Latent Factor Scores Research Articles

Factorial invariance of the Wechsler Intelligence Scale for Children, Fifth Edition, across the UK, US and Australia & New Zealand.

This study examined the factorial invariance of the factor structure of the Wechsler Intelligence Scale for Children, Fifth Edition (WISC-V) across the UK, US and Australia & New Zealand (A&NZ). The factorial equivalence of cognitive assessments should be demonstrated before assuming cross-culture generalizability and interpretations of score comparisons. Data were obtained from the UK, US and A&NZ normative standardizations of the WISC-V. The samples consisted of 415 UK, 2200 US and 528 A&NZ children, aged 6-16. Confirmatory factor analysis was applied separately in each sample to establish the baseline model. Next, tests of factorial invariance were undertaken using the recommended hierarchical approach, firstly across the UK and A&NZ samples and then across the UK and US samples. The five-factor first-order scoring model was found to be excellent fit across all three samples independently. Strict factorial invariance of the WISC-V was demonstrated firstly across the UK and A&NZ and secondly the UK and US nationally representative standardization samples. Comparison of latent means found small but significant differences in female children across the UK and A&NZ samples. Consistent with previous research, these results demonstrate the generality of the WISC-V factor structure across the UK, US and A&NZ. Furthermore, as the WISC-V factor structure aligns with the Cattell-Horn-Carroll (CHC) model of cognitive abilities, the results add further support to the cross-cultural generalizability of the CHC model. Small but significant differences in latent factor scores found across samples support the development and use of local normative data.

Perceptions of Racial-Ethnic Inequities in COVID-19 Healthcare and Willingness to Receive the COVID-19 Vaccine.

Perceptions of the US healthcare system can impact individuals' healthcare utilization, including vaccination intentions. This study examined the association between perceived racial-ethnic inequities in COVID-19 healthcare and willingness to receive the COVID-19 vaccine. This study used data from REACH-US, a nationally representative online survey of a large, diverse sample of U.S. adults (N=5145 January 26, 2021-March 3, 2021). Confirmatory factor and regression analyses examined a latent factor of perceived racial-ethnic inequities in COVID-19 healthcare, whether the factor was associated with willingness to receive the COVID-19 vaccine, and whether associations varied across racial-ethnic groups reported as probit estimates (B) and 95% confidence intervals (CIs). Perceived racial-ethnic inequities in COVID-19 healthcare were highest among Black/African American adults (mean latent factor score: 0.65 ± 0.43) and lowest among White adults (mean latent factor score: 0.04 ± 0.67). Black/African American (B = -0.08; 95% CI = -0.19, 0.03) and Native Hawaiian/Pacific Islander (B = -0.08; 95% CI = -0.23, 0.07) adults who perceived greater racial-ethnic inequities in COVID-19 healthcare were less willing than participants who perceived lower inequities. In contrast, American Indian/Alaska Native (B = 0.15; 95% CI = -0.01, 0.30), Asian (B = 0.20; 95% CI = 0.08, 0.31), Hispanic/Latino (English language preference) (B = 0.22; 95% CI = 0.01, 0.43), Multiracial (B = 0.23; 95% CI = 0.09, 0.36), and White (B = 0.31; 95% CI = 0.19, 0.43) adults who perceived greater racial-ethnic inequities in COVID-19 healthcare were more willing to receive the COVID-19 vaccine than participants perceiving higher inequities. Greater perceived racial-ethnic inequities in COVID-19 healthcare were associated with less willingness to receive the COVID-19 vaccine among Black/African American and Native Hawaiian/Pacific Islander adults.

Genetic associations with dementia-related proteinopathy: Application of item response theory.

