A network analysis of catatonia symptoms across diagnoses.

BACKGROUND: Catatonia, as a transdiagnostic construct, manifests across various psychiatric and non-psychiatric conditions. Understanding how symptom variations impact the catatonia construct and differ across primary diagnoses (schizophrenia, bipolar disorder, unipolar depression, and neurological/metabolic/immunological condition) is essential to refine diagnostic and therapeutic approaches. This study aims to compare the symptom networks and centrality measures of these diagnoses. METHODS: We conducted a network analysis using Bush-Francis Catatonia Rating Scale (BFCRS) data from 118 patients, examining centrality measures and network comparisons across the four primary diagnostic groups. RESULTS: In the general catatonia network, the three most central symptoms identified were Excitement (1.462), Perseveration (1.456), and Impulsivity (1.332). While the overall structure of the catatonia networks did not show significant differences between diagnoses in terms of symptom connections and centrality, variations in centrality measures were observed among the different networks. CONCLUSIONS: The study reinforces the notion of catatonia as an independent syndrome relatively to psychiatric or non-psychiatric diagnoses. However, the variation in centrality of symptoms across different primary diagnoses provides critical insights that could aid clinicians in tailoring diagnostic and therapeutic strategies. Future research should further explore these relationships and develop more refined approaches to managing catatonia.

Modeling longitudinal relationships between sleep disturbances and depressed mood in postpartum: A cross-lagged panel design.

BACKGROUND: This short communication explores the interrelationships between depressed mood and sleep disturbances in one-year postpartum period. METHODS: Utilizing data from the Interaction of Gene and Environment of Depression during PostPartum Cohort (IGEDEPP) involving 3310 French postpartum women, we employed a cross-lagged panel model (CLPM) to analyze the relationships between these two symptoms, across three time points (immediate postpartum [<1 week after delivery], early postpartum [<2 months after delivery], and late postpartum [2 months to 1 years after delivery]). RESULTS: Depressed mood significantly influences sleep disturbances in late postpartum (ß = 0.096, z-value = 7.4; p < 0.001) but not in early postpartum (p-value = 0.9). We found no cross-lagged influence of sleep disturbances on depressed mood in early (p = 0.066) or in late postpartum (p = 0.060). Moreover, depressed mood and sleep disturbances in immediate postpartum are predictive of similar symptoms in the two other postpartum periods (between each of the three periods, p = 0.006 and p < 0.001 for depressed mood, and p = 0.039 and p < 0.001 for sleep disturbances), thus demonstrating the stability of these symptoms over time. LIMITATIONS: Although conducted with a prospectively assessed cohort, this study faces limitations due to potential methodological biases. CONCLUSIONS: This study is a pioneering analysis of mutual causal interactions between depressed mood and sleep disturbances in the postpartum period, highlighting the need for vigilant monitoring, early detection, prevention of worsen outcomes and intervention on these symptoms.

Sleep Health Analysis Through Sleep Symptoms in 35,808 Individuals Across Age and Sex Differences: Comparative Symptom Network Study.

