Decentering, Acceptance, and Non-Attachment: Challenging the Question “Is It Me?”

Among mindfulness measures the three constructs acceptance, decentering, and non-attachment are psychometrically closely related, despite their apparent semantic differences. These three facets present robust psychometric features and can be considered core themes in most “third wave” clinical models. The aim of the present study was to explore the apparently different content domains (acceptance, decentering, and non-attachment) by administering various psychometric scales in a large sample of 608 volunteers. Resilience and depression were also assessed. Exploratory and confirmatory factor analyses performed in two randomly selected subsamples showed a bifactor approximation. The explained common variance suggested a unidimensional nature for the general factor, with good psychometric properties, which we named “Delusion of Me” (DoM). This construct is also strongly correlated with resilience and depression, and appears to be a solid latent general construct closely related to the concept of “ego.” DoM emerges as a potentially transdiagnostic construct with influence on well-being and clinical indexes such as resilience and depression. Further studies should analyze the potential utility of this new construct at a therapeutic level.

Entwicklung und Validierung eines Kurzfragebogens zur Erfassung eines motivierenden Unterrichtsstils

Zusammenfassung. Die vorliegende Studie beschreibt die Entwicklung und Validierung eines Kurzfragebogens zur Erfassung eines motivierenden Unterrichtsstils für Schülerinnen und Schüler der fünften bis zwölften Schulstufe (KEMU 5–12) im Sinne der Selbstbestimmungstheorie ( Ryan & Deci, 2020 ). Ein motivierender Unterrichtstil ist durch Autonomieunterstützung und Struktur der Lehrperson gekennzeichnet und kann das Engagement und das psychische Wohlbefinden von Schülerinnen und Schülern steigern. Anhand zweier heterogener Stichproben ( N 1 = 1,155, N 2 = 1,686) wurden die Faktorenstruktur, die Reliabilität und die valide Interpretierbarkeit der Testwerte des Fragebogens für den Einsatz in Forschungsarbeiten zur Beurteilung von Auswirkungen eines motivierenden Unterrichtsstils sowie zu Gruppenvergleichen untersucht. Indizes zur Beurteilung der Dimensionalität (Percentage of Uncontamined Correlations, Explained Common Variance, Omega Hierarchical) weisen auf einen starken Generalfaktor hin und sprechen dafür, dass eine eindimensionale Modellierung des KEMU 5–12 unverzerrte Schätzungen für Strukturparameter liefert. Die Reliabilität der Skala ist in beiden Stichproben ausgezeichnet (>ω t = .88 und .85). Außerdem konnte skalare Messinvarianz für Geschlecht, Schulstufe, Fach und Erhebungsmethode belegt werden. Die theoriekonformen Korrelationen mit selbstbestimmter Motivation, Flowerleben, schulischem Wohlbefinden, den unterrichtsbezogenen Emotionen Freude, Angst, Ärger und Langeweile sowie mit Noten sprechen für eine valide Interpretierbarkeit der Testwerte in den genannten Einsatzbereichen. Mit dem KEMU 5–12 kann somit ein motivierender Unterrichtsstil reliabel, valide und ökonomisch erfasst werden.

Psychometric properties of a new scale for measuring academic positive psychological capital

Positive psychological capital (PsyCap) is the name given to a set of psychological dimensions (hope, resilience, self-efficacy, and optimism) that may support students in their effort to achieve better academic results and even improve the employability of graduates. These dimensions could help students to achieve better academic results and impact fresh graduates’ ability to stand the labour market in times of crisis. A scale, called Academic PsyCap, was specifically developed to evaluate the four PsyCap dimensions among students and fresh graduates. To deeply investigate the structural validity of the scale, three alternative models (one-factor model, correlated four-factor model, bifactor model) were run on the responses provided by about 1,600 fresh graduates at the University of Padua. The results indicated that the bifactor model fit the data better than the other two models. In this model, all items significantly loaded on both their own domain specific factor and on the general factor. The values of Percentage of Uncontaminated Correlations (PUC), Explained Common Variance (ECV), and Hierarchical Omega suggested that multidimensionality in the scale was not severe enough to disqualify the use of a total PsyCap score. The scale was found to be invariant across gender and academic degree (bachelor’s and master’s degree). Internal consistency indices were satisfactory for the four dimensions and the total scale.

