A New Look on Long-COVID Effects: The Functional Brain Fog Syndrome

Epidemiological data and etiopathogenesis of brain fog are very heterogeneous in the literature, preventing adequate diagnosis and treatment. Our study aimed to explore the relationship between brain fog, neuropsychiatric and cognitive symptoms in the general population. A sample of 441 subjects underwent a web-based survey, including the PANAS, the DASS-21, the IES-R, the Beck Cognitive Insight Scale, and a questionnaire investigating demographic information, brain fog, subjective cognitive impairments (Scc) and sleep disorders. ANOVA, ANCOVA, correlation and multiple stepwise regression analyses were performed. In our sample, 33% of participants were defined as Healthy Subjects (HS; no brain fog, no Scc), 27% as Probable Brain Fog (PBF; brain fog or Scc), and 40% as Functional Brain Fog (FBF; brain fog plus Scc). PBF and FBF showed higher levels of neuropsychiatric symptoms than HS, and FBF showed the worst psychological outcome. Moreover, worse cognitive symptoms were related to the female gender, greater neuropsychiatric symptoms, sleep disorders, and rumination/indecision. Being a woman and more severe neuropsychiatric symptoms were predictors of FBF severity. Our data pointed out a high prevalence and various levels of severity and impairments of brain fog, suggesting a classificatory proposal and a multifaceted etiopathogenic model, thus facilitating adequate diagnostic and therapeutic approaches

Estimating Successful Internal Mobility: A Comparison Between Structural Equation Models and Machine Learning Algorithms

Internal mobility often depends on predicting future job satisfaction, for such employees subject to internal mobility programs. In this study, we compared the predictive power of different classes of models, i.e., (i) traditional Structural Equation Modeling (SEM), with two families of Machine Learning algorithms: (ii) regressors, specifically least absolute shrinkage and selection operator (Lasso) for feature selection and (iii) classifiers, specifically Bagging meta-model with the k-nearest neighbors algorithm (k-NN) as a base estimator. Our aim is to investigate which method better predicts job satisfaction for 348 employees (with operational duties) and 35 supervisors in the training set, and 79 employees in the test set, all subject to internal mobility programs in a large Italian banking group. Results showed average predictive power for SEM and Bagging k-NN (accuracy between 61 and 66%; F1 scores between 0.51 and 0.73). Both SEM and Lasso algorithms highlighted the predictive power of resistance to change and orientation to relation in all models, together with other personality and motivation variables in different models. Theoretical implications are discussed for using these variables in predicting successful job relocation in internal mobility programs. Moreover, these results showed how crucial it is to compare methods coming from different research traditions in predictive Human Resources analytics

COVID-19 and Stressful Adjustment to Work: A Long-Term Prospective Study About Homeworking for Bank Employees in Italy

The COVID-19 evolution has forced the massive introduction of homeworking (HW) for most employees in the initial stages of the pandemic and then return to work, mainly due to the vaccination campaign. These multiple abrupt adjustment demands in work may be a source of intense stress for office workers with consequences on wellbeing and the quality of life. This long-term prospective study aimed at investigating the effect of adaptation demands on a broad population of employees of a large Italian banking group in the job-related stress framework. We administered a web-based survey to 1,264 participants in Reopening after the first lockdown, from June to October 2020, at 841 subjects in Second Wave, corresponding to the rise of contagions from November 2020 to January 2021, and to 491 individuals in Vaccination Round, which ranged from February to June 2021. We assessed workaholism by using the Dutch Work Addiction Scale (DUWAS-10), work-family conflicting overlap by using the Work and Family Conflict Scale (WAFCS), and concern for back to work (BW) and for HW by specific questions. Higher WAFCS scores characterized Reopening and Vaccination Round while Second Wave had the highest level of concern for HW. Women and younger individuals showed the highest concern for BW, WAFCS, and DUWAS-10 scores regardless of the pandemic stage. HW days per week were related to more heightened concern for BW and lower concern for HW, DUWAS, and WAFCS scores. The number of children was related to lower Concern for BW and higher WAFCS scores in Reopening and Second Wave. Our data showed that massive adjustment demands in work and family routine represented a significant source of stress for employees, regardless of the different pandemic stages. The highest level of fatigue emerged in women and younger subjects. These results shed light on the need for a road map to promote a gradual and structured adjustment for workers and encourage organizations to consider homeworking as a valid stable alternative

A Novel Role for Dbx1-Derived Cajal-Retzius Cells in Early Regionalization of the Cerebral Cortical Neuroepithelium

Patterning of the cerebral cortex during embryogenesis depends not only on passive diffusion of morphogens but also on signal delivery by Cajal-Retzius neurons that migrate over long distances

The contribution of shape features and demographic variables to disembedding abilities

Humans typically perceive visual patterns in a global manner, and are remarkably capable of extracting object shapes based on properties such as proximity, closure, symmetry, and good continuation. Notwithstanding people’s attitude toward perceptual grouping, the research highlighted differences in disembedding performance across individuals, summarized by the field dependence/independence dimension. Previous studies revealed that age and educational attainment explain part of this variability, whereas the role of sex is still highly debated. Also, which stimulus features primarily influence inter-individual variations in perceptual grouping has to be fully determined. Building upon these premises, we assessed the role of age, level of education and sex on performance at the Leuven-Embedded Figure Test - a proxy of disembedding abilities - in a sample of 391 cisgender individuals. We also investigated whether stimulus symmetry, closure, complexity, and continuation relate to task accuracy as a function of personal characteristics. Overall, target asymmetry and continuation with the embedding context increase task difficulty, whereas target complexity demonstrates a U-shaped relationship with disembedding performance. Further, results unveil sex differences that have not been reported so far in adults and support the association between age, educational attainment, and disembedding abilities. Male individuals also benefit more from target symmetry and closure and are better at recognizing shapes when the embedding context is challenging. Lastly, highly educated adults better recognize asymmetrical and open targets, as well as shapes embedded in complex contexts. Taken together, our findings show how shape features relate to individual characteristics in explaining field independence