IU Indianapolis ScholarWorks :: Browsing by Subject "Mediation analysis"

Browsing by Subject "Mediation analysis"

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A study of error reporting by nurses: the significant impact of nursing team dynamics
(Sage, 2023) Thompson Munn, Lindsay; Lynn, Mary R.; Knafl, George J.; Schade Willis, Tina; Jones, Cheryl B.; Pediatrics, School of Medicine
Background: Error reporting is crucial for organisational learning and improving patient safety in hospitals, yet errors are significantly underreported. Aims: The aim of this study was to understand how the nursing team dynamics of leader inclusiveness, safety climate and psychological safety affected the willingness of hospital nurses to report errors. Methods: The study was a cross-sectional design. Self-administered surveys were used to collect data from nurses and nurse managers. Data were analysed using linear mixed models. Bootstrap confidence intervals with bias correction were used for mediation analysis. Results: Leader inclusiveness, safety climate and psychological safety significantly affected willingness to report errors. Psychological safety mediated the relationship between safety climate and error reporting as well as the relationship between leader inclusiveness and error reporting. Conclusion: The findings of the study emphasise the importance of nursing team dynamics to error reporting and suggest that psychological safety is especially important to error reporting.
American Muslim Well-Being in the Era of Rising Islamophobia: Mediation Analysis of Muslim American Social Capital and Health
(2023-04) Miller, Keith Matthew; Kondrat, David; Khaja, Khadija; Fukui, Sadaaki; Latham-Mintus, Kenzie
This study aims to examine American Muslim well-being and social capital in the face of Islamophobia. Ecological frameworks and social capital theory were synthesized to provide an approach for research, analysis, and social work practice. A mediation analysis was conducted to test the mediating effect of cognitive social capital on the relationship between structural social capital and distress. The paths of structural social capital, cognitive social capital, and distress were conceptualized using the ecological framework of Berkman and colleagues. Special attention was paid to how experiences of Islamophobic discrimination affect cognitive social capital and distress. Structural social capital was operationalized as the number of active memberships in civic organizations; Cognitive social capital was operationalized as trust in major institutions such as schools and the local police and Distress was operationalized using the Kessler Distress Scale. It was hypothesized that an increase in structural social capital would show a decrease in distress with cognitive social capital mediating the path. Results showed that cognitive social capital mediates the relationship between structural social capital and distress. However, an inconsistent mediation was found where an increase in cognitive social capital shows a decrease in distress, but higher levels of structural social capital show an increase in distress. Lastly, the results of the analysis were interpreted to inform current interventions with the American Muslim community through a social work lens.
Brain-wide genome-wide colocalization study for integrating genetics, transcriptomics and brain morphometry in Alzheimer’s disease
(Elsevier, 2023) Bao, Jingxuan; Wen, Junhao; Wen, Zixuan; Yang, Shu; Cui, Yuhan; Yang, Zhijian; Erus, Guray; Saykin, Andrew J.; Long, Qi; Davatzikos, Christos; Shen, Li; Radiology and Imaging Sciences, School of Medicine
Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases. However, the AD mechanism has not yet been fully elucidated to date, hindering the development of effective therapies. In our work, we perform a brain imaging genomics study to link genetics, single-cell gene expression data, tissue-specific gene expression data, brain imaging-derived volumetric endophenotypes, and disease diagnosis to discover potential underlying neurobiological pathways for AD. To do so, we perform brain-wide genome-wide colocalization analyses to integrate multidimensional imaging genomic biobank data. Specifically, we use (1) the individual-level imputed genotyping data and magnetic resonance imaging (MRI) data from the UK Biobank, (2) the summary statistics of the genome-wide association study (GWAS) from multiple European ancestry cohorts, and (3) the tissue-specific cis-expression quantitative trait loci (cis-eQTL) summary statistics from the GTEx project. We apply a Bayes factor colocalization framework and mediation analysis to these multi-modal imaging genomic data. As a result, we derive the brain regional level GWAS summary statistics for 145 brain regions with 482,831 single nucleotide polymorphisms (SNPs) followed by posthoc functional annotations. Our analysis yields the discovery of a potential AD causal pathway from a systems biology perspective: the SNP chr10:124165615:G>A (rs6585827) mutation upregulates the expression of BTBD16 gene in oligodendrocytes, a specialized glial cells, in the brain cortex, leading to a reduced risk of volumetric loss in the entorhinal cortex, resulting in the protective effect on AD. We substantiate our findings with multiple evidence from existing imaging, genetic and genomic studies in AD literature. Our study connects genetics, molecular and cellular signatures, regional brain morphologic endophenotypes, and AD diagnosis, providing new insights into the mechanistic understanding of the disease. Our findings can provide valuable guidance for subsequent therapeutic target identification and drug discovery in AD.
