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The Levenson Self-Report Psychopathy Scale (LSRPS) is a psychometric tool composed of 26 items to assess psychopathic traits. This study aims to perform a network analysis of this scale in a large sample composed of 100 hospitalized psychiatric patients and 256 French-speaking Belgian university students in medicine and to compare the network structure. We estimated a regularized partial correlation network for the 26 items of the questionnaire. Node predictability is used to assess the connectivity of items. The network comparison test (NCT) and statistical inference on sum scores are conducted to compare networks from the inpatients and the university students. The networks composed of LSRPS are mostly connected positively, but some negative interconnections were observed in both inpatients and university students, and node connectivity varies. Although the scores from inpatients are substantially higher than those of university students, network analysis didn't show any statistical difference in the overall connectedness. Network analysis is a valuable tool for exploring psychopathic traits and offers new insight into how they interact. In the network estimation, we concluded that the two domains of psychopathy are interrelated. This interconnectivity was observed in both subject groups. We hypothesize that such interconnectivity was present because environmental and genetic factors are intricately intertwined in the appearance of primary and secondary psychopathy. Meanwhile, although inpatients may have higher scores of psychopathic traits, those traits' connectedness isn't different from that of the general population. This finding aligns well with the theory of hysteresis in network analysis, which states that the connections among components of mental disorders do not disappear or reappear over time, but their importance may vary. Further studies may replicate our findings using different sample groups.

"Teen dating violence" is a poorly studied issue in the literature. Several sociodemographic and psychiatric risk factors have been identified in the literature, and the consequences are numerous. The aim of this mixed study is to establish an initial inventory of the problem in French-speaking Belgium, to establish links with the socio-demographic and overall health characteristics of the population, and to issue recommendations for the future.A study by questionnaire was conducted among 103 young people aged between 14 and 18 living in French-speaking Belgium and speaking French in particular. Qualitative and quantitative (descriptive and inferential statistics) analyses were performed.29.1% of respondents experienced violence. Significant links exist between the fact of having experienced violence and consumption as well as the presence of STDs. The combination of potential risk factors predicts a considerable part of the violence in the sample. A significant link exists between the fact of being subjected to violence and a high score on the scale of depression and violence suffered and committed.The prevalence of teen dating violence is relatively high in Belgium. A link between these and a large part of the potential consequences studied could be highlighted through the study.

The impact of diagnostic delay in mental health is significant in terms of neurocognitive impairment, comorbidities, prognostic and socio-economical cost. For this reason, diagnostical research in psychiatry and the classification methods are continuously questioned. The network theory of mental disorders aims at contributing to the improvement of psychiatric diagnosis and considers mental disorders as the results of complex sets of interactions among symptoms instead of being their common cause. In this study, we use network theory and its associate statistical methods, namely Gaussian Graphical Models, centrality, and cluster analysis, to estimate respectively the interactions among symptoms from different disorders, their relative importance, and how they overlap, in a sample of psychiatric inpatients. The community detection found nine clusters with their interactions. Many are closely related to DSM criteria but some of them share symptoms from both diagnostics. One central symptom of the construct is Insomnia. There was a significant difference in the sum scores for psychotic symptoms, but not for bipolar symptoms, across psychotic and bipolar patients. This study needs however to be replicated in a bigger sample of different patients. Computing Bayesian Network to assess causalities in the network and adding other variables (such as biomarkers or therapeutic responses) could contribute to a more personalized diagnostic. How symptoms connect to each other in a specific time frame would define a person phenotype. Network analysis allows for investigating connections, identifying which symptoms are relatively important to the self-determination of disorders as well as how network nodes predict each other and arise in communities. For instance, in psychotic and mood disorders, sleep related symptoms or altered speech features and the importance of their communities in the probable transfer of symptomatology.

Attention deficit hyperactivity disorder (ADHD) is a neuropsychiatric disorder interfering with the normal development of the child. The disorder can be screened at school with the Conners Teacher Rating Scale Revised Short (CTRS-R:S). This scale goes beyond the disorder itself and covers a wider construct, that of abnormal child behavior. This can be understood as a complex system of mutually influencing entities. We analyzed a data set of 525 children in French-speaking primary schools from Belgium, and estimated a network structure, as well as to determine the local dependence of items through Unique Variable Analysis. A reduced network was computed including 15 non-locally dependent items. The structural consistency of the network was not affected by redundant items and was structurally sound. The reduction of the number of variables in network studies is important to improve the investigation of network structures as well as better interpret results from inference measures.

