betAS: intuitive analysis and visualization of differential alternative splicing using beta distributions.

Next-generation RNA sequencing allows alternative splicing (AS) quantification with unprecedented resolution, with the relative inclusion of an alternative sequence in transcripts being commonly quantified by the proportion of reads supporting it as percent spliced-in (PSI). However, PSI values do not incorporate information about precision, proportional to the respective AS events' read coverage. Beta distributions are suitable to quantify inclusion levels of alternative sequences, using reads supporting their inclusion and exclusion as surrogates for the two distribution shape parameters. Each such beta distribution has the PSI as its mean value and is narrower when the read coverage is higher, facilitating the interpretability of its precision when plotted. We herein introduce a computational pipeline, based on beta distributions accurately modeling PSI values and their precision, to quantitatively and visually compare AS between groups of samples. Our methodology includes a differential splicing significance metric that compromises the magnitude of intergroup differences, the estimation uncertainty in individual samples, and the intragroup variability, being therefore suitable for multiple-group comparisons. To make our approach accessible and clear to both noncomputational and computational biologists, we developed betAS, an interactive web app and user-friendly R package for visual and intuitive differential splicing analysis from read count data.

A Bayesian hierarchical sparse factor model for estimating simultaneous covariance matrices for gestational outcomes in consecutive pregnancies.

Covariance estimation for multiple groups is a key feature for drawing inference from a heterogeneous population. One should seek to share information about common features in the dependence structures across the various groups. In this paper, we introduce a novel approach for estimating the covariance matrices for multiple groups using a hierarchical latent factor model that shrinks the factor loadings across groups toward a global value. Using a sparse spike and slab model on these loading coefficients allows for a sparse formulation of our model. Parameter estimation is accomplished through a Markov chain Monte Carlo scheme, and a model selection approach is used to select the number of factors to use. We validate our model through extensive simulation studies. Finally, we apply our methodology to the NICHD Consecutive Pregnancies Study to estimate the correlations between birth weights and gestational ages of three consecutive birth within four different subgroups (underweight, normal, overweight, and obese) of women.

Social group connections support mental health following wildfire.

PURPOSE: As environmental disasters become more common and severe due to climate change, there is a growing need for strategies to bolster recovery that are proactive, cost-effective, and which mobilise community resources. AIMS: We propose that building social group connections is a particularly promising strategy for supporting mental health in communities affected by environmental disasters. METHODS: We tested the social identity model of identity change in a disaster context among 627 people substantially affected by the 2019-2020 Australian fires. RESULTS: We found high levels of post-traumatic stress, strongly related to severity of disaster exposure, but also evidence of psychological resilience. Distress and resilience were weakly positively correlated. Having stronger social group connections pre-disaster was associated with less distress and more resilience 12-18 months after the disaster, via three pathways: greater social identification with the disaster-affected community, greater continuity of social group ties, and greater formation of new social group ties. New group ties were a mixed blessing, positively predicting both resilience and distress. CONCLUSIONS: We conclude that investment in social resources is key to supporting mental health outcomes, not just reactively in the aftermath of disasters, but also proactively in communities most at risk.

A baseline comparison of three diagnostic groups using the Progress Monitoring Tool for Eating Disorders.

Utilisation of intensive inpatient treatment for eating disorders (EDs) has climbed in the last decade, illuminating a need for better consensus on what constitutes effective treatment and context-appropriate progress/outcome monitoring during residential stays. The novel Progress Monitoring Tool for Eating Disorders (PMED) measure is specifically designed for inpatient settings. Previous research supports the factorial validity and internal consistency of the PMED; however, additional work is needed to determine its appropriateness for complex patient populations. This study used measurement invariance (MI) testing to determine if the PMED administered at programme admission measures the same items in similar ways across patients with anorexia nervosa restricting- and binge-purge subtypes (AN-R; AN-BP) and bulimia nervosa (BN, N = 1121; Mage  = 24.33 years, SD = 10.20; 100% female). Progressively constrained models were used to determine the level of invariance upheld between the three groups. Results indicated that, while the PMED meets configural and metric MI, it does not display scalar invariance. Said otherwise, the PMED similarly assesses constructs and items across AN-R, AN-BP, and BN, however the same score overall may reflect different levels of psychopathology for patients in one diagnostic category versus another. Comparisons of severity between different EDs should be made with caution, however the PMED appears to be a sound tool for understanding the baseline functioning of patients with EDs in an inpatient setting.

