Anxiety sensitivity in school attending youth : exploratory and confirmatory factor analysis of the 18-item CASI in a multicultural South African sample

CITATION: Martin, L., Kidd, M. & Seedat, S. 2016. Anxiety sensitivity in school attending youth: exploratory and confirmatory factor analysis of the 18-item CASI in a multicultural South African sample. Frontiers in Psychology, 6:1996, doi:10.3389/fpsyg.2015.01996.The original publication is available at http://journal.frontiersin.org/journal/psychologyENGLISH SUMMARY : Anxiety sensitivity (AS) is a risk factor for the development of anxiety disorders in youth. To date, the applicability of the Childhood Anxiety Sensitivity Index (CASI) in youth from a low or middle income country (LMIC) setting on the African continent has not been assessed. A representative sample of 1149 secondary school learners from 29 schools in Cape Town, South Africa, participated in the study. Participants completed the CASI on a single occasion. One-, two-, and four-factor models of the CASI were assessed. A one-factor solution that comprised items predominantly represented by physical concerns appeared to provide the best fit to our data, however, relatively low variance (26%) was explained. Subsequent item deletion resulted in a 9-item ‘physical concerns’ factor that showed good construct reliability (0.83) but also explained a low amount of variance (35%). In terms of gender, a one-factor model provided the best fit, however, low variance was explained (i.e., 25%). Configural, metric and scalar invariance of the CASI by gender was determined. Our results suggest that the 18-item CASI is not applicable to our target population and may require adaptation in this population; however, replication of this study in other multicultural adolescent samples in South Africa is first needed to further assess the validity of the AS construct as measured by the CASI.http://journal.frontiersin.org/article/10.3389/fpsyg.2015.01996/fullPublisher's versio

BDNF Val66Met and DRD2 Taq1A polymorphisms interact to influence PTSD symptom severity: A preliminary investigation in a South African population

BACKGROUND: We evaluated the role that selected variants in serotonin transporter (5-HTT), dopamine receptor 2 (DRD2) and brain-derived neurotrophic factor (BDNF) genes play in PTSD symptom severity in an at-risk population. We also investigated the interaction between the genetic variants to determine whether these variables and the interactions between the variables influenced the severity of PTSD symptoms. METHODS: PTSD symptoms were quantitatively assessed using the Davidson Trauma Scale (DTS) in 150 participants from an at-risk South African population. All participants were genotyped for the 5-HTTLPR, DRD2 Taq1A and BDNF Val66Met polymorphisms. Gene–gene interactions were investigated using various linear models. All analyses were adjusted for age, gender, major depressive disorder diagnosis, level of resilience, level of social support and alcohol dependence. RESULTS: A significant interaction effect between DRD2 Taq1A and BDNF Val66Met variants on DTS score was observed. On the background of the BDNF Val66Val genotype, DTS score increased significantly with the addition of a DRD2 Taq1A A1 allele. However, on the BDNF Met66 allele background, the addition of an A1 allele was found to reduce total DTS score. CONCLUSIONS: This study provides preliminary evidence for an epistatic interaction between BDNF Val66Met and DRD2 Taq1A polymorphisms on the severity of PTSD symptoms, where both too little and too much dopamine can result in increased PTSD symptom severity.Web of Scienc

Performance evaluation of the Pima™ point-of-care CD4 analyser using capillary blood sampling in field tests in South Africa

<p>Abstract</p> <p>Background</p> <p>Point-of-care CD4 testing can provide immediate CD4 reporting at HIV-testing sites. This study evaluated performance of capillary blood sampling using the point-of-care Pima™ CD4 device in representative primary health care clinics doing HIV testing.</p> <p>Methods</p> <p>Prior to testing, prescribed capillary-sampling and instrument training was undertaken by suppliers across all sites. Matching venous EDTA samples were drawn throughout for comparison to laboratory predicate methodology (PLG/CD4). In Phase I, Pima™ cartridges were pipette-filled with EDTA venous blood in the laboratory (N = 100). In Phase II (N = 77), Pima™ CD4 with capillary sampling was performed by a single operator in a hospital-based antenatal clinic. During subsequent field testing, Pima™ CD4 with capillary sampling was performed in primary health care clinics on HIV-positive patients by multiple attending nursing personnel in a rural clinic (Phase-IIIA, N = 96) and an inner-city clinic (Phase-IIIB, N = 139).</p> <p>Results</p> <p>Pima™ CD4 compared favourably to predicate/CD4 when cartridges were pipette-filled with venous blood (bias -17.3 ± STDev = 36.7 cells/mm³; precision-to-predicate %CV < 6%). Decreased precision of Pima™ CD4 to predicate/CD4 (varying from 17.6 to 28.8%SIM CV; mean bias = 37.9 ± STDev = 179.5 cells/mm³) was noted during field testing in the hospital antenatal clinic. In the rural clinic field-studies, unacceptable precision-to-predicate and positive bias was noted (mean 28.4%SIM CV; mean bias = +105.7 ± STDev = 225.4 cells/mm³). With additional proactive manufacturer support, reliable performance was noted in the subsequent inner-city clinic field study where acceptable precision-to-predicate (11%SIM CV) and less bias of Pima™ to predicate was shown (BA bias ~11 ± STDev = 69 cells/mm³).</p> <p>Conclusions</p> <p>Variable precision of Pima™ to predicate CD4 across study sites was attributable to variable capillary sampling. Poor precision was noted in the outlying primary health care clinic where the system is most likely to be used. Stringent attention to capillary blood collection technique is therefore imperative if technologies like Pima™ are used with capillary sampling at the POC. Pima™ CD4 analysis with venous blood was shown to be reproducible, but testing at the point of care exposes operators to biohazard risk related to uncapping vacutainer samples and pipetting of blood, and is best placed in smaller laboratories using established principles of Good Clinical Laboratory Practice. The development of capillary sampling quality control methods that assure reliable CD4 counts at the point of care are awaited.</p