Although dementia-related proteinopathy has a strong negative impact on public health, and is highly heritable, understanding of the related genetic architecture is incomplete. We applied multidimensional generalized partial credit modeling (GPCM) to test genetic associations with dementia-related proteinopathies. Data were analyzed to identify candidate single nucleotide variants for the following proteinopathies: Aβ, tau, α-synuclein, and TDP-43. Final included data comprised 966 participants with neuropathologic and WGS data. Three continuous latent outcomes were constructed, corresponding to TDP-43-, Aβ/Tau-, and α-synuclein-related neuropathology endophenotype scores. This approach helped validate known genotype/phenotype associations: for example, TMEM106B and GRN were risk alleles for TDP-43 pathology; and GBA for α-synuclein/Lewy bodies. Novel suggestive proteinopathy-linked alleles were also discovered, including several (SDHAF1, TMEM68, and ARHGEF28) with colocalization analyses and/or high degrees of biologic credibility. A novel methodology using GPCM enabled insights into gene candidates for driving misfolded proteinopathies. Latent factor scores for proteinopathies were estimated using a generalized partial credit model. The three latent continuous scores corresponded well with proteinopathy severity. Novel genes associated with proteinopathies were identified. Several genes had high degrees of biologic credibility for dementia risk factors.

Unreliable Continuous Treatment Indicators in Propensity Score Analysis

Propensity score analyses (PSA) of continuous treatments often operationalize the treatment as a multi-indicator composite, and its composite reliability is unreported. Latent variables or factor scores accounting for this unreliability are seldom used as alternatives to composites. This study examines the effects of the unreliability of indicators of a latent treatment in PSA using the generalized propensity score (GPS). A Monte Carlo simulation study was conducted varying composite reliability, continuous treatment representation, variability of factor loadings, sample size, and number of treatment indicators to assess whether Average Treatment Effect (ATE) estimates differed in their relative bias, Root Mean Squared Error, and coverage rates. Results indicate that low composite reliability leads to underestimation of the ATE of latent continuous treatments, while the number of treatment indicators and variability of factor loadings show little effect on ATE estimates, after controlling for overall composite reliability. The results also show that, in correctly specified GPS models, the effects of low composite reliability can be somewhat ameliorated by using factor scores that were estimated including covariates. An illustrative example is provided using survey data to estimate the effect of teacher adoption of a workbook related to a virtual learning environment in the classroom.

Bayesian penalty methods for evaluating measurement invariance in moderated nonlinear factor analysis.

Measurement invariance (MI) is one of the main psychometric requirements for analyses that focus on potentially heterogeneous populations. MI allows researchers to compare latent factor scores across persons from different subgroups, whereas if a measure is not invariant across all items and persons then such comparisons may be misleading. If full MI does not hold further testing may identify problematic items showing differential item functioning (DIF). Most methods developed to test DIF focused on simple scenarios often with comparisons across two groups. In practical applications, this is an oversimplification if many grouping variables (e.g., gender, race) or continuous covariates (e.g., age) exist that might influence the measurement properties of items; these variables are often correlated, making traditional tests that consider each variable separately less useful. Here, we propose the application of Bayesian Moderated Nonlinear Factor Analysis to overcome limitations of traditional approaches to detect DIF. We investigate how modern Bayesian shrinkage priors can be used to identify DIF items in situations with many groups and continuous covariates. We compare the performance of lasso-type, spike-and-slab, and global-local shrinkage priors (e.g., horseshoe) to standard normal and small variance priors. Results indicate that spike-and-slab and lasso priors outperform the other priors. Horseshoe priors provide slightly lower power compared to lasso and spike-and-slab priors. Small variance priors result in very low power to detect DIF with sample sizes below 800, and normal priors may produce severely inflated type I error rates. We illustrate the approach with data from the PISA 2018 study. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Spatial water quality analysis of the watercourses in Northwestern New Territories (Hong Kong)

Abstract River water is an important source for drinking water supply in Northwestern New Territories of Hong Kong. Thus, there is no denying the fact that monitor the quality of river water is a must for the locals. In this study, a mixed multivariate analysis method was used to lower monitoring costs by optimizing the layout of water quality monitoring stations. To this purpose, the data from a period of five years and over 36,000 observations was evaluated in this article. The cluster analysis approach was also used to categorize monitoring stations into three groups. What's more, three latent factors that predominantly influence the river water quality were assessed using factor analysis: anthropogenic pollution, seawater intrusion and geological processes, and the nitrification process. A spatial pattern using the three latent factor scores was plotted and six redundant monitoring stations were identified by this pattern. Finally, discriminant analysis was used to extract seven significant parameters. The results showed that the surface water-monitoring program of the watercourses in the Northwestern New Territories (Hong Kong) could be adjusted by reducing the monitoring stations to 18 and the measured chemical parameters to seven to ensure the detection of water quality and reduce the cost.