Measurement invariance in the social sciences: Historical development, methodological challenges, state of the art, and future perspectives.

This review summarizes the current state of the art of statistical and (survey) methodological research on measurement (non)invariance, which is considered a core challenge for the comparative social sciences. After outlining the historical roots, conceptual details, and standard procedures for measurement invariance testing, the paper focuses in particular on the statistical developments that have been achieved in the last 10 years. These include Bayesian approximate measurement invariance, the alignment method, measurement invariance testing within the multilevel modeling framework, mixture multigroup factor analysis, the measurement invariance explorer, and the response shift-true change decomposition approach. Furthermore, the contribution of survey methodological research to the construction of invariant measurement instruments is explicitly addressed and highlighted, including the issues of design decisions, pretesting, scale adoption, and translation. The paper ends with an outlook on future research perspectives.

Life Change, Social Identity, and Health.

Life change affects health. Research aimed at understanding the consequences of life change has primarily focused on the important roles played by stress, social support, individual differences, and broader socioeconomic factors in shaping health outcomes, most notably mental health decline. In this review we extend these accounts by exploring social identity-based determinants of adjustment to life change. We do so by drawing on social identity theorizing and, in particular, the Social Identity Model of Identity Change (SIMIC). This points to the importance of multiple, maintained, new, and compatible group memberships as determinants of people's responses and adjustment to life change. We apply this model to understand the health consequences of adjustment to life change in four diverse areas: pursuit of higher education, migration, trauma and resilience, and recovery from illness and injury. Finally, we provide direction for future research on SIMIC and the health consequences of life change.

Unpacking Racial/Ethnic Differences in the Associations between Neighborhood Disadvantage and Academic Achievement: Mediation of Future Orientation and Moderation of Parental Support.

Despite the extensive literature on the deleterious effects of perceived neighborhood disadvantage on academic achievement, there is a dearth of information on racial/ethnic differences in the underlying roles of future orientation and parental support that may mediate or moderate this association. Using data from 3618 students in grades 6-9 (50% female, Meanage = 12.9 [1.3], 6.99% Black, 10.39% Hispanic/Latino, 82.61% White) in two communities in North Carolina during 2009-2014 who completed the School Success Profile, a self-report social environmental assessment, this study conducted multiple group analyses across three racial/ethnic groups (Black, Hispanic/Latino, White), revealing that perceived neighborhood disadvantage was associated with lower future orientation, which in turn was related to poorer academic achievement. The mediating effects were stronger among Black youth compared to White and Hispanic/Latino adolescents. Adolescents with high parental support were minimally affected by perceived neighborhood disadvantage. The findings identify nuanced racial/ethnic disparities in perceived neighborhood influences on academic achievement and raise important intervention targets to promote academic achievement among disadvantaged subgroups.

Decomposition of Mean Sex Differences in Alcohol Use Within a Genetic Factor Model.

A wealth of literature suggests that normative and heavy alcohol consumption continue to follow a historical pattern of greater prevalence among males as compared to females. Some prior research suggested that sex-specific factors might explain some of this gender gap. Generally speaking, though, more recent studies have indicated that the sources of differences for most complex traits, both genetic and environmental, are similar for males and females. To the best of our knowledge, however, no studies have tested whether genetic and environmental factors common to both sexes are more often expressed in males, on average, thereby accounting for some of the mean sex difference in alcohol use. The current study used nationally representative data from American twin respondents and a multiple group genetic factor model with a mean structure to address this gap in the literature. Results provide no evidence of sex differences in covariance structure and suggest that genetic and nonshared environmental influences common to both sexes largely explain why male alcohol use is more frequent and severe, on average, than is female use. In contrast, shared environmental influences seem to play a less important role. We discuss our findings in the context of the existing literature and chart out directions for future research.