Background: Acute heart failure (AHF) is a disease with high incidence and mortality. Since 2016, new definitions were adopted for AHF requiring early management to improve prognosis. The aim of th...

Abnormal child behavior is a complex entity including among others disorders such as ADHD, a neuropsychiatric disorder interfering with the normal development of the child, and combining many comorbidities. There are no specific tools designed to assess abnormal child behavior, although well-known ADHD screening tools such as the CTRS-R:S go beyond the disorder itself and cover the wider construct. This can be understood as the complex system of mutually influencing entities, that is why the aim of this study was to investigate the items of the CTRS-R:S as a psychological network. We analyzed a data set of 525 children in French-speaking primary schools from Belgium, and estimated a Bayesian Gaussian Graphical Model with a Bayes Factor of 30. We identified highly connected nodes from each community of the CTRS-R:S to build an additional network of communities. In the domain network, Oppositional and Cognitive skills share the strongest connection in the network. The 28-item network was overall positively connected albeit the presence of some negative connections. The spinglass algorithm identified eight domains in the CTRS-R:S network that causally influence each other. The network approach is a useful framework to investigate the domains of abnormal child behavior as well as the interplay between individual symptoms.

Bayesian Networks are probabilistic graphical models that represent conditional independence relationships among variables as a directed acyclic graph (DAG), where edges can be interpreted as causal effects connecting one causal symptom to an effect symptom. These models can help overcome one of the key limitations of partial correlation networks whose edges are undirected. This tutorial aims to introduce Bayesian Networks to identify admissible causal relationships in cross-sectional data, as well as how to estimate these models in R through three algorithm families with an empirical example data set of depressive symptoms. In addition, we discuss common problems and questions related to Bayesian networks. We recommend Bayesian networks be investigated to gain causal insight in psychological data. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The aim of this work is to explore the construct of autistic traits through the lens of network analysis with recently introduced Bayesian methods. A conditional dependence network structure was estimated from a data set composed of 649 university students that completed an autistic traits questionnaire. The connectedness of the network is also explored, as well as sex differences among female and male subjects in regard to network connectivity. The strongest connections in the network are found between items that measure similar autistic traits. Traits related to social skills are the most interconnected items in the network. Sex differences are found between female and male subjects. The Bayesian network analysis offers new insight on the connectivity of autistic traits as well as confirms several findings in the autism literature., SCOPUS: ar.j, info:eu-repo/semantics/published

Purpose SARS-CoV-2 vaccines are a key step in fighting the pandemic. Nevertheless, their rapid development did not allow for testing among specific population subgroups such as pregnant and breastfeeding women, or elaborating specific guidelines for healthcare personnel working in high infection risk specialties, such as otolaryngology (ORL). This clinical consensus statement (CCS) aims to offer guidance for SARS-CoV-2 vaccination to this high-risk population based on the best evidence available. Methods A multidisciplinary international panel of 33 specialists judged statements through a two-round modified Delphi method survey. Statements were designed to encompass the following topics: risk of SARS-Cov-2 infection and use of protective equipment in ORL; SARS-Cov-2 infection and vaccines and respective risks for the mother/child dyad; and counseling for SARS-CoV-2 vaccination in pregnant, breastfeeding, or fertile healthcare workers (PBFHW). All ORL PBFHW were considered as the target audience. Results Of the 13 statements, 7 reached consensus or strong consensus, 2 reached no consensus, and 2 reached near-consensus. According to the statements with strong consensus otorhinolaryngologists—head and neck surgeons who are pregnant, breastfeeding, or with childbearing potential should have the opportunity to receive SARS-Cov-2 vaccination. Moreover, personal protective equipment (PPE) should still be used even after the vaccination. Conclusion Until prospective evaluations on these topics are available, ORL-HNS must be considered a high infection risk specialty. While the use of PPE remains pivotal, ORL PBFHW should be allowed access to SARS-CoV-2 vaccination provided they receive up-to-date information., info:eu-repo/semantics/published

