Estimates Of Indirect Effects Research Articles

The relationship between young college students' recognition of national COVID-19 crisis governance capabilities and the improvement of national identity: the mediating role of online participation in public health critical events.

Improving the young college students' national identity is crucial for ensuring social stability and fostering development during public health critical events such as COVID-19. Young college students' recognition of national COVID-19 crisis governance capabilities can influence their national identity, and online participation in public health criticalevents may serve as a crucial role in shaping this intricate relationship. To investigate this possibility, the present study established an intermediary model to examine the impact of online participation in public health critical events on young college students' recognition of national COVID-19 crisis governance capabilities and improvement of national identity. This cross-sectional survey study employed a convenience sampling method to investigate a total of 3041 young college students in China. The correlations between study variables were analyzed using Spearman's rank correlation. The mediation model was established using PROCESS Model 4 with 5000 bootstrap samples in SPSS. The bias-corrected bootstrap method provided statistical efficacy and identification interval estimation. Young college students' recognition of national COVID-19 crisis governance capabilities (r=0.729, P<0.001) and online participation in public health critical events (r=0.609, P<0.001) were positively correlated with improvement of their national identity. The relationship between these two factors was partially mediated by online participation in public health critical events (Indirect effect estimate=0.196, P<0.001). Online participation in public health critical events played a mediating role in the association between college students' recognition of national COVID-19 crisis governance capabilities and the improvement of national identity. Our findings provide a novel intervention strategy for improving college students' national identity, which is to encourage their online participation in public health critical events.

Agricultural carbon emission efficiency and agricultural practices: Implications for balancing carbon emissions reduction and agricultural productivity increment

The current Ukraine War underlines the importance of grain self-sufficiency. After the adoption of the Paris Agreement, two major challenges developing countries are facing in the coming decades are increasing agricultural production to ensure food security and reducing carbon emissions (CE). The key to such an “environment-development dilemma” is to improve agricultural carbon emission efficiency (CEE). Using China as the study site, we systematically analyze the impacts of agricultural management activities on agricultural CEE from 1997 to 2019. Global and local Moran's I index tests provide evidence of a positive spatial dependence of agricultural CEE. Using the LISA cluster map, we observe that high CEE regions tend to be distributed together, dominated by environmental conditions. However, with the promotion of agricultural management activities, such a clustering pattern vanished. Our spatial Durbin model (SDM) estimation results indicate that there are significant nonlinear relationships between agricultural practices and agricultural CEE. While the consumption of fertilizers and pesticides has economies of scale effects, the deployment of agricultural machinery and irrigation have diseconomies of scale effects on local CEE. Based on the SDM results, the direct and indirect effect estimation results suggest that the significant direct and spillover effects of many practices on agricultural CEE have opposite nonlinear shapes, implying a more complicated situation in promoting these activities, as the positive regional effect of an agricultural activity might have a negative impact on adjacent regions. All the results indicate that local policymakers should carefully tailor agricultural development policies based on local environmental conditions.

Cost-effectiveness of PCV20 to Prevent Pneumococcal Disease in the Pediatric Population: A German Societal Perspective Analysis.

Since 2009, a pneumococcal conjugate vaccine (PCV) covering 13 serotypes (PCV13) has been included by Germany's Standing Committee on Vaccinations for infants, resulting in major reductions in pneumococcal disease (PD). Higher-valent vaccines may further reduce PD burden. This cost-effectiveness analysis compared 20-valent PCV (PCV20) under a 3+1 schedule with 15-valent PCV (PCV15) and PCV13, both under 2+1 schedule, in Germany's pediatric population. A Markov model with annual cycles over a 10-year time horizon was adapted to simulate the clinical and economic impact of pediatric vaccination with PCV20 versus lower-valent PCVs in Germany. The model used PCV13 clinical effectiveness and impact studies as well as PCV7 efficacy studies for vaccine direct and indirect effect estimates. Epidemiologic, utility, and medical cost inputs were obtained from published sources. Benefits and costs were discounted at 3% from a German societal perspective. Outcomes included PD cases, deaths, costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs). In the base case, PCV20 provided greater health benefits than PCV13, averting more cases of invasive pneumococcal disease (IPD; 15,301), hospitalized and non-hospitalized pneumonia (460,197 and 472,365, respectively), otitis media (531,634), and 59,265 deaths over 10 years. This resulted in 904,854 additional QALYs and a total cost saving of €2,393,263,611, making PCV20 a dominant strategy compared with PCV13. Compared to PCV15, PCV20 was estimated to avert an additional 11,334 IPD, 704,948 pneumonia, and 441,643 otitis media cases, as well as 41,596 deaths. PCV20 was associated with a higher QALY gain and lower cost (i.e., dominance) compared with PCV15. The robustness of the results was confirmed through scenario analyses as well as deterministic and probabilistic sensitivity analyses. PCV20 3+1 dominated both PCV13 2+1 and PCV15 2+1 over 10 years. Replacing lower-valent PCVs with PCV20 would result in greater clinical and economic benefits, given PCV20's broader serotype coverage.