Multimodal data integration via mediation analysis with high-dimensional exposures and mediators
(Wiley, 2022) Zhao, Yi; Li, Lexin; Alzheimer's Disease Neuroimaging Initiative; Biostatistics and Health Data Science, School of Medicine
Motivated by an imaging proteomics study for Alzheimer's disease (AD), in this article, we propose a mediation analysis approach with high-dimensional exposures and high-dimensional mediators to integrate data collected from multiple platforms. The proposed method combines principal component analysis with penalized least squares estimation for a set of linear structural equation models. The former reduces the dimensionality and produces uncorrelated linear combinations of the exposure variables, whereas the latter achieves simultaneous path selection and effect estimation while allowing the mediators to be correlated. Applying the method to the AD data identifies numerous interesting protein peptides, brain regions, and protein-structure-memory paths, which are in accordance with and also supplement existing findings of AD research. Additional simulations further demonstrate the effective empirical performance of the method.
Multimodal neuroimaging data integration and pathway analysis
(Wiley, 2021) Zhao, Yi; Li, Lexin; Caffo, Brian S.; Biostatistics, School of Public Health
With advancements in technology, the collection of multiple types of measurements on a common set of subjects is becoming routine in science. Some notable examples include multimodal neuroimaging studies for the simultaneous investigation of brain structure and function and multi-omics studies for combining genetic and genomic information. Integrative analysis of multimodal data allows scientists to interrogate new mechanistic questions. However, the data collection and generation of integrative hypotheses is outpacing available methodology for joint analysis of multimodal measurements. In this article, we study high-dimensional multimodal data integration in the context of mediation analysis. We aim to understand the roles that different data modalities play as possible mediators in the pathway between an exposure variable and an outcome. We propose a mediation model framework with two data types serving as separate sets of mediators and develop a penalized optimization approach for parameter estimation. We study both the theoretical properties of the estimator through an asymptotic analysis and its finite-sample performance through simulations. We illustrate our method with a multimodal brain pathway analysis having both structural and functional connectivity as mediators in the association between sex and language processing.
Pathway Lasso: Pathway Estimation and Selection with High-Dimensional Mediators
(International Press, 2022) Zhao, Yi; Luo, Xi; Biostatistics, School of Public Health
In many scientific studies, it becomes increasingly important to delineate the pathways through a large number of mediators, such as genetic and brain mediators. Structural equation modeling (SEM) is a popular technique to estimate the pathway effects, commonly expressed as the product of coefficients. However, it becomes unstable and computationally challenging to fit such models with high-dimensional mediators. This paper proposes a sparse mediation model using a regularized SEM approach, where sparsity means that a small number of mediators have a nonzero mediation effect between a treatment and an outcome. To address the model selection challenge, we innovate by introducing a new penalty called Pathway Lasso. This penalty function is a convex relaxation of the non-convex product function for the mediation effects, and it enables a computationally tractable optimization criterion to estimate and select pathway effects simultaneously. We develop a fast ADMM-type algorithm to compute the model parameters, and we show that the iterative updates can be expressed in closed form. We also prove the asymptotic consistency of our Pathway Lasso estimator for the mediation effect. On both simulated data and an fMRI data set, the proposed approach yields higher pathway selection accuracy and lower estimation bias than competing methods.
Piecing together fragments: Linguistic cohesion mediates the relationship between executive function and metacognition in schizophrenia
(Elsevier, 2020-01) Lundin, Nancy B.; Hochheiser, Jesse; Minor, Kyle S.; Hetrick, William P.; Lysaker, Paul H.; Psychiatry, School of Medicine
Speech disturbances are prevalent in psychosis. These may arise in part from executive function impairment, as research suggests that inhibition and monitoring are associated with production of cohesive discourse. However, it is not yet understood how linguistic and executive function impairments in psychosis interact with disrupted metacognition, or deficits in the ability to integrate information to form a complex sense of oneself and others and use that synthesis to respond to psychosocial challenges. Whereas discourse studies have historically employed manual hand-coding techniques, automated computational tools can characterize deep semantic structures that may be closely linked with metacognition. In the present study, we examined whether higher executive functioning promotes metacognition by way of altering linguistic cohesion. Ninety-four individuals with schizophrenia-spectrum disorders provided illness narratives and completed an executive function task battery (Delis-Kaplan Executive Function System). We assessed the narratives for linguistic cohesion (Coh-Metrix 3.0) and metacognitive capacity (Metacognition Assessment Scale – Abbreviated). Selected linguistic indices measured the frequency of connections between causal and intentional content (deep cohesion), word and theme overlap (referential cohesion), and unique word usage (lexical diversity). In path analyses using bootstrapped confidence intervals, we found that deep cohesion and lexical diversity independently mediated the relationship between executive functioning and metacognitive capacity. Findings suggest that executive control abilities support integration of mental experiences by way of increasing causal, goal-driven speech and word expression in individuals with schizophrenia. Metacognitive-based therapeutic interventions for psychosis may promote insight and recovery in part by scaffolding use of language that links ideas together.
