Unique Variance Research Articles

An examination of the unique contributions of body image and internalized weight bias to psychological well-being outcomes

High correlations between measures of internalized weight bias (IWB) and body image (BI) have resulted in concerns that IWB is conceptually redundant with BI. This investigation examined the contribution of the unique variance of BI and IWB on three important, weight-related factors: self-esteem, depressive symptoms, and body shame. The study included 403 participants recruited through a Qualtrics research panel. Participants were required to be aged 18 + and have a BMI > 25. The sample contained three equally represented, self-identified racial/ethnic groups: Black non-Hispanic (N = 140), Hispanic (N = 133), and White non-Hispanic (N = 130). When BI was entered in the first step of the regression model, it accounted for 14–40% of the variance in various models; the addition of IWB in step two contributed 11–18% of unique variance. By contrast, when IWB was entered in the first step, it accounted for 25–56% of the variance in various models, with the addition of BI contributing between 0% and 2% unique variance. Therefore, even with a high correlation among the constructs of IWB and BI, IWB was able to contribute unique variance in predicting depressive symptoms, self-esteem, and body shame, and is not redundant with the construct of BI.

Assessing the Impact of Person-Environment fit on Turnover Intention Through Multiple Linear Regression

Focusing on key antecedents of intended turnover may enable organizations to intervene before reaching scenarios where employee turnover is inevitable. The current study aimed to establish which type of fit plays the most prominent role in employees’ turnover intention. To achieve this aim, multiple linear regression was used. By establishing which type of fit influences employees’ thoughts of quitting the most, organizations can adopt better retention strategies as opposed to casting a net and hoping for the best. This cross-sectional study used secondary data from 384 retail employees. Three distinct fit scales and a turnover intention scale were administered. The study’s hypothesis was assessed through multiple linear regression, relative weight analysis, and commonality analysis. Needs-supplies fit was the only variable that had a statistically significant negative association with turnover intention. Needs-supplies fit had the biggest contribution (23.64%) to the multiple R 2 value (34.25%) of the multiple linear regression model. Commonality analysis showed that needs-supplies fit accounted for the highest percentage (16.85%) of unique variance in explaining turnover intention. To enhance the probability of retaining employees, organizations may want to fine-tune their retention strategies based on establishing congruence between what employees need and what can be done to meet these desired needs. The current study stresses the importance of distinguishing between different types of person-environment fit as they may not similarly relate to outcomes.

The relationship between difficulties in the regulation of positive and negative emotions and binge-eating symptoms in young adults

It is well-established that binge-eating (BE) is linked to emotion regulation (ER) difficulties. However, research to date has focused almost exclusively on difficulties regulating negative emotions, with little attention to the relationship between positive emotion dysregulation and BE. Further, research is inconclusive regarding which specific facets of ER difficulties are most strongly associated with BE behaviour. Therefore, the current study examined whether difficulties regulating both negative as well as positive emotions explained unique variance in BE among young adults. The study also aimed to identify which particular dimensions of negative and positive ER difficulties were most strongly related to BE symptoms. Participants (N = 449) ages 18–25 completed self-report measures of difficulties regulating positive and negative emotions, BE symptoms, and psychological distress. Hierarchical regression analyses showed that BE was related to difficulties regulating both positive emotions and negative emotions, after controlling for psychological distress and BMI. Lack of emotional clarity and lack of access to ER strategies when faced with strong negative emotions were the facets of negative ER difficulties most strongly associated with BE. Impulsivity when experiencing strong positive emotions was the facet of positive ER difficulties most strongly associated with BE. These findings support the ER model of BE and suggest that difficulties regulating both positive and negative emotions contribute to BE among young adults.

Contributions of enlarged perivascular spaces and white matter hyperintensities to cognitive performance in the Alzheimer’s disease continuum – shared and unique effects