BACKGROUND: Sleep health is a multidimensional construct that includes objective and subjective parameters and is influenced by individual sleep-related behaviors and sleep disorders. Symptom network analysis allows modeling of the interactions between variables, enabling both the visualization of relationships between different factors and the identification of the strength of those relationships. Given the known influence of sex and age on sleep health, network analysis can help explore sets of mutually interacting symptoms relative to these demographic variables. OBJECTIVE: This study aimed to study the centrality of symptoms and compare age and sex differences regarding sleep health using a symptom network approach in a large French population that feels concerned about their sleep. METHODS: Data were extracted from a questionnaire provided by the Réseau Morphée health network. A network analysis was conducted on 39 clinical variables related to sleep disorders and sleep health. After network estimation, statistical analyses consisted of calculating inferences of centrality, robustness (ie, testifying to a sufficient effect size), predictability, and network comparison. Sleep clinical variable centralities within the networks were analyzed by both sex and age using 4 age groups (18-30, 31-45, 46-55, and >55 years), and local symptom-by-symptom correlations determined. RESULTS: Data of 35,808 participants were obtained. The mean age was 42.7 (SD 15.7) years, and 24,964 (69.7%) were women. Overall, there were no significant differences in the structure of the symptom networks between sexes or age groups. The most central symptoms across all groups were nonrestorative sleep and excessive daytime sleepiness. In the youngest group, additional central symptoms were chronic circadian misalignment and chronic sleep deprivation (related to sleep behaviors), particularly among women. In the oldest group, leg sensory discomfort and breath abnormality complaint were among the top 4 central symptoms. Symptoms of sleep disorders thus became more central with age than sleep behaviors. The high predictability of central nodes in one of the networks underlined its importance in influencing other nodes. CONCLUSIONS: The absence of structural difference between networks is an important finding, given the known differences in sleep between sexes and across age groups. These similarities suggest comparable interactions between clinical sleep variables across sexes and age groups and highlight the implication of common sleep and wake neural circuits and circadian rhythms in understanding sleep health. More precisely, nonrestorative sleep and excessive daytime sleepiness are central symptoms in all groups. The behavioral component is particularly central in young people and women. Sleep-related respiratory and motor symptoms are prominent in older people. These results underscore the importance of comprehensive sleep promotion and screening strategies tailored to sex and age to impact sleep health.

Diagnostic staging and stratification in psychiatry and oncology: clarifying their conceptual, epistemological and ethical implications.

Staging and stratification are two diagnostic approaches that have introduced a more dynamic outlook on the development of diseases, thus participating in blurring the line between the normal and the pathological. First, diagnostic staging, aiming to capture how diseases evolve in time and/or space through identifiable and gradually more severe stages, may be said to lean on an underlying assumption of "temporal determinism". Stratification, on the other hand, allows for the identification of various prognostic or predictive subgroups based on specific markers, relying on a more "mechanistic" or "statistical" form of determinism. There are two medical fields in which these developments have played a significant role and have given rise to sometimes profound nosological transformations: oncology and psychiatry. Drawing on examples from these two fields, this paper aims to provide much needed conceptual clarifications on both staging and stratification in order to outline how several epistemological and ethical issues may, in turn, arise. We argue that diagnostic staging ought to be detached from the assumption of temporal determinism, though it should still play an essential role in adapting interventions to stage. In doing so, it would help counterbalance stratification's own epistemological and ethical shortcomings. In this sense, the reflections and propositions developed in psychiatry can offer invaluable insights regarding how adopting a more transdiagnostic and cross-cutting perspective on temporality and disease dynamics may help combine both staging and stratification in clinical practice.

Diversity, epistemic injustice and medicalization.

This Viewpoint explores challenges within the neurodiversity framework, with a particular focus on autism, and discusses three critical aspects: the risk of epistemic injustice, the balance between over and undermedicalization, and the terminological complexities associated with the "neuro-" prefix. It underscores the importance of a balanced approach that avoids overmedicalization while providing essential support, addresses concerns about the indiscriminate use of "neurodiverse", questions the terminology on neurodiversity, and suggests considering a broader term like "biopsychosocial diversity". Ultimately, this Viewpoint advocates for a measured approach to neurodiversity, emphasizing historical context and a diverse perspective to foster collaboration between cognitive science and behavior research.

Corrigendum: Serum D-dimer is not predictive of placenta-mediated complications in pregnancy at high risk: the multicentric prospective cohort AngioPred study.

[This corrects the article DOI: 10.3389/fcell.2023.1115622.].

Eco-anxiety: An adaptive behavior or a mental disorder? Results of a psychometric study.

