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Rumination is a transdiagnostic correlate and risk factor for mental disorders. However, few studies have explored rumination and its components in everyday life, or their associations with other transdiagnostic processes, such as deficits in attention control, which may be an explanatory mechanism or consequence of rumination. Inspired by the Nolen-Hoeksema’s operationalization of rumination, we investigated the associations between five features of rumination and attention control. Forty participants answered six items four times per day over a two-week period. Using a multilevel vector autoregressive approach, we computed three networks representing temporal, contemporaneous, and between-subjects associations. The results showed that negativity of thoughts temporally drives all other features of rumination and predicts diminished attention control. Negativity was the only feature negatively associated with attention control within the same time point, emphasizing negativity as a driving force of rumination and as a potent pathway in the interplay between rumination’s features and attention control.

Network analyses have become increasingly common within the field of psychology, and temporal network analyses in particular are quickly gaining traction, with many of the initial articles earning substantial interest. However, substantial heterogeneity exists within the study designs and methodology, rendering it difficult to form a comprehensive view of its application in psychology research. Since the field is quickly growing and since there have been many study-to-study variations in terms of choices made by researchers when collecting, processing, and analyzing data, we saw the need to audit this field and formulate a comprehensive view of current temporal network analyses. To systematically chart researchers' practices when conducting temporal network analyses, we reviewed articles conducting temporal network analyses on psychological variables (published until March 2021) in the framework of a scoping review. We identified 43 articles and present the detailed results of how researchers are currently conducting temporal network analyses. A commonality across results concerns the wide variety of data collection and analytical practices, along with a lack of consistency between articles about what is reported. We use these results, along with relevant literature from the fields of ecological momentary assessment and network analysis, to formulate recommendations on what type of data is suited for temporal network analyses as well as optimal methods to preprocess and analyze data. As the field is new, we also discuss key future steps to help usher the field's progress forward and offer a reporting checklist to help researchers navigate conducting and reporting temporal network analyses.

Parental burnout is a growing subject of research, but thus far this research has not examined whether the features of parental burnout fluctuate over time. Moreover, parenting and parental burnout are inextricable from their family context. Therefore, a critical next step involves examining how parental burnout features temporally unfold and interact with the ever-changing family environment. To do so, we developed an 11-item experience sampling methodology (ESM) tool to measure self-reported parental burnout features (specifically emotional exhaustion, emotional distance, and feeling fed up), as well as partner relationship, children’s behavior, behavior toward children, social support, and perceived resources. We conducted two two-week periods of ESM data collection (one with French-language ESM items; n = 9; one with English-language ESM items; n=23) and one eight-week data collection with the French-language ESM items (n=50). We collected the ESM data using formr, an open-source platform, and we provide open access to all materials (including a formr template, allowing free use of the assessment tool), analysis code, and data: https://osf.io/s2yv5/. Participants’ responses indicated sufficient within-person variability (assessed via intraclass correlation) and support for convergent and discriminant validity (assessed by correlating aggregated ESM responses with retrospective questionnaire scores on parental burnout, depression, anxiety, and stress). Lastly, we found that the three parental burnout ESM items had high between-subject reliability and moderate within-subject reliability. Participating parents found the ESM survey easy to answer and not burdensome. Finally, we discuss how assessing parental burnout over time can help usher parental burnout research and treatment forward.

What is it to be “an ideal parent”? Does the answer differ across countries and social classes? To answer these questions in a way that minimizes bias and ethnocentrism, we used open-ended questions to explore ideal-parent beliefs among 8,357 mothers and 3,517 fathers from 37 countries. Leximancer Semantic Network Analysis was utilized to first determine parenting culture zones (i.e., countries with shared ideal-parent beliefs) and then extract the predominant themes and concepts in each culture zone. The results yielded specific types of ideal-parent beliefs in five parenting culture zones: being “responsible and children/family-focused” for Asian parents, being “responsible and proper demeanor-focused” for African parents, and being “loving and responsible” for Hispanic-Italian parents. Although the most important themes and concepts were the same in the final two zones—being “loving and patient,” there were subtle differences: English-speaking, European Union, and Russian parents emphasized “being caring,” while French-speaking parents valued “listening” or being “present.” Ideal-parent beliefs also differed by education levels within culture zones, but no general pattern was discerned across culture zones. These findings suggest that the country in which parents were born cannot fully explain their differences in ideal-parent beliefs and that differences arising from social class or education level cannot be dismissed. Future research should consider how these differences affect the validity of the measurements in question and how they can be incorporated into parenting intervention research within and across cultures.

