AUTHOR=Ding Yu , Hu Ruikang , Guo Binghang , Wang Zezhong , Dong Qirui , Zhao Zhifeng , Wu Wen 

TITLE=Profiles of cognitive fusion and associated factors among Chinese high school students: a latent profile analysis

JOURNAL=Frontiers in Psychology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2025.1569773

DOI=10.3389/fpsyg.2025.1569773

ISSN=1664-1078

ABSTRACT=BackgroundThe study aimed to analyze the potential categories of cognitive fusion (CF) among Chinese high school students and to explore the cut-off values and influencing factors for distinguishing the subgroups of cognitive fusion.Methods1,014 high school students in Hebi City, Henan Province, China were recruited by Cognitive Fusion Questionnaire from August to October 2024. Latent profile analysis was performed on the cognitive fusion score. The influencing factors associated with different classifications were investigated via multinomial logistic regression and the optimal cut-off value was identified based on the receiver operating characteristic area under curve (ROC AUC).ResultsThe cognitive fusion of high school students could be categorized into three subgroups: the low-CF group (14.6%), moderate-CF group (58.6%), and high-CF group (26.8%). The high-CF group identified by the questionnaire had a cut-off value of 47.5, with sensitivity at 0.996 and specificity at 0.992. For the low-CF group, the cut-off value was 30.5, sensitivity was 0.986, and specificity was 0.993. Regression analysis revealed that grade12 (aOR = 2.009, 95%CI: 1.323–3.050) and female (aOR = 1.563, 95%CI: 1.085–2.250) were linked to the moderate-CF group. Additionally, students in grade 11 (aOR = 1.940, 95% CI: 1.156–3.256), grade 12 (aOR = 1.704, 95% CI: 1.063–2.730), and females (aOR = 2.147, 95% CI: 1.426–3.233) were more likely to belong to the high-CF group.ConclusionHigh school students’ cognitive fusion scores can be classified into three potential categories. The screening tool demonstrates effectiveness in identifying high cognitive fusion groups, with significant differences observed across categories based on gender and grade level. Tailored interventions targeting the specific characteristics of each category may contribute to reducing cognitive fusion among high school students.