Identifying and Seeing beyond Multiple Sequence Alignment Errors Using Intra-Molecular Protein Covariation

BACKGROUND: There is currently no way to verify the quality of a multiple sequence alignment that is independent of the assumptions used to build it. Sequence alignments are typically evaluated by a number of established criteria: sequence conservation, the number of aligned residues, the frequency of gaps, and the probable correct gap placement. Covariation analysis is used to find putatively important residue pairs in a sequence alignment. Different alignments of the same protein family give different results demonstrating that covariation depends on the quality of the sequence alignment. We thus hypothesized that current criteria are insufficient to build alignments for use with covariation analyses. METHODOLOGY/PRINCIPAL FINDINGS: We show that current criteria are insufficient to build alignments for use with covariation analyses as systematic sequence alignment errors are present even in hand-curated structure-based alignment datasets like those from the Conserved Domain Database. We show that current non-parametric covariation statistics are sensitive to sequence misalignments and that this sensitivity can be used to identify systematic alignment errors. We demonstrate that removing alignment errors due to 1) improper structure alignment, 2) the presence of paralogous sequences, and 3) partial or otherwise erroneous sequences, improves contact prediction by covariation analysis. Finally we describe two non-parametric covariation statistics that are less sensitive to sequence alignment errors than those described previously in the literature. CONCLUSIONS/SIGNIFICANCE: Protein alignments with errors lead to false positive and false negative conclusions (incorrect assignment of covariation and conservation, respectively). Covariation analysis can provide a verification step, independent of traditional criteria, to identify systematic misalignments in protein alignments. Two non-parametric statistics are shown to be somewhat insensitive to misalignment errors, providing increased confidence in contact prediction when analyzing alignments with erroneous regions because of an emphasis on they emphasize pairwise covariation over group covariation

Student’s perspectives, satisfaction and experiences with online and classroom learning during the COVID-19 pandemic : findings and implications on blended learning

Objectives: The coronavirus disease 2019 (COVID-19) pandemic disrupted classroom-based learning, necessitating the adoption of online learning in most universities. However, there has been a lack of information on university students' perspectives regarding online learning during the COVID-19 pandemic. This study assessed the perspectives, satisfaction, and experiences with online and classroom learning among human health students at the University of Zambia. Methods: This cross-sectional study was conducted among 737 students at the University of Zambia from October 2022 to April 2023. Data were analysed using Stata version 16.1. Results: Of the 737 participants, 51.6% were female and 56.5% agreed that blended learning should continue even after the COVID-19 pandemic. However, 78.4% of the students believed that group discussions were more suitable in the classroom than online learning. Most students (67.1%) disagreed that they preferred online learning to classroom learning. Further, 77.6% of the students disagreed that online learning gave more satisfaction than classroom learning. Conclusions: This study found that most students recommended the continuation of blended learning after the pandemic. However, they believed that follow-up tutorials and assessments were better undertaken in physical classrooms than online learning. These findings are important in sensitising stakeholders in the education sector and governments to consider blended learning as a teaching strategy in the future. There is a need to develop and implement curricula that offer blended learning to students as well as ensure the students have the necessary facilities and equipment to support such learning

Abnormal White Matter Integrity in Adolescents with Internet Addiction Disorder: A Tract-Based Spatial Statistics Study

Background: Internet addiction disorder (IAD) is currently becoming a serious mental health issue around the globe. Previous studies regarding IAD were mainly focused on associated psychological examinations. However, there are few studies on brain structure and function about IAD. In this study, we used diffusion tensor imaging (DTI) to investigate white matter integrity in adolescents with IAD. Methodology/Principal Findings: Seventeen IAD subjects and sixteen healthy controls without IAD participated in this study. Whole brain voxel-wise analysis of fractional anisotropy (FA) was performed by tract-based spatial statistics (TBSS) to localize abnormal white matter regions between groups. TBSS demonstrated that IAD had significantly lower FA than controls throughout the brain, including the orbito-frontal white matter, corpus callosum, cingulum, inferior fronto-occipital fasciculus, and corona radiation, internal and external capsules, while exhibiting no areas of higher FA. Volume-of-interest (VOI) analysis was used to detect changes of diffusivity indices in the regions showing FA abnormalities. In most VOIs, FA reductions were caused by an increase in radial diffusivity while no changes in axial diffusivity. Correlation analysis was performed to assess the relationship between FA and behavioral measures within the IAD group. Significantly negative correlations were found between FA values in the left genu of the corpus callosum and the Screen for Child Anxiety Related Emotional Disorders, and between FA values in the left external capsule and the Young’s Internet addiction scale

The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia : design, results and future prospects

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.Peer reviewe

The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia: design, results and future prospects

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites