This study aimed to investigate the psychometric properties of the Pediatric Symptom Checklist-17 (PSC-17) in a sample of children orphaned or made vulnerable (OVC) by HIV in Zambia. Caregivers of 1,076 OVC (55.1% boys; = 12.91 years) completed the PSC-17. Competing models, including confirmatory factor analysis (CFA), hierarchical CFA, bifactor CFA, exploratory structural equation modeling (ESEM), and bifactor ESEM, were tested to evaluate the optimal factor structure of the PSC-17. Results showed that the bifactor ESEM provided the best approximation of the PSC-17 data with a well-defined general psychosocial problems factor explaining 72% of the reliable variance in the total score and an internalizing factor containing 63% of reliable variance unique from the general factor. The observed overall psychosocial problems score was associated with lower academic achievement and working memory (with small effect sizes), supporting the discriminant validity of score interpretation. Results of multiple indicators multiple causes (MIMIC) analyses revealed that all items functioned equivalently across child gender and age.

Intensive longitudinal studies and experience sampling methods are becoming more common in psychology. While they provide a unique opportunity to ask novel questions about within-person processes relating to personality, there is a lack of methods specifically built to characterize the interplay between traits and states. We thus introduce a Bayesian multivariate mixed-effects location scale model (M-MELSM). The formulation can simultaneously model both personality traits (the location) and states (the scale) for multivariate data common to personality research. Variables can be included to predict either (or both) the traits and states, in addition to estimating random effects therein. This provides correlations between location and scale random effects, both across and within each outcome, which allows for characterizing relations between any number of personality traits and the corresponding states. We take a Bayesian approach, not only to make estimation possible, but also because it provides the necessary information for use in psychological applications such as hypothesis testing. To illustrate the model we use data from 194 individuals that provided daily ratings of negative and positive affect, as well as their physical activity in the form of step counts over 100 consecutive days. We describe the fitted model, where we emphasize, with visualization, the richness of information provided by the M-MELSM. We demonstrate Bayesian hypothesis testing for the correlations between the random effects. We conclude by discussing limitations of the MELSM in general and extensions to the M-MELSM specifically for personality research.

The Multidimensional Acculturative Stress Inventory (MASI) is an established measure of acculturative stress for people of Mexican origin living in the United States that has been associated with mental health outcomes in this population. We translated the MASI into German and adapted it for use with Turkish-origin immigrants in Germany. The MASI includes filter questions asking if a potentially stressful event had actually occurred before reporting the stress appraisal of these situations. Measurement invariance testing has become a standard practice to evaluate questionnaire translations, however, measurement invariance of filter questions has been scarcely studied. In Study I, we evaluated measurement invariance of the filter questions between a German-based Turkish sample ( = 233) and the Mexican-origin sample from the original study ( = 174) and could show partial strong factorial invariance for three of the four factors. In Study II, a validation study, relations between the German MASI scores and measures of acculturation and stress indicated discriminant validity. This study contributes to research on measurement invariance of filter questions, thereby providing a measure of acculturative stress that can be used in future research to understand the etiology of health disparities in Turkish-origin immigrants in Germany.

Since the 1920s, psychologists have sought to assess the sex- and gender-related attributes of men and women, including primarily aspects of personality and focusing on positive characteristics. In this paper, we introduce a new questionnaire for assessing gender-related attributes with a broader approach than provided by previous ones. Therefore, the questionnaire includes (a) not only personality traits but also cognitions and interests and (b) not only positive but also negative and neutral characteristics. Two independent datasets were acquired (Study 1: = 1,466; Study 2: = 471) for development and psychometric analyses. Factor analysis confirmed a hierarchical structure with two separate dimensions of masculinity and femininity overarching the multiple first-order domains of personality, cognition, and interests. Analyses of reliability and convergence with other gender identity and personality scales revealed sufficient values. The new instrument discriminated between the biological sexes and was related to the gender quotas in participants' occupations and social environments, thus providing evidence for criterion-related validity. Therefore, we propose the Gender-Related Attributes Survey (GERAS) as a useful tool for objectively assessing gender-related attributes across multiple facets in gender and sex-difference research.

Grit, the passion and perseverance for long-term goals, has received attention from personality psychologists because it predicts success and academic achievement. Grit has also been criticized as simply another measure of self-control or conscientiousness. A precise psychometric representation of grit is needed to understand how the construct is unique and how it overlaps with other constructs. Previous research suggests that the Short Grit Scale (Grit-S) has several psychometric limitations, such as uncertain factor structure within and across populations, uncertainty about reporting total or subscale scores, and different assessment precision at low and high levels on the construct. We conducted modern psychometric techniques including parallel analysis, measurement invariance, extrinsic convergent validity, and Item Response Theory models on two American samples. Our results suggest that the Grit-S is essentially unidimensional and that there is construct overlap with the self-control construct. Subscale factors were the result of an item doublet, where two items had high correlated uniquenesses, showed similar item information, and were more likely to exhibit measurement bias. Findings replicated across samples. Finally, we discuss recommendations for the use of the Grit-S based on the theoretical interpretation of the unidimensional factor and our empirical findings.