Age group differences in association between IADL decline and depressive symptoms in community-dwelling elderly.

BACKGROUND: Instrumental Activities of Daily Living (IADL) is an indicator of whether a community-dwelling elderly can live independently. IADL decline was reported to be associated with aging and depression. The present study aimed to investigate whether the association between IADL decline and depressive symptoms differs with aging, using two age groups of community-dwelling Japanese elderly in their 70s and 80s. METHODS: We conducted longitudinal analysis among participants in their 70s and 80s at the baseline from Septuagenarians, Octogenarians, Nonagenarians Investigation with Centenarians (SONIC) study. IADL was assessed by The Tokyo Metropolitan Institute of Gerontology (TMIG) index of competence. As a main predictor, depressive symptoms were measured by the five-item version of the Geriatrics Depression Scale (GDS-5). As possible confounders, we considered cognitive function, body mass index, solitary living, education, economic status, medical history of stroke and heart disease, hypertension, dyslipidemia, diabetes, and sex. We obtained odds ratios (ORs) of IADL decline for having depressive symptoms in each age group (70s/80s) and tested interactions between depressive symptoms and age groups in relation to IADL decline in 3 years by logistic regression. Additionally, to confirm age group differences, we conducted multiple group analysis. RESULTS: There were 559 participants in their 70s and 519 in their 80s. Compared to participants without depressive symptoms, those with depressive symptoms had higher OR of IADL decline in 70s (OR [95% CI] = 2.33 [1.13, 4.78]), but not in 80s (OR [95% CI] = 0.85 [0.46, 1.53]). There were significant interactions between depressive symptoms and age groups in relation to IADL decline (p-value = 0.03). Multiple group analyses showed differences between the age groups by Akaike information criterion (AIC), and ORs (95%CI) decline for depressive symptoms was 2.33 (1.14, 4.77) in 70s and 0.85 (0.47, 1.54) in 80s. CONCLUSION: The association of depressive symptoms and IADL decline during the 3 years was significantly different between the 70s and 80s age groups, and significant association was found only in people in their 70s. Detecting depressive symptoms may be a key for preventing IADL decline in people in their 70s and not for those in their 80s.

Investigating ethnic variations in reporting of psychotic symptoms: a multiple-group confirmatory factor analysis of the Psychosis Screening Questionnaire.

BACKGROUND: Epidemiological evidence suggests risk for psychosis varies with ethnicity in Western countries. However, there is little evidence to date on the cross-cultural validity of screening instruments used for such comparisons. METHODS: Combining two existing UK population-based cohorts, we examined risk for reporting psychotic symptoms across White British (n = 3467), White Irish (n = 851), Caribbean (n = 1899), Indian (n = 2590), Pakistani (n = 1956) and Bangladeshi groups (n = 1248). We assessed the psychometric properties of the Psychosis Screening Questionnaire (PSQ) with a multiple-group confirmatory factor analysis, assessing the equivalence of factor loadings, response thresholds and residual variances in an analysis of measurement non-invariance. RESULTS: Compared with prevalence among British Whites (5.4%), the prevalence of self-reported psychotic symptoms was greater in the Caribbean group (12.7%, adjusted OR = 2.38 [95% CI 1.84-3.07]). Prevalence was also increased among Pakistani individuals (8.3%, adjusted OR = 1.36 [1.01-1.84]) although this difference was driven by a greater likelihood of reporting paranoid symptoms. PSQ items for thought interference, strange experience and hallucination were measured in equivalent ways across ethnic groups. However, our measurement models suggested that paranoid symptoms were measured less reliably among ethnic minorities than among British Whites and appeared to exaggerate latent differences between Pakistani and White British groups when measurement non-invariance was not accounted for. CONCLUSIONS: Notwithstanding evidence for measurement non-invariance, the greater risk for reporting psychotic symptoms among Caribbean individuals is unlikely to be an artefact of measurement. Greater residual variance in the recording of paranoid symptoms among ethnic minority respondents warrants caution in using this item to investigate ethnic variation in psychosis risk.