Purpose The Oswestry Disability Index (ODI) is a common aggregate measure of disability for people with Low Back Pain (LBP). Scores on individual items and the relationship between items of the ODI may help understand the complexity of low back disorders and their response to treatment. In this study, we present a network analysis to explore how individualised physiotherapy or advice might influence individual items of the ODI, and the relationship between those items, at different time points for people with LBP. Methods Data from a randomised controlled trial (n = 300) comparing individualised physiotherapy versus advice for low back pain were used. A network analysis was performed at baseline, 5, 10, 26 and 52 weeks, with the 10 items of the Oswestry Disability Index modelled as continuous variables and treatment group (Individualised Physiotherapy or Advice) modelled as a dichotomous variable. A Mixed Graphical Model was used to estimate associations between variables in the network, while centrality indices (Strength, Closeness and Betweenness) were calculated to determine the importance of each variable. Results Individualised Physiotherapy was directly related to lower Sleep and Pain scores at all follow-up time points relative to advice, as well as a lower Standing score at 10-weeks, and higher Lifting and Travelling scores at 5-weeks. The strongest associations in the network were between Sitting and Travelling at weeks 5 and 26, between Walking and Standing at week 10, and between Sitting and Standing scores at week 52. ODI items with the highest centrality measures were consistently found to be Pain, Work and Social Life. Conclusion This study represents the first to understand how individualised physiotherapy or advice differentially altered disability in people with LBP. Individualised Physiotherapy directly reduced Pain and Sleep more effectively than advice, which in turn may have facilitated improvements in other disability items. Through their high centrality measures, Pain may be considered as a candidate therapeutic target for optimising LBP management, while Work and Socialising may need to be addressed via intermediary improvements in lifting, standing, walking, travelling or sleep. Slower (5-week follow-up) improvements in Lifting and Travelling as an intended element of the Individualised Physiotherapy approach did not negatively impact any longer-term outcomes. Trials registration ACTRN12609000834257.

Partial correlation networks have emerged as an increasingly popular model for studyingmental disorders. Although conditional independence is a fundamental concept in networkanalysis, which corresponds to the null hypothesis, the focus is typically to detect and thenvisualize non-zero partial correlations (i.e., the “edges” connecting nodes) in a graph. As aresult, it may be tempting to interpret a missing edge as providing evidence for itsabsence—analogously to misinterpreting a non-significant p-value. In this work, we firstestablish that a missing edge is incorrectly interpreted as providing evidence for conditionalindependence, with examples spanning from substantive applications to tutorials thatinstruct researchers to misinterpret their networks. We then go beyond misguided“inferences” and establish that null associations are interesting in their own right. In thefollowing section, three illustrative examples are provided that employ Bayesian hypothesistesting to formally evaluate the null hypothesis, including a reanalysis of twopsychopathology networks, confirmatory testing to determine whether a particularpost-traumatic stress disorder symptom is disconnected from the network, and attenuationdue to correcting for covariates. Our results shed light upon conditionally independentsymptoms and demonstrate that a missing edge does not necessarily correspond toevidence for the null hypothesis. These findings are accompanied with a simulation studythat provides insights into the sample size needed to accurately detect null relations. Weconclude with implications for both clinical to theoretical inquiries.

Smart medical technologies are augmenting clinical practice by offering the patient an increased autonomy and the clinician more advanced tools to predict, detect, monitor, and treat diseases. Augmented Medicine, a new framework of techniques that extends to clinical practice from the applied medical research aiming to introduce and improve tools, is rapidly gaining popularity. In this chapter, we will outline the principles of Augmented Medicine and its main applications in clinical practice, as well as future directions of this promising field.

The aim of this paper is to explore the network structures of alexithymia components and compare results with relevant prior literature.In a large sample of university students, undirected and directed network structures of items from the Bermond Vorst Alexithymia Questionnaire form B are estimated with state-of-the-art network analysis and structure learning tools. Centrality estimates are used to address the topic of item redundancy and select relevant alexithymia components to study.Alexithymia components present positive as well as negative connections; poor fantasy and emotional insight are identified as central items in the network.The undirected network structure of alexithymia components reports new features with respect to prior literature, and the directed network structures offers new insight on the construct.