Interpreting population- and family-based genome-wide association studies in the presence of confounding.

A central aim of genome-wide association studies (GWASs) is to estimate direct genetic effects: the causal effects on an individual's phenotype of the alleles that they carry. However, estimates of direct effects can be subject to genetic and environmental confounding and can also absorb the "indirect" genetic effects of relatives' genotypes. Recently, an important development in controlling for these confounds has been the use of within-family GWASs, which, because of the randomness of mendelian segregation within pedigrees, are often interpreted as producing unbiased estimates of direct effects. Here, we present a general theoretical analysis of the influence of confounding in standard population-based and within-family GWASs. We show that, contrary to common interpretation, family-based estimates of direct effects can be biased by genetic confounding. In humans, such biases will often be small per-locus, but can be compounded when effect-size estimates are used in polygenic scores (PGSs). We illustrate the influence of genetic confounding on population- and family-based estimates of direct effects using models of assortative mating, population stratification, and stabilizing selection on GWAS traits. We further show how family-based estimates of indirect genetic effects, based on comparisons of parentally transmitted and untransmitted alleles, can suffer substantial genetic confounding. We conclude that, while family-based studies have placed GWAS estimation on a more rigorous footing, they carry subtle issues of interpretation that arise from confounding.

The derivative-based approach to nonlinear mediation models: insights and applications

AbstractTraditional mediation analysis has been developed in the context of linear models, enabling the estimation of indirect effects through the product of regression coefficients. However, in the presence of nonlinearities, defining and estimating indirect effects becomes more challenging. While nonlinear mediation models are relatively easy to address in the counterfactual-based framework, very few generalizations to nonlinear associational settings have been proposed. One of the most intuitive is the derivative-based approach that, however, seems not to be widely spread among scholars. In this paper, we deepen such an approach to nonlinear mediation models, clarifying and proposing solutions to some issues which have not been addressed by the previous literature. Specifically, we discussed discrete exposures, binary mediators and extensions of this approach to more complex settings like the multilevel one. We also propose to estimate confidence intervals for the indirect effect within a Bayesian framework and compare its performance to that of other approaches in the literature through a simulation study. Finally, a real data application is presented.

Multi-modal analysis of inflammation as a potential mediator of depressive symptoms in young people with HIV: The GOLD depression study.

People living with HIV are at three times greater risk for depressive symptoms. Inflammation is a notable predictor of depression, and people with HIV exhibit chronic inflammation despite antiretroviral therapy. We hypothesised that inflammatory biomarkers may mediate the association between HIV status and depressive symptoms. Participants (N = 60, 53% girls, median [interquartile range (IQR)] age 15.5 [15.0, 16.0] years, 70% living with HIV, of whom 90.5% were virally-suppressed) completed the nine-item Patient Health Questionnaire (PHQ-9). We measured choline and myo-inositol in basal ganglia, midfrontal gray matter, and peritrigonal white matter using magnetic resonance spectroscopy, and 16 inflammatory proteins in blood serum using ELISA and Luminex™ multiplex immunoassays. Using structural equation mediation modelling, we calculated standardised indirect effect estimates with 95% confidence intervals. Median [IQR] total PHQ-9 score was 3 [0, 7]. HIV status was significantly associated with total PHQ-9 score (B = 3.32, p = 0.022). Participants with HIV showed a higher choline-to-creatine ratio in the basal ganglia than those without HIV (β = 0.86, pFDR = 0.035). In blood serum, participants with HIV showed higher monocyte chemoattractant protein-1 (MCP-1, β = 0.59, pFDR = 0.040), higher chitinase-3 like-1 (YKL-40, β = 0.73, pFDR = 0.032), and lower interleukin-1beta (IL-1β, β = -0.67, pFDR = 0.047) than those without HIV. There were no significant associations of any biomarkers with total PHQ-9 score. None of the indirect effects were significant, mediating <13.1% of the association. Findings remained consistent when accounting for age, gender, and time between neuroimaging and PHQ-9 administration. Using a robust analytical approach in a community-based sample, we have shown that participants living with HIV reported greater depressive symptoms than those without HIV, but we did not find that neuroimaging and blood biomarkers of inflammation significantly mediated this association. Further studies with participants experiencing severe depression may help to elucidate the links between HIV, inflammation, and depression.