AbstractBackgroundIndependent contributions of enlarged perivascular spaces (ePVS) to cognition remain elusive due to their intertwining with white matter hyperintensities (WMH). We studied the unique and shared effects of ePVS and WMH on cognitive performance in 397 subjects along the Alzheimer’s disease (AD) continuum.MethodsWe quantified baseline volumes of WMH, basal ganglia (BG) and centrum semiovale (CSO) ePVS in participants of the multicentre DELCODE study (Controls = 81/Subjective Cognitive Decline = 151/Mild Cognitive Impairment = 79/AD = 45/AD relatives = 41) and regressed age, sex, pTau181, and image quality out of them.We established cognitive domain scores (memory, working memory, language, executive, visuospatial) based on a comprehensive cognitive test battery and confirmatory factor analysis, and assessed preclinical Alzheimer’s cognitive composite (PACC5) scores.Using principle component (PC) analysis, we estimated unique and shared variances. We began by extracting the first PC (PC1)—a weighted average of ePVS and WMH volumes—which indicated overall cerebrovascular dysfunction (Figure 1). We then regressed PC1 out of ePVS and WMH volumes to estimate their unique variances, which should reflect glymphatic function and white matter (WM) damage, respectively.For each cognitive domain, we compared null linear regression models (years of education, age, sex, pTau181, and image quality) to those enriched with the shared (PC1) and unique variances of BG‐/CSO‐ePVS and WMH.ResultsOverall cerebrovascular dysfunction—PC1—substantially affected all cognitive domains negatively.BG‐ePVS’ unique variance—surrogate for glymphatic function—contributed to better memory (B = 0.19, 95%‐CI[0.02;0.36]), language (B = 0.25, 95%‐CI[0.09;0.42]) and PACC5 performance (B = 0.25, 95%‐CI[0.07;0.43]) beyond overall cerebrovascular dysfunction. However, WM damage—WMH unique variance—contributed more substantially and negatively to the same cognitive domains (memory: R²PC1 = 0.365<R²PC1+BG‐ePVS = 0.372<R²PC1+WMH = 0.382; language: R²PC1 = 0.353<R²PC1+BG‐ePVS = 0.366<R²PC1+WMH = 0.370; PACC5: R²PC1 = 0.300<R²PC1+BG‐ePVS = 0.313<R²PC1+WMH = 0.324; Table 1), and moreover to executive (B = ‐0.10, 95%‐CI[‐0.18;‐0.02]) and visuospatial performance (B = ‐0.07, 95%‐CI[‐0.14;‐0.00]).CSO‐ePVS’ unique variance did not correlate with any cognitive domain.ConclusionsOverall cerebrovascular dysfunctions and WM damage—reflected by the shared variance between ePVS and WMH as well as the unique WMH variance—contributed distinctively to poorer cognitive performance. The contrasting positive impact of unique BG‐ePVS variance could represent a “glymphatic or vascular reserve” in a region important for different cognitive processes—this hypothesis, however, requires further investigation.

The investigation of hippocampal free‐water as a biomarker for cognitive impairment and decline in older adults

AbstractBackgroundWhile diffusion MRI derived free‐water (FW) metrics have shown promise in predicting cognitive impairment and decline in aging and Alzheimer’s disease (AD), it is unclear whether hippocampal FW metrics would be superior to traditional structural neuroimaging biomarkers (i.e., hippocampal volume, AD Schwarz Signature, AD McEvoy Signature). We examined the relationships between hippocampal FW metrics and traditional neuroimaging biomarkers with longitudinal memory and executive function.MethodVanderbilt Memory & Aging Project participants [n = 298, age at baseline: 73 ± 7 years, 40% mild cognitive impairment (MCI)] underwent longitudinal neuropsychological assessment and brain MRI over a 7 year follow‐up (mean: 3 ± 2 years) period. Structural MRI was used to quantify hippocampal volume in addition to Schwarz and McEvoy signatures. Diffusion MRI in conjunction with the FW elimination technique was used to quantify hippocampal FW and FW‐corrected fractional anisotropy (FAFWcorr). Linear regression was used to determine the association of each biomarker with baseline memory and executive function. A subsequent competitive model analysis was conducted to determine how much additional variance was provided by each biomarker compared to the covariate only model, which included age, sex, race/ethnicity, apolipoprotein‐e4 status, cognitive status, and modified Framingham Stroke Risk Profile scores. Additionally, linear mixed‐effects regression was used to determine the association between baseline biomarker values with longitudinal memory and executive function scores. All analyses were corrected for multiple comparisons using the FDR procedure.ResultAt baseline, all biomarkers (excluding hippocampal FAFWcorr) were significantly associated with cognitive performance (Table 1), with hippocampal FW exhibiting the most significant association for memory (pFDR = 3.92×10‐6) and executive function (pFDR = 5.35×10‐3). Competitive models revealed that hippocampal FW contributed the most unique variance beyond covariates for memory (ΔRadj2 = 3.87%) and executive function (ΔRadj2 = 1.59%). Longitudinal models (Table 2, Figure 1) largely mirrored cross‐sectional models by demonstrating that hippocampal FW was most significantly associated with longitudinal decline in memory (pFDR = 5.04×10‐13) and executive function (pFDR = 6.15×10‐5).ConclusionThis study shows that hippocampal FW is a sensitive biomarker for cognitive impairment and decline, and provides strong evidence for further exploration of this measure in aging and AD.