Multisample adjusted U-statistics that account for confounding covariates.

Multisample U-statistics encompass a wide class of test statistics that allow the comparison of 2 or more distributions. U-statistics are especially powerful because they can be applied to both numeric and nonnumeric data, eg, ordinal and categorical data where a pairwise similarity or distance-like measure between categories is available. However, when comparing the distribution of a variable across 2 or more groups, observed differences may be due to confounding covariates. For example, in a case-control study, the distribution of exposure in cases may differ from that in controls entirely because of variables that are related to both exposure and case status and are distributed differently among case and control participants. We propose to use individually reweighted data (ie, using the stratification score for retrospective data or the propensity score for prospective data) to construct adjusted U-statistics that can test the equality of distributions across 2 (or more) groups in the presence of confounding covariates. Asymptotic normality of our adjusted U-statistics is established and a closed form expression of their asymptotic variance is presented. The utility of our approach is demonstrated through simulation studies, as well as in an analysis of data from a case-control study conducted among African-Americans, comparing whether the similarity in haplotypes (ie, sets of adjacent genetic loci inherited from the same parent) occurring in a case and a control participant differs from the similarity in haplotypes occurring in 2 control participants.

A multiple-group measurement scale for interprofessional collaboration: Adaptation and validation into Italian and German languages.

This article presents a study that aimed to validate a translation of a multiple-group measurement scale for interprofessional collaboration (IPC). We used survey data gathered over a three month period as part of a mixed methods study that explored the nature of IPC in Northern Italy. Following a translation from English into Italian and German the survey was distributed online to over 5,000 health professionals (dieticians, nurses, occupational therapists, physicians, physiotherapists, speech therapists and psychologists) based in one regional health trust. In total, 2,238 different health professions completed the survey. Based on the original scale, three principal components were extracted and confirmed as relevant factors for IPC (communication, accommodation and isolation). A confirmatory analysis (3-factor model) was applied to the data of physicians and nurses by language group. In conclusion, the validation of the German and Italian IPC scale has provided an instrument of acceptable reliability and validity for the assessment of IPC involving physicians and nurses.

An analysis of the effects of intrapartum factors, neonatal characteristics, and skin-to-skin contact on early breastfeeding initiation.

This study aims to determine relationships between intrapartum factors, neonatal characteristics, skin-to-skin contact (SSC), and early breastfeeding initiation after spontaneous vaginal and Caesarean section or operative vaginal birth. A total of 915 mother-newborn dyads were considered in a hypothetical model based on integrated concepts of breastfeeding initiation model, infant learning framework, and attachment theory. Multiple-group path analysis was used to determine whether differences exist between effects of immediate SSC (≤30 min) on early breastfeeding initiation in different modes of birth. SSC, mode of birth, labour duration, and neonatal intensive care unit admission were significantly associated with early breastfeeding initiation, as indicated by the path analysis model, which included all samples. Women with immediate SSC were more likely to initiate early breastfeeding in different modes of birth. In the spontaneous vaginal birth group, women showed a lower likelihood of initiating early breastfeeding when their neonates were admitted to the neonatal intensive care unit and presented an Apgar score of <7 at 1 min. Multiple-group analysis showed no significant difference between effects of immediate SSC on early breastfeeding initiation in different modes of birth (critical ratio = -0.309). Results showed that models satisfactorily fitted the data (minimum discrepancy divided by degrees of freedom = 1.466-1.943, goodness of fit index = 0.981-0.986, comparative fit index = 0.947-0.955, and root mean square error of approximation = 0.023-0.032). Our findings emphasize the crucial importance of prioritizing promotion of immediate SSC under different modes of birth.

[Measurement invariance of sub-health questionnaire in doctor and nurse].