Contains fulltext : 288062.pdf (Publisher’s version ) (Closed access) There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = -0.077, pFWE = 0.037; right: d = -0.104, pFWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = -0.034, pFWE = 0.045). Smaller bilateral putamen volumes (left: d = -0.141, pFWE

Neuroimaging studies point to neurostructural abnormalities in youth with anxiety disorders. Yet, findings are based on small-scale studies, often with small effect sizes, and have limited generalizability and clinical relevance. These issues have prompted a paradigm shift in the field towards highly powered (i.e., big data) individual-level inferences, which are data-driven, transdiagnostic, and neurobiologically informed. Here, we built and validated neurostructural machine learning (ML) models for individual-level inferences based on the largest-ever multi-site neuroimaging sample of youth with anxiety disorders (age: 10-25 years, N=3,343 individuals from 32 global sites), as compiled by three ENIGMA Anxiety Working Groups: Panic Disorder (PD), Generalized Anxiety Disorder (GAD), and Social Anxiety Disorder (SAD). ML classifiers were trained on MRI-derived regional measures of cortical thickness, surface area, and subcortical volumes to classify patients and healthy controls (HC) for each anxiety disorder separately and across disorders (transdiagnostic classification). Modest, yet robust, classification performance was achieved for PD vs. HC (AUC=0.62), but other disorder-specific and transdiagnostic classifications were not significantly different from chance. However, above chance-level transdiagnostic classifications were obtained in exploratory subgroup analyses of male patients vs. male HC, unmedicated patients vs. HC, and patients with low anxiety severity vs. HC (AUC 0.59-0.63). The above chance-level classifications were based on plausible and specific neuroanatomical features in fronto-striato-limbic and temporo-parietal regions. This study provides a realistic estimate of classification performance in a large, ecologically valid, multi-site sample of youth with anxiety disorders, and may as such serve as a benchmark.

Paranoid beliefs have been conceptualized as a central psychological process linked to schizophrenia and many mental disorders. Research on paranoia has indicated that it is pivotal to consider not only levels but also dynamics aspects of incriminated related-mechanisms over time. In the present study, we conceptualized paranoia as a system of interacting elements. To do so, we used temporal network analysis to unfold the temporal dynamics between core psychological paranoia-related mechanisms, such as self-esteem, sadness, feeling close to others, and experiential avoidance. Time-series data of 23 participants with high scores in paranoia and/or interpersonal sensitivity were collected via experience sampling methodology (ESM). We applied a multilevel vector autoregressive (mlVAR) model approach and computed three distinct and complementary network models (i.e., contemporaneous, temporal, and between-subject) to disentangle associations between paranoia-related mechanisms in three different time frames. The contemporaneous model indicated that paranoia and sadness co-occurred within the same time frame, while sadness was associated with both low self-esteem and lack of closeness to others. The temporal model highlighted the importance of feeling close to others in predicting low paranoia levels in the next time frame. Finally, the between-subject model largely replicated association found in both contemporaneous and temporal models. The current study reveals that the network approach offers a viable data-driven methodology for elucidating how paranoia-related mechanisms fluctuate over time and may determine its severity. Moreover, this novel perspective may open up new directions towards identifying potential targets for prevention and treatment of paranoia-related problems.

Many parents have days where they encounter emotional exhaustion, emotional distance from their children, and feeling fed up with being a parent. Some parents experience these characteristics to a severe extent—a clinical phenomenon termed parental burnout. Parental burnout arises when parents chronically endure severe stress without sufficient resources to cope, which may lead to detrimental consequences not only for the parent, but also for their partner (e.g., marital conflict) and children (i.e., neglect and violence). However, uncertainty remains regarding how these features interact and trigger one another over time (potentially becoming increasingly severe), nor how the daily variations of the family context influence these features. Therefore, in this study, we recruited 50 parents (with main analyses focusing on 43 mothers with a coparent, and sensitivity analyses with the full sample) from the general population to rate the core features of parental burnout and the family context daily over 56 days. We used multilevel vector autoregressive models to generate network models. Results suggest that exhaustion contributes to parental burnout: it self-predicts and is closely associated with feeling fed up and finding children difficult to manage. Distance, by contrast, is mainly negatively connected to sharing positive moments with children. Contextual variables also interact with parental burnout features, illustrating the relevance of examining parenting within the family system context. If future research confirms a central role of exhaustion in parental burnout development, prevention efforts can focus on decreasing parental exhaustion.

