.46 modules (SD 2.25), with 46% (38/82) being compliant (completing ≥4 modules). Similar effect sizes and compliance rates were found for unguided i-RFCBT. Guided i-RFCBT can reduce the onset of depression in high-risk young people reporting high levels of worry/rumination and stress. The feasibility study argues for formally testing unguided i-RFCBT for prevention: if the observed effect sizes are robustly replicated in a phase III trial, it has potential as a scalable prevention intervention. ISRCTN Registry ISRCTN12683436; https://www.isrctn.com/ISRCTN12683436 (Archived by WebCite at http://www.webcitation.org/77fqycyBX). RR2-10.1186/s13063-015-1128-9.

Cognitive rumination, a transdiagnostic symptom across mental health disorders, has traditionally been assessed through self-report measures. However, these measures are limited by their temporal nature and subjective bias. The rise in wearable technologies offers the potential for continuous, real-time monitoring of physiological indicators associated with rumination. This scoping review investigates the current state of research on using wearable technology to detect cognitive rumination. Specifically, we examine the sensors and wearable devices used, physiological biomarkers measured, standard measures of rumination used, and the comparative validity of specific biomarkers in identifying cognitive rumination. The review was performed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines on IEEE, Scopus, PubMed, and PsycInfo databases. Studies that used wearable devices to measure rumination-related physiological responses and biomarkers were included (n = 9); seven studies assessed one biomarker, and two studies assessed two biomarkers. Electrodermal Activity (EDA) sensors capturing skin conductance activity emerged as both the most prevalent sensor (n = 5) and the most comparatively valid biomarker for detecting cognitive rumination via wearable devices. Other commonly investigated biomarkers included electrical brain activity measured through Electroencephalogram (EEG) sensors (n = 2), Heart Rate Variability (HRV) measured using Electrocardiogram (ECG) sensors and heart rate fitness monitors (n = 2), muscle response measured through Electromyography (EMG) sensors (n = 1) and movement measured through an accelerometer (n = 1). The Empatica E4 and Empatica Embrace 2 wrist-worn devices were the most frequently used wearable (n = 3). The Rumination Response Scale (RRS), was the most widely used standard scale for assessing rumination. Experimental induction protocols, often adapted from Nolen-Hoeksema and Morrow’s 1993 rumination induction paradigm, were also widely used. In conclusion, the findings suggest that wearable technology offers promise in capturing real-time physiological responses associated with rumination. However, the field is still developing, and further research is needed to validate these findings and explore the impact of individual traits and contextual factors on the accuracy of rumination detection.

Background Rumination plays a pivotal role in the onset, recurrence, and persistence of residual symptoms in major depressive disorder (MDD), making it a critical therapeutic target in the development of novel interventions. Rumination-Focused Cognitive-Behavioral Therapy (RFCBT), an adapted form of cognitive-behavioral therapy specifically designed to address ruminative thinking patterns, has garnered increasing attention in clinical research. In light of these developments, the present study was conducted to evaluate the efficacy of RFCBT in reducing rumination severity, depressive symptoms, and negative affect among individuals with recurrent MDD. Methods This randomized clinical trial enrolled 44 university students diagnosed with MDD. Participants were randomly assigned in equal proportions to either the group-based Rumination-Focused Cognitive-Behavioral Therapy (g-RFCBT) condition or a waitlist (WL) control group. The g-RFCBT received 10 weekly group therapy sessions supplemented by two individual sessions (the initial session and the 12th session), while participants in the WL group received no intervention until the conclusion of the study. Assessments were conducted at four time points; pre-treatment, post-treatment, 2-month follow-up, and 6-month follow-up. Outcome measures included the Beck Depression Inventory-II (BDI-II), the Repetitive Thinking Questionnaire-31 (RTQ-31), and the Negative Affect subscale of the Positive and Negative Affect Schedule (PANAS-NA). Results Repeated measures ANOVA revealed statistically significant improvements in the g-RFCBT group compared to the WL group. Within-group analyses indicated that RFCBT led to a 65% reduction in depressive symptoms and a 30% reduction in both rumination and negative affect from baseline to post-treatment. Furthermore, the g-RFCBT exhibited significantly greater reduction in depression, rumination, and negative affect compared to the WL group, with treatment effects sustained through the 6-month follow-up period. Conclusions Group-based Rumination-Focused Cognitive-Behavioral Therapy (g-RFCBT) demonstrated significant efficacy in reducing the severity of depressive symptoms, rumination, and negative affect among individuals with major depressive disorder (MDD). Moreover, these therapeutic benefits were maintained over a 6-month follow-up period, suggesting durable treatment effects. Trial registration This randomized clinical trial, consisting of an intervention and a waitlist control condition, that was registered in the Iranian Registry of Clinical Trials (IRCT Id: IRCT20181117041676N1) (Registration Date: June 3, 2019). Graphical Abstract

