Structural Equation Modeling of Common Cognitive Abilities in Preschool-Aged Children Using WPPSI-IV and BRIEF-P
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ABSTRACT:
SUBMITTER: Fiedler S
PROVIDER: S-EPMC9323403 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundAlthough the consequences of food insecurity on physical health and nutritional status of youth living have been reported, its effect on their mental health remains less investigated in developing countries. The aim of this study was to examine the pathways through which food insecurity is associated with poor mental health status among youth living in Ethiopia.MethodsWe used data from Jimma Longitudinal Family Survey of Youth (JLFSY) collected in 2009/10. A total of 1,521 youth were included in the analysis. We measured food insecurity using a 5-items scale and common mental disorders using the 20-item Self-Reporting Questionnaire (SRQ-20). Structural and generalized equation modeling using maximum likelihood estimation method was used to analyze the data.ResultsThe prevalence of common mental disorders was 30.8% (95% CI: 28.6, 33.2). Food insecurity was independently associated with common mental disorders (? = 0.323, P<0.05). Most (91.8%) of the effect of food insecurity on common mental disorders was direct and only 8.2% of their relationship was partially mediated by physical health. In addition, poor self-rated health (? = 0.285, P<0.05), high socioeconomic status (? = -0.076, P<0.05), parental education (? = 0.183, P<0.05), living in urban area (? = 0.139, P<0.05), and female-headed household (? = 0.192, P<0.05) were associated with common mental disorders.ConclusionsFood insecurity is directly associated with common mental disorders among youth in Ethiopia. Interventions that aim to improve mental health status of youth should consider strategies to improve access to sufficient, safe and nutritious food.
| S-EPMC5113011 | biostudies-literature
Project description:A key challenge in the field of cognitive neuroscience is to identify discriminable cognitive functions, and then map these functions to brain activity. In the current study, we set out to explore the relationships between performance arising from different cognitive tasks thought to tap different domains of cognition, and then to test whether these distinct latent cognitive abilities also are subserved by corresponding "latent" brain substrates. To this end, we tested a large sample of adults under the age of 40 on twelve cognitive tasks as they underwent fMRI scanning. Exploratory factor analysis revealed 4-factor model, dissociating tasks into processes corresponding to episodic memory retrieval, reasoning, speed of processing and vocabulary. An analysis of the topographic covariance patterns of the BOLD-response acquired during each task similarity also converged on four neural networks that corresponded to the 4 latent factors. These results suggest that distinct ontologies of cognition are subserved by corresponding distinct neural networks.
| S-EPMC7010254 | biostudies-literature
Project description:Gene expression is controlled by multiple regulators and their interactions. Data from genome-wide gene expression assays can be used to estimate molecular activities of regulators within a model organism and extrapolate them to biological processes in humans. This approach is valuable in studies to better understand complex human biological systems which may be involved in diseases and hence, have potential clinical relevance. In order to achieve this, it is necessary to infer gene interactions that are not directly observed (i.e. latent or hidden) by way of structural equation modeling (SEM) on the expression levels or activities of the downstream targets of regulator genes. Here we developed an R Shiny application, termed "Structural Equation Modeling of In silico Perturbations (SEMIPs)" to compute a two-sided t-statistic (T-score) from analysis of gene expression data, as a surrogate to gene activity in a given human specimen. SEMIPs can be used in either correlational studies between outcome variables of interest or subsequent model fitting on multiple variables. This application implements a 3-node SEM model that consists of two upstream regulators as input variables and one downstream reporter as an outcome variable to examine the significance of interactions among these variables. SEMIPs enables scientists to investigate gene interactions among three variables through computational and mathematical modeling (i.e. in silico). In a case study using SEMIPs, we have shown that putative direct downstream genes of the GATA Binding Protein 2 (GATA2) transcription factor are sufficient to infer its activities in silico for the conserved progesterone receptor (PGR)-GATA2-SRY-box transcription factor 17 (SOX17) genetic network in the human uterine endometrium.