Resume L’activation comportementale ameliore la sante mentale et le fonctionnement psychologique et ce, particulierement dans la depression. L’activation comportementale est egalement associee a une amelioration de differents mecanismes comme l’activation, l’evitement ou encore la satisfaction environnementale. Inspires par de recentes etudes ayant mis en evidence des modifications de l’activite neuronale de regions liees au controle cognitif ainsi que de regions associees au traitement de la recompense apres une intervention par activation comportementale dans la depression, mais egalement par les modeles cognitifs de la depression qui suggerent que les biais attentionnels joueraient un role de maintien de l’humeur depressive, nous avons teste l’effet d’un programme d’activation comportementale sur l’attention selective envers l’information triste et positive. Huit etudiantes presentant une symptomatologie depressive moyenne a moderee ont participe a un programme d’activation comportementale etale sur six semaines. Les resultats suggerent que l’activation comportementale ameliore l’attention selective envers l’information emotionnelle positive. Cette etude preliminaire est pionniere dans l’investigation de l’impact d’un programme d’activation comportementale sur l’attention selective vis-a-vis d’un materiel positif.

Introduction The exploration of cognitive impairments associated with tobacco use disorder has expanded during the last decades, centrally showing working memory and executive deficits among smokers. Despite their critical role in everyday life and in the smoking cessation process, attentional abilities have seldom been explored. Previous studies yielded discordant results, and the involvement of attentional deficits in smoking habits remains unclear. Aims and Methods Capitalizing on the Attention Network Test, a theory-grounded task allowing the simultaneous but distinct evaluation of three attentional networks (alerting, orienting, executive control), we explored attentional abilities in three groups of 25 college students (nonsmokers, light smokers, heavy smokers), matched for demographic and psychopathological characteristics. Results While light smokers did not present any deficit compared with nonsmokers, heavy smokers showed a specific impairment of the executive control subcomponent of attention, contrasting with preserved alerting and orienting attentional abilities. The executive control deficit was not related to current craving or to smoking duration. Conclusions Beyond the already explored memory and executive deficits, tobacco use disorder is associated with attentional impairments, characterized by a reduced ability to focus attentional resources on pertinent stimuli and resist to distractors interference. Given the assumed role of attentional impairments in smoking, our findings suggest that a critical step in future translational iterations is to develop neuropsychological rehabilitation programs tapping into the executive network of attention among smokers. Implications This study clarifies the presence and extent of attentional impairments in tobacco use disorder. We measured three attention networks (alerting, orienting, executive control) in light smokers, heavy smokers and matched healthy controls through a theory-grounded task (Attention Network Test). Heavy smokers (but not light ones) present a specific deficit for the executive control of attention. This deficit, uncorrelated with psychopathological comorbidities or current craving, appears directly related to smoking. Given the currently scattered literature on this topic, attentional processes deserve a thorough audit in tobacco use disorder, notably to develop specific neurocognitive rehabilitation.

Parental burnout results from chronic stress in parenting, and it can be accompanied by harmful behaviors such as parental neglect and violence (Mikolajczak & Roskam, 2018). Network analysis examines psychological phenomena within a system of its constituents, and thus it is promising for understanding the distinct features of parental burnout and behaviors related to it. Recently, Blanchard et al. (2021) conducted the first network analysis of parental burnout and related harmful behaviors in the family context, but did so using an outdated measure and conceptualization of parental burnout. In the present study, in a sample of French-speaking parents (N = 3144, from five different previous studies), we aimed to investigate how each of the four features in the new conceptualization of parental burnout (i.e., emotional exhaustion, feeling fed up, emotional distance, and contrast with the previous parental self) interact with one another and with parental neglect and violence in a network system. In this preregistered reanalysis, we generated two network models commonly used with cross-sectional data: a Graphical Gaussian Model and a Directed Acyclic Graph. Our results point to emotional exhaustion and feeling fed up as key driving forces of the network structure, while emotional distance appears as a critical feature tying parental burnout with parental neglect and violence.