Cognitive behavioral therapy (CBT) and pharmacotherapy are primary treatments for major depressive disorder (MDD). However, their differential effects on the neural networks associated with rumination, or repetitive negative thinking, remain poorly understood. This study included 135 participants, whose rumination severity was measured using the rumination response scale (RRS) and whose resting brain activity was measured using functional magnetic resonance imaging (fMRI) at baseline and after 16 weeks. MDD patients received either standard CBT based on Beck’s manual (n = 28) or pharmacotherapy (n = 32). Using a hidden Markov model, we observed that MDD patients exhibited increased activity in the default mode network (DMN) and decreased occupancies in the sensorimotor and central executive networks (CEN). The DMN occurrence rate correlated positively with rumination severity. CBT, while not specifically designed to target rumination, reduced DMN occurrence rate and facilitated transitions toward a CEN-dominant brain state as part of broader therapeutic effects. Pharmacotherapy shifted DMN activity to the posterior region of the brain. These findings suggest that CBT and pharmacotherapy modulate brain network dynamics related to rumination through distinct therapeutic pathways.

Adopting the information processing perspective, the current study aims to investigate the differential effects of affective and cognitive ruminations on individuals’ affective states and learning behavior, and to further explore their differential mediating roles in transmitting effects of challenge and hindrance stressors on affect and behavior. A two-wave survey, in which stressors and ruminations were measured in the first wave and affective states and learning behavior were measured in the second, was conducted to obtain responses from 410 employees. As expected, affective and cognitive ruminations were differently associated with challenge stressors (i.e., cognitive job insecurity) and hindrance stressors (i.e., interpersonal conflict), and yielded different effects in terms of positive affect, negative affect, and learning behavior. Specifically, the results showed that: (a) cognitive job insecurity was significantly and positively related to cognitive rumination, while interpersonal conflict was significantly and positively related to affective rumination; (b) affective and cognitive ruminations were significantly associated with positive or negative affect, but in the exact opposite direction; (c) cognitive rumination, but not affective rumination, was significantly related to learning behavior; and (d) cognitive rumination mediated the effect of cognitive job insecurity on positive affect and learning behavior, while affective rumination mediated the effect of interpersonal conflict on negative affect. The current study contributes to the literature on rumination by introducing a new perspective, and sheds new light on the understanding of how and why affective and cognitive ruminations may lead to different affective states and behaviors.

The objective of the present study was to establish the heritability of pain catastrophizing and its subdomains of helplessness, magnification, and rumination and to further explore the genetic and environmental sources that may contribute to pain catastrophizing as well as to its commonly reported psycho-affective correlates, including neuroticism, anxiety sensitivity, and fear of pain. N = 2,401 female twin individuals from the TwinsUK registry were subject to univariate and multivariate twin analyses. Well validated questionnaires including the Pain Catastrophizing Scale, the Pain Anxiety Symptom Scale, the Ten Item Personality Index, and the Anxiety Sensitivity Index were used to assess the study variables. Moderate estimates of heritability for pain catastrophizing (36%) and the three subdomains of helplessness (35%), rumination (27%), and magnification (36%) were detected. The high correlations observed between the three subdomains were explained mainly by overlapping genetic factors, with a single factor loading on all three phenotypes. High genetic correlations between pain catastrophizing and its psycho-affective correlates of fear of pain and anxiety sensitivity were found, while the genetic overlap between neuroticism and pain catastrophizing was low. Each measure of negative affect demonstrated relatively distinct environmental contributing factors, with very little overlap. This is the first study to show shared genetic factors in the observed association between pain catastrophizing and other measures of negative affect. Our findings provide deeper insight into the aetiology of pain catastrophizing and confirm that it is at least partially distinct from other measures of negative affect and personality that may influence the development and treatment of chronic pain conditions. Further research in males is warranted to check the comparability of the findings.