The investigation of hippocampal free‐water as a biomarker for cognitive impairment and decline in older adults

AbstractBackgroundWhile diffusion MRI derived free‐water (FW) metrics have shown promise in predicting cognitive impairment and decline in aging and Alzheimer’s disease (AD), it is unclear whether hippocampal FW metrics would be superior to traditional structural neuroimaging biomarkers (i.e., hippocampal volume, AD Schwarz Signature, AD McEvoy Signature). We examined the relationships between hippocampal FW metrics and traditional neuroimaging biomarkers with longitudinal memory and executive function.MethodVanderbilt Memory & Aging Project participants [n = 298, age at baseline: 73 ± 7 years, 40% mild cognitive impairment (MCI)] underwent longitudinal neuropsychological assessment and brain MRI over a 7 year follow‐up (mean: 3 ± 2 years) period. Structural MRI was used to quantify hippocampal volume in addition to Schwarz and McEvoy signatures. Diffusion MRI in conjunction with the FW elimination technique was used to quantify hippocampal FW and FW‐corrected fractional anisotropy (FAFWcorr). Linear regression was used to determine the association of each biomarker with baseline memory and executive function. A subsequent competitive model analysis was conducted to determine how much additional variance was provided by each biomarker compared to the covariate only model, which included age, sex, race/ethnicity, apolipoprotein‐e4 status, cognitive status, and modified Framingham Stroke Risk Profile scores. Additionally, linear mixed‐effects regression was used to determine the association between baseline biomarker values with longitudinal memory and executive function scores. All analyses were corrected for multiple comparisons using the FDR procedure.ResultAt baseline, all biomarkers (excluding hippocampal FAFWcorr) were significantly associated with cognitive performance (Table 1), with hippocampal FW exhibiting the most significant association for memory (pFDR = 3.92×10−6) and executive function (pFDR = 5.35×10−3). Competitive models revealed that hippocampal FW contributed the most unique variance beyond covariates for memory (ΔRadj 2 = 3.87%) and executive function (ΔRadj 2 = 1.59%). Longitudinal models (Table 2, Figure 1) largely mirrored cross‐sectional models by demonstrating that hippocampal FW was most significantly associated with longitudinal decline in memory (pFDR = 5.04×10−13) and executive function (pFDR = 6.15×10−5).ConclusionThis study shows that hippocampal FW is a sensitive biomarker for cognitive impairment and decline, and provides strong evidence for further exploration of this measure in aging and AD.

A Twin Analysis of AD Brain Signatures and Abnormal White Matter

AbstractBackgroundAlzheimer’s disease (AD) and vascular disease frequently co‐occur and may interact additively or synergistically on risk for cognitive decline, though the degree of shared overlap between these pathologies remains unclear. Our group has demonstrated the utility of AD signatures, or composite MRI metrics in brain regions associated with AD pathology, for prediction of AD‐related changes beginning in midlife. Our novel signature based on gray matter mean diffusivity (MD) aided 12‐year prediction of incident mild cognitive impairment among cognitively unimpaired adults in their 50s, captured unique phenotypic and genetic variance not otherwise explained by an AD signature based on cortical thickness/volume or general brain aging, and robustly predicted thickness/volume signatures over a decade later. Here, we leveraged twin data from the Vietnam Era Twin Study of Aging (VETSA) to delineate shared and unique genetic and environmental influences on two AD signatures and white matter hyperintensities (WMHs), which have been consistently linked to vascular origin.MethodParticipants were 512 men from the VETSA (age = 67.52, SD = 2.60). Our validated thickness/volume signature, novel MD signature based on the same brain regions as the thickness/volume signature, and WMH volume were used in biometrical twin analyses to examine their phenotypic, genetic, and environmental relationships. We adjusted each AD signature for an MRI‐based measure of brain age to detect associations with WMH that were specific to AD‐related brain regions versus general brain aging. We also examined regional WMH parcellations.ResultPhenotypic and genetic correlations demonstrated significant associations between the MD signature and WMH (rp = 0.26 [95% CI: 0.15, 0.36]; rg = 0.34 [95% CI: 0.10, 0.57]). In contrast, phenotypic and genetic correlations between the thickness/volume signature and WMHs were nonsignificant. Environmental correlations between each AD signature and WMH were similarly nonsignificant. Results were similar for each WMH parcellation, suggesting global WMH effects.ConclusionA gray matter MD signature and WMHs share significant genetic influences, whereas a thickness/volume signature was not associated with WMHs. AD signatures based on brain microstructure, such as the MD signature, may capture very early AD‐related and vascular‐related changes that are not captured by a macrostructural signature at the same timepoint.

