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Introduction : Faisant partie des ambitions des hautes autorités de santé en vue d’une amélioration de la qualité des soins, la collaboration interprofessionnelle (CIP) représente encore actuellement un défi au sein du service des soins intensifs. Ces derniers sont un service hospitalier où de multiples professionnels de la santé spécialisés sont amenés à collaborer dans un contexte de travail influencé par le caractère critique des prises en soins des patients. Bien que les infirmiers et les médecins déclarent travailler en interprofessionnalité, la littérature démontre que leur pratique ne reflète pas ce concept. Les soins sont fournis par des tribus de médecins, d’infirmiers, de kinésithérapeutes, … où les interactions sont plus souvent intra-professionnelles qu’interprofessionnelles, impactant négativement la CIP. Cette notion tribale est reprise dans un concept appelé le tribalisme médical. 
Matériel et méthodes : Cette étude utilise une approche mixte combinant une scoping review et une phase qualitative phénoménologique multicentrique afin de : 1) Réaliser l’état des lieux de l’influence que deux composantes du tribalisme médical, la domination et les stéréotypes de genre, peuvent avoir sur la collaboration médico-infirmière hospitalière. 2) Analyser la façon dont se traduit le tribalisme médical au sein de la collaboration médico-infirmière dans les services de soins intensifs de trois hôpitaux wallons. 
Résultats : La scoping review identifie dans quel contexte le concept du tribalisme médical s’ancre de façon générale dans le secteur hospitalier. La phase qualitative phénoménologique multicentrique apporte des arguments quant à la façon dont le tribalisme médical se traduit au sein des relations médecins-infirmiers ; infirmiers-infirmiers ; médecins-médecins. 
Conclusion : La hiérarchie médico-infirmière persistante dans les services de soins intensifs entrave les relations interprofessionnelles, marquées par les stigmates historiques. Les professionnels ont un fort attachement à leur service, mais aussi à leur profession respective créant des comportements tribaux "Nous contre Eux". Pour atténuer ceux-ci, les managers médico-infirmiers des unités se doivent de faire preuve d’exemplarité en promouvant un leadership respectant l’interprofessionnalité. Encourageant une collaboration interprofessionnelle, une révision de la formation professionnelle semble aussi pertinente. Introduction : As part of the health authorities' ambitions for improving the quality of care, Interprofessional Collaboration (IPC) still represents a challenge within the Intensive Care Units (ICU). ICUs are hospital departments where multiple specialized healthcare professionals collaborate in a work environment influenced by the critical nature of patient care. Although nurses and physicians report working interprofessionally, the literature demonstrates that their practice does not reflect this concept. Care is provided by tribes of physicians, nurses, physiotherapists, etc., where interactions are more often intraprofessional than interprofessional, negatively impacting IPC. This tribal notion is captured in a concept called medical tribalism. 
Materials and Methods: This study employs a mixed-methods approach combining a scoping review and a multicentric qualitative phenomenological phase to : 1) Assess the influence of two components of medical tribalism, dominance and gender stereotypes, on hospital medical-nursing collaboration. 2) Analyze how medical tribalism manifests within medical nursing collaboration in the intensive care units of three hospitals in Wallonia. Results: The scoping review identifies the general context in which the concept of medical tribalism is rooted within the hospital sector. The multicentric qualitative phenomenological phase provides insights into how medical tribalism translates within physician-nurse, nurse nurse, and physician-physician relationships. 
Conclusion: Persistent medical-nursing hierarchy in ICUs hinders interprofessional relations, marked by historical stigmas. Professionals exhibit strong attachment to their unit and respective profession, creating tribal behaviors of "Us versus Them." To mitigate these, medical-nursing unit managers must demonstrate exemplary leadership by promoting interprofessional respect. To promote interprofessional collaboration, a revision of professional training also appears relevant.

Tribalisme médical --- -collaboration interprofessionnelle --- Médecin --- Infirmier --- Domination médico-infirmière --- Stéréotype de genre --- Medical tribalism --- Interprofessional collaboration --- Physician --- Nurse --- Medical-nursing dominance --- Gender stereotypes --- Sciences de la santé humaine > Santé publique, services médicaux & soins de santé

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[The role of women in entrepreneurship, management and corporate governance is regarded as central to the development and welfare of economies. Since the early 1980s, there has been increased interest in women managers and entrepreneurs, often from an interdisciplinary approach, combining, for example, sociology, psychology, management and organisational studies and economics. Nowadays, research on women in management and organisations is continuously and rapidly evolving (Paoloni and Demartini, 2016). Research on how women face new business challenges within organisations—as entrepreneurs, owners, managers, as well as workers—can contribute to understanding the new drivers affecting value creation dynamics in our knowledge-based society (Cesaroni, Demartini and Paoloni, 2017). Accordingly, this book tries to offer some insights on how women create, process and share knowledge in their business activity through the application and exploitation of novel creative ideas and solutions]

n/a --- gender stratification --- gender --- role salience --- female entrepreneurship --- motherhood --- new high-technology ventures --- high tech female entrepreneur --- career paths --- women founders --- mumpreneurs --- glass ceiling --- public governance --- leadership --- economic variable classification --- work–family balance --- gender gap --- Chile --- underperformance hypothesis --- career management --- gender equality --- Innovative female startups --- gender stereotypes --- entrepreneurship --- startups --- economic crisis --- gender-responsive budget --- chartered public accountants --- decision-making --- women in top management --- stakeholder engagement --- woman startups --- Italy --- accounting profession --- gender analysis --- gender issues --- women --- governance --- work-family balance

