Examination of Differential Item Function for Resilience Scale Items with Latent Classes Based on Intolerance of Uncertainty
Year: 2023 Vol: 8 Number: 3
The concept of resilience encompasses various elements such as spirituality, cultural heritage, adverse life events, and family lineage. Due to this diversity, examining the items measuring resilience, which is one of the concepts evaluated within the scope of positive psychology, differential item function (DIF), is considered important in terms of revealing the structure. As well as determining DIF, there is a need to reveal the reasons for its sources. At this point, the variable intolerance of uncertainty, which is highly related to resilience, is addressed. In this context, the general purpose of this research is to examine whether the resilience scale items show DIF before and after the latent classes have been created within the scope of intolerance of uncertainty. The research, in which the Brief Resilience and Intolerance of Uncertainty scales were used, was conducted with 718 university students. In the first stage of data analyses, likelihood ratio, one of the DIF determination methods, was used. In the second stage, the latent class analysis was carried out to create latent classes within the scope of intolerance of uncertainty. According to the results of this research, all items within the scope of gender for the Brief Resilience scale show a middle level of DIF. Within the scope of Latent Class analysis, it was determined that the four- class model was compatible with the data. After the groups were formed, DIF was examined in terms of gender for the Brief Resilience scale within each group. DIF was not determined in any of the items in class 1 and class 4. However, in class 3, all items showed moderate DIF. It was determined that the DIF results changed after the created latent classes. All these results show that intolerance of uncertainty may be the source of DIF determined in resilience scale items. Therefore, it is recommended to study the interrelated variables together when studying DIF.