Latent structure evidence of the Depression, Anxiety and Stress Scales - Short Form

This study aimed to investigate the psychometric properties of the Depression, Anxiety and Stress Scales - Short Form in a Brazilian sample. The instrument was answered online by 250 university students. The following models were tested through Confirmatory Factor Analysis: one-dimensional, three oblique factors, hierarchical, and bifactor. The estimated indices showed a better adjustment for a bifactor model composed of three specific factors and one global factor. Additional statistical analysis, such as explained common variance and omega hierarchical estimates, indicated that the measure is predominantly one-dimensional. The results also indicated evidence of convergent validity (Average Extracted Variance between 0.48 and 0.60), internal consistency (Cronbach's alpha between 0.87 and 0.94) and temporal reliability of the instrument (Intraclass Correlation Coefficient between 0.64 and 0.74).

Measuring Positive Mental Health in the Postpartum Period: The Bifactor Structure of the Mental Health Continuum–Short Form in Portuguese Women

This study aimed to investigate the factor structure of the Mental Health Continuum–Short Form (MHC-SF) in the postpartum context using a single-factor model, a correlated three-factor model, and a bifactor model. The reliability and validity of the MHC-SF were also examined. The total sample consisted of 882 postpartum Portuguese women. Confirmatory factor analysis showed that the bifactor model yielded a significantly better fit to the data than the other models. The unidimensionality strength indices (explained common variance = .76, percentage of uncontaminated correlations = .69) and the ω H values supported the general factor of positive mental health, which accounted for 91.5% of the reliable variance in the total score. Additionally, the MHC-SF showed high reliability (ω = .96), and its total and subscale scores were significantly correlated with other measures related to mental health. The results of this study suggest a strong general factor of positive mental health and support the use of its total score in this context.

Evaluating Bifactor Models of Psychopathology Using Model-Based Reliability Indices

There is has been a rapid increase in quantitative researchers applying the bifactor model to psychopathology data. The bifactor model, which typically includes a general p factor and internalizing and externalizing residual factors, consistently demonstrates superior model fit to competing models, including the correlated factors model, which typically includes internalizing and externalizing factors. However, the bifactor model’s superior fit might stem from its tendency to overfit noise and flexibly fit most datasets. An alternative approach to evaluating bifactor models that does not rely on fit statistics is model-based reliability assessment. Reliability indices, including omega/omega hierarchical, explained common variance, and percent uncontaminated correlations can be used to determine the viability of the general and specific psychopathology factors and the extent that the underlying data structure and its measurement is multidimensional. In this methodological review, we identified 49 studies published between 2009 and 2019 that applied the bifactor model to at least two separate symptom domains and calculated reliability indices from the standardized factor loading matrices. We also predicted variation in the p factor’s strength, indexed by the explained common variance, from study characteristics. We found that psychopathology measures tend to be multidimensional, with 57% of the variance explained by the p factor and the remaining variance explained by specific factors. By contrast, most of the variance in observed total scores (74%) was explained by the p factor, while relatively little of the variance in in observed subscale scores (37%) was explained by specific factors beyond the p factor. Finally, 62% of the variability in the p factor’s strength could be predicted by study characteristics, most notably the informant (in a simultaneous regression model), but also age, percent uncontaminated correlations, and the number of items (in separate regression models). We conclude that the latent structure of psychopathology is multidimensional, but its measurement is governed by a single dimension, the strength of which is predicted by study characteristics, particularly the informant.

Core Symptom Index (CSI): testing for bifactor model and differential item functioning