For decades, science has attempted to understand the world by boiling concepts down to their simplest components in a quest for reductionism; but, there is now a move to map the world's complexities via a network perspective. Clinical psychology has embraced this perspective as well, and researchers have started to conceptualize mental disorders as network systems. In this chapter, we review and discuss the theoretical conjectures, levels of evidence, current challenges and future directions, as well as the potential translational value of this new approach to psychopathology.

Despite the large-scale dissemination of mindfulness-based interventions, debates persist about the very nature of mindfulness. To date, one of the dominant views is the five-facet approach, which suggests that mindfulness includes five facets (i.e., Observing, Describing, Nonjudging, Nonreactivity, and Acting with Awareness). However, uncertainty remains regarding the potential interplay between these facets. In this study, we investigated the five-facet model via network analysis in an unselected sample (n = 1704). We used two distinct computational network approaches: a Gaussian graphical model (i.e., undirected) and a directed acyclic graph, with each model determining the relations between the facets and their relative importance in the network. Both computational approaches pointed to the facet denoting Acting with Awareness as playing an especially potent role in the network system. Altogether, our findings offer novel data-driven clues for the field's larger quest to ascertain the very foundations of mindfulness.

Network analyses have become increasingly common within the field of psychology, and temporal network analyses, in particular, are quickly gaining traction, with many of the initial articles earning substantial interest. However, substantial heterogeneity exists within the study designs and methodology, rendering it difficult to form a comprehensive view of its application in psychology research. Since the field is quickly growing and that there have been many study-to-study variations in terms of choices made by researchers when collecting, processing, and analyzing data, we saw the need to audit this field and formulate a comprehensive view of current temporal network. To systematically chart researchers’ practices when conducting temporal network analyses, we reviewed articles conducting temporal network analyses on psychological variables (published until March 2021) in the framework of a scoping review. We identified 43 articles and presented the detailed results of how researchers are currently conducting their temporal network analyses. A commonality across results concerns the wide variety of data collection and analytical practices, along with a lack of consistency between articles about what is reported. We use these results, along with relevant literature from the fields of ecological momentary assessment and network analysis, to formulate recommendations on what type of data is suited for temporal network analyses as well as optimal methods to preprocess and analyze data. As the field is new, we also discuss key future steps to help usher the field’s progress forward and offer a reporting checklist to help researchers navigate conducting and reporting temporal network analyses.

L’objectif principal de ce rapport est de vérifier l’hypothèse selon laquelle l’adoption d’une pratique active de recherche d’information liée à la crise sanitaire sur les réseaux sociaux, peut être comprise comme une pratique à risque dans l’infodémie. Un second objectif est d’identifier l’existence de différents profils de vulnérabilité dans l’infodémie et de comprendre les pratiques d’information associées à ces différents profils à risque de mésinformation. La démarche adoptée est donc d’abord une approche comparative entre différents types de profil. Il ne s’agit pas de réaliser une étude longitudinale représentative de l’évolution du vécu de la crise de la population belge francophone. L’enquête CoviCom est une enquête par questionnaire en quatre vagues qui a été menée en Belgique francophone entre le 30 mars 2020 (soit 12 jours après l’entrée en vigueur du premier confinement en Belgique) et le 29 mars 2021. Au total, l’enquête a collecté 10.148 réponses aux quatre vagues de l’enquête (avril 2020 confinement, mai 2020 déconfinement, novembre 2020 seconde vague épidémie et mars 2021 troisième vagues épidémie). The main objective of this report is to test the hypothesis that the adoption of an active information-seeking practice related to the health crisis on social networks can be understood as a risk practice in the Covid-19 infodemic. A second objective is to identify the existence of different vulnerability profiles in the infodemic and to understand the information practices associated with these different profiles at risk of misinformation. The approach adopted is therefore firstly a comparative approach between different types of profile. It is not a question of carrying out a longitudinal study representative of the evolution of the French-speaking Belgian population's experience of the crisis. The CoviCom survey is a four-wave questionnaire survey that was conducted in French-speaking Belgium between 30 March 2020 (i.e. 12 days after the entry into force of the first containment in Belgium) and 29 March 2021. In total, the survey collected 10,148 responses to the four waves of the survey (April 2020 containment, May 2020 decontainment, November 2020 second wave epidemic and March 2021 third wave epidemic).