The novel frontal alpha asymmetry factor and its association with depression, anxiety, and personality traits.

Frontal alpha asymmetry (FAA) is widely examined in EEG research, yet a procedural consensus on its assessment is lacking. In this study, we tested a latent factorial approach to measure FAA. We assessed resting-state FAA at broad, low, and high alpha bands (8-13; 8-10.5; and 11-13 Hz) using mastoids as reference electrodes and Current Source Density (CSD) transformation (N = 139 non-clinical participants). From mastoid-referenced data, we extracted a frontal alpha asymmetry factor (FAAf) and a parietal factor (PAAf) subjecting all asymmetry indices to a varimax-rotated, principal component analysis. We explored split-half reliability and discriminant validity of the mastoid factors and the mastoid and CSD raw asymmetry indices (F3/4, F7/8, P3/4, and P7/8). Both factor and raw scores reached an excellent split-half reliability (>.99), but only the FAAf reached the maximum discriminant validity from parietal scores. Next, we explored the correlations of latent factor and raw FAA scores with symptoms of depression, anxiety, and personality traits to determine which associations were driven by FAA after variance from parietal activity was removed. After correcting for false discovery rate, only FAAf at the low alpha band was negatively associated with depression symptoms (a latent CES-D factor) and significantly diverged from PAAf's association with depression symptoms. With respect to personality traits, only CSD-transformed F7/8 was positively correlated with Conscientiousness and significantly diverged from the correlations between Conscientiousness and P3/4 and P7/8. Overall, the latent factor approach shows promise for isolating functionally distinct resting-state EEG signatures, although further research is needed to examine construct validity.

Predicting conversion from mild cognitive impairment to Alzheimer’s disease with multimodal latent factors

ABSTRACT Introduction We studied the ability of latent factor scores to predict conversion from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) and investigated whether multimodal factor scores improve predictive power, relative to single-modal factor scores. Method We conducted exploratory factor analyses (EFAs) and confirmatory factor analyses (CFAs) of the baseline data of MCI subjects in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to generate factor scores for three data modalities: neuropsychological (NP), magnetic resonance imaging (MRI), and cerebrospinal fluid (CSF). Factor scores from single or multiple modalities were entered in logistic regression models to predict MCI to AD conversion for 160 ADNI subjects over a 2-year interval. Results NP factors attained an area under the curve (AUC) of .80, with a sensitivity of .66 and a specificity of .77. MRI factors reached a comparable level of performance (AUC = .80, sensitivity = .66, specificity = .78), whereas CSF factors produced weaker prediction (AUC = .70, sensitivity = .56, specificity = .79). Combining NP factors with MRI or CSF factors produced better prediction than either MRI or CSF factors alone. Similarly, adding MRI factors to NP or CSF factors produced improvements in prediction relative to NP or CSF factors alone. However, adding CSF factors to either NP or MRI factors produced no improvement in prediction. Conclusions Latent factor scores provided good accuracy for predicting MCI to AD conversion. Adding NP or MRI factors to factors from other modalities enhanced predictive power but adding CSF factors did not.

Information criteria for latent factor models: A study on factor pervasiveness and adaptivity

We study the information criteria extensively under general conditions for high-dimensional latent factor models. Upon carefully analyzing the estimation errors of the principal component analysis method, we establish theoretical results on the estimation accuracy of the latent factor scores, incorporating the impact from possibly weak factor pervasiveness; our analysis does not require the same factor strength of all the leading factors. To estimate the number of the latent factors, we propose a new penalty specification with a two-fold consideration: i) being adaptive to the strength of the factor pervasiveness, and ii) favoring more parsimonious models. Our theory establishes the validity of the proposed approach under general conditions. Additionally, we construct examples to demonstrate that when the factor strength is too weak, scenarios exist such that no information criterion can consistently identify the latent factors. We illustrate the performance of the proposed adaptive information criteria with extensive numerical examples, including simulations and a real data analysis.