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One of the most promising developments in modelling knowledge is cognitive network science, which aims to investigate cognitive phenomena driven by the networked, associative organization of knowledge. For example, investigating the structure of semantic memory via semantic networks has illuminated how memory recall patterns influence phenomena such as creativity, memory search, learning, and more generally, knowledge acquisition, exploration, and exploitation. In parallel, neural network models for artificial intelligence (AI) are also becoming more widespread as inferential models for understanding which features drive language-related phenomena such as meaning reconstruction, stance detection, and emotional profiling. Whereas cognitive networks map explicitly which entities engage in associative relationships, neural networks perform an implicit mapping of correlations in cognitive data as weights, obtained after training over labelled data and whose interpretation is not immediately evident to the experimenter. This book aims to bring together quantitative, innovative research that focuses on modelling knowledge through cognitive and neural networks to gain insight into mechanisms driving cognitive processes related to knowledge structuring, exploration, and learning. The book comprises a variety of publication types, including reviews and theoretical papers, empirical research, computational modelling, and big data analysis. All papers here share a commonality: they demonstrate how the application of network science and AI can extend and broaden cognitive science in ways that traditional approaches cannot.

Information technology industries --- text mining --- big data --- analytics --- review --- self-organization --- computational philosophy --- brain --- synaptic learning --- adaptation --- functional plasticity --- activity-dependent resonance states --- circular causality --- somatosensory representation --- prehensile synergies --- robotics --- COVID-19 --- social media --- hashtag networks --- emotional profiling --- cognitive science --- network science --- sentiment analysis --- computational social science --- Twitter --- VADER scoring --- correlation --- semantic network analysis --- intellectual disability --- adolescents --- EEG --- emotional states --- working memory --- depression --- anxiety --- graph theory --- classification --- machine learning --- neural networks --- phonotactic probability --- neighborhood density --- sub-lexical representations --- lexical representations --- phonemes --- biphones --- cognitive network --- smart assistants --- knowledge generation --- intelligent systems --- web components --- deep learning --- web-based interaction --- cognitive network science --- text analysis --- natural language processing --- artificial intelligence --- emotional recall --- cognitive data --- AI --- pharmacological text corpus --- automatic relation extraction --- gender stereotypes --- story tropes --- movie plots --- network analysis --- word co-occurrence network --- n/a

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One of the most promising developments in modelling knowledge is cognitive network science, which aims to investigate cognitive phenomena driven by the networked, associative organization of knowledge. For example, investigating the structure of semantic memory via semantic networks has illuminated how memory recall patterns influence phenomena such as creativity, memory search, learning, and more generally, knowledge acquisition, exploration, and exploitation. In parallel, neural network models for artificial intelligence (AI) are also becoming more widespread as inferential models for understanding which features drive language-related phenomena such as meaning reconstruction, stance detection, and emotional profiling. Whereas cognitive networks map explicitly which entities engage in associative relationships, neural networks perform an implicit mapping of correlations in cognitive data as weights, obtained after training over labelled data and whose interpretation is not immediately evident to the experimenter. This book aims to bring together quantitative, innovative research that focuses on modelling knowledge through cognitive and neural networks to gain insight into mechanisms driving cognitive processes related to knowledge structuring, exploration, and learning. The book comprises a variety of publication types, including reviews and theoretical papers, empirical research, computational modelling, and big data analysis. All papers here share a commonality: they demonstrate how the application of network science and AI can extend and broaden cognitive science in ways that traditional approaches cannot.

text mining --- big data --- analytics --- review --- self-organization --- computational philosophy --- brain --- synaptic learning --- adaptation --- functional plasticity --- activity-dependent resonance states --- circular causality --- somatosensory representation --- prehensile synergies --- robotics --- COVID-19 --- social media --- hashtag networks --- emotional profiling --- cognitive science --- network science --- sentiment analysis --- computational social science --- Twitter --- VADER scoring --- correlation --- semantic network analysis --- intellectual disability --- adolescents --- EEG --- emotional states --- working memory --- depression --- anxiety --- graph theory --- classification --- machine learning --- neural networks --- phonotactic probability --- neighborhood density --- sub-lexical representations --- lexical representations --- phonemes --- biphones --- cognitive network --- smart assistants --- knowledge generation --- intelligent systems --- web components --- deep learning --- web-based interaction --- cognitive network science --- text analysis --- natural language processing --- artificial intelligence --- emotional recall --- cognitive data --- AI --- pharmacological text corpus --- automatic relation extraction --- gender stereotypes --- story tropes --- movie plots --- network analysis --- word co-occurrence network --- n/a