PNPLA3 rs738409 and Risk of Fibrosis in NAFLD: Exploring Mediation Pathways Through Intermediate Histological Features
(Wolters Kluwer, 2022) Vilar-Gomez, Eduardo; Pirola, Carlos J.; Sookoian, Silvia; Wilson, Laura A.; Lian, Tiebing; Chalasani, Naga; Medicine, School of Medicine
Background and aims: It is unclear whether rs738409 (p.I148M) missense variant in patatin-like phospholipase domain-containing 3 rs738409 promotes fibrosis development by triggering specific fibrogenic pathways or by creating an unfavorable microenvironment by promoting steatosis, inflammation, and ultimately fibrosis. We tested the hypothesis that intermediate histologic traits, including steatosis, lobular and portal inflammation, and ballooning may determine the effect of rs738409 on liver fibrosis among individuals with biopsy-proven NAFLD. Approach and results: Causal mediation models including multiple mediators in parallel or sequentially were performed to examine the effect of rs738409, by decomposing its total effect on fibrosis severity into direct and indirect effects, mediated by histology traits in 1153 non-Hispanic White patients. Total effect of rs738409 on fibrosis was β = 0.19 (95% CI: 0.09-0.29). The direct effect of rs738409 on fibrosis after removing mediators' effects was β = 0.09 (95% CI: 0.01-0.17) and the indirect effect of rs738409 on fibrosis through all mediators' effects were β = 0.010 (95% CI: 0.04-0.15). Among all mediators, the greatest estimated effect size was displayed by portal inflammation (β = 0.09, 95% CI: 0.05-0.12). Among different sequential combinations of histology traits, the path including lobular inflammation followed by ballooning degeneration displayed the most significant indirect effect (β = 0.023, 95% CI: 0.011-0.037). Mediation analysis in a separate group of 404 individuals with biopsy-proven NAFLD from other races and ethnicity showed similar results. Conclusions: In NAFLD, nearly half of the total effect of the rs738409 G allele on fibrosis severity could be explained by a direct pathway, suggesting that rs738409 may promote fibrosis development by activating specific fibrogenic pathways. A large proportion of the indirect effect of rs738409 on fibrosis severity is mediated through portal inflammation.
The Association Between Leisure Activity Engagement and Health-Related Quality of Life in Middle-Aged and Older People With HIV
(Oxford University Press, 2022) Wion, Rachel K.; Fazeli, Pariya L.; Vance, David E.; School of Nursing
Background and objectives: Middle-aged and older adults with human immunodeficiency virus (HIV) are at risk for decreased health-related quality of life (HRQoL), which may be improved by engaging in leisure activities. We examined associations between HRQoL and participation in cognitive, physical, social, and passive leisure activities, and whether depressive symptoms mediated these relationships. Wilson and Cleary's conceptual model of HRQoL guided this study. Research design and methods: In this cross-sectional observational study, we enrolled 174 adults living with HIV aged 40 and older (M = 51.3, SD = 7.03). Participants completed assessments of leisure activities, depressive symptoms, and HRQoL. Data were analyzed using Spearman's rho correlations, hierarchal multiple regression, and mediation analyses. Results: Greater engagement in physical activities was associated with higher physical HRQoL (b = 2.02, p < .05). Greater engagement in social activities was associated with both higher physical (b = 1.44, p < .05) and mental HRQoL (b = 1.95, p < .01). However, all associations between leisure activities and HRQoL were fully attenuated by depressive symptoms. Cognitive and passive leisure activities were not significantly correlated with HRQoL. Mediation analyses confirmed that depressive symptoms were the mediator mechanism by which social activities affected mental and physical HRQoL. Discussion and implications: More frequent engagement in physical and social leisure activities is associated with better HRQoL, and social leisure activities improve HRQoL via their impact on mood. Interventions to increase leisure activities, especially among people living with HIV who have poorer affective functioning, may be the most effective approach to improving HRQoL.

Browsing by Subject "Mediation analysis"

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