A Twin Analysis of AD Brain Signatures and Abnormal White Matter

AbstractBackgroundAlzheimer’s disease (AD) and vascular disease frequently co‐occur and may interact additively or synergistically on risk for cognitive decline, though the degree of shared overlap between these pathologies remains unclear. Our group has demonstrated the utility of AD signatures, or composite MRI metrics in brain regions associated with AD pathology, for prediction of AD‐related changes beginning in midlife. Our novel signature based on gray matter mean diffusivity (MD) aided 12‐year prediction of incident mild cognitive impairment among cognitively unimpaired adults in their 50s, captured unique phenotypic and genetic variance not otherwise explained by an AD signature based on cortical thickness/volume or general brain aging, and robustly predicted thickness/volume signatures over a decade later. Here, we leveraged twin data from the Vietnam Era Twin Study of Aging (VETSA) to delineate shared and unique genetic and environmental influences on two AD signatures and white matter hyperintensities (WMHs), which have been consistently linked to vascular origin.MethodParticipants were 512 men from the VETSA (age = 67.52, SD = 2.60). Our validated thickness/volume signature, novel MD signature based on the same brain regions as the thickness/volume signature, and WMH volume were used in biometrical twin analyses to examine their phenotypic, genetic, and environmental relationships. We adjusted each AD signature for an MRI‐based measure of brain age to detect associations with WMH that were specific to AD‐related brain regions versus general brain aging. We also examined regional WMH parcellations.ResultPhenotypic and genetic correlations demonstrated significant associations between the MD signature and WMH (rp = 0.26 [95% CI: 0.15, 0.36]; rg = 0.34 [95% CI: 0.10, 0.57]). In contrast, phenotypic and genetic correlations between the thickness/volume signature and WMHs were nonsignificant. Environmental correlations between each AD signature and WMH were similarly nonsignificant. Results were similar for each WMH parcellation, suggesting global WMH effects.ConclusionA gray matter MD signature and WMHs share significant genetic influences, whereas a thickness/volume signature was not associated with WMHs. AD signatures based on brain microstructure, such as the MD signature, may capture very early AD‐related and vascular‐related changes that are not captured by a macrostructural signature at the same timepoint.

The association between change and stability in subjective health ratings and dementia risk: a multi‐cohort study in Swedish and Danish twins

AbstractBackgroundPoorer self‐rated health (SRH) is associated with increased dementia risk (Stephan et al., 2021). However, it is unclear whether genetic and/or environmental variance accounts for this risk. Although SRH declines with age (Finkel et al. 2020), it is unknown whether rates of change in SRH are independently associated with dementia outcomes. Using a validated latent dementia index (LDI) (Beam et al., 2022), we tested whether stability and change components of SRH predicted LDI via genetic and environmental pathways in two international cohorts of twins.MethodOur data consisted of two samples of monozygotic (MZ) and dizygotic (DZ) twins. We used data from the Swedish Adoption Twin Study of Aging (SATSA; Ntwins = 548, Npairs = 339) and the Longitudinal Study of Aging Danish Twins (LSADT; Ntwins = 3238, Npairs = 2561). Bivariate Cholesky decompositions and three‐level growth‐curve models with predictive intercepts and slopes were used for our cross‐sectional and longitudinal analyses respectively. All models were estimated in Mplus (Muthen & Muthen, 2017) using maximum likelihood with robust standard errors.ResultsCross‐sectional model results indicate that those with poorer SRH have lower LDI scores (b = ‐0.01, p = .008), even after adjusting for shared genetic covariance, age, sex, education, and depressive symptoms. Predictive growth models indicate that rates of change in SRH are negatively associated with LDI after adjusting for age, sex, education, and depressive symptoms (b = ‐0.17, p = .032). The degree of genetic confounding in the association between rates of change and LDI was inconclusive.ConclusionOur study provides novel insights into the relationship between individual ratings of health and dementia risk. SRH predicted dementia likelihood after controlling for genetic confounding, opening up the possibility that subjective ratings of health account for unique variance in dementia risk. Additionally, changes in SRH also predicted dementia likelihood beyond their mean score. Taken together these results highlight the importance of subjective health measures in understanding dementia risk.

