In the present study, we tested whether civic identity consisting of moral and political identity via the bifactor model of civic identity with the Stanford Civic Purpose dataset. Previous research in youth development proposed that civic identity consists of two closely related identity constructs, i.e., moral and political identity. Given the bifactor model in factor analysis assumes the presence of both the general and specific factors, we hypothesized that the bifactor model would better fit the data than (...) conventional alternative models. Thus, we compared the candidate models, including the bifactor model, with confirmatory factor analysis. To address the concern about the potential overfitting of the bifactor model, we additionally conducted cross-validation and measurement invariance tests across different gender groups and time points. The analysis results supported our hypothesis that the bifactor model better fitted the data. Both the cross-validation and measurement invariance test results suggested that the overfitting issue was not a significant concern. In the present study, we empirically demonstrated that the bifactor model of civic identity consisting of moral and political identity, which was supposed to be more consistent with the theoretical and conceptual framework of civic identity, better fitted the data than conventional alternative models. (shrink)

Psychopathy refers to a range of complex behaviors and personality traits, including callousness and antisocial behavior, typically studied in criminal populations. Recent studies have used self-reports to examine psychopathic traits among noncriminal samples. The goal of the current study was to examine the underlying factor structure of the Self-Report of Psychopathy Scale–Short Form (SRP-SF) across complementary samples and examine the impact of gender on factor structure. We examined the structure of the SRP-SF among 2,554 young adults from three undergraduate samples (...) and a high-risk young adult sample. Using confirmatory factor analysis, a four-correlated factor model and a four-bifactor model showed good fit to the data. Evidence of weak invariance was found for both models across gender. These findings highlight that the SRP-SF is a useful measure of low-level psychopathic traits in noncriminal samples, although the underlying factor structure may not fully translate across men and women. (shrink)

Interdisciplinary research collaboration is crucial for addressing complex global challenges, and measuring researchers' perceptions of it is vital. The Perception of Interdisciplinary Research Collaboration (PIRC) Scale was meticulously developed and validated in this study to enable researchers to assess these perceptions comprehensively. The scale was developed in line with the team science theory. This cross-sectional study involved concept analysis, face and content validity, item pretesting, and pilot testing. A panel of eight specialists from relevant fields meticulously reviewed the items in (...) the instrument, and their inputs and suggestions were followed to refine the instrument, resulting in a 64-item questionnaire. A sample of 1,932 academic staff members with interdisciplinary research experience were selected from six universities in South-South Nigeria for a pilot study. A simple random sampling technique was employed in selecting these participants. Exploratory factor analysis yielded six underlying dimensions within the PIRC Scale, such as: "challenges of Interdisciplinary Disciplinary Research (IDR) collaboration," "IDR collaborative experiences," "motivations for IDR collaboration," "benefits of IDR collaboration," "career impact of IDR collaboration," and "IDR team dynamics." Confirmatory factor analysis confirmed this structure and revealed the bifactor model as the best-fitting model over the unidimensional, oblique and higher-order models. Utilising the Fornell-Larcker approach, strong convergent and discriminant validity was established across all dimensions, with Average Variance Extracted (AVE) above .50 and the square root of the AVE for all factors being greater than the correlation coefficients of each factor with other factors. Cronbach's alpha and McDonald's omega values exceeded the acceptable threshold of 0.70, with item-total correlation analyses further supporting the reliability of each sub-scale and the overall instrument. In conclusion, the PIRC scale can be valuable for researchers, institutions, and policymakers to assess and enhance interdisciplinary research collaboration. It can empower stakeholders to obtain useful information about researchers' perceptions of interdisciplinary research, promote effective collaboration, allocate resources efficiently, and foster innovation. (shrink)

Interdisciplinary research collaboration is crucial for addressing complex global challenges, and measuring researchers' perceptions of it is vital. The Perception of Interdisciplinary Research Collaboration (PIRC) Scale was meticulously developed and validated in this study to enable researchers to assess these perceptions comprehensively. The scale was developed in line with the team science theory. This cross-sectional study involved concept analysis, face and content validity, item pretesting, and pilot testing. A panel of eight specialists from relevant fields meticulously reviewed the items in (...) the instrument, and their inputs and suggestions were followed to refine the instrument, resulting in a 64-item questionnaire. A sample of 1,932 academic staff members with interdisciplinary research experience were selected from six universities in South-South Nigeria for a pilot study. A simple random sampling technique was employed in selecting these participants. Exploratory factor analysis yielded six underlying dimensions within the PIRC Scale, such as: "challenges of Interdisciplinary Disciplinary Research (IDR) collaboration," "IDR collaborative experiences," "motivations for IDR collaboration," "benefits of IDR collaboration," "career impact of IDR collaboration," and "IDR team dynamics." Confirmatory factor analysis confirmed this structure and revealed the bifactor model as the best-fitting model over the unidimensional, oblique and higher-order models. Utilising the Fornell-Larcker approach, strong convergent and discriminant validity was established across all dimensions, with Average Variance Extracted (AVE) above .50 and the square root of the AVE for all factors being greater than the correlation coefficients of each factor with other factors. Cronbach's alpha and McDonald's omega values exceeded the acceptable threshold of 0.70, with item-total correlation analyses further supporting the reliability of each sub-scale and the overall instrument. In conclusion, the PIRC scale can be valuable for researchers, institutions, and policymakers to assess and enhance interdisciplinary research collaboration. It can empower stakeholders to obtain useful information about researchers' perceptions of interdisciplinary research, promote effective collaboration, allocate resources efficiently, and foster innovation. (shrink)