Methods for the estimation of direct and indirect vaccination effects by combining data from individual- and cluster-randomized trials.

Both individually and cluster randomized study designs have been used for vaccine trials to assess the effects of vaccine on reducing the risk of disease or infection. The choice between individually and cluster randomized designs is often driven by the target estimand of interest (eg, direct versus total), statistical power, and, importantly, logistic feasibility. To combat emerging infectious disease threats, especially when the number of events from one single trial may not be adequate to obtain vaccine effect estimates with a desired level of precision, it may be necessary to combine information across multiple trials. In this article, we propose a model formulation to estimate the direct, indirect, total, and overall vaccine effects combining data from trials with two types of study designs: individual-randomization and cluster-randomization, based on a Cox proportional hazards model, where the hazard of infection depends on both vaccine status of the individual as well as the vaccine status of the other individuals in the same cluster. We illustrate the use of the proposed model and assess the potential efficiency gain from combining data from multiple trials, compared to using data from each individual trial alone, through two simulation studies, one of which is designed based on a cholera vaccine trial previously carried out in Matlab, Bangladesh.

Assessment of inter-relationships between yield and yieldattributes in safflower (Carthamus tinctorius L.)

Character association studies in 29 genotypes of safflower for seven characters conducted at Agricultural Research Station, Tandur revealed significant positive association of single plant yield with test weight, number of effective capitula per plant, plant height and number of seeds per capitulum. Estimates of direct and indirect effects of component characters on single plant yield at genotypic level revealed that test weight contributed for maximum positive direct effect on single plant yield followed by days to maturity, plant height and number of seeds per capitulum. Also, these traits had positive and significant association with grain yield. Critical analysis of character association and path analysis showed that these characters should be given importance to isolate superior lines with genetic potentiality for high grain yield.

Gender differences in direct and indirect associations of trauma types with disordered eating in a national U.S. veteran sample.

Disordered eating (DE) in military veterans has been linked to trauma exposure, but the mechanisms underlying this association remain unclear. The current study documented the direct associations of DE with multiple trauma types in a gender-balanced sample of veterans and examined indirect associations of trauma and DE via self-reported PTSD symptoms and concerns about shape and weight. Participants included 1,187 veterans (50% women, 46% men, 4% another) from multiple service eras. Sampling weights were applied to enhance representativeness to the national veteran population. Gender-stratified, weighted models revealed associations of premilitary, warfare, and postseparation trauma with DE in men and associations of premilitary, military sexual (MST), and postseparation trauma with DE in women. Monte Carlo estimation of indirect effects showed support for indirect associations of premilitary, warfare, and postseparation-related trauma/stressor exposure with DE via PTSD symptoms among men; postseparation stressors were also indirectly associated with DE via shape and weight concerns. Among women, each trauma type was indirectly associated with DE via shape and weight concerns but not PTSD symptoms. When trauma exposures were examined concurrently, MST and postseparation trauma exposure were uniquely associated with DE via shape and weight concerns among women. Only the indirect association of postseparation trauma/stressor exposure with DE via shape and weight concerns was significant among men. Findings support the need for gender-specific interventions that target different mechanisms contributing to DE symptoms among veterans. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Policies to reduce child poverty and child maltreatment: A scoping review and preliminary estimates of indirect effects