Physical function predicts declarative memory

AbstractBackgroundNo cure currently exists for Alzheimer’s disease; however, early detection may help create therapies and treatments to slow cognitive decline. The concept of early detection is simple, but is complicated by the inability of primary care physicians to recognize symptoms until late disease manifestation and failure to provide appropriate screening tools for disease detection. Thus, the purpose of the present investigation was to determine predictors of cognitive performance among community‐dwelling older adults.Method63 community‐dwelling older adults (80.0 ± 5.5 years) participated in the present investigation. Declarative memory was used as the measure of cognition. Physical function was measured using the Short Physical Performance Battery (SPPB), dual‐task fast walking time, and sit‐to‐stand velocity. Linear regression analysis was used to predict cognition from physical function. Odds ratios were used to determine the magnitude of influence of physical function on cognitive function. ANOVA was used to determine differences in individual physical function variable between low and high cognitive groups.ResultsThe linear regression model included dual‐task fast 10‐m walking time, sex, education, and SPPB score and accounted for 39% of the variance in cognitive ability (p<.001). The physical function variables accounted for 8.8% and 8.5% of unique variance in cognition, respectively. For participants performing below the 50th percentile for dual‐task fast walking time, there was a 3.6‐fold increase in declarative memory scores (CI: 1.44‐9.35). Similarly, SPPB values indicative of mobility dysfunction was associated with a 3.2‐times increase in cognitive impairment (CI: 1.31‐7.87). Results of the one‐way ANOVA revealed significant differences in SPPB (p = .002), peak sit‐to‐stand velocity (p = .007), and dual‐task fast walking time (p = .001). The high cognitive group had significantly better physical function compared to the lower cognitive group.ConclusionResults from the present investigation support the use of physical function in predicting current declarative memory among a sample of community‐dwelling adults with no diagnosed cognitive impairment. Future research is needed to determine the ability to predict changes in cognition longitudinally.

The hierarchical relations among mathematical competencies: From fundamental numeracy to complex mathematical skills.

Mathematical competencies can be conceptualized as layers of knowledge, with numeracy skills as the foundational core and more complex mathematical skills as the additional layers over the core. In this study, we tested an expanded hierarchical symbol integration (HSI) model by examining the hierarchical relations among mathematical skills. Undergraduate students (N = 236) completed order judgement, simple arithmetic, fraction arithmetic, algebra, and verbal working memory tasks. In a series of hierarchical multiple regressions, we found support for the hierarchical model: Additive skills (i.e., addition and subtraction) predicted unique variance in multiplicative skills (i.e., multiplication and division); multiplicative skills predicted unique variance in fraction arithmetic; and fraction skills predicted unique variance in algebra. These results support the framework of the HSI model in which mathematical competencies are related hierarchically, capturing the increasing complexity of symbolic mathematical skills. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Associations of APOE4 and Alzheimer’s disease biomarkers with cortical reinstatement and episodic memory in clinically unimpaired older adults