OBJECTIVE: Eco-anxiety is a complex construct that has been created to grasp the psychological impact of the consequences of global warming. The concept needs a reliably valid questionnaire to better evaluate its impact on the risk of anxiety and depressive disorders. The Eco-Anxiety Questionnaire (EAQ-22) evaluates two dimensions: 'habitual ecological anxiety' and 'distress related to eco-anxiety'. However, a version in French, one of the world's widely spoken languages, was until now lacking. We aimed to translate and validate the French EAQ-22 and to evaluate the prevalence of the level of the two dimensions of eco-anxiety and the relationship with anxiety and depressive symptoms in a representative adult sample of the French general population. METHODS: This study was performed under the auspices of the Institut national du sommeil et de la vigilance (INSV). Participants (18-65 years) were recruited by an institute specialized in conducting online surveys of representative population samples (quota sampling). Two native French speakers and two native English speakers performed a forward-backward translation of the questionnaire. The Hospital Anxiety and Depression scale (HAD) was administered to assess anxiety (HAD-A) and depressive (HAD-D) symptoms and for external validity. Internal structural validity and external validity were analysed. RESULTS: Evaluation was performed on 1004 participants: mean age 43.47 years (SD=13.41, range: [19-66]); 54.1% (n=543) women. Using the HAD, 312 (31.1%) patients had current clinically significant anxiety symptoms (HAD-A>10) and 150 (14.9%) had current clinically significant depressive symptoms (HAD-D>10). Cronbach's alpha coefficient was 0.934, indicating very good internal consistency. Correlation between EAQ-22 and HAD scores was low (r[1004]=0.209, P<0.001), 'habitual ecological anxiety' was correlated less with HAD-A and HAD-D than 'distress related to eco-anxiety', indicating good external validity. CONCLUSION: This study validates the French EAQ-22 and paves the way for using the EAQ-22 as a global tool for assessing eco-anxiety. Further prospective studies are now required to better evaluate the impact of eco-anxiety on the occurrence of anxiety and depressive disorder.

The importance of social relationships in depression in autistic adolescents: a narrative-review.

Objective: The impact of social relationships on autistic adolescents has been recently studied. However, the link between social relationships and depression in autistic adolescents seem underrepresented in the scientific literature. Especially no specific assessment tool has been developed to evaluate depression in autistic adolescents. The aim of this narrative review is to raise the impact of social relationships on depression in autistic adolescents. We aim to propose lines of thought on the creation of a sensitive tool for identifying depression in this population. Methods: We conducted two types of searches for articles and reviews on PubMed, Embase, and Cochrane. First, regarding social relationships, we searched the following terms: [("adolesc*" OR "youth") AND ("ASD" OR "autis*") AND ("social communication" OR "peer relationship") AND ("depress*")]. Secondly, regarding assessment tool, we searched the following terms: [("tool" OR "assess*") AND ("depress*") AND ("ASD" OR "Autis*)"]. Results: Social impact, verbal skills, and good social motivation are risk factors of depression in autistic adolescents. Social impairment during childhood is related to peer victimization and is a risk factor for depression. There is no specific tool to measure depression in autistic adolescents. Conclusion: No specific tool based on social relationships was developed to evaluate depression in autistic adolescents. Depression in autistic adolescents needs to be assessed considering the social and pragmatic specificities of autism. Social communication and difficulties in peer relationships may be evaluated in specific assessment tools based on social relationships for depression in autistic adolescents.

Symptom content analysis of OSA questionnaires: time to identify and improve relevance of diversity of OSA symptoms?

STUDY OBJECTIVES: Obstructive sleep apnea (OSA) is a heterogeneous condition covering many clinical phenotypes in terms of the diversity of symptoms. Patient-based OSA screening questionnaires used in routine practice contain significantly varying contents that can impact the reliability and validity of the screening. We investigated to what extent common patient-based OSA screening questionnaires differ or overlap in their item content by conducting a rigorous, methodical, and quantified content overlap analysis. METHODS: We conducted an item content analysis of 11 OSA screening questionnaires validated in adult populations and characterized their overlap using a 4-step approach: (1) selection of OSA screening questionnaires, (2) item extraction and selection, (3) extraction of symptoms from items, and (4) assessment of content overlap with the Jaccard index (from 0, no overlap, to 1, full overlap). RESULTS: We extracted 72 items that provided 25 distinct symptoms from 11 selected OSA questionnaires. The overlap between them was weak (mean Jaccard index: 0.224; ranging from 0.138 to 0.329). All questionnaires contained symptoms of the "OSA symptom" dimension (eg, snoring or witnessed apneas). The STOP-BANG (0.329) and the Berlin (0.280) questionnaires exhibited the highest overlap content. Ten symptoms (40%) were investigated in only 1 questionnaire. CONCLUSIONS: The heterogeneity of content and the low overlap across these questionnaires reflect the challenges of screening OSA. The different OSA questionnaires potentially capture varying aspects of the disorder, with the risk of biased results in studies. Suggestions are made for better OSA screening and refinement of clinical OSA phenotypes. CITATION: Gauld C, Baillieul S, Martin VP, et al. Symptom content analysis of OSA questionnaires: time to identify and improve relevance of diversity of OSA symptoms? J Clin Sleep Med. 2024;20(7):1105-1117.

