Mediating Role of Emotional Intelligence in the Relationship Between Resilience and Academic Engagement in Adolescents: Differences Between Men and Women

Begoña María Tortosa Martínez, María del Carmen Pérez-Fuentes, María del Mar Molero Jurado Department of Psychology, University of Almería, Almería, SpainCorrespondence: Begoña María Tortosa Martínez, Department of Psychology, University of Almería, Almería, 04120, Spain, Tel +34 950015598, Email [email protected]: Resilience and academic engagement have become some of the most important elements in the academic context, due to their relationships with school adjustment, the protective role against risky behaviors and the well-being of adolescents.Purpose: Therefore, the objective of this study was to analyze the relationships established between the variables of resilience and academic engagement, the differences according to sex, as well as to determine the mediating role of emotional intelligence in the relationship between resilience and academic engagement in adolescence.Participants and Methods: A cross-sectional descriptive study was performed. The sample consisted of 802 secondary school students, with an average age of 13.65 years (SD = 1.24) (where 50.6% were women and 49.4% men) who filled out the Connor-Davidson Resilience Scale (CD-RISC 10), the General Academic Engagement Scale for Spanish Adolescents (CAADE) and the Spanish version of the Wong Law Emotional Intelligence Scale (WLEIS-S).Results: The results showed the existence of positive relationships between resilience and factors of academic engagement. Furthermore, the mediation models showed the direct effect of emotional intelligence on this relationship. On the other hand, with respect to sex, men showed significantly higher averages in resilience and emotional intelligence, with no significant differences in the variable of academic engagement.Conclusion: Concluding, design of emotional intelligence intervention programs in secondary is recommended as an effective measure for promoting resilience and a positive academic trajectory.Keywords: resilience, academic engagement, emotional intelligence, adolescents, mediation model

Sexual dysfunction and satisfaction in obsessive compulsive disorder: protocol for a systematic review and meta-analysis

Background Obsessive compulsive disorder (OCD) is a chronic mental health condition recognized as one of the most serious causes of disability and impaired quality of life. In the literature, there is no review about sexual dysfunction and satisfaction in OCD. The current paper presents the protocol for a systematic review and meta-analysis aimed to summarize data (1) comparing the presence of sexual dysfunction between groups with OCD and non-clinical groups, (2) investigating prevalence of each one of the sexual dysfunctions in patients with OCD, (3) comparing risk for sexual dysfunction in OCD groups with the prevalence in control groups, (4) comparing sexual satisfaction between OCD groups and non-clinical groups, and (5) investigating moderators of sexual dysfunction in OCD groups as compared with control groups. Gender, age, marital status, OCD symptom severity and subtypes, comorbid depressive disorders, comorbid anxiety disorders, concurrent psychiatric medications, comorbid general medical disease, and study quality will be investigated as moderators. Methods The protocol is reported according to PRISMA-P guidelines. The search will be conducted by independent reviewers during the second week of December 2019 by using electronic databases (Scopus, PubMed, EMBASE, PsycINFO, CINAHL, and the Cochrane Library), by contacting the authors of the included studies to identify further data, by examining the references of the included studies, and by handsearching conference proceedings and theses/doctoral dissertations. The study quality will be independently evaluated using the Newcastle-Ottawa Quality Assessment Scale. Random-effect meta-analyses will be computed. If there is insufficient data for a specific outcome, only a systematic review will be performed. Discussion This review may support clinical practice highlighting the importance of the assessment of sexuality in patients with OCD and suggesting the use of therapeutic strategies dedicated to sexuality in this clinical population with the aim of improving patients’ quality of life. Potential limitations will regard the heterogeneity of the studies in terms of the instruments used to assess sexual dysfunction/satisfaction and of the definitions used to conceptualize sexual dysfunction