The fear of COVID-19 scale: Its structure and measurement invariance across 48 countries.

Coronavirus disease (COVID-19) has been a source of fear around the world. We asked whether the measurement of this fear is trustworthy and comparable across countries. In particular, we explored the measurement invariance and cross-cultural replicability of the widely used Fear of COVID-19 scale (FCV-19S), testing community samples from 48 countries (N = 14,558). The findings indicate that the FCV-19S has a somewhat problematic structure, yet the one-factor solution is replicable across cultural contexts and could be used in studies that compare people who vary on gender and educational level. The validity of the scale is supported by a consistent pattern of positive correlations with perceived stress and general anxiety. However, given the unclear structure of the FCV-19S, we recommend using latent factor scores, instead of raw scores, especially in cross-cultural comparisons. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Social Emotional Learning Competencies in Belize Children: Psychometric Validation Through Exploratory Structural Equation Modeling.

In the nation of Belize, and in particular the south side of Belize City, the main metropolitan area of the nation, significant economic disparities have led to child and adolescent exposure to high rates of violent crime, gang activity, unsafe neighborhoods, sexual, and physical violence. Problems associated with poor Social-Emotional Character Development are especially prevalent among boys. Consequently, valid culture-relevant measures are required that identify problematic behavior for policy-based intervention and evaluation of educational programs designed to ameliorate this problem. The present study demonstrates the application of Exploratory Structural Equation Modeling to existing measures through the investigation of structural validity and generalizability of the Social-Emotional and Character Development Scale with a large sample of children from schools in Belize (N = 1,877, Ages 10–13). Exploratory structural equation modeling results demonstrate the original factor correlations were reduced, providing less biased estimates than confirmatory factor analysis (CFA). Moreover, a multi-group Exploratory Structural Equation Modeling analysis illuminates significant differences between latent factor scores of males and females for most factors. Using this newer factor analytic procedure, original factors are reconceptualized to better situate the Social Emotional Character Development Scales into the larger body of Social-Emotional Learning (SEL) competencies literature.

Measurement invariance testing of longitudinal neuropsychiatric test scores distinguishes pathological from normative cognitive decline and highlights its potential in early detection research.

Alzheimer's disease (AD) is a growing challenge worldwide, which is why the search for early-onset predictors must be focused as soon as possible. Longitudinal studies that investigate courses of neuropsychological and other variables screen for such predictors correlated to mild cognitive impairment (MCI). However, one often neglected issue in analyses of such studies is measurement invariance (MI), which is often assumed but not tested for. This study uses the absence of MI (non-MI) and latent factor scores instead of composite variables to assess properties of cognitive domains, compensation mechanisms, and their predictability to establish a method for a more comprehensive understanding of pathological cognitive decline. An exploratory factor analysis (EFA) and a set of increasingly restricted confirmatory factor analyses (CFAs) were conducted to find latent factors, compared them with the composite approach, and to test for longitudinal (partial-)MI in a neuropsychiatric test battery, consisting of 14 test variables. A total of 330 elderly (mean age: 73.78 ± 1.52 years at baseline) were analyzed two times (3 years apart). EFA revealed a four-factor model representing declarative memory, attention, working memory, and visual-spatial processing. Based on CFA, an accurate model was estimated across both measurement timepoints. Partial non-MI was found for parameters such as loadings, test- and latent factor intercepts as well as latent factor variances. The latent factor approach was preferable to the composite approach. The overall assessment of non-MI latent factors may pose a possible target for this field of research. Hence, the non-MI of variances indicated variables that are especially suited for the prediction of pathological cognitive decline, while non-MI of intercepts indicated general aging-related decline. As a result, the sole assessment of MI may help distinguish pathological from normative aging processes and additionally may reveal compensatory neuropsychological mechanisms.

Mapping MMPI-3 scales onto the hierarchical taxonomy of psychopathology.