Recent conceptualizations of interoception suggest several facets to this construct, including "interoceptive sensibility” and “self-report interoceptive scales", both of which are assessed with questionnaires. Although these conceptual efforts have helped move the field forward, uncertainty remains regarding whether current measures converge on their measurement of a common construct. To address this question, we first identified -via a systematic review- the most cited questionnaires of interoceptive sensibility. Then, we examined their correlations, their overall factorial structure, and their network structure in a large community sample (n = 1003). The results indicate that these questionnaires tap onto distinct constructs, with low overall convergence and interrelationships between questionnaire items. This observation mitigates the interpretation and replicability of findings in self-report interoception research. We call for a better match between constructs and measures.

This study aimed to delineate the specific characteristics of binge drinking habits by capitalizing on data-driven network analysis. Such an approach allowed us to consider binge drinking as a network system of interacting elements, thus identifying the key variables involved in this phenomenon. A total of 1,455 university students with excessive drinking habits were included in this study. We assessed the most critical features of binge drinking (i.e., the consumption of more than six alcohol units per occasion, drunkenness frequency, consumption speed), together with alcohol use and more general alcohol-related components of dysfunction and harm. All variables were considered in the network analysis. Centrality analysis identified drunkenness frequency as the most influential variable in the entire network. Community detection analysis showed three distinct subnetworks related to alcohol use, drunkenness, and dysfunction/harm components. Drunkenness frequency and blackout occurrence emerged as core bridge items in the binge drinking network. Drunkenness is recognized as the hallmark feature of binge drinking.

Background: The use of network analyses in psychology has increasingly gained traction in the last few years. A network perspective views psychological constructs as dynamic systems of interacting elements. Objective: We present the first study to apply network analyses to examine how the hallmark features of parental burnout — i.e., exhaustion related to the parental role, emotional distancing from children, and a sense of ineffectiveness in the parental role — interact with one another and with maladaptive behaviors related to the partner and the child(ren), when these variables are conceptualized as a network system. Participants and setting: In a preregistered fashion, we reanalyzed the data from a French-speaking sample (n = 1551; previously published in Mikolajczak, Brianda, Avalosse, & Roskam, 2018), focusing on seven specific variables: the three hallmark parental burnout features, partner conflict, partner estrangement, neglectful behavior toward children, and violent behavior toward children. Methods: We computed two types of network models, a graphical Gaussian model to examine network structure, potential communities, and influential nodes, and a directed acyclic graph to examine the probabilistic dependencies among the different variables. Results: Both network models pointed to emotional distance as an especially potent mechanism in activating all other nodes. Conclusions: These results suggest emotional distance as critical to the maintenance of the parental burnout network and a prime candidate for future interventions, while affirming that network analysis can successfully expose the structure and relationship of variables related to parental burnout and its consequences related to the partner and the child(ren).

Network science has allowed varied scientific fields to investigate and visualize complex relations between many variables, and psychology research has begun to adopt a network perspective. In this paper, we consider how leaving behind reductionist approaches and instead embracing a network perspective can advance the field of parental burnout. Although research into parental burnout is in its early stages, we argue that a network approach to parental burnout could set up the scene for radically new vistas in parental burnout research. We claim that such an approach can allow simultaneous investigations (and clear visualizations) of many variables related to parental burnout and their interactions, integrates smoothly with prior family systems theories, and prioritizes dynamic research questions. We likewise discuss potential future clinical applications, such as interventions targeting central nodes and treatment personalized to a specific family’s network system. We also review practical considerations, limitations, and future directions for researchers interested in applying a network approach to parental burnout research.