This study includes a scoping review of prior studies investigating the effects of policy changes on child poverty rates. It further conducts an empirical analysis to estimate the relationship between child poverty rates and child maltreatment report (CMR) rates, utilizing national county-level data. The study then calculates the indirect effects of policy changes on CMR rates, mediated through child poverty rates, by integrating information from previous studies with its own empirical findings. Among the policy changes explored in prior studies, those related to a child allowance and a fully refundable Child Tax Credit demonstrate the largest indirect effects but also the highest costs. The expansion of in-kinds and near-cash benefits, such as the Supplemental Nutrition Assistance Program benefits and housing vouchers, shows moderate effects with moderate costs. Tax credits like the Earned Income Tax Credit exhibit lower effects and costs when targeted at the lowest earners, and moderate effects and costs for broader expansion. Focused tax credits, such as the Child and Dependent Care Tax Credit, had lower effects and costs, even if made fully refundable. Despite certain limitations, the study's approach yields consistent estimates with a recent simulation study, indicating its potential validity. While some proposed policy changes may seem expensive, implementing them is anticipated to substantially reduce CMR rates, with the benefits outweighing the associated costs. Overall, the findings suggest that addressing child poverty to reduce CMRs is an attractive strategy with numerous potential benefits.

A cross-sectional analysis of the relationships between anxiety sensitivity and youth irritability: the mediated roles of insomnia and selective attention for threat

BackgroundIrritability is common in multiple psychiatric disorders and is hallmark of disruptive mood dysregulation disorder. Child irritability is associated with higher risk of suicide and adulthood mental health problems. However, the psychological mechanisms of irritability are understudied. This study examined the relationship between anxiety sensitivity and irritability among youth, and further explored three possible mediated factors: selective attention for threat, delayed reward discounting, and insomnia.MethodsParticipants were 1417 students (51.7% male; mean age 13.83 years, SD = 1.48) recruited from one high school in Hunan province, China. Self-report questionnaires were used to measure irritability (The Affective Reactivity Index and The Brief Irritability Test), anxiety sensitivity (The Childhood Anxiety Sensitivity Index), selective attention for threat (The Davos Assessment of Cognitive Biases Scale-attention for threat bias subscale), insomnia (The Youth Self-Rating Insomnia Scale), and delayed reward discounting (The 27-item Monetary Choice Questionnaire). Structural equation modal (SEM) was performed to examine mediated relations.ResultsAnxiety sensitivity was modestly related to irritability and insomnia (r from 0.25 to 0.54) and slightly correlated with selective attention for threat (r from 0.12 to 0.28). However, there is no significant relationship of delayed rewards discounting with anxiety sensitivity and irritability. The results of SEM showed that selective attention for threat (indirect effect estimate = 0.04) and insomnia (indirect effect estimate = 0.20) partially mediate the relationship between anxiety sensitivity and irritability, which explained 34% variation.ConclusionsAnxiety sensitivity is an important susceptibility factor for irritability. Selective attention for threat and insomnia are two mediated mechanisms to understand the relationship between anxiety sensitivity and irritability.

Estimation of Direct and Indirect Effect of Yield Attributing Characters on Grain Yield in Kodo Millet (Paspalum scrobiculatum L.)

The present study on “Estimation of direct and indirect effect of yield attributing characters on grain yield in kodo millet (Paspalum scrobiculatum L.)” was carried out at Instructional cum Research Farm of S.G. College of Agriculture and Research Station Kumhrawand, Jagdalpur, Chhattisgarh. In this study direct effect of productive tillers per plant on grain yield per plot was positive and high at genotypic and phenotypic level. Indicated true relationship of this trait and direct selection through this character will be effective.