Sleepiness should be reinvestigated through the lens of clinical neurophysiology: A mixed expertal and big-data Natural Language Processing approach.

Historically, the field of sleep medicine has revolved around electrophysiological tools. However, the use of these tools as a neurophysiological method of investigation seems to be underrepresented today, from both international recommendations and sleep centers, in contrast to behavioral and psychometric tools. The aim of this article is to combine a data-driven approach and neurophysiological and sleep medicine expertise to confirm or refute the hypothesis that neurophysiology has declined in favor of behavioral or self-reported dimensions in sleep medicine for the investigation of sleepiness, despite the use of electrophysiological tools. Using Natural Language Processing methods, we analyzed the abstracts of the 18,370 articles indexed by PubMed containing the terms 'sleepiness' or 'sleepy' in the title, abstract, or keywords. For this purpose, we examined these abstracts using two methods: a lexical network, enabling the identification of concepts (neurophysiological or clinical) related to sleepiness in these articles and their interconnections; furthermore, we analyzed the temporal evolution of these concepts to extract historical trends. These results confirm the hypothesis that neurophysiology has declined in favor of behavioral or self-reported dimensions in sleep medicine for the investigation of sleepiness. In order to bring sleepiness measurements closer to brain functioning and to reintroduce neurophysiology into sleep medicine, we discuss two strategies: the first is reanalyzing electrophysiological signals collected during the standard sleep electrophysiological test; the second takes advantage of the current trend towards dimensional models of sleepiness to situate clinical neurophysiology at the heart of the redefinition of sleepiness.

The 68 symptoms of the clinical high risk for psychosis: Low similarity among fourteen screening questionnaires.

The Clinical High Risk for psychosis (CHR) is a heterogeneous condition with multiple symptoms. CHR screening is challenging in routine care, as a wide variety of questionnaires exists. We propose to explore the extent to which these questionnaires differ or overlap in item content. We performed a systematic and quantitative analysis of item content in a set of widely-used CHR screening questionnaires. Items were extracted from questionnaires and reworded according to the Structured Interview for Psychosis-Risk Syndromes (SIPS). Then, symptoms were generated from individual items. The Jaccard Index was calculated to assess content overlap. The 14 analysed questionnaires were composed of 347 items, from which 198 symptoms were generated and, in turn, collapsed into 68 distinct symptoms. Positive symptoms were the most commonly represented. The overall overlap across questionnaires showed weak similarity (Jaccard = 0.19±0.50). CHR screening questionnaires might evaluate the same broad clinical construct, but have different scopes within that construct, and may be more or less comprehensive than one another. Clinicians and researchers should be mindful of the specific features of each instrument for optimal CHR screening.

Content analysis of insomnia questionnaires: A step to better evaluate the complex and multifaceted construct of insomnia disorder.

Insomnia disorder is a mental disorder that includes various types of symptoms (e.g., insomnia initiating, worries, mood disturbances) and impairments (e.g., distress related to sleep alterations). Self-report questionnaires are the most common method for assessing insomnia but no systematic quantified analysis of their content and overlap has been carried out. We used content analysis and a visualization method to better identify the different types of clinical manifestations that are investigated by nine commonly used insomnia questionnaires for adults and the Jaccard index to quantify the degree to which they overlap. Content analysis found and visualized 16 different clinical manifestations classified into five dimensions ("Insomnia symptoms", "Insomnia-related symptoms", "Daytime symptoms", "Insomnia-related impairments", "Sleep behaviors"). The average Jaccard Index was 0.409 (moderate overlap in content). There is a lack of distinction between symptoms and impairments, and the assessment of sleep duration and hyperarousal symptoms remains overlooked. This preliminary analysis makes it possible to visualize the content of each of the nine questionnaires and to select the most appropriate questionnaire based on the issue to be addressed. Suggestions are made regarding the development of future questionnaires to better distinguish symptoms and impairments, and the different phenotypes of insomnia disorder.