AbstractBackgroundCortical reinstatement is a key neural correlate of episodic remembering across the lifespan and explains significant variability in memory performance among older adults. We assessed whether Alzheimer’s disease (AD) risk factors – cerebrospinal fluid (CSF) Aβ42/Aβ40, CSF pTau181, plasma pTau181, and APOE genotype – impact cortical reinstatement in clinically unimpaired older adults.MethodParticipants were 150 clinically unimpaired older adults enrolled in the Stanford Aging and Memory Study (SAMS). APOE genotype was determined from whole‐genome sequencing and participants were classified as ε4 carriers (N = 38) or non‐carriers (N = 112). CSF Aβ42/Aβ40 and pTau181 and plasma pTau181 were quantified using the automated Lumipulse G system. Cortical reinstatement was quantified during successful retrieval of word‐picture associations using fMRI multivoxel pattern analysis (MVPA) in five regions of interest, including parahippocampal gyrus (PHG), ventral temporal cortex (VTC), middle temporal gyrus (MTG), angular gyrus (ANG), and posterior medial cortex (PMC). Regression analyses examined cross‐sectional relationships between regional cortical reinstatement and a) APOE genotype (N = 150), b) CSF Aβ42/Aβ40 and pTau181 (N = 113), and (c) plasma pTau181 (N = 140), as well as associations of these variables with associative memory discrimination (d’). All models included age, sex, and regional MVPA classifier accuracy during memory encoding.ResultAPOE ε4 genotype was negatively associated with reinstatement strength in VTC (β = ‐0.54, p < .005), MTG (β = ‐0.32, p < .05), and ANG (β = ‐0.32, p < .05) and CSF Aβ42/Aβ40 burden was linked to weaker reinstatement in ANG (β = 0.16, p < .05). In VTC, the effect of APOE ε4 on reinstatement remained significant after controlling for CSF Aβ42/Aβ40 (β = ‐0.47, p < .05); a similar pattern was observed in MTG and ANG. Although CSF pTau181 was unrelated to reinstatement strength, both pTau181 and cortical reinstatement explained unique variance in memory performance (pTau181: β = ‐0.26, p < .005, reinstVTC: β = 0.39, p < .001). Analogous findings were observed with plasma pTau181.ConclusionThese results suggest that APOE ε4 impacts cortical reinstatement, and that this effect may be independent of amyloid burden. These effects of APOE ε4 may be distinct from tau‐mediated effects on episodic memory in human aging.

Uncertainty analysis of intra-module environmental stress parameter design in light use efficiency-based gross primary productivity estimation models

Terrestrial gross primary productivity is a key part in the carbon cycle, and the light use efficiency model is a widely employed tool for its estimation. However, since the specific designs of environmental stress parameters in light use efficiency models have obvious disparities, even for a single module (e.g., the temperature stress module), the uncertainties related to intra-module environmental stress parameters in light use efficiency models remain unclear. Thus, we gathered mainstream temperature and water stress parameters in light use efficiency models from existing publications, and employed a compatible framework to assess them from three perspectives: (1) identifying similarities and differences of environmental stress parameters; (2) evaluating the error propagation effect of input data under different environmental stress parameter combinations; and (3) assessing the generalization ability of environmental stress parameters. The results showed that the temperature stress parameters exhibited general homogeneity (shared 67.87% variance), while water stress parameters displayed noticeable internal variations (shared variance below 1.0%). Meanwhile, we revealed that the current flexible parameter combination method in light use efficiency model construction should be more cautious, since the flexible environmental stress parameter combinations would influence the error propagation effect from input data to final gross primary productivity estimations. In addition, our analysis found that the variance of environmental stress parameters was closely coupled to model estimation accuracy, and there was a positive relationship between the unique variance of temperature stress parameters and the ability of temperature stress parameters to describe gross primary productivity variation. Overall, the current environmental stress parameters demonstrated acceptable performance across most situations, except for biomes with high temperatures. This study provided a foundation towards the development of future parameter design, which may also inspire the application of empirical environmental factors in other gross primary productivity models.

Dual-systems models of the genetic architecture of impulsive personality traits: neurogenetic evidence of distinct but related factors.

Dual-systems models, positing an interaction between two distinct and competing systems (i.e. top-down self-control, and bottom-up reward- or emotion-based drive), provide a parsimonious framework for investigating the interplay between cortical and subcortical brain regions relevant to impulsive personality traits (IPTs) and their associations with psychopathology. Despite recent developments in multivariate analysis of genome-wide association studies (GWAS), molecular genetic investigations of these models have not been conducted. Using IPT GWAS, we conducted confirmatory genomic structural equation models (GenomicSEM) to empirically evaluate dual-systems models of the genetic architecture of IPTs. Genetic correlations between dual-systems factors and relevant cortical and subcortical neuroimaging phenotypes (regional/structural volume, cortical surface area, cortical thickness) were estimated and compared. GenomicSEM dual-systems models underscored important sources of shared and unique genetic variance between top-down and bottom-up constructs. Specifically, a dual-systems genomic model consisting of sensation seeking and lack of self-control factors demonstrated distinct but related sources of genetic influences (rg = 0.60). Genetic correlation analyses provided evidence of differential associations between dual-systems factors and cortical neuroimaging phenotypes (e.g. lack of self-control negatively associated with cortical thickness, sensation seeking positively associated with cortical surface area). No significant associations were observed with subcortical phenotypes. Dual-systems models of the genetic architecture of IPTs tested were consistent with study hypotheses, but associations with relevant neuroimaging phenotypes were mixed (e.g. no associations with subcortical volumes). Findings demonstrate the utility of dual-systems models for studying IPT genetic influences, but also highlight potential limitations as a framework for interpreting IPTs as endophenotypes for psychopathology.

