Relationship between the fear of COVID-19 and social isolation and depression in elderly individuals

Exploring the factor structure of a Chinese version of the CORE-OM: insights from network approach and bifactor modeling

OBJECTIVE

The Clinical Outcomes in Routine Evaluation (CORE-OM) is a measure of clinical outcomes that has been widely used in mental health research. Nevertheless, the exploration of the factor structure of the CORE-OM yields diverse results. This study aims to explore the factor structure with an innovative method known as exploratory graph analysis (EGA) and supplemented with bifactor modeling.

METHOD

A Chinese version of the CORE-OM was administrated to a total of 1361 clinical college students. We first examined the factor structure of the CORE-OM using EGA, and then compared the model derived by EGA with other models using CFA to find the most reasonable model.

RESULTS

The result of EGA indicated a four-factor model of CORE-OM. The CFA further suggested a bifactor model with a four-factor structure combined with a general factor. The bifactor modeling suggested a significant proportion of shared variance among the variables was attributed to the general factor. The four-factor bifactor model exhibited a satisfactory fit to the data.

CONCLUSION

The results confirm the robustness and parsimonious nature of a four-factor bifactor model for the Chinese version of CORE-OM. It is suitable for measuring intrapersonal psychological distress, positive emotions, interpersonal problems, and risk-related issues among the Chinese population.