The advent of large-scale assessment, but also the more frequent use of longitudinal and multivariate approaches to measurement in psychological, educational, and sociological research, caused an ...increased demand for psychometrically sound short scales. Shortening scales economizes on valuable administration time, but might result in inadequate measures because reducing an item set could: a) change the internal structure of the measure, b) result in poorer reliability and measurement precision, c) deliver measures that cannot effectively discriminate between persons on the intended ability spectrum, and d) reduce test-criterion relations. Different approaches to abbreviate measures fare differently with respect to the above-mentioned problems. Therefore, we compare the quality and efficiency of three item selection strategies to derive short scales from an existing long version: a Stepwise COnfirmatory Factor Analytical approach (SCOFA) that maximizes factor loadings and two metaheuristics, specifically an Ant Colony Optimization (ACO) with a tailored user-defined optimization function and a Genetic Algorithm (GA) with an unspecific cost-reduction function. SCOFA compiled short versions were highly reliable, but had poor validity. In contrast, both metaheuristics outperformed SCOFA and produced efficient and psychometrically sound short versions (unidimensional, reliable, sensitive, and valid). We discuss under which circumstances ACO and GA produce equivalent results and provide recommendations for conditions in which it is advisable to use a metaheuristic with an unspecific out-of-the-box optimization function.
Metaheuristics are optimization algorithms that efficiently solve a variety of complex combinatorial problems. In psychological research, metaheuristics have been applied in short-scale construction ...and model specification search. In the present study, we propose a bee swarm optimization (BSO) algorithm to explore the structure underlying a psychological measurement instrument. The algorithm assigns items to an unknown number of nested factors in a confirmatory bifactor model, while simultaneously selecting items for the final scale. To achieve this, the algorithm follows the biological template of bees’ foraging behavior: Scout bees explore new food sources, whereas onlooker bees search in the vicinity of previously explored, promising food sources. Analogously, scout bees in BSO introduce major changes to a model specification (e.g., adding or removing a specific factor), whereas onlooker bees only make minor changes (e.g., adding an item to a factor or swapping items between specific factors). Through this division of labor in an artificial bee colony, the algorithm aims to strike a balance between two opposing strategies diversification (or exploration) versus intensification (or exploitation). We demonstrate the usefulness of the algorithm to find the underlying structure in two empirical data sets (Holzinger–Swineford and short dark triad questionnaire, SDQ3). Furthermore, we illustrate the influence of relevant hyperparameters such as the number of bees in the hive, the percentage of scouts to onlookers, and the number of top solutions to be followed. Finally, useful applications of the new algorithm are discussed, as well as limitations and possible future research opportunities.
The goal of this study was to psychometrically evaluate the Multidimensional Assessment of Interoceptive Awareness (MAIA), a popular self-report questionnaire claimed to assess the most important ...subjective aspects of interoception. We collected data in two samples (N = 644 and N = 1,516) and focused on the factor structure and validity of MAIA, as well as its associations with personality traits. Confirmatory Factor Analysis suggested that six of the eight subscales measure a common general factor of self-reported interoception; two MAIA subscales, Not-Worrying and Not-Distracting were only weakly related to this factor. Whereas the general factor correlated strongly with a measure of perceived attentiveness to normal nonemotive body processes, and moderately with Extraversion, Openness and Conscientiousness, the Not-Worrying factor showed moderate to strong negative correlations with Emotionality, pain catastrophization, and anxiety-related aspects of body focus. Not-Distracting was only weakly associated with the validating scales. Overall, these findings do not support the claimed eight-factor structure of the MAIA but indicate the existence of an overarching general factor. Additionally, this study provides evidence that interoceptive awareness, as measured by the MAIA, is related to, but distinct from personality.
Worries about possible harmful effects of new technologies (modern health worries) have intensely been investigated in the last decade. However, the comparability of translated self-report measures ...across countries is often problematic. This study aimed to overcome this problem by developing psychometrically sound brief versions of the widely used 25-item Modern Health Worries Scale (MHWS) suitable for multi-country use. Based on data of overall 5,176 individuals from four European countries (England, Germany, Hungary, Sweden), Ant Colony Optimization was used to identify the indicators that optimize model fit and measurement invariance across countries. Two scales were developed. A short (12-item) version of the MHWS that represents the four-factor structure of the original version and an ultra-short (4-item) scale that only measures the general construct. Both scales show that overall levels of health worries were highest in England and Hungary, but that the main reason for concern (e.g. electromagnetic radiation or food related fears) differs considerably between these countries. This study also shows that even if measurement invariance of translated self-report instruments across countries is problematic, it can be optimized by using adequate item selection procedures. Differences of modern health worries across countries and recommendations for cross-cultural research are discussed.
Situational Judgment Tests (SJTs) are criterion valid low fidelity measures that have gained much popularity as predictors of job performance. A broad variety of SJTs have been studied, but SJTs ...measuring personality are still rare. Personality traits such as Conscientiousness are valid predictors of many educational, work and life-related outcomes and SJTs are less prone to faking than classical self-report measurements. We developed an SJT measure of Dependability, a core facet of Conscientiousness, by gathering critical incidents in semi-structured interviews using the construct definition of Dependability as a prompt. We examined the psychometric properties of the newly developed SJTs across two studies (N = 546 general population; N = 440 sales professionals). The internal validity of the SJTs was examined by correlating the SJT scores with related self-report measures of Dependability and Conscientiousness, as well as testing the unidimensionality of the measure with CFA. Additionally, we specified a bi-factor model of SJT, self-report and behavioral checklist measures of Dependability accounting for common and specific measurement variance. External validity was examined by correlating the SJT scale and specific factor with work-related outcomes. The results show that the Dependability SJTs with an expert based scoring procedure were psychometrically sound and correlated moderately to highly with traditional self-report measures of Dependability and Conscientiousness. However, a large proportion of SJT variance cannot be accounted for by personality alone. This supports the notion that SJTs measure general domain knowledge about the effectiveness of personality-related behaviors. We conclude that SJT measures of personality can be a promising addition to classical self-report assessments and can be used in a wide variety of applications beyond measurement and selection, for instance as formative assessments of personality.