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19

Data availability: Downloadable summary data are available through the GenOMICC data site (https://genomicc.org/data). Summary statistics are available, but without the 23andMe summary statistics, except for the 10,000 most significant hits, for which full summary statistics are available. The full GWAS summary statistics for the 23andMe discovery dataset will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. For further information and to apply for access to the data, see the 23andMe website (https://research.23andMe.com/dataset-access/). All individual-level genotype and whole-genome sequencing data (for both academic and commercial uses) can be accessed through the UKRI/HDR UK Outbreak Data Analysis Platform (https://odap.ac.uk). A restricted dataset for a subset of GenOMICC participants is also available through the Genomics England data service. Monocyte RNA-seq data are available under the title ‘Monocyte gene expression data’ within the Oxford University Research Archives (https://doi.org/10.5287/ora-ko7q2nq66). Sequencing data will be made freely available to organizations and researchers to conduct research in accordance with the UK Policy Framework for Health and Social Care Research through a data access agreement. Sequencing data have been deposited at the European Genome–Phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGAS00001007111.Extended data figures and tables are available online at https://www.nature.com/articles/s41586-023-06034-3#Sec21 .Supplementary information is available online at https://www.nature.com/articles/s41586-023-06034-3#Sec22 .Code availability: Code to calculate the imputation of P values on the basis of SNPs in linkage disequilibrium is available at GitHub (https://github.com/baillielab/GenOMICC_GWAS).Acknowledgements: We thank the members of the Banco Nacional de ADN and the GRA@CE cohort group; and the research participants and employees of 23andMe for making this work possible. A full list of contributors who have provided data that were collated in the HGI project, including previous iterations, is available online (https://www.covid19hg.org/acknowledgements).Change history: 11 July 2023: A Correction to this paper has been published at: https://doi.org/10.1038/s41586-023-06383-z. -- In the version of this article initially published, the name of Ana Margarita Baldión-Elorza, of the SCOURGE Consortium, appeared incorrectly (as Ana María Baldion) and has now been amended in the HTML and PDF versions of the article.Copyright © The Author(s) 2023, Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).GenOMICC was funded by Sepsis Research (the Fiona Elizabeth Agnew Trust), the Intensive Care Society, a Wellcome Trust Senior Research Fellowship (to J.K.B., 223164/Z/21/Z), the Department of Health and Social Care (DHSC), Illumina, LifeArc, the Medical Research Council, UKRI, a BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070 and BBS/E/D/30002275) and UKRI grants MC_PC_20004, MC_PC_19025, MC_PC_1905 and MRNO2995X/1. A.D.B. acknowledges funding from the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z), the Edinburgh Clinical Academic Track (ECAT) programme. This research is supported in part by the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant MC_PC_20029). Laboratory work was funded by a Wellcome Intermediate Clinical Fellowship to B.F. (201488/Z/16/Z). We acknowledge the staff at NHS Digital, Public Health England and the Intensive Care National Audit and Research Centre who provided clinical data on the participants; and the National Institute for Healthcare Research Clinical Research Network (NIHR CRN) and the Chief Scientist’s Office (Scotland), who facilitate recruitment into research studies in NHS hospitals, and to the global ISARIC and InFACT consortia. GenOMICC genotype controls were obtained using UK Biobank Resource under project 788 funded by Roslin Institute Strategic Programme Grants from the BBSRC (BBS/E/D/10002070 and BBS/E/D/30002275) and Health Data Research UK (HDR-9004 and HDR-9003). UK Biobank data were used in the GSMR analyses presented here under project 66982. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government, British Heart Foundation and Diabetes UK. The work of L.K. was supported by an RCUK Innovation Fellowship from the National Productivity Investment Fund (MR/R026408/1). J.Y. is supported by the Westlake Education Foundation. SCOURGE is funded by the Instituto de Salud Carlos III (COV20_00622 to A.C., PI20/00876 to C.F.), European Union (ERDF) ‘A way of making Europe’, Fundación Amancio Ortega, Banco de Santander (to A.C.), Cabildo Insular de Tenerife (CGIEU0000219140 ‘Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19’ to C.F.) and Fundación Canaria Instituto de Investigación Sanitaria de Canarias (PIFIISC20/57 to C.F.). We also acknowledge the contribution of the Centro National de Genotipado (CEGEN) and Centro de Supercomputación de Galicia (CESGA) for funding this project by providing supercomputing infrastructures. A.D.L. is a recipient of fellowships from the National Council for Scientific and Technological Development (CNPq)-Brazil (309173/2019-1 and 201527/2020-0)