Does strict invariance matter? Valid group mean comparisons with ordered-categorical items

Measurement invariance (MI) of a psychometric scale is a prerequisite for valid group comparisons of the measured construct. While the invariance of loadings and intercepts (i.e., scalar invariance) supports comparisons of factor means and observed means with continuous items, a general belief is that the same holds with ordered-categorical (i.e., ordered-polytomous and dichotomous) items. However, as this paper shows, this belief is only partially true—factor mean comparison is permissible in the correctly specified scalar invariance model with ordered-polytomous items but not with dichotomous items. Furthermore, rather than scalar invariance, full strict invariance—invariance of loadings, thresholds, intercepts, and unique factor variances in all items—is needed when comparing observed means with both ordered-polytomous and dichotomous items. In a Monte Carlo simulation study, we found that unique factor noninvariance led to biased estimations and inferences (e.g., with inflated type I error rates of 19.52%) of (a) the observed mean difference for both ordered-polytomous and dichotomous items and (b) the factor mean difference for dichotomous items in the scalar invariance model. We provide a tutorial on invariance testing with ordered-categorical items as well as suggestions on mean comparisons when strict invariance is violated. In general, we recommend testing strict invariance prior to comparing observed means with ordered-categorical items and adjusting for partial invariance to compare factor means if strict invariance fails.

The personal and the social: Twin contributors to climate action

Identifying predictors of environmentally significant behaviors (ESBs) can inform interventions to mitigate and adapt to climate change. Most past research, and the theories that shape it, focus on factors residing within individuals rather than within their social context. This paper argues for greater emphasis on social variables, as complements to person-level variables, in predicting ESBs. A sample of 2868 Australian survey panel members completed an online questionnaire containing measures of five personal variables, five social variables, and four types of ESBs. All predictors were positively associated with all ESBs. Controlling for sociodemographic and person-level variables, the block of social predictors explained unique variance in all criteria, especially in a measure of pro-environmental behavior. The strongest predictors were personal norm and community involvement. The social variables also had indirect and moderating effects. Better understanding, and improved interventions, can come from closer analysis of the roles of social variables in shaping ESBs.

The Impact of Social-engagement, Social-support and Self-esteem on Life Satisfaction in UK Youth: A Sequential Explanatory Mixed Methods Study

Significant changes in adolescent physiology and psychology have been linked to a decline in adolescents sense of well-being. Thats why its so important to study what makes people happy in order to help teenagers flourish. The purpose of this research is to demonstrate the value of a correlational design and thematic analysis in revealing the underlying mechanisms at play in teenage social connection, self-esteem, and life satisfaction through the use of a mixed-methods sequential explanatory display. Our predictions that self-esteem (26%), social-support (1%) and social-engagement (1%) each accounted for a significant portion of the unique variance on the Satisfaction with Life Scale are supported by data from the Seventh-Sweep Study-Wave 7 Dataset (N=759). The quantitative results are corroborated by a thematic analysis of social-media and newspaper comments (N=126), which reveals that young people with high self-esteem are more likely to have positive school and social connections, use coping techniques, and express their true selves. Low self-esteem, on the other hand, may have detrimental effects on happiness, such as the promotion of psychological disorder and risky behaviours as well as underpinning academic and social isolation. Therefore, it may be beneficial for adolescents well-being to place an emphasis on school connectedness, social support, and positive self-perception.

Subjective cognitive complaints and objective cognitive functioning in combat veterans: Effects of PTSD and deployment mild TBI

Objectives (1) Examine the relationship between subjective cognitive complaints and objective cognitive functioning in combat veterans; and (2) evaluate conditional effects of posttraumatic stress disorder (PTSD) and deployment-related mild traumatic brain injury (TBI) within that relationship. Method Combat veterans (N = 225, 86.22% male) completed a lifetime TBI interview, a structured interview assessing PTSD symptoms, a neuropsychological assessment battery, and a self-report measure of cognitive symptoms. Results All correlations between subjective cognitive complaints and objective cognitive measures were not statistically significant. Hierarchical linear regression indicated that cognitive performance was not significantly related to cognitive complaints, but both PTSD diagnosis and history of deployment mild TBI explained a significant amount of unique variance in self-reported cognitive symptoms. Interactions between the studied variables were not significant. Conclusions PTSD and history of deployment mild TBI were uniquely related to cognitive complaints, but cognitive test performance was not. No confounding effects of PTSD or deployment mild TBI were observed in the relationship between cognitive performance and cognitive complaints. This provides support that symptom distress may be a better explanatory factor for perception of lower cognitive functioning than actual cognitive performance.

