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.

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.

Why could sleep medicine never do without polysomnography?

Given the clinical, methodological, conceptual and modelling challenges within the field of sleep medicine, polysomnography (PSG) has emerged as a central diagnostic tool over time. It has been highly beneficial to clinical practice over the years, thanks to the scientific data that it provides. More recently, sleep medicine has sought answers in precision medicine, broadening its quest for biomarkers that take into account environmental factors, big data, and nosological refinement. However, despite these innovative developments that are relatively independent of PSG, sleep medicine remains intimately associated with the latter. The aim of this paper was to show the central role of PSG for sleep medicine. Indeed, PSG is central to sleep medicine, not only due to the empirical data it provides but also because it represents an obligatory passage point (OPP) within the discipline. It crystallizes debate, pulls disparate types of data together, and facilitates a common language for the different specialties involved in sleep medicine, thereby lending legitimacy and credibility to the specialty. Thus, the role of polysomnography as an OPP in the field of sleep medicine reinforces the discipline, especially because critics (e.g., of the Apnea Hypopnea Index) cannot easily find fault with it.

Symptom network analysis of the sleep disorders diagnostic criteria based on the clinical text of the ICSD-3.

The third edition of the International Classification of Sleep Disorders (ICSD-3) is the authoritative clinical text for the diagnosis of sleep disorders. An important issue of sleep nosology is to better understand the relationship between symptoms found in conventional diagnostic manuals and to compare classifications. Nevertheless, to our knowledge, there is no specific exhaustive work on the general structure of the networks of symptoms of sleep disorders as described in diagnostic manuals. The general aim of the present study was to use symptom network analysis to explore the diagnostic criteria in the ICSD-3 manual. The ICSD-3 diagnostic criteria related to clinical manifestations were systematically identified, and the units of analysis (symptoms) were labelled from these clinical manifestation diagnostic criteria using three rules ("Conservation", "Splitting", "Lumping"). A total of 37 of the 43 main sleep disorders with 160 units of analysis from 114 clinical manifestations in the ICSD-3 were analysed. A symptom network representing all individual ICSD-3 criteria and connections between them was constructed graphically (network estimation), quantified with classical metrics (network inference with global and local measures) and tested for robustness. The global measure of the sleep symptoms network shows that it can be considered as a small world, suggesting a strong interconnection between symptoms in the ICSD-3. Local measures show the central role of three kinds of bridge sleep symptoms: daytime sleepiness, insomnia, and behaviour during sleep symptoms. Such a symptom network analysis of the ICSD-3 structure could provide a framework for better systematising and organising symptomatology in sleep medicine.

Popular and Scientific Discourse on Autism: Representational Cross-Cultural Analysis of Epistemic Communities to Inform Policy and Practice.

BACKGROUND: Social media provide a window onto the circulation of ideas in everyday folk psychiatry, revealing the themes and issues discussed both by the public and by various scientific communities. OBJECTIVE: This study explores the trends in health information about autism spectrum disorder within popular and scientific communities through the systematic semantic exploration of big data gathered from Twitter and PubMed. METHODS: First, we performed a natural language processing by text-mining analysis and with unsupervised (machine learning) topic modeling on a sample of the last 10,000 tweets in English posted with the term #autism (January 2021). We built a network of words to visualize the main dimensions representing these data. Second, we performed precisely the same analysis with all the articles using the term "autism" in PubMed without time restriction. Lastly, we compared the results of the 2 databases. RESULTS: We retrieved 121,556 terms related to autism in 10,000 tweets and 5.7x109 terms in 57,121 biomedical scientific articles. The 4 main dimensions extracted from Twitter were as follows: integration and social support, understanding and mental health, child welfare, and daily challenges and difficulties. The 4 main dimensions extracted from PubMed were as follows: diagnostic and skills, research challenges, clinical and therapeutical challenges, and neuropsychology and behavior. CONCLUSIONS: This study provides the first systematic and rigorous comparison between 2 corpora of interests, in terms of lay representations and scientific research, regarding the significant increase in information available on autism spectrum disorder and of the difficulty to connect fragments of knowledge from the general population. The results suggest a clear distinction between the focus of topics used in the social media and that of scientific communities. This distinction highlights the importance of knowledge mobilization and exchange to better align research priorities with personal concerns and to address dimensions of well-being, adaptation, and resilience. Health care professionals and researchers can use these dimensions as a framework in their consultations to engage in discussions on issues that matter to beneficiaries and develop clinical approaches and research policies in line with these interests. Finally, our study can inform policy makers on the health and social needs and concerns of individuals with autism and their caregivers, especially to define health indicators based on important issues for beneficiaries.

Erotomania and phenotypic continuum in a family frameshift variant of AUTS2: a case report and review.

BACKGROUND: Pathogenic variants of the AUTS2 (Autism Susceptibility candidate 2) gene predispose to intellectual disability, autism spectrum disorder, attention deficit hyperactivity disorder, facial dysmorphism and short stature. This phenotype is therefore associated with neurocognitive disturbances and social cognition, indicating potential functional maladjustment in the affected subjects, and a potentially significant impact on quality of life. Although many isolated cases have been reported in the literature, to date no families have been described. This case reports on a family (three generations) with a frameshift variant in the AUTS2 gene. CASE PRESENTATION: The proband is 13 years old with short stature, dysmorphic features, moderate intellectual disability and autism spectrum disorder. His mother is 49 years old and also has short stature and similar dysmorphic features. She does not have autism disorder but presents an erotomaniac delusion. Her cognitive performance is heterogeneous. The two aunts are also of short stature. The 50-year-old aunt has isolated social cognition disorders. The 45-year-old aunt has severe cognitive impairment and autism spectrum disorder. The molecular analysis of the three sisters and the proband shows the same AUTS2 heterozygous duplication leading to a frame shift expected to produce a premature stop codon, p.(Met593Tyrfs*85). Previously reported isolated cases revealed phenotypic and cognitive impairment variability. In this case report, these variabilities are present within the same family, presenting the same variant. CONCLUSIONS: The possibility of a phenotypic spectrum within the same family highlights the need for joint psychiatry and genetics research.

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.

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.

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.

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.

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.

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.

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.].