ABSTRACTObjectives:The Core Symptom Index (CSI) is designed to measure anxiety, depression and somatization symptoms. This study examined the construct validity of CSI using confirmatory factor analysis (CFA) including a bifactor model and explored differential item functioning (DIF) of the CSI. The criterion and concurrent validity were evaluated.Methods:In all, 803 elderly patients, average age 69.24 years, 70% female, were assessed for depressive disorders and completed the CSI and the geriatric depression scale (GDS). A series involving CFA for ordinal scale was applied. Factor loadings and explained common variance were analyzed for general and specific factors; and Omega was calculated for model-based reliability. DIF was analyzed using the Multiple-Indicator Multiple-Cause model. Pearson’s correlation, ANOVA, and ROC analysis were used for associations and to compare CSI and GDS in predicting major depressive disorders (MDD).Results:The bifactor model provided the best fit to the data. Most items loaded on general rather than specific factors. The explained common variance was acceptable, while Omega hierarchical for the subscale and explained common variance for the subscales were low. Two DIF items were identified; ‘crying’ for sex items and ‘self-blaming’ for education items. Correlation among CSI and clinical disorders and the GDS were found. AUC for the GDS was 0.83, and for the CSI was 0.81.Conclusion:CSI appears sufficiently unidimensional. Its total score reflected a single general factor, permitting users to interpret the total score as a sufficient reliable measure of the general factors. CSI could serve as a screening tool for MDD.

A Cross-National Analysis of the Psychometric Properties of the Geriatric Anxiety Inventory

Objectives Assessing late-life anxiety using an instrument with sound psychometric properties including cross-cultural invariance is essential for cross-national aging research and clinical assessment. To date, no cross-national research studies have examined the psychometric properties of the frequently used Geriatric Anxiety Inventory (GAI) in depth. Method Using data from 3,731 older adults from 10 national samples (Australia, Brazil, Canada, The Netherlands, Norway, Portugal, Spain, Singapore, Thailand, and United States), this study used bifactor modeling to analyze the dimensionality of the GAI. We evaluated the “fitness” of individual items based on the explained common variance for each item across all nations. In addition, a multigroup confirmatory factor analysis was applied, testing for measurement invariance across the samples. Results Across samples, the presence of a strong G factor provides support that a general factor is of primary importance, rather than subfactors. That is, the data support a primarily unidimensional representation of the GAI, still acknowledging the presence of multidimensional factors. A GAI score in one of the countries would be directly comparable to a GAI score in any of the other countries tested, perhaps with the exception of Singapore. Discussion Although several items demonstrated relatively weak common variance with the general factor, the unidimensional structure remained strong even with these items retained. Thus, it is recommended that the GAI be administered using all items.

The Structure of the Rosenberg Self-Esteem Scale

The Rosenberg Self-Esteem Scale (RSES; Rosenberg, 1965 ) intends to measure a single dominant factor representing global self-esteem. However, several studies have identified some form of multidimensionality for the RSES. Therefore, we examined the factor structure of the RSES with a fixed-effects meta-analytic structural equation modeling approach including 113 independent samples (N = 140,671). A confirmatory bifactor model with specific factors for positively and negatively worded items and a general self-esteem factor fitted best. However, the general factor captured most of the explained common variance in the RSES, whereas the specific factors accounted for less than 15%. The general factor loadings were invariant across samples from the United States and other highly individualistic countries, but lower for less individualistic countries. Thus, although the RSES essentially represents a unidimensional scale, cross-cultural comparisons might not be justified because the cultural background of the respondents affects the interpretation of the items.

Kinematic Structure at the Early Flight Position in Ski Jumping

The purpose of our research was to establish the variability of correlation between the length of the jumps and selected multi-item kinematic variables (n=9) in the early flight phase technique of ski jumping. This study was conducted on a sample of elite Slovenian ski jumpers (N=29) who participated in the experiment on a jumping hill in Hinterzarten, Germany (HS95m) on the 20th of August, 2008. The highest and most significant correlations (p=0.01) with the length of the ski jump were found in the multi-item variable height of flying, which was also expressed with the highest level of stability of the explained total variance (TV) on the first factor (TV=69.13%). The most important characteristic of the aerodynamic aspect of early flight was the variable angle between the body chord and the horizontal axis with significantly high correlations (p<0.05). The stability of that aerodynamic factor was very high (TV=65.04%). The results were essentially similar for the multi-item variable angle between left leg and the horizontal axis (TV=61.88%). The rest of the multi-item kinematic variables did not have significant correlations with the multi-item variable length of jump. Only two more variables, the angle between the upper body and the horizontal plane (TV=53.69%), and the angle between left ski and left leg (TV=50.13%), had an explained common variance on the first factor greater than 50% of total variance. The results indicated that some kinematic parameters of ski jumping early flight technique were more important for success considering the length of the jump.