A New Story on the Multidimensionality of the MSPSS: Validity of the Internal Structure through Bifactor ESEM

The internal structure of the Multidimensional Scale of Perceived Social Support (MSPSS) in adolescents has been evaluated with some factorial analysis methodologies but not with bifactor exploratory structural equation modeling (ESEM), and possibly the inconsistency in the internal structure was dependent on these approaches. The objective of the study was to update evidence regarding its internal structure of MSPSS, by means of a detailed examination of its multidimensionality The participants were 460 adolescents from an educational institution in the Callao region, Lima, Peru. The structure was modeled using unidimensional, three-factor and bifactor models with confirmatory factor analysis (CFA) and ESEM approaches. The models showed good levels of fit, with the exception of the unidimensional model; however, the multidimensionality indicators supported the superiority of the bifactor ESEM. In contrast, the general factor was not strong enough, and the interfactorial correlations were substantially lower. It is concluded that the MSPSS can be interpreted by independent but moderately correlated factors, and there is possible systematic variance that potentially prevented the identification of a general factor.

Cross-national structure of economic competence: Insights from a German and Russian assessment

In this paper, we present a study, which models and measures the competencies of higher education students in business and economics—within and across countries. To measure student competencies in a valid and reliable way, the Test of Understanding in College Economics was used, which assesses microeconomic and macroeconomic competencies. The test was translated into several languages and adapted for different university contexts. In the presented study, the test contents were also compared with regard to the educational standards and the university curricula in Russia and Germany. Our findings from the cross-national analysis suggest one strong general factor of economic competence, which encompasses micro- and macroeconomic dimensions. This points to a stronger interconnection between learning and understanding economic contents than previous research suggests and indicates far-reaching curricular and instructional consequences for higher education economics as well as needs for further research, which are discussed in this paper.

Dimensions of Self-Reported Driving Difficulty in Autistic and Non-Autistic Adults and their Relationship with Autistic Traits

A survey asked autistic and non-autistic people about the driving difficulties they experience and their autistic traits. Principle components analysis was used to identify how reported difficulties clustered together in each group, and regression was used to determine which subscales of the Autism Spectrum Quotient predict these factors. For autistic drivers three factors of driving difficulty emerged: a Driving Executive factor, predicted by Attention Switching; a Driving Understanding factor, predicted by Communication; and a Driving Social Interaction factor, predicted by Attention Switching. For non-autistic drivers only one Driving General factor emerged, predicted by Communication. This suggests autistic people may experience at least three distinct domains of difficulty when driving which may relate to their particular profile of autistic features.

A bioenergetic model that links psychopathology and intelligence: Implications for research and clinical practice

Decomposing the structure of human cerebral function in its domains, such as affect regulation or cognition, forms the backbone of psychiatric diagnosis and treatment. Research continues to decipher the domains and hierarchical structure of cerebral function. So far, the findings strongly suggest two higher-order latent factors of general psychopathology (p factor) and general intelligence (g factor). Both general factors are functions of the same organ, covary, share risk factors as well as biomarkers, and benefit from the same treatments. However, to our knowledge, a model that connects both components of cerebral function within a higher-order latent factor and describes its potential biological underpinning is lacking. First, we suggest the general factor of cerebral function (c factor) as the shared variance of the measures of g and p in a bi-factor model. Second, we propose and provide evidence that mitochondrial bioenergetics (MB) is one core biological underpinning of c. Third, we describe how this c factor mito-bioenergetics (CMB) model may transform research and clinical practice by advancing knowledge of treatment effects, risk factors, biomarkers and clinical outcomes. Finally, we present a CMB model-based hypothesis stating that fatigue—as a phenotypical correlate of MB—directly loads on c.

Confirmatory Factor Analysis of Three Versions of the Depression Anxiety Stress Scale (DASS-42, DASS-21, and DASS-12) in Polish Adults