The Self-rating Depression Scale (SDS) is a psychometric tool composed of 20 items used to assess depression symptoms. The aim of this work is to perform a network analysis of this scale in a large sample composed of 1090 French-speaking Belgian university students. We estimated a regularized partial correlation network and a Directed Acyclic Graph for the 20 items of the questionnaire. Node predictability (shared variance with surrounding nodes in the network) was used to assess the connectivity of items. The network comparison test was performed to compare networks from female and male students. The network composed of items from the SDS is overall positively connected, although node connectivity varies. Item 11 (“My mind is as clear as it used to be”) is the most interconnected item. Networks from female and male students did not differ. DAG reported directed edges among items. Network analysis is a useful tool to explore depression symptoms and offers new insight as to how they interact. Further studies may endeavor to replicate our findings in different samples, including clinical samples to replicate the network structures and determine possible viable targets for clinical intervention., SCOPUS: ar.j, info:eu-repo/semantics/published

This study investigates the Contingencies of Self-Worth Scale (CSWS) in a sample of 680 university students from a network perspective. We estimated regularized partial correlations among seven CSWS domains: family support, competition, appearance, God's love, academic competence, virtue and other's approval. Competition – academic competence and competition – appearance represent the strongest connections in the network. Mean node predictability (shared variance with surrounding nodes) is 0.25. Appearance and academic competence were the most central (i.e., interconnected) domains in the network. Future studies should explore the network structure of self-worth in other healthy adult samples, and also in people with psychopathology. We provide the anonymized dataset as well as the full code in the supplementary materials to ensure complete reproducibility of the results.

The brain undergoes ionizing radiation (IR) exposure in many clinical situations, particularly during radiotherapy for malignant brain tumors. Cranial radiation therapy is related with the hazard of long-term neurocognitive decline. The detrimental ionizing radiation effects on the brain closely correlate with age at treatment, and younger age associates with harsher deficiencies. Radiation has been shown to induce damage in several cell populations of the mouse brain. Indeed, brain exposure causes a dysfunction of the neurogenic niche due to alterations in the neuronal and supporting cell progenitor signaling environment, particularly in the hippocampus—a region of the brain critical to memory and cognition. Consequent deficiencies in rates of generation of new neurons, neural differentiation and apoptotic cell death, lead to neuronal deterioration and lasting repercussions on neurocognitive functions. Besides neural stem cells, mature neural cells and glial cells are recognized IR targets. We will review the current knowledge about radiation-induced damage in stem cells of the brain and discuss potential treatment interventions and therapy methods to prevent and mitigate radiation related cognitive decline.

Table 1 has been removed from the aforementioned article as full appropriate permission was not obtained. Please refer to the original reference for the table: Friborg O, Martinussen M and Rosenvinge JH (2006) Likert-based vs. semantic differential-based scorings of positive psychological constructs: a psychometric comparison of two versions of a scale measuring resilience. Personality and Individual Differences 40, 873 884.The authors apologise for this error., SCOPUS: er.j, info:eu-repo/semantics/published

L’approche des "networks" connaît un succès de plus en plus important en psychiatrie et neurosciences computationnelles. Cette nouvelle méthodologie, issue de la translation de modèles de physique statistique en médecine, accorde une nouvelle vue ontologique sur les troubles mentaux, en les définissant comme des systèmes complexes émergeant de l’interconnexion entre différents symptômes. Cet article propose au clinicien une introduction tant théorique que méthodologique au potentiel dont dispose cette approche pour l’amélioration du diagnostic et traitement des maladies psychiatriques, en fournissant quelques exemples d’application explorée en recherche clinique.

The aim of this study is to explore network structures of the Toronto Alexithymia Scale in a large sample of 1925 French-speaking Belgian university students and compare results with previous studies from different samples and tools to identify potential targets for clinical intervention. We estimated network models for the 20 items of the Toronto Alexithymia Scale and for its three domains difficulty identifying feelings, difficulty describing feelings, and externally oriented thinking. We explored item connectivity through node predictability (shared variance with other network components). We performed an exploratory graph analysis to explore the dimensionality of our data set and compare results with the original three-factor model; because a different model was proposed, we estimated an additional network structure on the new structure. Items from the Toronto Alexithymia Scale connect both within and between domains. The three-domain network identifies difficulty describing feelings as the most connected domain. The exploratory graph analysis reported that three items from externally oriented thinking form a new domain, distraction. In the new four-domain network, difficulty describing feelings remains the most interconnected domain; however, two negative connections are found. Our findings support the relative importance of identifying and describing feelings as a meaningful target for intervention., SCOPUS: ar.j, info:eu-repo/semantics/published

Objectives: The aim of this work is to explore the Narcissistic Personality Inventory (NPI) using network analysis in a dataset of 942 university students from the French-speaking part of Belgium. Methods: We estimated an Ising Model for the forty items in the questionnaire and explored item interconnectedness with strength centrality. We provide in the supplementary materials the dataset used for the analyses as well as the full code to ensure the reproducibility of our results. Results: The NPI is presented as an overall positively connected network with items from entitlement, authority and superiority reporting the highest centrality estimates. Conclusions: Network analysis highlights new properties of items from the NPI. Future studies should endeavor to replicate our findings in other samples, both clinical and non-clinical., SCOPUS: ar.j, info:eu-repo/semantics/published