A major goal in the development of the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF), and subsequently, the Minnesota Multiphasic Personality Inventory-3 (MMPI-3) was linking the instrument to contemporary models of psychopathology. The present study evaluated whether the higher order structure of MMPI-3 scales, and in particular, the 26 Specific Problems as well as RC6 and RC8 (markers of thought disorder) scales aligned with the Hierarchical Taxonomy of Psychopathology (HiTOP) model. For this purpose, a large diverse mental health sample (n = 1,537) and a male prison inmate sample (n = 452) were used to capture a diverse range of psychopathology. Confirmatory factor analyses generally supported the six HiTOP spectra in both samples, albeit with some important qualifications. Associations between latent factor scores and conceptually relevant external criterion measures further supported the validity of this model. Furthermore, Goldberg's sequential hierarchical factoring approach was used to evaluate the structure of MMPI-3 SP and RC6/RC8 at descending levels of the hierarchy. Again, most of the HiTOP spectra were replicated. The structures for the mental health and prison samples were generally similar with substantive differences being linked to their respective contexts. Overall, the results indicate that the hierarchical organization of the MMPI-3 scales is generally consistent with the extant psychopathology literature, which constitutes good support for overall construct validity of the scales. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Understanding Rural Women's Domestic Work Experiences (DWE) in Ibadan, Nigeria: Development of a Measurement Tool Using Confirmatory Factor Analysis.

Gender norms prescribe domestic labor as primarily a female’s responsibility in developing countries. Many domestic tasks depend on access to water, so the physical, emotional, and time demands of domestic labor may be exacerbated for women living in water-insecure environments. We developed a set of domestic work experience (DWE) measures tailored to work in rural areas in developing countries, assessed rural Nigerian women’s DWE, and examined relationships among the measures. Interviewer-administered survey data were collected between August and September from 256 women in four rural Nigerian communities. Latent factors of DWE were identified by analyzing survey items using confirmatory factor analysis. Pearson’s correlation was used to examine relationships among latent factor scores, and multivariate linear regression models were used to determine if factor scores significantly differed across socio-demographic characteristics. The DWE measures consisted of latent factors of the physical domain (frequency of common domestic tasks, water sourcing and carriage, experience of water scarcity), the psychosocial domain (stress appraisal and demand–control), and the social domain (social support). Significant correlations were observed among the latent factors within and across domains. Results revealed the importance of measuring rural Nigerian women’s DWE using multiple and contextual approaches rather than relying solely on one exposure measure. Multiple inter-related factors contributed to women’s DWE. Water insecurity exacerbated the physical and emotional demands of domestic labor DWE varied across age categories and pregnancy status among rural Nigerian women.

Effects of methylphenidate on cognitive functions in boys with attention deficit hyperactivity disorder: Does baseline performance matter?

Objective: Although attention deficit hyperactivity disorder (ADHD) is associated with cognitive deficits, there is considerable heterogeneity and only a minority of individuals with the disorder demonstrate a deficit in any cognitive domain. Recent studies indicate that the relationships between ADHD symptoms and cognition are complex with a dissociation between medication responses across these two domains. Method: We examined whether methylphenidate (MPH) differentially impacts on cognition in those with and without pretreatment cognitive deficits in a 4-week randomized controlled crossover of high (0.6 mg/kg/dose) and low (0.3 mg/kg/dose) dose MPH and placebo in 75 medication-naive boys with ADHD. Cognition was assessed using tasks from the Cambridge Neuropsychological Test Automated Battery (CANTAB). Confirmatory factor analysis (CFA) was used to form latent cognitive factors of executive functioning, visual memory, and reaction time, as well as a general cognition factor. Results: Compared to placebo, both high and low MPH doses significantly improved performance on pattern recognition (PR), spatial recognition (SR), and simple reaction time. The low, but not the high, dose improved performance on the Stockings of Cambridge (SOC) and delayed matching-to-sample tasks. Both doses also significantly improved performance on the executive functioning, visual memory, reaction time skills, and general cognitive latent variables. There were however no differences in the effects of MPH on cognition between those with and without a baseline cognitive deficit, for either the observed task values or the latent cognitive factor scores. Conclusions: We conclude that MPH can enhance executive functioning, visual memory, reaction time, and general cognitive function in boys with ADHD. These improvements are not dependent on baseline cognitive performance. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Associations between Family Maltreatment Perpetration and Latent Profiles of Personal and Family Strengths among Active-Duty Air Force Members

