Evidence map›Paper›PMID 40883438›Full record

ArticleScientific reports2025

Latent profile analysis and influencing factors of cognitive flexibility among Chinese high school students.

Huapeng Guan, Ruikang Hu, Ziyue Zhang, MengTing Shu, Zhen Wang, Wen Wu

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Article in Scientific reports, 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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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Huapeng Guan *Afliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, 25000, China.
Ruikang Hu *Medical School of Chinese People's Liberation Army (PLA), Beijing, 100853, China.
Ziyue Zhang *Hospital of Troop 96608, Hanzhong, 723102, China.
MengTing ShuDepartment of Dermatology and Venereology, Capital Institute of Pediatric, No. 2# Yabao Street, ChaoYang District, Beijing, 100020, China.
Zhen WangHospital of Troop 96608, Hanzhong, 723102, China. swzwang@126.com.
Wen WuHospital of Troop 96608, Hanzhong, 723102, China. wuwen18301966750@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the advancement of research in educational psychology, cognitive flexibility (CF), as a pivotal ability that enables individuals to adapt to complex environments and tackle challenges, has garnered increasing attention from scholars. For high school students, there is a lack of research regarding latent profiles of cognitive flexibility and associated risk factors. To identify latent profiles of cognitive flexibility among high school students and develop targeted interventions. From August to October 2024, 1,014 high school students in Hebi City were surveyed using a comprehensive questionnaire incorporating the Cognitive Flexibility Inventory. Latent profile analysis was employed to identify subgroups of CF among students and a binary logistic regression model was used to analyze the associated influencing factors. The optimal cut-off value for grouping was determined by calculating the receiver operating characteristic (ROC) area under curve. Results show that CF could be divided into 2 classes: class1 moderate-CF group (73.5%) and class2 high-CF group (26.5%). The results of the regression analysis indicated that male was a predictor of the high-CF group (OR = 1.414, 95% CI: 1.034-1.935). The higher aesthetic sensitivity and Proactive Personality Scale scores (OR = 1.774, 95% CI: 1.413-2.228; OR = 1.108, 95% CI: 1.080-1.137) were significantly more likely to be in the high-CF group. Additionally, students with a higher ease of excitation score (OR = 0.608, 95% CI: 0.502-0.736) were more likely to belong to the moderate-CF group. Based on the ROC, a cut-off value of 68.5 was established to identify the high-CF group, with sensitivity at 0.862 and specificity at 0.946. It is recommended that educational and mental health interventions focus on individual differences among students to comprehensively enhance cognitive flexibility and regulatory capacity.

Indexed as

CognitionStudentsAdolescentChinaCognitive FlexibilityEast Asian PeopleFemaleHumansMaleROC CurveSchoolsSurveys and QuestionnairesCognitive flexibilityEnvironmental sensitivityHigh school studentsLatent profile analysisProactive personality

Identifiers

PMID40883438
PMCPMC12397312

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.