Soilfoodwebs: An R package for analyzing and simulating nutrient fluxes through food webs

Soil food web models can calculate the fluxes of carbon and nitrogen between soil organisms and so estimate the impact of individual organisms on ecosystem processes. These modelling approaches go beyond standard techniques in ecology. So, an open-source tool supporting them along with an analysis of their strengths and weaknesses could help. We present the R package soilfoodwebs, which calculates carbon and nitrogen fluxes through food webs and contributes four new features that are documented in the literature but unavailable in open-source software: (1) diet and physiological rates that balance multiple chemical elements, (2) estimates of parameter and structural uncertainty, (3) estimates of direct and indirect effects of taxa on ecosystem processes, and (4) a conversion from equilibrium food web analyses to simulations that can estimate the response to change. soilfoodwebs balances carbon and nitrogen demand by adjusting each organism's diet and the efficiency with which they use carbon. We outline the theory behind the package and demonstrate its functions using soil food web models available in the literature. Our analysis shows that the calculation of fluxes and the contributions of individual taxa to mineralization or decomposition rates is the strength of the soilfoodwebs package and soil food web models. We also show that more detailed information on population regulation (i.e., density-dependence) is needed for using these models to predict trends over time. Outputs from soil food web models can be compared with ecosystem measurements (e.g., mineralization, decomposition) and guide empirical work towards functionally important and undocumented soil biodiversity.

Interplay Between Chronic Kidney Disease, Hypertension, and Stroke: Insights From a Multivariable Mendelian Randomization Analysis.

Chronic kidney disease (CKD) increases the risk of stroke, but the extent through which this association is mediated by hypertension is unknown. We leveraged large-scale genetic data to explore causal relationships between CKD, hypertension, and cerebrovascular disease phenotypes. We used data from genome-wide association studies of European ancestry to identify genetic proxies for kidney function (CKD diagnosis, estimated glomerular filtration rate [eGFR], and urinary albumin-to-creatinine ratio [UACR]), systolic blood pressure (SBP), and cerebrovascular disease (ischemic stroke and its subtypes and intracerebral hemorrhage). We then conducted univariable, multivariable, and mediation Mendelian randomization (MR) analyses to investigate the effect of kidney function on stroke risk and the proportion of this effect mediated through hypertension. Univariable MR revealed associations between genetically determined lower eGFR and risk of all stroke (odds ratio [OR] per 1-log decrement in eGFR, 1.77; 95% CI 1.31-2.40; p < 0.001), ischemic stroke (OR 1.81; 95% CI 1.31-2.51; p < 0.001), and most strongly with large artery stroke (LAS) (OR 3.00; 95% CI 1.33-6.75; p = 0.008). These associations remained significant in the multivariable MR analysis, controlling for SBP (OR 1.98; 95% CI 1.39-2.82; p < 0.001 for all stroke; OR 2.16; 95% CI 1.48-3.17; p < 0.001 for ischemic stroke; OR 4.35; 95% CI 1.84-10.27; p = 0.001 for LAS), with only a small proportion of the total effects mediated by SBP (6.5% [0.7%-16.8%], 6.6% [0.8%-18.3%], and 7.2% [0.5%-24.8%], respectively). Total, direct and indirect effect estimates were similar across a number of sensitivity analyses (weighted median, MR-Egger regression). Our results demonstrate an independent causal effect of impaired kidney function, as assessed by decreased eGFR, on stroke risk, particularly LAS, even when controlled for SBP. Targeted prevention of kidney disease could lower atherosclerotic stroke risk independent of hypertension.

The impact of reduced worry on general functioning: Amediation analysis from a randomized trial.

Previous lab findings have indicated that excessive worry may impair cognitive performance and problem solving capabilities but it is unclear if excessive worry also leads to broader impairments in general functioning. We report a secondary process data analysis of a large randomized waitlist-controlled trial (N=670) of a self-guided online psychological intervention for dysfunctional worry related to the Covid-19 pandemic. Specific aims were to investigate (1) if improvements in general functioning were mediated by reductions in worry related to Covid-19 during the acute intervention phase, and (2) if reduced worry related to Covid-19 during acute intervention phase had a positive long-term impact on general functioning up to 1year after the end of the intervention. To address aim 1, we used a mediation analysis framework where outcome (general functioning measured with an adapted version of the Work and Social Adjustment Scale) and the hypothesized mediator (worry measured with an adapted version of the Generalised Anxiety Disorder 7-Item Scale) were administered weekly during the controlled phase of the trial of 3weeks. To address aim 2, we investigated if reductions in worry during the 3-week treatment period predicted improved general functioning at 1- and 12months after treatment completion. Results showed that improvements in general functioning at week 3 were mediated by reductions in worry during the first 2weeks of treatment (indirect effect estimate -0.08; 95% CI -0.15, -0.02). A sensitivity analysis indicated that the mediation effects dropped significantly when the residual correlation values between the mediator and the outcome exceeded r=0. A reversed causation model was not significant. Additionally, reductions in worry during treatment predicted subsequent improvements in general functioning at both 1- and 12-month follow-ups (p<.05, -.001). Altogether, these results provide further support of the importance of targeting worry as a way to improve functioning among the large population of individuals with high levels of worry.