Storm on predictive brain: A neurocomputational account of ketamine antidepressant effect.

For the past decade, ketamine, an N-methyl-D-aspartate receptor (NMDAr) antagonist, has been considered a promising treatment for major depressive disorder (MDD). Unlike the delayed effect of monoaminergic treatment, ketamine may produce fast-acting antidepressant effects hours after a single administration at subanesthetic dose. Along with these antidepressant effects, it may also induce transient dissociative (disturbing of the sense of self and reality) symptoms during acute administration which resolve within hours. To understand ketamine's rapid-acting antidepressant effect, several biological hypotheses have been explored, but despite these promising avenues, there is a lack of model to understand the timeframe of antidepressant and dissociative effects of ketamine. In this article, we propose a neurocomputational account of ketamine's antidepressant and dissociative effects based on the Predictive Processing (PP) theory, a framework for cognitive and sensory processing. PP theory suggests that the brain produces top-down predictions to process incoming sensory signals, and generates bottom-up prediction errors (PEs) which are then used to update predictions. This iterative dynamic neural process would relies on N-methyl-D-aspartate (NMDAr) and α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic receptors (AMPAr), two major component of the glutamatergic signaling. Furthermore, it has been suggested that MDD is characterized by over-rigid predictions which cannot be updated by the PEs, leading to miscalibration of hierarchical inference and self-reinforcing negative feedback loops. Based on former empirical studies using behavioral paradigms, neurophysiological recordings, and computational modeling, we suggest that ketamine impairs top-down predictions by blocking NMDA receptors, and enhances presynaptic glutamate release and PEs, producing transient dissociative symptoms and fast-acting antidepressant effect in hours following acute administration. Moreover, we present data showing that ketamine may enhance a delayed neural plasticity pathways through AMPAr potentiation, triggering a prolonged antidepressant effect up to seven days for unique administration. Taken together, the two sides of antidepressant effects with distinct timeframe could constitute the keystone of antidepressant properties of ketamine. These PP disturbances may also participate to a ketamine-induced time window of mental flexibility, which can be used to improve the psychotherapeutic process. Finally, these proposals could be used as a theoretical framework for future research into fast-acting antidepressants, and combination with existing antidepressant and psychotherapy.

Major depressive episode and postpartum depression: A network analysis comparison on the IGEDEPP cohort.

INTRODUCTION: Major depression episode (MDE) and postpartum depression (PPD) have the same diagnosis criteria, but dissimilarities may be present regarding the frequency and structure of depressive symptoms. METHODS: We used data from the IGEDEPP Cohort (France) to examine DSM-5 depressive symptoms in two groups of women: 486 with PPD and 871 with a history of non-perinatal MDE. We compare (i) the frequency of each depressive symptom adjusted for the severity of depression, (ii) the global structure of depressive symptom networks, and (iii) the centrality of each symptom in the two networks. RESULTS: Women with PPD were significantly more likely to have appetite disturbance, psychomotor symptoms, and fatigue than those with MDE, while sadness, anhedonia, sleep disturbance, and suicidal ideation were significantly less common. There were no significant differences in the global structure of depressive symptoms of MDE and PPD. However, the most central criterion of the MDE network was "Sadness" while it was "Suicidal ideations" for the PPD network. "Sleep" and "Suicidal ideations" criteria were more central for PPD network, whereas "Culpability" was more important for MDE network than for PPD network. CONCLUSION: We found differences in depressive symptoms expression between PPD and MDE, which justify continuing to clinically distinguish PPD from MDE.

[Dissociative identity disorder in adolescents: From self-diagnosis to transient illness]. / Trouble dissociatif de l'identité de l'adolescent : de l'autodiagnostic à la maladie transitoire.