OBJECTIVE: To examine the measurement invariance of sub-health questionnaire in doctor and nurse, and compare their sub-health status. METHODS: Totally 1832 doctors and nurses were selected by multi-stage stratified cluster random sampling method and investigated with a sub-health questionnaire. Measurement invariance between two groups was tested by multiple group confirmatory factor analysis. RESULTS: The test of measurement invariance for the one-factor model showed that the subhealth questionnaire met the criteria for measurement invariance( ΔCFI < 0. 01). The level of strict invariance( equal factor loadings, intercepts, and residual variances between groups) was achieved. When the latent means were compared, differences between groups were not statistically significant( the latent means of the dimensions were0. 029, 0. 050, 0. 054 and 0. 010, respectively, and the P value were 0. 385, 0. 168, 0. 092 and 0. 753, respectively). CONCLUSION: The sub-health questionnaire has the universal applicability to the medical staff.

Exploring Factor Model Parameters across Continuous Variables with Local Structural Equation Models.

Using an empirical data set, we investigated variation in factor model parameters across a continuous moderator variable and demonstrated three modeling approaches: multiple-group mean and covariance structure (MGMCS) analyses, local structural equation modeling (LSEM), and moderated factor analysis (MFA). We focused on how to study variation in factor model parameters as a function of continuous variables such as age, socioeconomic status, ability levels, acculturation, and so forth. Specifically, we formalized the LSEM approach in detail as compared with previous work and investigated its statistical properties with an analytical derivation and a simulation study. We also provide code for the easy implementation of LSEM. The illustration of methods was based on cross-sectional cognitive ability data from individuals ranging in age from 4 to 23 years. Variations in factor loadings across age were examined with regard to the age differentiation hypothesis. LSEM and MFA converged with respect to the conclusions. When there was a broad age range within groups and varying relations between the indicator variables and the common factor across age, MGMCS produced distorted parameter estimates. We discuss the pros of LSEM compared with MFA and recommend using the two tools as complementary approaches for investigating moderation in factor model parameters.

Socioeconomic and gender group differences in early literacy skills: a multiple-group confirmatory factor analysis approach.

Socioeconomic status and gender are important demographic variables that strongly relate to academic achievement. This study examined the early literacy skills differences between 4 sociodemographic groups, namely, boys ineligible for free or reduced-price lunch (FRL), girls ineligible for FRL, boys eligible for FRL, and girls eligible for FRL. Data on kindergarteners (N = 462) were analysed using multiple-group confirmatory factory analysis. Early literacy skill differences between boys and girls are more nuanced than previously reported; subsidy status and gender interact. Both boys and girls from high-poverty households performed significantly lower than the girls from low-poverty households in alphabet knowledge, phonological awareness, and spelling. There were gender gaps, with a female advantage, among children from high-poverty households in alphabet knowledge and spelling and among children from low-poverty households in alphabet knowledge. These results highlight the importance of employing methodologically sound techniques to ascertain group differences in componential early literacy skills.

Psychometric Evaluation of the Brief Acculturation Scale for Hispanics.

This study examined the psychometric properties of the Brief Acculturation Scale for Hispanics (BASH), a four-item, language-based measure of acculturation. Participants in the study were 435 Hispanic Americans from a large metropolitan area with English or Spanish language preference. Internal consistency reliability was strong in both language-preference groups. Multiple-group confirmatory factor analysis was used to evaluate the structural validity of the measure. A unidimensional factor structure was found for both English and Spanish language-preference groups and items loaded equivalently across groups, demonstrating measurement invariance. The BASH had good convergent validity and incremental validity. Overall, this study provides further evidence that the BASH offers a brief, reliable, and valid measure of acculturation to be used among Hispanic Americans.

Factorial invariance of college students' scores on the Lifestyle Practices and Health Consciousness Inventory.

