Evidence map›Paper›PMID 41404170›Full record

ArticleFrontiers in psychology2025

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

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

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Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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7 authors.

Yu Ding *The Battalion 2 of Cadet Brigade, School of Basic Medicine, Naval Military Medical University (NMMU), Shanghai, China.
Ruikang Hu *Medical School of Chinese People's Liberation Army (PLA), Beijing, China.
Binghang Guo *The Battalion 3 of Cadet Brigade, School of Basic Medicine, Naval Military Medical University (NMMU), Shanghai, China.
Zezhong Wang *Department of Health Management, Faculty of Military Health Service, The Navy Military Medical University (NMMU), Shanghai, China.
Qirui DongUnit 96863 of Chinese People's Liberation Army, Luoyang, China.
Zhifeng ZhaoMedical School of Chinese People's Liberation Army (PLA), Beijing, China.
Wen WuDepartment of Respiratory Digestive and Occupational Disease Treatment, 96608 Military Hospital of Chinese People's Liberation Army, Hanzhong, China.

Funding

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6 · The paper itself

Abstract

Background: The 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. Methods: 1,014 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). Results: The 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. Conclusion: High 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.

Indexed as

acceptance and commitment therapycognitive fusionhigh school studentlatent profile analysisreceiver operating characteristic area under curve

Identifiers

PMID41404170
PMCPMC12702884

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