Accurate measurement of depressive symptoms in the cancer setting is critical for ensuring optimal quality of life and patient outcomes. The present study compared the one-factor, correlated two-factor, correlated four-factor, and second-order factor models of the Center for Epidemiologic Studies Depression Scale (CES-D), a commonly used measure in oncology settings. Given the importance of adequate psychometric performance of the CES-D across age groups, a second aim was to examine measurement invariance between younger and older adults with cancer. Participants ( = 663) were recruited from outpatient clinics at a large cancer center. Over one-fourth of the sample endorsed clinically significant depressive symptoms (25.9%, = 165). Confirmatory factor analysis of the CES-D supported the hypothesized correlated four-factor model as the best fit. The second-order factor also demonstrated good fit, but interpretations of the factors were more complex. Factors were highly correlated (range = .38-.91). There was also support for full scalar invariance between age groups, suggesting that regardless of age, respondents endorse the same response category for the same level of the latent trait (i.e., depression) on the CES-D. Taken together, the results suggest that the CES-D is a viable depression screening option for oncology settings and does not require scoring adjustments for respondent age.

Contemporary theories of social anxiety emphasize the role of cognitive processes. Although social anxiety disorder is one of the most common mental health problems in adolescents, there are very few self-report instruments available to measure cognitive processes related to social anxiety in adolescents, let alone non-English instruments. The Self-Statements during Public Speaking Scale (SSPS; Hofmann & DiBartolo, 2000) is a brief self-report measure designed to assess self-statements related to public speaking, the most commonly feared social performance situation. In order to fill this gap in the literature, we translated the SSPS into Spanish and administered it to 1,694 adolescents from a community sample, a clinical sample composed of 71 subjects with a principal diagnosis of social anxiety disorder; and a clinical control group consisting of 154 patients. The scale showed good psychometric properties, supporting the use of the Spanish version of the SSPS in adolescents.

This study provides evidence that an Italian version of the Positive and Negative Affect Schedule (PANAS) is a reliable and valid self-report measure. In an Italian sample (N = 600), the PANAS showed solid psychometric properties, and several American findings with the PANAS were replicated. The replicability of the PANAS factor structure was confirmed by high congruence coefficients between the American and Italian varimax solutions. Alternative models were tested with Confirmatory Factor Analysis; as in previous studies, the two-factor model achieved the best fit, but absolute fit indices varied with the estimation methods used. The independence/bipolarity issue was also explored: Positive and negative affect scales remain substantially independent after accounting for measurement error and acquiescence. Some predictions from the tripartite model of anxiety and depression were confirmed, and external correlates of the PANAS replicated those found in other languages and cultures. These analyses offer strong support for the construct validity of the Italian PANAS.

The Perceived Empathic Self-Efficacy Scale (PESE) and the Perceived Social Self-Efficacy Scale (PSSE) were developed to assess, respectively, individuals' self-efficacy beliefs regarding both empathic responding to others' needs or feelings and managing interpersonal relationships. In this study of young adults, a unidimensional factorial structure of both scales was found in Italy, the United States, and Bolivia. Complete invariance at the metric level and partial invariance at the scalar level were found across gender and countries for both scales. The construct and incremental validity of both PESE and PSSE were further examined in a different sample of Italian young adults. Patterns of association of the PESE or PSSE with self-esteem, psychological well-being, and the use of adaptive and maladaptive coping strategies were found, often over and beyond their associations with empathy or extraversion, respectively.

Rapid advances in mobile data-transfer technologies offer new possibilities in the use of cell phones to conduct assessments of a person's natural environment in real time. This paper describes features of a new Internet-based, cell phone-optimized assessment technique (ICAT), which consists of a retrospective baseline assessment combined with text messages sent to the participants' personal cell phones providing a hyperlink to an Internet-stored cell phone-optimized questionnaire. Two participation conditions were used to test variations in response burden. Retention rates, completion rates, and response times in different subgroups were tested by means of χ² tests, Cox regression, and logistic regression. Among the 237 initial participants, we observed a retention rate of 90.3% from the baseline assessment to the cell-phone part, and 80.4% repeated participation in the 30 daily assessments. Each day, 40-70% of the questionnaires were returned, a fourth in less than 3 minutes. Qualitative interviews underscored the ease of use of ICAT. This technique appears to be an innovative, convenient, and cost-effective way of collecting data on situational characteristics while minimizing recall bias. Because of its flexibility, ICAT can be applied in various disciplines, whether as part of small pilot studies or large-scale, crosscultural, and multisite research projects.

The use of dynamic network models has grown in recent years. These models allow researchers to capture both lagged and contemporaneous effects in longitudinal data typically as variations, reformulations, or extensions of the standard vector autoregressive (VAR) models. To date, many of these dynamic networks have not been explicitly compared to one another. We compare three popular dynamic network approaches-GIMME, uSEM, and LASSO gVAR-in terms of their differences in modeling assumptions, estimation procedures, statistical properties based on a Monte Carlo simulation, and implications for affect and personality researchers. We found that all three approaches dynamic networks provided yielded group-level empirical results in partial support of affect and personality theories. However, individual-level results revealed a great deal of heterogeneity across approaches and participants. Reasons for discrepancies are discussed alongside these approaches' respective strengths and limitations.