A brief primer on conducting regression-based causal mediation analysis.

We provide an overview of regression-based causal mediation analysis in the field of traumatic stress and guidance on how to conduct mediation analysis using our R package regmedint. We discuss the causal interpretations of the quantities that causal mediation analysis estimates, including total, direct, and indirect effects, especially when the interaction between exposure and mediator is permitted. We discuss the assumptions that must be fulfilled for mediation analyses to validly estimate these causal quantities, discuss suitable study designs for assessing mediation, and describe how causal mediation analysis differs from traditional methods of mediation. To illustrate how to conduct and interpret mediation analysis using our R package regmedint, we use data from a published longitudinal study to assess the extent to which children's externalizing behavior mediates changes in parental negative feelings during the COVID-19 lockdown. We compare the results to those obtained using traditional methods, thus illustrating the importance of accounting for exposure-mediator interaction when an interaction may be present. When the exposure and the mediator interact, traditional methods can provide estimates of direct and indirect effects that differ from those provided by more flexible causal mediation methods. When the exposure and the mediator do not interact, traditional methods and causal mediation method may estimate similar direct and indirect effects depending on the model specification. In contrast to traditional methods of mediation analysis, regression-based causal mediation methods seek to estimate specific interventional quantities, not mere associations, and the causal methods explicitly allow for exposure-mediator interactions. We recommend using these methods by default rather than using more restrictive traditional methods. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Associations of Military-Related Traumatic Brain Injury With New-Onset Mental Health Conditions and Suicide Risk

Research to identify the direct and indirect associations of military-related traumatic brain injury (TBI) with suicide has been complicated by a range of data-related challenges. To identify differences in rates of new-onset mental health conditions (ie, anxiety, mood, posttraumatic stress, adjustment, alcohol use, and substance use disorders) among soldiers with and without a history of military-related TBI and to explore the direct and indirect (through new-onset mental health disorders) associations of TBI with suicide. This retrospective cohort study used data from the Substance Use and Psychological Injury Combat Study (SUPIC) database. Demographic, military, and health data from the Department of Defense within SUPIC were compiled and linked with National Death Index records to identify deaths by suicide. Participants included US Army soldiers who returned from an Afghanistan or Iraq deployment. Data were analyzed from September to December 2022. Military-related TBI. The outcome of interest was suicide. Secondary outcomes were incidence of new-onset mental health conditions. Mediation analyses consisted of accelerated failure time (AFT) models in conjunction with the product of coefficients method. The 6 new-onset mental health diagnosis categories and the 2 or more categories variable were each considered separately as potential mediators; therefore, a total of 14 models plus the overall AFT model estimating the total effect associated with TBI in suicide risk were fit. The study included 860 892 soldiers (320 539 soldiers [37.2%] aged 18-24 at end of index deployment; 766 454 [89.0%] male), with 108 785 soldiers (12.6%) with at least 1 documented TBI on their military health record. Larger increases in mental health diagnoses were observed for all conditions from before to after documented TBI, compared with the matched dates for those without a history of TBI, with increases observed for mood (67.7% vs 37.5%) and substance use (100% vs 14.5%). Time-to-suicide direct effect estimates for soldiers with a history of TBI were similar across mediators. For example, considering new-onset adjustment disorders, time-to-suicide was 16.7% faster (deceleration factor, 0.833; 95% CI, 0.756-0.912) than for soldiers without a history of TBI. Indirect effect estimates of associations with TBI were substantial and varied across mediators. The largest indirect effect estimate was observed through the association with new-onset substance use disorder, with a time to suicide 63.8% faster (deceleration factor, 0.372; 95% CI, 0.322-0.433) for soldiers with a history of TBI. In this longitudinal cohort study of soldiers, rates of new-onset mental health conditions were higher among individuals with a history of TBI compared with those without. Moreover, risk for suicide was both directly and indirectly associated with history of TBI. These findings suggest that increased efforts are needed to conceptualize the accumulation of risk associated with multiple military-related exposures and identify evidence-based interventions that address mechanisms associated with frequently co-occurring conditions.