The histopathologic examination is important after tonsillectomy, irrespective to the surgical indication., info:eu-repo/semantics/published

AimsThe Resilience Scale for Adults (RSA) is a questionnaire that measures protective factors of mental health. The aim of this paper is to perform a network analysis of the RSA in a dataset composed of 675 French-speaking Belgian university students, to identify potential targets for intervention to improve protective factors in individuals.MethodsWe estimated a network structure for the 33-item questionnaire and for the six domains of resilience: Perception of self, planned future, social competence, structured style, family cohesion and social competence. Node predictability (shared variance with surrounding nodes in the network) was used to assess the connectivity of items. An exploratory graph analysis (EGA) was performed to detect communities in the network: The number of communities detected being different than the original number of factors proposed in the scale, we estimated a new network with the resulting structure and verified the validity of the new construct which was proposed. We provide the anonymised dataset and code in external online materials (10.17632/64db36w8kf.2) to ensure complete reproducibility of the results.ResultsThe network composed of items from the RSA is overall positively connected with strongest connections arising among items from the same domain. The domain network reports several connections, both positive and negative. The EGA reported the existence of four communities that we propose as an additional network structure. Node predictability estimates show that connectedness varies among the items and domains of the RSA.ConclusionsNetwork analysis is a useful tool to explore resilience and identify targets for clinical intervention. In this study, the four domains acting as components of the additional four-domain network structure may be potential targets to improve an individual's resilience. Further studies may endeavour to replicate our findings in different samples., SCOPUS: ar.j, info:eu-repo/semantics/published

We present the case of a 54 year old male complaining of abdominal pain localised in the right flank and irradiating in other abdominal regions. The pain was previously associated with kidney stones, but persisted months after their total evacuation. Suffering from Crohn's disease, low dose corticosteroids likely caused a particularly invalidating chronic prostatitis, which antibiotic treatment aggravated the symptoms of Crohn's disease, therefore complicating the therapeutic care by causing a vicious circle. Further epidemiological and microbiological studies are needed in order to establish an association between low dose steroid for Crohn's disease and chronic pelvic pain syndrome.On présente le cas d’un homme de 54 ans se plaignant d’une douleur dans le flanc droit irradiant dans d’autres régions abdominales. La douleur était précédemment associée à la présence de lithiases urinaires, mais persiste des mois après leur évacuation. Souffrant d’une maladie de Crohn, le traitement par faible dose de corticostéroïdes a vraisemblablement causé une prostatite chronique particulièrement invalidante, dont le traitement antibiotique aggrave les symptômes de la maladie de Crohn compliquant ainsi la prise en charge thérapeutique par un cercle vicieux. Des études épidémiologiques et microbiologiques plus approfondies sont nécessaire afin d’établir l’association entre le traitement stéroïde à faible dose pour la maladie de Crohn et le syndrome douloureux pelvien.

Un manuel de description pour la dissection de la tête, du cou et de la base du crâne.

Ce syllabus décrit la physiopathologie des principales maladies humaines ainsi que des bases d'anatomie et physiologie.

Vaccines: why and how do we need to improve vaccine coverage?

Ce syllabus vient en supplément et en aide de mes étudiants pour l'étude de différentes matières des sciences de la vie, comme la physiologie, la physiopathologie et la biologie humaine.

Ce syllabus comprend une description de la physiopathologie des principales maladies du système nerveux.

The fossa navicularis is an anatomical variant of the skull base thought to be a rare finding. It represents a bony depression in the skull base. The authors here report the case of a fossa navicularis magna in a 9-year-old female who had been treated for recurrent episodes of meningitis.A literature review was also done to highlight the unique features and clinical importance of this distinctive radiological skull base finding. The literature search covered papers from the 19th century up to 2018. Earlier authors described “fossa navicularis” as a very rare skull base finding. So far, only three cases of fossa navicularis with associated clival or intracranial infection have been reported in the literature. This is the fourth reported case, and the defect was closed endoscopically via a transnasal route. This morphological skull base anomaly should be considered in the differential diagnoses for an unexplained skull base infective pathology.Skull base surgeons should be aware of the existence of the fossa navicularis because of its clinical importance in rendering a prompt diagnosis and appropriate treatment.