| S-EPMC8652139 | biostudies-literature
Project description:At least 282 Food Policy Councils (FPCs) are currently working to improve access to healthy foods in their communities by connecting food system sectors, gathering community input, and advising food policy. Empirical research on FPCs is limited. This study empirically evaluates FPCs to better understand the relationships between Organizational Capacity, Social Capital, and Council Effectiveness by testing a FPC Framework adapted from Allen and colleagues (2012). Members of all FPCs in the U.S., Canada, and Native American Tribes and First Nations were invited to complete the Food Policy Council Self-Assessment Tool (FPC-SAT). Structural equation modeling was used to test the FPC Framework. Three hundred and fifty-four FPC members from 95 councils completed the FPC-SAT. After slight modification, a revised FPC Framework was a good fit with the data (?2 = 40.085, df = 24, p-value = .021, comparative fit index = 0.988, Tucker Lewis index = 0.982, root mean squared error of approximation = 0.044, p-close = .650). A moderation analysis revealed that community context influences the relationship between Social Capital and Council Effectiveness within the FPC Framework. The FPC Framework can guide capacity building interventions and FPC evaluations. The empirically tested framework can help FPCs efficiently work toward achieving their missions and improving their local food system.
| S-EPMC7262635 | biostudies-literature
Project description:ObjectivesWhen examining the relationship between smoking intensity and toxicant exposure biomarkers in an effort to understand the potential risk for smoking-related disease, individual biomarkers may not be strongly associated with smoking intensity because of the inherent variability in biomarkers. Structural equation modeling (SEM) offers a powerful solution by modeling the relationship between smoking intensity and multiple biomarkers through a latent variable.MethodsBaseline data from a randomized trial (N = 1250) were used to estimate the relationship between smoking intensity and a latent toxicant exposure variable summarizing five volatile organic compound biomarkers. Two variables of smoking intensity were analyzed: the self-report cigarettes smoked per day and total nicotine equivalents in urine. SEM was compared with linear regression with each biomarker analyzed individually or with the sum score of the five biomarkers.ResultsSEM models showed strong relationships between smoking intensity and the latent toxicant exposure variable, and the relationship was stronger than its counterparts in linear regression with each biomarker analyzed separately or with the sum score.ConclusionsSEM is a powerful multivariate statistical method for studying multiple biomarkers assessing the same class of harmful constituents. This method could be used to evaluate exposure from different combusted tobacco products.
| S-EPMC9075702 | biostudies-literature
Project description:Background: The Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) has been adapted to 28 different cultures and there has been considerable interest in examining its structure through exploratory and confirmatory factor analysis. This study investigates item and scale properties of the Egyptian WAIS-IV using item response theory (IRT) models. Methods: The sample consisted of 250 adults from Egypt. The item-level and subtest statistical properties of the Egyptian WAIS-IV were established using a combination of four dichotomous IRT models and four polytomous IRT models. In addition, factor analysis was performed to investigate the dimensionality of each subtest. Results: Factor analysis indicated the unidimensionality of each subtest. Among IRT models, the two-parameter logistic model provided a good fit for dichotomous subtests, while the graded response model fitted the polytomous data. Most items of the Egyptian WAIS-IV showed high discrimination, and the scale was adequately informative across the levels of latent traits (i.e., cognitive variables). However, each subtest included at least some items with limited ability to distinguish between individuals with differing levels of the cognitive variable being measured. Furthermore, most subtests have items that do not follow the difficulty rank they are ascribed in the WAIS-IV manual. Conclusions: Overall, the results suggest that the Egyptian WAIS-IV offers a highly valid assessment of intellectual abilities, despite the need for some improvements.
| S-EPMC8297006 | biostudies-literature
Project description:When a cognitive ability is assessed repeatedly, test scores and ability estimates are often observed to increase across test sessions. This phenomenon is known as the retest (or practice) effect. One explanation for retest effects is that situational test anxiety interferes with a testee's performance during earlier test sessions, thereby creating systematic measurement bias on the test items (interference hypothesis). Yet, the influence of anxiety diminishes with test repetitions. This explanation is controversial, since the presence of measurement bias during earlier measurement occasions cannot always be confirmed. It is argued that people from the lower end of the ability spectrum become aware of their deficits in test situations and therefore report higher anxiety (deficit hypothesis). In 2014, a structural equation model was proposed that specifically allows the comparison of these two hypotheses with regard to explanatory power for the negative anxiety-ability correlation found in cross-sectional assessments. We extended this model for usage in longitudinal studies to investigate the impact of test anxiety on test performance and on retest effects. A latent neighbor-change growth curve was implemented into the model that enables an estimation of retest effects between all pairs of successive test sessions. Systematic restrictions on model parameters allow testing the hypothetical reduction in anxiety interference over the test sessions, which can be compared to retest effect sizes. In an empirical study with seven measurement occasions, we found that a substantial reduction in interference upon the second test session was associated with the largest retest effect in a figural matrices test, which served as a proxy measure for general intelligence. However, smaller retest effects occurred up to the fourth test administration, whereas evidence for anxiety-induced measurement bias was only produced for the first two test sessions. Anxiety and ability were not negatively correlated at any time when the interference effects were controlled for. Implications, limitations, and suggestions for future research are discussed.
