Latent Profile Analysis of Cognitive Emotion Regulation Strategies among Medical Postgraduate Students
Objective To identify the potential categories of cognitive emotion regulation strategies of medical graduate students,and compare the differences in demographic characteristics and empirical avoidance among diffe-rent potential categories of medical graduate students.Methods Using the convenience sampling method,an online questionnaire survey was conducted among 1 019 medical graduate students in a city in Henan Province from October to December 2020,including general information questionnaires,cognitive emotion regulation questionnaire,and ac-ceptance and action questionnaires.Data analysis was performed using chi-square test,analysis of variance,latent pro-file analysis and multivariate logistic regression.Results The cognitive emotion regulation of medical graduate students could be divided into three potential categories:low adaptive-low maladaptive(n=59),highadaptive-medium maladaptive(n=441)and medium adaptive-high maladaptive cognitive emotion regulation strategy group(n=519);the potential categories of cognitive emotion regulation of medical graduate students were significantly different in gender,only child or not,the purpose of postgraduate study and the distribution of experiential avoidance(P＜0.05);the experiential avoidance score of medical graduate students in the group of the high adaptive-medium ma-ladaptive and medium adaptive-high maladaptive cognitive emotion regulation strategies were lower[the scores were(13.42±8.65)and(16.05±6.53),respectively].Conclusion There is heterogeneity in cognitive emotion regulation of medical graduate students.According to the different characteristics of each category of medical graduate students,targeted intervention measurements should be given to weaken the use of non-adaptive cognitive emotion regulation strategies and promote the healthy development of their physical and mental health.
Medical masterCognitive emotion regulationLatent profile analysisEmpirical avoidanceInfluence factor
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NSTL
万方数据