Although individual and family strengths have been found to impact family maltreatment risk, optimal approaches to their assessment are lacking. To substantiate the utility of holistically assessing multiple strengths among active-duty Air Force members (i.e., Airmen) who might be at risk of perpetrating family maltreatment, the current study aimed to identify latent patterns of personal and family strengths among Airmen and assess associations with family maltreatment perpetration. A representative a sample of 30,187 Airmen from the 2011 Air Force Community Assessment Survey was used to identify patterns across latent-factor scores representing unit leader support, informal support, family functioning, individual fitness, and personal resilience. Latent profile analysis was conducted to extract an optimal number of response patterns and estimate associations with family maltreatment perpetration. A five-profile solution was optimal, representing patterns marked by low (10%), below average (26%), mixed (16%), above average (36%), and high (12%) levels of personal and family strengths. Predicted probabilities of family maltreatment among families not identifying as stepfamilies were 39%, 21%, 14%, 10%, and 8% across low, below average, mixed, above average, and high patterns, respectively. Among stepfamilies (20% of sample), predicted probabilities were 49%, 29%, 21%, 15%, and 12%, respectively. Findings encourage a holistic assessment of personal and family strengths among Airmen. The Personal and Family Strengths Inventory, which was developed to gauge these strengths, can position practitioners well to engage Airmen in conversations around strengths and growth opportunities for the purposes of service planning aimed at preventing family maltreatment.

The Symbol Digit Modalities Test (SDMT) is sensitive but non-specific in MS: Lexical access speed, memory, and information processing speed independently contribute to SDMT performance

BackgroundThe Symbol Digit Modalities Test (SDMT) is the most sensitive metric of neurocognitive function in multiple sclerosis (MS), and is consistently interpreted as a measure of information processing speed (IPS). ObjectiveTo evaluate the cognitive psychometric profile captured by the SDMT to identify whether different cognitive processes independently underlie performance. MethodsThree samples of MS patients (total n=661; 185 research patients at MS center; 370 clinical patients at MS center; 106 persons with MS from the community) completed objective assessments of neuropsychological function across cognitive domains. Exploratory factor analysis (EFA) was used to derive latent cognitive factor scores, and operationalize cognitive domain composite scores, to understand the unique, shared and redundant contribution of different cognitive domains to SDMT performance using hierarchical multiple regression and commonality analysis. ResultsAcross three independent samples we provide converging strong evidence that the cognitive domains of Memory, IPS and Rapid Automatized Naming (lexical access speed) jointly and uniquely contribute to SDMT performance. ConclusionThe SDMT measures multiple cognitive processes, which likely explains the high degree of sensitivity to cognitive change in MS. Researchers and clinicians should interpret the SDMT as a multifarious measure of general cognition rather than a specific test of IPS.

Confirmatory factor analysis and measurement invariance of the English, Mandarin, and Malay versions of the SF-12v2 within a representative sample of the multi-ethnic Singapore population

BackgroundThe Short Form Health Survey (SF-12v2) is an increasingly popular measure of health-related quality of life (HRQoL) in Singapore. In order to examine whether the SF-12v2 was appropriate for use in the population, the factor structure and validity of the English, Mandarin, and Malay versions were assessed in a representative sample of the general population of Singapore.Methods6126 respondents were recruited for the Singapore Mental Health Study 2016 (SMHS 2016), a cross-sectional and population-based survey. Confirmatory factor analyses (CFA) were conducted to examine the fit of a two-factor model for the SF-12v2 within a representative sample and amongst the different language (English, Mandarin, Malay) subgroups. Multiple-group CFAs (MGCFA) were conducted to test measurement invariance across the different languages, ethnicities, and chronic illnesses subgroups. CFA-generated latent factor scores (FSCORE command in MPlus) were also compared with the composite scores derived from the developer’s scoring method via correlations. Sociodemographic correlates of the latent physical and mental health scores were explored.ResultsCFA results within the full sample supported a two-factor model (RMSEA = 0.044; CFI = 0.991; TLI = 0.988; SRMR = 0.044) in which physical functioning, role physical, bodily pain and general health items loaded onto a latent physical health factor, while role emotional, mental health, social functioning, and vitality items loaded onto a latent mental health factor. Physical and mental health factors were allowed to correlate, unlike the developer’s orthogonal scoring method. All standardized loadings were high and statistically significant. Both factors had high internal consistency. CFA within subsamples of English, Mandarin, and Malay languages indicated similar findings. MGCFA results indicate that measurement invariance held across the different languages, ethnicities, and those with and without chronic illnesses. ConclusionThe present study identified a two-factor (physical and mental health) structure within the general population and amongst the three different languages and demonstrated the measurement invariance of SF-12v2 across different subgroups. Findings indicate that algorithm-derived PCS and MCS should be interpreted with caution as they may result in inaccurate conclusions regarding the relationships between HRQoL and its correlates. Future studies using the SF-12v2 within the general population of Singapore should consider utilizing the factor structure put forth in the present study to obtain more appropriate estimates of HRQoL.