Wellbeing and distress in young people with chronic conditions: how do positive psychology variables relate to mental health outcomes?

ABSTRACT Objective The aim of this study was to determine the unique and shared contributions of various positive psychology constructs (gratitude, optimism, hope, self-compassion, self-efficacy, and emotion regulation) to wellbeing and distress outcomes in young people living with a diverse range of chronic health conditions. Methods and Measures 169 Australians (84.0% female, mean age = 21.2) who reported living with a chronic physical condition completed a cross-sectional survey assessing wellbeing, distress, and each positive psychology variable. Two multiple regressions were used to determine the unique and shared contributions of the positive psychology variables to wellbeing and distress outcomes. Results When considered alongside symptom severity, the variables explained 53.4% and 38.1% of variance in distress and wellbeing, respectively. Only optimism and self-efficacy accounted for unique and significant variance in the model predicting wellbeing, accounting for 6.1% and 4.6% of unique variance, respectively. For the distress model, optimism, self-compassion, and emotion regulation each accounted for significant variance. When considered alongside other variables, hope and gratitude did not contribute to either model. Conclusion Findings suggest that individual positive psychology variables differentially contribute to wellbeing and distress outcomes in young people with chronic conditions. Optimism appears to account for unique variance in both outcomes, suggesting it may be a parsimonious target to promote complete mental health in this population.

30 Exploring the Differential Importance of Modifiable Fitness Variables on Cognitive Performance in Older Adults

Objective:To identify the relative contributions and importance of modifiable fitness and demographic variables to cognitive performance in a cohort of healthy older adults.Participants and Methods:Metrics of modifiable fitness (gait speed, respiratory function, grip strength, and body mass index (BMI)) and cognition (executive function, episodic memory, and processing speed) were assessed in 619 older adults from the Health and Retirement Study 2016 wave (mean age = 74.9, sd = 6.9; mean education = 13.4 years, sd = 2.6; 42% female). General linear models were employed to assess the contribution of modifiable fitness variables in predicting three domains of cognition: executive function, episodic memory, and processing speed. Demographics (age, sex, education, time between appointments, and a chronic disease score) were entered as covariates for each model. Relative importance metrics were computed for all variables in each model using Lindeman, Merenda, and Gold (lmg) analysis, a technique which decomposes a given model’s explained variance to describe the average contribution of each predictor variable, independent of its position in the linear model.Results:When all variables were entered into the general linear model, demographic and modifiable fitness variables explained 35%, 24%, and 26% of the variance in executive function, episodic memory, and processing speed, respectively (all three models were significant, p <0.001). Age, education, respiratory function, and walking speed had higher relative importance values (all lmgs > 1.8) compared to BMI, grip strength, and other covariates in all three models (all lmgs < 1.3). Gender was also relatively important in the executive function (lmg = 4.2) and episodic memory models (lmg = 5.0). Of the modifiable fitness variables, walking speed and respiratory function had the greatest lmg values (5.8 and 6.4 respectively) in the executive function model, similar to demographic variables age (lmg = 6.0) and education (lmg = 8.9). When demographic variables were entered as covariates, modifiable fitness variables collectively accounted for an additional 9.7%, 6.3%, and 6.0% variance in the executive function, episodic memory, and processing speed models respectively (all three models were significant, p <0.001).Conclusions:Our findings indicate that walking speed and respiratory function are of similar importance compared to “traditional” demographic variables such as age and education in predicting cognitive performance in a cohort of healthy older adults. Moreover, modifiable fitness variables accounted for unique variance in executive function, episodic memory, and processing speed after accounting for age and education. Modifiable fitness variables explained the most unique variance in executive function. These results extend the current literature by demonstrating that modifiable fitness variables, even when assessed with brief and relatively coarse measures of physical performance, may be useful in predicting cognitive function. Moreover, the results highlight the need to assess metrics of cognitive reserve, such as education, as well as modifiable fitness variables and their respective roles in accounting for cognitive performance. The data further suggest that relative contributions of physical performance metrics may vary by cognitive domain in healthy older adults.