An extended validation of the Communal Coping Strategies Inventory for Competitive Team Sports: A multilevel approach

A questionnaire that can properly measure communal coping in sport is required to further investigate and understand how individuals in a team collectively cope with stressful sport situations. The Communal Coping Strategies Inventory for Competitive Team Sports (CCSICTS; Leprince et al., 2019) needed to be validated at the collective level and in its situational form to be used in broader sport situations. The aims of the present work were to improve and further validate the factorial structure of the CCSICTS at both individual and team levels. With a sample of 380 French athletes, representing 56 teams, Study 1 showed support for a multilevel, hierarchical and four-dimensional factorial structure of the revised version of the CCSICTS at both individual and team levels. With a sample of 641 French athletes, representing 75 teams, Study 2 confirmed the factorial structure obtained in Study 1 at individual and team levels, and its validity in sport-specific situations. The results of both studies also highlighted a bifactorial structure, allowing interpretation of communal coping as an overall team capacity to adapt to stress. As such, the psychometric qualities of the CCSICTS-R have been established at individual and team levels. The CCSICTS-R enables proper and distinct measurement of the characteristics of communal coping in sport (i.e., hierarchical, multidimensional, multilevel, both situational and dispositional) and can be used from both research and practical perspectives.

Alternations in the multilevel structures of chickpea protein during fermentation and their relationship with digestibility

This study investigated the effects of fermentation on in vitro protein digestibility of chickpeas and their relationship with the variations of multilevel structures of chickpea protein. The results showed that lactobacillus fermentation not only increased the solubility of chickpea protein but also enhanced the hydrolysis of protein during gastric and intestinal digestion by altering the multilevel structures of chickpea protein. The degree of hydrolysis, free amino acid content, and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) revealed that macromolecule chickpea protein was hydrolyzed during fermentation. Raman and UV spectroscopy scans indicated that the α-helix content increased while the content of β-sheet in chickpea protein dropped significantly after fermentation. As for fermented chickpea protein, the aromatic acid residues were gradually more exposed than the unfermented chickpea protein, and the intramolecular disulfide bond was generally converted to the intermolecular form. Our findings showed that fermentation changed the multilevel structures of chickpea protein, degrading spherical structures into looser states that were more responsible for their effective hydrolysis during digestion. Furthermore, better digestibility of chickpea protein would stimulate the use of chickpea fermentation in food products.

Identifying strategies to improve PANSS based dimensional models in schizophrenia: Accounting for multilevel structure, Bayesian model and clinical staging

BACKGROUND

Dimensional approaches can decompose a construct in a set of continuous variables, improving the characterization of complex phenotypes, such as schizophrenia. However, the five-factor model of the Positive and Negative Syndrome Scale (PANSS), the most used instrument in schizophrenia research, yielded poor fits in most confirmatory factor analysis (CFA) studies, raising concerns about its applications. Thus, we aimed to identify dimensional PANSS CFA models with good psychometric properties by comparing the traditional CFA with three methodological approaches: Bayesian CFA, multilevel modeling, and Multiple Indicators Multiple Causes (MIMIC) modeling.

METHODS

Clinical data of 700 schizophrenia patients from four centers were analyzed. We first performed a traditional CFA. Next, we tested the three techniques: 1) a Bayesian CFA; 2) a multilevel analysis using the centers as level; and 3) a MIMIC modeling to evaluate the impact of clinical staging on PANSS factors and items.

RESULTS

CFA and Bayesian CFA produced poor fit models. However, when adding a multilevel structure to the CFA model, a good fit model emerged. MIMIC modeling yielded significant differences in the factor structure between the clinical stages of schizophrenia. Sex, age, age of onset, and duration of illness did not significantly affect the model fit.

CONCLUSION

Our comparison of different CFA methods highlights the need for multilevel structure to achieve a good fit model and the potential utility of staging models (rather than the duration of illness) to deal with clinical heterogeneity in schizophrenia. Large prospective samples with biological data should help to understand the interplay between psychometrics concerns and neurobiology research.