OBJECTIVE: The aims of the present study were to validate college students' scores on the Lifestyle Practices and Health Consciousness Inventory (LPHCI), a screening tool for appraising Global Wellness (combined mental and physical health) and test for differences in Global Wellness across key demographic variables associated with college student health. METHOD: A non-probability sample of 708 college students across four campus locations in three different cities was recruited to test the LPHCI's psychometric properties. RESULTS: Factorial invariance testing demonstrated psychometric equivalence in the meaning of Global Wellness between college students across ethnicity, generational status, and help-seeking history. We also found statistically, however, not practically significant demographic differences in Global Wellness between college students by ethnicity and help-seeking history. CONCLUSION: Findings extend the generalizability of LPHCI scores to a normative sample of college students. Implications for college healthcare providers and directions for future research are discussed.

Assessing anxiety symptom severity in Rwandese adolescents: cross-gender measurement invariance of GAD-7.

Background: Anxiety disorders are among the most common mental health problems experienced by adolescents worldwide because of their evident significant impact on their quality of life and functioning. The generalized anxiety disorder item (GAD-7) was manufactured to identify the severity of self-reported anxiety symptoms. Efforts to address and screen for mental health problems in Rwanda have been limited, and the importance of screening for anxiety disorders is high. The primary aim of this study was to analyze the psychometric properties of the Kinyarwanda version of the Generalized Anxiety Disorder GAD-7, and then test the measurement invariance of the GAD-7 by gender. Methods: We used the Rwandese version of GAD-7 among secondary school students in Kigali city (n=1813). Measurement invariance of the GAD-7 across gender and report on anxiety symptom severity prevalence. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to examine measurement invariance. Results: Our findings demonstrated that in the sample of 1813 adolescents aged between 12 and 17 years, generalized anxiety symptoms prevalence rates were higher in females (46.4%) than males (n= 29.8%) GAD-7 demonstrated good reliability and validity coefficients with a Cronbach's α of .077 and KMO and Bartlett test of Sphericity = 0.835. In addition to these psychometric properties, the GAD-7 screening scale had equivalence for configural and metric invariance across groups with excellent fit indices, and we confirmed partial scalar invariance across groups. Conclusion: The GAD-7 can be used in cross-group comparison of generalized anxiety disorder prevalence, and we acknowledge that full scalar invariance is generally difficult to confirm, especially due to gender differences. We recommend that future studies further investigate populations living in rural areas and conduct trials that will focus on anxiety-specific treatment in Rwandan Clinical health care centers to determine the diagnostic accuracy of this screening tool.

Exploring the group heterogeneity in the impact of social cohesion on the walking frequency of older adults in China.

Background: Walkable neighborhoods are closely related to an increase in walking frequency and the strengthening of social cohesion. These factors, in turn, contribute to lower BMI and other positive health-related outcomes. However, with a rapid increase in aging populations in China and the fact that women are facing more challenges than men as they age, especially mobility challenges because they tend to live longer leading to probabilities to become widowed. Nevertheless, less attention has been paid to understanding the gender difference between these relationships. Methods: Based on a survey of 533 older adults in Dalian, China, this study tried to investigate the intertwined relationship between perceived walkability, social cohesion, walking frequency, and BMI. A Structural Equation Model (SEM) and multiple-group analysis were applied to test the proposed framework. Results: First, results show that gender differences existed among the above interrelationships, and the most substantial gender gap was found in effects of social cohesion on BMI. Second, perceived walkability only has a direct effect (0.149) on walking frequencies for female seniors. Third, although the relationships between perceived walkability and BMI are not directly related in both male and female models, the indirect connection (-0.053) is substituted for female seniors. Besides, the inhibiting effect of walking on BMI, which is -0.511, is also valid for female seniors. Finally, in terms of the role of social cohesion, both the positive impacts of perceived walkability on it (0.225 for males and 0.325 for females) and its promoting effects on walking have been confirmed in male (0.142) and female models (0.103). The negative direct effect of social cohesion on BMI (-0.083) is only confirmed in male seniors. Conclusion: Insights derived from this analysis can help bring forward gender-specific interventions to build a more inclusive walkable and social environment to improve the mobility and physical health of older adults.