Factor structure and psychometric properties of the Persian versions of the Pediatric Daytime Sleepiness Scale and Morningness-Eveningness Scale for Children.

BACKGROUND:The Pediatric Daytime Sleepiness Scale (PDSS) and the Morningness–Eveningness Scale for Children (MESC) are widely used to measure two important facets of sleep patterns, but neither have been adapted and validated for use in Iran. The purpose of this study was to examine the psychometric properties and factor structure of the Persian versions of the PDSS and the MESC in a sample of Iranian adolescents.MATERIALS AND METHODS:The Persian versions of PDSS and MESC were translated and administered to a representative sample (n = 407) of Iranian early adolescents, aged 9–15 years, who attended school in morning shifts. The factor structure of both scales, found in prior studies, was tested using Confirmatory Factor Analyses to assess their validity and reliability.RESULTS:The results revealed that the model fit indices of the one factor solution of the PDSS and the two factor solution of the MESC were acceptable to good. A high Pearson correlation was found between raw and latent factor scores for the PDSS and the two factors derived from the MESC (i.e., Morningness and Planning). Furthermore, the higher the PDSS score (more daytime sleepiness), the lower the MESC scores (more eveningness), indicating criterion validity of the scales showing the expected increase in daytime sleepiness in evening oriented adolescents who wake up early for attending school.CONCLUSION:The Persian versions of the PDSS and the MESC can be considered reliable and valid tools for evaluating, respectively, daytime sleepiness and morningness-eveningness in the adolescent population of Iran.

Foster children's complex psychopathology in the context of cumulative childhood trauma: The interplay of ICD-11 complex PTSD, dissociation, depression, and emotion regulation

BackgroundFoster children experience maltreatment at exceptionally high rates with increased risk to develop ICD-11 complex posttraumatic stress disorder (CPTSD). While rates of comorbidity between CPTSD and various disorders are high, the interplay between constituent aspects of psychopathology is not clearly understood. No study used network analysis to model the interplay between these aspects as potentially maintaining a stable condition of psychopathology, and research on the etiology and maintenance of CPTSD in children is especially scarce. MethodsAltogether, 208 Austrian foster children completed a set of standardized measures, resulting in a final sample of N = 122 foster children meeting the inclusion criteria. Experiences of childhood trauma, ICD-11 CPTSD, depression, dissociation, adaptive, and maladaptive emotion regulation were assessed. Following an exploratory approach, analyses were conducted using latent single indicator factor scores in two network models. ResultsDomains of CPTSD, PTSD and disturbances in self-organization (DSO), evidenced as most central factors in children's complex psychopathology. Including cumulative childhood trauma did not influence the connectedness of factors in any relevant way. Shortest direct paths from cumulative childhood trauma to CPTSD included dissociation (PTSD) and adaptive emotion regulation (DSO) as mediating factors. LimitationsResults are based on a small sample of highly-traumatized foster children, potentially limiting current findings’ generalizability. ConclusionsCPTSD identified as central in children's complex psychopathology, while the role of childhood trauma seems stronger for the onset than the maintenance of such psychopathology. The current network revealed central disorders and distinct mediating factors as important targets for treatment strategies and future research.