International audience; Mobile phone use and misuse have become a pressing challenge in today’s society. Dangerous mobile phone use, such as the use of a mobile phone while driving, is widely practiced, though banned in several jurisdictions. Research aiming at unfolding the psychological predictors of dangerous mobile phone use have so far been scarce. Especially, researchers have never taken the role of self-esteem into account, which is unfortunate given prior research linking self-esteem to addictive mobile phone use. In the present study, we evaluated the asso- ciations between both explicit and implicit self-esteem and dangerous mobile phone use, with a particular focus on phoning while driving. To do so, we assessed implicit self-esteem among 95 participants (89 females) via the Implicit Association Test and explicit self-esteem via a self-reported measure. Problematic mobile phone use and demographic data were assessed with self-reported measures. Implicit self-esteem predicted dangerous mobile phone use, even after we controlled for demographic data and mobile phone dependence. Explicit self-esteem, however, was related to neither dependence nor dangerous use of the mobile phone, thereby supporting the importance of distinguishing between explicit and implicit self-esteem. Our results set the scene for new research avenues regarding mobile phone use while driving.

Previous literature has consistently reported socio-affective information processing impairments in patients with severe alcohol use disorder (SAUD). Some recent studies have also suggested that these patients might exhibit biases toward stimuli indicating social threat, such as angry or disgusted faces. Such biases have been largely documented in other psychopathological disorders like anxiety, where they play a critical role in the emergence and maintenance of the disorder. A comprehensive understanding of these biases in SAUD would thus deepen the understanding of interpersonal difficulties and relapse-related factors. However, to date, no study has directly explored these biases in SAUD. In order to initiate efforts to address this issue, we first review preliminary evidence supporting the hypothesis of biased processing of social threat in SAUD. Then, we identify possible pathways through which such biases might negatively impact the course of the disorder. Finally, we provide precise recommendations and available materials to develop research in this promising field, and underline the related theoretical and clinical perspectives.

Cohort studies have displayed mixed findings on changes in mental symptoms severity in 2020, when the COVID- 19 pandemic outbreak started. Network approaches can provide additional insights by analyzing the connectivity of such symptoms. We assessed the network structure of mental symptoms in the Brazilian Longitudinal Study of Health (ELSA-Brasil) in 3 waves: 2008–2010, 2017–2019, and 2020, and hypothesized that the 2020 network would present connectivity changes. We used the Clinical Interview Scheduled-Revised (CIS-R) questionnaire to evaluates the severity of 14 common mental symptoms. Networks were graphed using unregularized Gaussian models and compared using centrality and connectivity measures. The predictive power of centrality measures and individual symptoms were also estimated. Among 2011 participants (mean age: 62.1 years, 58% females), the pandemic symptom 2020 network displayed higher overall connectivity, especially among symptoms that were related to general worries, with increased local connectivity between general worries and worries about health, as well as between anxiety and phobia symptoms. There was no difference between 2008 and 2010 and 2017–2019 networks. According to the network theory of mental disorders, external factors could explain why the network structure became more densely connected in 2020 compared to previous observations. We speculate that the COVID-19 pandemic and its innumerous social, economical, and political consequences were prominent external factors driving such changes; although further assessments are warranted.

Emotional intelligence (EI) can be defined as the ability to identify, express, understand, manage, and use emotions. EI has been shown to have an important impact on health, relationships, and work/academic performance. In this article, we present a systematic review of 46 EI intervention studies on adult populations in order to assess their outcomes. Overall, these findings provide some support for the efficacy of EI programs. However, important limitations in most of the studies restrict the generalizability of their results. We discuss the contributions and limitations of these studies and make recommendations for the development and implementation of future interventions.

Distortions of duration perception provoked by emotion-induced arousal changes are explained by modifications of an internal clock pace. Yet, uncertainty still abounds regarding whether changes of arousal induced by physical exercise yield such temporal distortions. Here, we report two experiments aiming to test separately the impact of, on the one hand, a physical induction of arousal and, on the other hand, a task delay on duration categorisation. In Experiment 1, participants performed a duration categorisation task before and after heart-rate manipulation (increase, decrease, or no change). Duration overestimation was observed after HR manipulation, irrespective of the condition, implying that changes of physiological arousal alone cannot explain the temporal bias observed. In Experiment 2, participants performed the duration task twice without delay or arousal manipulation, and no overestimation was observed. Together, these results suggest that the overestimation observed in the context of a delayed duration categorisation task is related to a distortion of memorised standard durations caused by time lag rather than by a physiological arousal effect.