The category of dissociative identity disorder (DID) has puzzled medical science and fascinated popular culture for almost 200 years. Its occurrence in young people raises at least two new questions addressed by science studies and embedded philosophy: self-diagnosis (related to cyberchondria and mass media-induced illness) and transient disease (related to looping effect and identity claim specific to adolescence). In an attempt to refine the sociocognitive model, we analyze the impact of these notions in understanding the local ecological niche in which contemporary adolescent DID occurs.

The centrality of craving in network analysis of five substance use disorders.

BACKGROUND AND AIMS: Among the 11 current diagnostic criteria, craving is a potential central marker for understanding and for treatment of Substance Use Disorders (SUD). Our objective was to explore craving centrality across SUD based on the study of symptom interactions in cross-sectional network analyses of DSM-5 SUD diagnostic criteria. We hypothesized the centrality of "Craving" in SUD across substance types. DESIGN: Participants from the ADDICTAQUI clinical cohort with regular use (2 times per week threshold for a substance) and at least one DSM-5 SUD. SETTING: Outpatient substance use treatment services in Bordeaux, France. PARTICIPANTS: The sample of 1359 participants, had a mean age of 39 years old and 67% were males. The prevalence of SUD over the time course of the study was: 93% for alcohol, 98% for opioids, 94% for cocaine, 94% for cannabis and 91% tobacco. MEASUREMENTS: Construction of a Symptom Network Model conducted on the DSM-5 SUD criteria evaluated over the past 12 months for Alcohol-, Cocaine-, Tobacco-, Opioid- and Cannabis Use disorder. FINDINGS: The only symptom that consistently remained in terms of centrality was "Craving" [3.96 - 6.17] (z-scores), indicating that it exhibits a high degree of connections in the entire symptom network regardless of the substance. CONCLUSION: Identifying craving as central in SUD symptoms network confirms the role of craving as a marker of addiction. This constitutes a major avenue in the understanding of the mechanisms of addiction, with implications to ameliorate diagnostic validity and clarify treatment targets.

Dynamical systems in computational psychiatry: A toy-model to apprehend the dynamics of psychiatric symptoms.

Introduction: These last years, scientific research focuses on the dynamical aspects of psychiatric disorders and their clinical significance. In this article, we proposed a theoretical framework formalized as a generic mathematical model capturing the heterogeneous individual evolutions of psychiatric symptoms. The first goal of this computational model based on differential equations is to illustrate the nonlinear dynamics of psychiatric symptoms. It offers an original approach to nonlinear dynamics to clinical psychiatrists. Methods: In this study, we propose a 3+1 dimensions model (x, y, z + f) reproducing the clinical observations encountered in clinical psychiatry with: a variable modeling environmental noise (z) on the patient's internal factors (y) with its temporal specificities (f) and symptomatology (x). This toy-model is able to integrate empirical or simulated data from the influence of perceived environmental over time, their potential importance on the internal and subjective patient-specific elements, and their interaction with the apparent intensity of symptoms. Results: Constrained by clinical observation of case formulations, the dynamics of psychiatric symptoms is studied through four main psychiatric conditions were modeled: i) a healthy situation, ii) a kind of psychiatric disorder evolving following an outbreak (i.e., schizophrenia spectrum), iii) a kind of psychiatric disorder evolving by kindling and bursts (e.g., bipolar and related disorders); iv) and a kind of psychiatric disorder evolving due to its high susceptibility to the environment (e.g., spersistent complex bereavement disorder). Moreover, we simulate the action of treatments on different psychiatric conditions. Discussion: We show that the challenges of dynamical systems allow to understand the interactions of psychiatric symptoms with environmental, descriptive, subjective or biological variables. Although this non-linear dynamical model has limitations (e.g., explanatory scope or discriminant validity), simulations provide at least five main interests for clinical psychiatry, such as a visualization of the potential different evolution of psychiatric disorders, formulation of clinical cases, information about attracting states and bifurcations, or the possibility of a nosological refinement of psychiatric models (e.g., staging and symptom network models).