| S-EPMC6963292 | biostudies-literature
Project description:The theory of planned behavior (TPB), socio-cognitive model (SCM), and information-motivation-behavioral skills (IMB) model are effective in predicting condom use. However, the adequacy of these three theoretical models in predicting the frequency of condom use (FCU) among young people has not been compared. This cross-sectional study tested the applicability and suitability of these three models in predicting the FCU, and analyzed the relationships among the postulated constructs.Sexually experienced adolescents (n = 410) aged 13-18 completed a survey assessing the TPB, SCM, and IMB model constructs. Participants were students recruited from 18 high schools, randomly selected from the north, south, east, and southeast of Spain. A structural equation modelling (SEM) analysis was applied to test TPB, SCM and IBM and constructs relationships of each model using R.The results of SEM demonstrated that behavioral skills predict behavior via motivation as hypothesized by the IMB model, but not directly via knowledge about condom use and sexually transmitted infections (STIs). Cognitive factors, such knowledge about condom use and STIs as well as condom use self-efficacy, directly predicted the FCU when modeled as per the SCM. According to the TPB, condom use intention was the best predictor of the FCU, and condom use intention was predicted by attitudes toward condom use and subjective norms related to condom use, but perceived control was not directly or indirectly related to the FCU. Based on the data, the TPB becomes the best-fit model for predicting the FCU among young people compared to the SCM and IMB model.From a statistical perspective, the TPB seems to be the most suitable model for predicting the FCU among young people compared to the other models. Overall, key direct predictors of the FCU in adolescents included condom use intention, behavioral skills and cognitive factors, such as STIs knowledge and condom use self-efficacy. The next step should be to test integrative models that include personal, contextual, environmental, and social factors.
| S-EPMC4712548 | biostudies-other
Project description:Firearm homicides disproportionately affect Black communities. Redlining - discriminatory lending practices of the early 20th century - are associated with current increased rates of firearm violence. Poverty and concentrated disadvantage are also associated with firearm violence. The interaction of these factors with racist redlining housing practices remains unclear. We used generalized structural equation modeling to characterize the mediators through which redlining practices of the 1930s led to present rates of firearm violence in Boston using a negative binomial model. Principle component analysis was used to create four distinct mediating variables representing census block socioeconomic and built environment information, while reducing dimensionality. We calculated the direct effect between harmful (Red and Yellow) vs beneficial (Green) designations and firearm incident rate, indirect effect between redlining designation and firearm incident rate through each mediating variable, and the total effect. The percentage mediation of each mediator was subsequently calculated. Red and Yellow areas of Boston were associated with an 11•1 (95% CI 5•5,22•4) and 11•4 (5•7,22•8) increased incident rate of shooting when compared to Green. In the pathway between Red designation and firearm incident rate, poverty and poor educational attainment mediated 20% of the interaction, share of rented housing mediated 8%, and Black share of the population 3%. In the pathway between Yellow designation and firearm incident rate, poverty and poor educational attainment mediated 16% of the association, and Black share of the population mediated 13%. Redlining practices of the 1930s potentially contribute to increased rates of firearm violence through changes to neighborhood environments, namely through preclusion from homeownership, poverty, poor educational attainment, and concentration (i.e. segregation) of Black communities. These downstream mediating factors serve as points for policy interventions to address urban firearm violence. Michael Poulson and Miriam Neufeld were supported by T32 Training Grants (HP10028, GM86308).
| S-EPMC8654098 | biostudies-literature
Project description:Structural equation models are increasingly used for clustered or multilevel data in cases where mixed regression is too inflexible. However, when there are many levels of nesting, these models can become difficult to estimate. We introduce a novel evaluation strategy, Rampart, that applies an orthogonal rotation to the parts of a model that conform to commonly met requirements. This rotation dramatically simplifies fit evaluation in a way that becomes more potent as the size of the data set increases. We validate and evaluate the implementation using a 3-level latent regression simulation study. Then we analyze data from a state-wide child behavioral health measure administered by the Oklahoma Department of Human Services. We demonstrate the efficiency of Rampart compared to other similar software using a latent factor model with a 5-level decomposition of latent variance. Rampart is implemented in OpenMx, a free and open source software.
| S-EPMC5875450 | biostudies-literature