The goal of this study was to examine differential and correlated change in personality across the adult lifespan. Studying differential and correlated change can help understand whether ...intraindividual trait change trajectories deviate from the norm and how these trajectories are coupled with each other. We used data from two large longitudinal panel studies from the United States that covered a total age range of 20 to 95 years on the first measurement occasion. We used correlated factor models and bivariate latent change score models to examine the rank-order stability and correlations between change across three measurement waves covering 18 years (N = 3250) and four measurement waves covering 12 years (N = 4145). We examined the moderation effects of continuous age on these model parameters using local structural equation modeling. The results suggest that the test–retest correlations decrease with increasing time between measurements but are unaffected by participants’ age. We found that change processes in Extraversion, Openness, Agreeableness, and Conscientiousness were strongly related, particularly in late adulthood. Correlated change patterns were highly stable across time intervals and similar to the initial cross-sectional Big Five correlations. We discuss potential mechanisms and implications for personality development research.
In this study, we developed an age-invariant 18-item short form of the HEXACO Personality Inventory for use in developmental personality research. We combined the item selection procedure ant colony ...optimization (ACO) and the model estimation approach local structural equation modeling (LSEM). ACO is a metaheuristic algorithm that evaluates items based on the quality of the resulting short scale, thus directly optimizing criteria that can only be estimated with combinations of items, such as model fit and measurement invariance. LSEM allows for model estimation and measurement invariance testing across a continuous age variable by weighting participants, rather than splitting the sample into artificial age groups. Using a HEXACO-100 dataset of N = 6,419 participants ranging from 16 to 90 years of age, we selected a short form optimized for model fit, measurement invariance, facet coverage, and balance of item keying. To achieve scalar measurement invariance and brevity, but maintain construct coverage, we selected 18 items to represent three out of four facets from each HEXACO trait domain. The resulting HEX-ACO-18 short scale showed adequate model fit and scalar measurement invariance across age. Furthermore, the usefulness and versatility of the item and person sampling procedures ACO and LSEM is demonstrated.
In this study, we addressed age differences in how people respond to interpersonal transgressions. Specifically, we examined whether the tendencies to respond with revenge, avoidance, and benevolence ...differ as a function of age in a cross-sectional study with a large sample (N = 1,413; age range: 19-83 years). We used local structural equation modeling (LSEM) to examine nonlinear mean level, structural, and variance-related differences in responses to transgressions across continuous age. We found a small increase in average benevolence and a small decrease in revenge mean levels during early adulthood. In contrast to research on avoidance related to interpersonal stressors, the current results suggest the opposite age pattern with a moderate decrease in avoidance with increasing age. Additionally, the strength of the negative correlation between benevolence and the two other response options decreased with age. This pattern indicates that younger adults generally either respond with a negative or positive reaction, whereas responses were more differentiated in old age. The current findings demonstrate the importance of addressing age differences in responses to interpersonal transgressors from multiple perspectives.
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CEKLJ, FFLJ, NUK, ODKLJ, PEFLJ
This article demonstrates how the metaheuristic item selection algorithm ant colony optimization (ACO) can be used to develop short scales for cross-cultural surveys. Traditional item selection ...approaches typically select items based on expert-guided assessment of item-level information in the full scale, such as factor loadings or item correlations with relevant outcomes. ACO is an optimization procedure that instead selects items based on the properties of the resulting short models, such as model fit and reliability. Using a sample of 5,567 respondents from five countries, we selected a 15-item short form of the Big Five Inventory–2 with the goal of optimizing model fit and measurement invariance in exploratory structural equation modeling, as well as reliability, construct coverage, and criterion-related validity of the scale. We compared the psychometric properties of the new short scale with the Big Five Inventory–2 extra-short form developed with a traditional approach. Whereas both short scales maintained the construct coverage and criterion-related validity of the full scale, the ACO short scale achieved better model fit and measurement invariance across countries than the Big Five Inventory–2 extra-short form. As such, ACO can be a useful tool to identify items for cross-cultural comparisons of personality.
Adverse perinatal outcomes, such as increased risks of pre-eclampsia, miscarriage, premature birth, and stillbirth have been reported in SARS-CoV-2 infection. For a better understanding of COVID-19 ...complications in pregnancy, histopathological changes in the placenta, which is the interface between mother and foetus, could be the place to look at. The aim of this study was to determine placental histopathological changes and their role in preterm birth in pregnant women with SARS-CoV-2 infection. We performed a prospective, observational study in a COVID-only hospital, which included 39 pregnant women with SARS-CoV-2 infection and preterm birth compared with a control group of 39 women COVID-19 negative with preterm birth and a placental pathology exam available. The microscopic examination of all placentas revealed placental infarction (64.1% vs. 30.8%), decidual arteriopathy (66.7% vs. 23.1%), intervillous thrombi (53.8% vs. 38.5%), perivillous fibrin deposits (59% vs. 46.2%), inflammatory infiltrate (69.2% vs. 46.2%), chorangiosis (17.9% vs. 10.3%), and accelerated maturation of the villi (23.1% vs. 28.2%).
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