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Sexuality is considered as a great human value related to happiness and satisfaction, but unfortunately, when affecting mental disorders, they tend to be associated with second level human functions. Nevertheless, sexual dysfunction often accompanies psychiatric disorder, intensely influencing compliance, quality of life and human relationships. Sexuality could be influenced either by a mental disorder itself, difficulties to get and maintain couple relationships or by the use of psychotropic treatments. Treatment-related adverse events are unfortunately under-recognized by clinicians, scarcely spontaneously communicated by patients, and rarely investigated in clinical trials. The most frequent psychotropic compounds that could deteriorate sexuality and quality of life include antidepressants, antipsychotics and mood regulators. There are important differences between them related to some variations in mechanisms of action including serotonin, dopamine and prolactin levels. Little is known about the relevance of sexuality and its dysfunctions in chronic and frequent mental and neurological disorders, such as psychosis, mood disorders, anxiety, phobias, eating disorders, alcohol or drug dependencies, epilepsy and childhood pathology. Poor sexual life, low satisfaction and more frequent risky sex behavior than in the general population are associated with severe mental diseases. There is a need for increasing research in this field, including epidemiological, psychological, neurophysiological, neuroanatomical and genetic variables related to sexual life to get a better understanding of the implicated mechanisms. To increase the sensibility of clinicians, the identification and management of sexual disturbances after the onset of any mental disorder should be highlighted. This would avoid unnecessary suffering and deterioration of quality of life.

Humanities --- Social interaction --- online pornography --- addiction --- cybersex --- internet --- compulsive sexual behavior --- hypersexuality --- dopaminergic system --- paroxetine --- agomelatine --- immunohistochemical study --- sexual dysfunction --- male rats --- sexual addiction --- sexual compulsivity --- phenomenology --- comorbidities --- opioid-related disorders --- methadone --- adverse effects --- erectile dysfunction --- medication adherence --- erotic stimulus processing --- serotonin --- noradrenaline --- dopamine --- fMRI --- healthy --- human --- sexual communication anxiety --- sexual perfectionism --- parent-child communication --- risky sexual behavior --- child sexual abuse --- female perpetrator --- mother-child incest --- gender stereotypes --- social taboo --- transgender --- anxiety --- depression --- social loneliness --- romantic loneliness --- autism --- sexual satisfaction --- Asperger syndrome --- sexual desire --- lubrication --- sexual intercourse --- sexual excitation --- sexual inhibition --- post-traumatic stress disorder --- veterans --- predictors --- sexuality --- mental health --- mental disorder --- hidradenitis suppurativa --- sexual abstinence --- partner status --- prison inmates --- eye tracking --- non-consensual image sharing --- intimate images --- objectification --- objectifying gaze --- rape myth acceptance --- sexting --- desvenlafaxine --- antidepressant --- treatment --- prsexdq-salsex questionnaire --- switching strategy --- female sexual dysfunction --- hormonal contraceptive --- libido --- desire --- sex life --- orgasm --- vaginal ring --- depot medroxyprogesterone acetate --- pornography --- delayed ejaculation --- NeMUP --- child sexual offending --- pedophilia --- SCID --- peyronie’s disease --- penile induration --- patient satisfaction --- research --- online pornography --- addiction --- cybersex --- internet --- compulsive sexual behavior --- hypersexuality --- dopaminergic system --- paroxetine --- agomelatine --- immunohistochemical study --- sexual dysfunction --- male rats --- sexual addiction --- sexual compulsivity --- phenomenology --- comorbidities --- opioid-related disorders --- methadone --- adverse effects --- erectile dysfunction --- medication adherence --- erotic stimulus processing --- serotonin --- noradrenaline --- dopamine --- fMRI --- healthy --- human --- sexual communication anxiety --- sexual perfectionism --- parent-child communication --- risky sexual behavior --- child sexual abuse --- female perpetrator --- mother-child incest --- gender stereotypes --- social taboo --- transgender --- anxiety --- depression --- social loneliness --- romantic loneliness --- autism --- sexual satisfaction --- Asperger syndrome --- sexual desire --- lubrication --- sexual intercourse --- sexual excitation --- sexual inhibition --- post-traumatic stress disorder --- veterans --- predictors --- sexuality --- mental health --- mental disorder --- hidradenitis suppurativa --- sexual abstinence --- partner status --- prison inmates --- eye tracking --- non-consensual image sharing --- intimate images --- objectification --- objectifying gaze --- rape myth acceptance --- sexting --- desvenlafaxine --- antidepressant --- treatment --- prsexdq-salsex questionnaire --- switching strategy --- female sexual dysfunction --- hormonal contraceptive --- libido --- desire --- sex life --- orgasm --- vaginal ring --- depot medroxyprogesterone acetate --- pornography --- delayed ejaculation --- NeMUP --- child sexual offending --- pedophilia --- SCID --- peyronie’s disease --- penile induration --- patient satisfaction --- research