The hallmark symptoms of social anxiety disorder (SAD) are fear and avoidance of social evaluative situations. Yet, even people without SAD sometimes fear and avoid certain social situations without ever developing the disorder. Apart from differences in number and severity, uncertainty abounds about how fear and avoidance of distinct interpersonal and social evaluative situations organize differently in people with and without SAD. Inspired by novel network approaches to psychopathology, we sought to characterize the network structure of fear and avoidance of distinct social evaluative situations among individuals with (n = 238) and without SAD (n = 232). Although the network structure and node centrality metrics did not differ between the groups, the network for those with SAD was more strongly interconnected than that of people free of the diagnosis. This study is the first to provide evidence that SAD can be conceptualized as a densely interconnected network of fear and avoidance of social situations. Our results are consistent with the network theory of mental disorders that regards networks with strong between-symptom connections as more pathogenic than similar networks with weaker connections. As prior studies indicated that overall network connectivity can predict the course of mental disorders, our findings set the scene for novel indicators of SAD prognosis.

Following the recent changes to the diagnostic category for addictive disorders in DSM-5, it is urgent to clarify what constitutes behavioural addiction to have a clear direction for future research and classification. However, in the years following the release of DSM-5, an expanding body of research has increasingly classified engagement in a wide range of common behaviours and leisure activities as possible behavioural addiction. If this expansion does not end, both the relevance and the credibility of the field of addictive disorders might be questioned, which may prompt a dismissive appraisal of the new DSM-5 subcategory for behavioural addiction. We propose an operational definition of behavioural addiction together with a number of exclusion criteria, to avoid pathologizing common behaviours and provide a common ground for further research. The definition and its exclusion criteria are clarified and justified by illustrating how these address a number of theoretical and methodological shortcomings that result from existing conceptualizations. We invite other researchers to extend our definition under an Open Science Foundation framework.

Craving is a key factor in substance-related and behavioral addictions, as illustrated by its recent inclusion as a diagnosis criterion in the most recent, fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. It globally refers to the subjective motivational state facilitating the emergence of addiction-related obsessive thoughts and compulsive approach behaviors, despite repeated efforts to stop the addictive behavior. Reduced craving may produce a cascade of downstream benefits, ultimately preventing relapse, but its underlying mechanisms remain uncertain. We present a conceptual, experimental, and clinical approach of craving that aligns it with the triadic model — a recently developed prominent model of addictive disorders. Our central assumption is that craving should not be considered as a unitary process but rather as the emerging consequence of the interplay between three subcomponents, namely (1) cognitive craving (or “obsessive craving”) related to cognitive abilities (e.g., executive functions), (2) automatic craving, linked to cue reactivity and implicit processes (e.g., attentional biases), and (3) physiological craving (or “relief craving”), corresponding to bodily perceptions and related to withdrawal symptoms. We relate these three components to the systems proposed by the triadic model and suggest that metacognitive abilities may constitute a mechanism bridging the three subcomponents. This approach offers an innovative and integrative conceptual framework to explore the interactions between craving and other key processes involved in addictive disorders.

Using a computational network approach, we reanalyzed data from a randomized controlled trial of attention bias modification (ABM) tasks on residual depression symptoms. The main aim was to characterize the symptom-to-symptom changes following ABM. ABM was associated with improvements in interest, which was in turn associated with improvements in other depression symptoms. Although there were no changes in the global network strength following ABM, the comparison with symptom change in the ABM and control group suggests that ABM leads to a reduction of the association between anxiety, depressed mood, and guilt. Findings suggest that reduction in depression symptoms following ABM may have been set in motion by increased interest and involvement in everyday activities, leading to a reduction of the adverse impact of anxiety and negative cognition. ABM may be more effective in patients in whom these symptoms are prominent.

Theories about the involvement of attention in feelings of fear and anxiety have been debated in philosophical circles since long before the foundation of experimental psychology and cognitive neuroscience. In this issue, Ghassemzadeh, Rothbart, and Posner (2019) provide a much-needed historical and conceptual review of the relations between attention and anxiety disorders. Throughout their paper, they argue that insights from the study of brain networks of attention offer a particularly viable prospect for best clarifying the complex relations between attentional processes and anxiety. We fully share this view. Moreover, we believe that the computational and conceptual tools of network analysis (also known as graph theory) can enable researchers to move even closer to elucidating the complex dynamic interplay between those phenomena. In this commentary, we explain why and how to use network analysis for this purpose.