Background: The Depression Anxiety Stress Scales (DASS) are designed to identify quickly and differentiate between the symptoms of depression and anxiety in the non-clinical population. Different versions (original and short) were validated in many cultures. Nevertheless, there are no data of factorial validity of the different versions of this scale in Polish culture. Thus, the aim of this study was to evaluate the factor structure using confirmatory factor analysis (CFA) and internal consistency of DASS-42 (original version) and two short versions (DASS-21 items and DASS-12 items) in the Polish population.Methods: The DASS-42 was administered to a non-clinical sample, broadly representative of the general Polish adult population (n = 1,021) in terms of demographic variables. The DASS-21 and DASS-12 version used in this study comprise seven and four items from each of the following corresponding three subscales of the Polish version of DASS-42.Results: There were two models that fitted best for DASS-42: (a) modified three correlated factors (depression, anxiety, and stress) with cross-loadings and (b) second order (general factor of psychological distress) and three factors with cross-loadings. There were also two models that fitted best for DASS-21 and DASS-12: (a) modified three correlated factors (depression, anxiety, and stress) and (b) second order (general factor of psychological distress) and three factors.Conclusions: All three versions of DASS appear to have an acceptable factorial structure. However, the shorter versions (DASS-21 and DASS-12) may be more feasible to use in general medical practice and also be less burdensome to participants.

Genetic and Environmental Architecture of Five Factor Model and Super-Factors: An Italian Twin Study

No previous research explored the genetic and environmental structure of Big Five dimensions of personality and higher-order factors in a single twin study, except, in part, for just one study. We used the twin design to estimate the effects of genes and environment on both Five Factor model and related second- and third-order factors (i.e., Alpha [stability], Beta [plasticity], and GFP [general factor of personality]). We analyzed data from 314 adult twins (157 pairs: 83 monozygotic, 74 dizygotic; mean age: 52 years) enrolled in the Italian Twin Register. Participants underwent clinical and instrumental evaluations, and completed a 25-adjective list drawn from the Short Adjectives Checklist to Measure Big Five (SACBIF). We applied quantitative genetic models to unravel the sources of variation and covariation for the Big Five and higher-order factors. We found a similar etiological architecture across the different levels of analysis, with moderate to substantial non-additive genetic and unique environmental influences on all the personality traits, and no shared environmental contribution for any of them. We also detected significant genetic correlations for the Big Five dimensions and the Alpha and Beta super-factors. With some limitations, our results suggest that the etiological architecture of personality may be invariant to the factor level of analysis.

Construction and Validation of the Legitimizing Income Inequality Scale

Although income inequality has become a focus of political and social discourse, counseling psychology research examining correlates and consequences of legitimizing income inequality remains sparse. A significant barrier to the study of income inequality is the lack of available measures to assess attitudes toward socioeconomic inequality. The purpose of this study was to develop and provide initial validity evidence for the Legitimizing Income Inequality Scale (LIIS). Results supported a bifactor structure for the LIIS with a general factor (ω = .95) and subfactors measuring Social Welfare Beliefs (ω = .92), Economic Fatalism (ω = .87), and Economic Meritocracy Beliefs (ω = .90). The LIIS significantly correlated in theoretically consistent directions with scores on measures of classist attitudes, socioeconomic conservatism, impression management, and colorblind racial attitudes. Implications for future research and training using the LIIS are provided.

A German Adaptation of the Prosociality Scale

Introduction: This paper presents a German translation of the 16-item Prosociality Scale. We analyzed its factor structure based on theoretical assumptions regarding the inclusion of empathy as one element of prosociality or as its underlying construct. Methods and Results: We translated the items into German taking into account both the English and the Italian item wordings. The scale's factor structure was analyzed with three models testing (1) unidimensionality, (2) a four-factor structure with four items on each factor, and (3) a variant of a bifactor model with a general factor including all items and three residual factors with four items each. We analyzed construct validity using the Interpersonal Reactivity Index. Finally, we identified two 13-item versions with good model fit. Conclusion: The German Prosociality Scale is not unidimensional. Empathy seems to be the underlying construct of prosociality, but it can also be considered an element of prosociality.

How Robust Is the p Factor? Using Multitrait-Multimethod Modeling to Inform the Meaning of General Factors of Youth Psychopathology

We used multitrait-multimethod (MTMM) modeling to examine general factors of psychopathology in three samples of youths ( Ns = 2,119, 303, and 592) for whom three informants reported on the youth’s psychopathology (e.g., child, parent, teacher). Empirical support for the p-factor diminished in multi-informant models compared with mono-informant models: The correlation between externalizing and internalizing factors decreased, and the general factor in bifactor models essentially reflected externalizing. Widely used MTMM-informed approaches for modeling multi-informant data cannot distinguish between competing interpretations of the patterns of effects we observed, including that the p factor reflects, in part, evaluative consistency bias or that psychopathology manifests differently across contexts (e.g., home vs. school). Ultimately, support for the p factor may be stronger in mono-informant designs, although it does not entirely vanish in multi-informant models. Instead, the general factor of psychopathology in any given mono-informant model likely reflects a complex mix of variances, some substantive and some methodological.