The Mediator Role of Psychological Resilience in the Relationship of Cognitive Flexibility and Fear of COVID-19

Covid-19 pandemic is thought to cause a lot of short or long-term mental disorders. In order to reduce these problems the pandemic will create to minimum, it is believed that psychological resilience and cognitive flexibility have an important function. In this respect, the direct and indirect relationships and the mediating role between the psychological resilience, cognitive flexibility and fear of Covid-19 were examined in a Turkish sample consisting of 511 people. The data obtained from this sample group were analyzed by structural equality model. Indirect effect estimate of psychological resilience for was tested with the SPSS Macro Process application on the basis of the bootstrap test. As a result of the analysis found that, mediating role of psychological resilience is significant in the relationship between cognitive flexibility and Covid-19 fear.

Estimation of separable direct and indirect effects in a continuous-time illness-death model.

In this article we study the effect of a baseline exposure on a terminal time-to-event outcome either directly or mediated by the illness state of a continuous-time illness-death process with baseline covariates. We propose a definition of the corresponding direct and indirect effects using the concept of separable (interventionist) effects (Robins and Richardson in Causality and psychopathology: finding the determinants of disorders and their cures, Oxford University Press, 2011; Robins et al. in arXiv:2008.06019 , 2021; Stensrud et al. in J Am Stat Assoc 117:175-183, 2022). Our proposal generalizes Martinussen and Stensrud (Biometrics 79:127-139, 2023) who consider similar causal estimands for disentangling the causal treatment effects on the event of interest and competing events in the standard continuous-time competing risk model. Unlike natural direct and indirect effects (Robins and Greenland in Epidemiology 3:143-155, 1992; Pearl in Proceedings of the seventeenth conference on uncertainty in artificial intelligence, Morgan Kaufmann, 2001) which are usually defined through manipulations of the mediator independently of the exposure (so-called cross-world interventions), separable direct and indirect effects are defined through interventions on different components of the exposure that exert their effects through distinct causal mechanisms. This approach allows us to define meaningful mediation targets even though the mediating event is truncated by the terminal event. We present the conditions for identifiability, which include some arguably restrictive structural assumptions on the treatment mechanism, and discuss when such assumptions are valid. The identifying functionals are used to construct plug-in estimators for the separable direct and indirect effects. We also present multiply robust and asymptotically efficient estimators based on the efficient influence functions. We verify the theoretical properties of the estimators in a simulation study, and we demonstrate the use of the estimators using data from a Danish registry study.

Insulin Homeostasis Mediates the Relationship Between Cardiorespiratory Fitness and Cognitive Speed in Aging Adults.

Cardiorespiratory fitness (CRF) supports cognition, though it is unclear what mechanisms underly this relationship. Insulin resistance adversely affects cognition but can be reduced with habitual exercise. We investigated whether insulin resistance statistically mediates the relationship between CRF and cognition. In our observational study, we included n = 1,131 cognitively unimpaired, nondiabetic older adults from a cohort characterized by elevated Alzheimer's disease (AD) risk. We estimated CRF (eCRF) using a validated equation that takes age, sex, body mass index, resting heart rate, and habitual physical activity as inputs. The Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) quantified insulin resistance. Standardized cognitive factor scores for cognitive speed/flexibility, working memory, verbal learning/memory, and immediate memory were calculated from a battery of neuropsychological tests. Linear regression models and bootstrapped estimates of indirect effects were used to determine whether HOMA-IR mediated significant relationships between eCRF and cognition. eCRF was positively associated with cognitive speed/flexibility (p = 0.034). When controlling for HOMA-IR, eCRF was no longer associated with cognitive speed/flexibility (p = 0.383). HOMA-IR had a significant indirect effect on the eCRF-cognition relationship (B = 0.025, CI = [0.003,0.051]). eCRF was not associated with working memory (p = 0.236), immediate memory (p = 0.345), or verbal learning/memory (p = 0.650). Among older adults at risk for AD, peripheral insulin resistance mediates the relationship between CRF and cognitive speed.