Rumination is strongly and consistently correlated with depression. Although multiple studies have explored the neural correlates of rumination, findings have been inconsistent and the mechanisms underlying rumination remain elusive. Functional brain imaging studies have identified areas in the default mode network (DMN) that appear to be critically involved in ruminative processes. However, a meta-analysis to synthesize the findings of brain regions underlying rumination is currently lacking. Here, we conducted a meta-analysis consisting of experimental tasks that investigate rumination by using Signed Differential Mapping of 14 fMRI studies comprising 286 healthy participants. Furthermore, rather than treat the DMN as a unitary network, we examined the contribution of three DMN subsystems to rumination. Results confirm the suspected association between rumination and DMN activation, specifically implicating the DMN core regions and the dorsal medial prefrontal cortex subsystem. Based on these findings, we suggest a hypothesis of how DMN regions support rumination and present the implications of this model for treating major depressive disorder characterized by rumination. •Rumination is strongly and consistently correlated with depression.•Meta-analyze the findings of brain regions regarding to rumination.•Specifically examined the contribution of three DMN subsystems to rumination.•Rumination is specifically correlated with the DMN core regions and the dorsal medial prefrontal cortex subsystem.

Childhood maltreatment is associated with increased risk for most forms of psychopathology. We examine emotion dysregulation as a transdiagnostic mechanism linking maltreatment with general psychopathology. A sample of 262 children and adolescents participated; 162 (61.8%) experienced abuse or exposure to domestic violence. We assessed four emotion regulation processes (cognitive reappraisal, attention bias to threat, expressive suppression, and rumination) and emotional reactivity. Psychopathology symptoms were assessed concurrently and at a 2-year longitudinal follow-up. A general psychopathology factor (p factor), representing co-occurrence of psychopathology symptoms across multiple internalizing and externalizing domains, was estimated using confirmatory factor analysis. Maltreatment was associated with heightened emotional reactivity and greater use of expressive suppression and rumination. The association of maltreatment with attention bias varied across development, with maltreated children exhibiting a bias toward threat and adolescents a bias away from threat. Greater emotional reactivity and engagement in rumination mediated the longitudinal association between maltreatment and increased general psychopathology over time. Emotion dysregulation following childhood maltreatment occurs at multiple stages of the emotion generation process, in some cases varies across development, and serves as a transdiagnostic mechanism linking child maltreatment with general psychopathology.

Background Rumination has been thought to relate to deficits in core executive functions (EFs), but the empirical findings for this idea are mixed. The aim of the present study is to synthesize existing literature to clarify these relations. Methods A comprehensive literature search revealed 34 published as well as unpublished studies on the associations between rumination and core EF. These studies report on 3,066 participants. The effect size in the meta‐analyses was obtained by the z transformation of correlation coefficients. Results Analysis revealed significant negative associations between rumination and both inhibition (r = ‒.23) and set‐shifting (r = ‒.19). There was no significant association between rumination and working memory. These associations were not moderated by age, sex, type of sample (depressed or healthy), type of outcome measure (accuracy vs. reaction time), or affective content of the task, although statistical power for these tests was limited. Conclusions We found significant negative associations between rumination and inhibition or set‐shifting. There was no significant association between rumination and working memory. Future research should adopt multiple measures of EF to provide clear evidence on the associations between EF and rumination. A better understanding of this relationship may have important implications for intervention of rumination, such as training programs to improve EF or teach compensatory strategies to mitigate the effects of EF impairments.

Grazing and ruminating are the most important behaviours for ruminants, as they spend most of their daily time budget performing these. Continuous surveillance of eating behaviour is an important means for monitoring ruminant health, productivity and welfare. However, surveillance performed by human operators is prone to human variance, time-consuming and costly, especially on animals kept at pasture or free-ranging. The use of sensors to automatically acquire data, and software to classify and identify behaviours, offers significant potential in addressing such issues. In this work, data collected from sheep by means of an accelerometer/gyroscope sensor attached to the ear and collar, sampled at 16 Hz, were used to develop classifiers for grazing and ruminating behaviour using various machine learning algorithms: random forest (RF), support vector machine (SVM), k nearest neighbour (kNN) and adaptive boosting (Adaboost). Multiple features extracted from the signals were ranked on their importance for classification. Several performance indicators were considered when comparing classifiers as a function of algorithm used, sensor localisation and number of used features. Random forest yielded the highest overall accuracies: 92% for collar and 91% for ear. Gyroscope-based features were shown to have the greatest relative importance for eating behaviours. The optimum number of feature characteristics to be incorporated into the model was 39, from both ear and collar data. The findings suggest that one can successfully classify eating behaviours in sheep with very high accuracy; this could be used to develop a device for automatic monitoring of feed intake in the sheep sector to monitor health and welfare.