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Latent Profile Analysis in Mental Health Research: Exploring Heterogeneity through Person Centric Approach

Submission Deadline: 31 October 2025 (closed) View: 795 Submit to Journal

Guest Editors

Dr. Md Zahir Ahmed

Email: ahmedzahirdu@gmail.com

Affiliation: School of Psychology, Zhejiang Normal University, 321004, Jinhua, China

Homepage:

Research Interests: Mental health; suicide ideation; bullying; disaster; social determinants

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Prof. Aibao Zhou

Email: zhouab@nwnu.edu.cn

Affiliation: School of Psychology, Northwest Normal University, 730070, Lanzhou, China

Homepage:

Research Interests: mental health; self-concept; disaster; experimental psychology

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Summary

Mental health disorders represent a complex and heterogeneous group of conditions that are influenced by a range of psychological, social, and biological factors. Traditional variable-centered approaches to mental health often focus on generalized symptom profiles or categorical diagnoses. However, these approaches fail to capture the underlying complexity of mental health experiences. Latent Profile Analysis (LPA) offers a person-centered approach that allows for the identification of unobserved subgroups within mental health populations based on shared patterns of symptoms, behaviors, or psychosocial characteristics.

The scope of this special issue of the International Journal of Mental Health Promotion extends to examining the power of LPA in advancing mental health research by highlighting how it can uncover diverse subgroups within various mental health conditions and improve diagnostic precision. Through LPA, researchers can better understand the varying symptom profiles of individuals with conditions like depression, anxiety, PTSD, and substance use disorders, ultimately contributing to more personalized treatment approaches. This issue will explore the potential of LPA in identifying distinct mental health profiles, understanding the trajectories of mental health over time, and developing tailored interventions. We invite contributions that examine the application of LPA in clinical settings, its role in treatment matching, and its ability to inform policy and practice. By embracing the complexity of mental health, this issue seeks to promote personalized, effective interventions that improve mental health outcomes globally.

Keywords

Latent Profile Analysis; Mental health; Heterogeneity; Personalized treatment; Depression; Anxiety; PTSD; Substance use; Psychopathology profiling; Intervention; Longitudinal trajectories

Published Papers

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ARTICLE

The Relationship between Emotional Labor Strategies and Job Performance of Rotating Teachers: A Latent Profile Analysis
Huanfang Wang, Xinyi Li, Fangfang Zhao, Ximeng Cui, Weijian Li
International Journal of Mental Health Promotion, Vol.27, No.11, pp. 1813-1827, 2025, DOI:10.32604/ijmhp.2025.069623
（This article belongs to the Special Issue: Latent Profile Analysis in Mental Health Research: Exploring Heterogeneity through Person Centric Approach)
Abstract Background: In China, the policy of rotating teachers between urban and rural schools has been implemented to reduce educational disparities and ensure equitable access to quality education. These teachers face unique professional and emotional challenges during the rotation process, making their emotional labor a critical factor influencing their job performance. This study aimed to explore the relationship between rotating teachers’ emotional labor strategies and job performance. Methods: This study conducted a cross-sectional survey among 577 rotating teachers selected through stratified random sampling from primary and secondary schools in mainland China. Date were collected using the Teacher… More >

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ARTICLE

Exploring Adolescents’ Social Anxiety, Physical Activity, and Core Self-Evaluation: A Latent Profile and Mediation Approach
Huazhe Wan, Wenying Huang, Wen Zhang, Chang Hu
International Journal of Mental Health Promotion, Vol.27, No.10, pp. 1611-1626, 2025, DOI:10.32604/ijmhp.2025.070457
（This article belongs to the Special Issue: Latent Profile Analysis in Mental Health Research: Exploring Heterogeneity through Person Centric Approach)
Abstract Background: Social anxiety is prevalent among adolescents and severely impacts their mental health and social functioning. This study aims to explore the underlying mechanisms and subgroup differences in adolescent social anxiety to provide a theoretical basis for targeted interventions. Methods: 3025 Chinese adolescents (Mean_age = 13.91 ± 1.60 years; 47% male) completed self-report measures of physical activity, core self-evaluation, and social anxiety. Variable-centered analyses employed PROCESS Model 4 with 5000 bootstrap samples; covariates were gender, grade, and place of residence. Person-centered analyses used latent profile analysis in Mplus 8.3 to identify subgroups based on social anxiety… More >

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ARTICLE

Moral Disengagement, Preference for Solitude, and Demographic Factors as Predictors of Aggressive Behavior Categorized by Latent Profile Analysis in Chinese Rural Boarding Junior High School Students
Yatong Li, Wangqin Hu
International Journal of Mental Health Promotion, Vol.27, No.9, pp. 1383-1398, 2025, DOI:10.32604/ijmhp.2025.066974
（This article belongs to the Special Issue: Latent Profile Analysis in Mental Health Research: Exploring Heterogeneity through Person Centric Approach)
Abstract Objectives: Adolescents’ aggression is widely studied, the underlying heterogeneity of aggression among rural Chinese boarding students remains unexplored. This study investigates the latent profiles of Chinese rural boarding junior high school students’ aggression and its correlations with moral disengagement and preference for solitude. Methods: A cross-sectional survey was conducted from 04–22 April 2022, using a convenient sampling method among 516 junior high school students from six Chinese rural boarding schools. The survey included the Aggression Questionnaire, the Moral Disengagement Scale (MDS), and the Preference for Solitude Scale (PSS). Results: Participants were divided into three latent… More >

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ARTICLE

The Developmental Trajectory of Family Functioning in Junior High School Students: Effects on Preference for Solitude and Social Avoidance
Liuyan Ren, Ruining Wang, Hohjin Im, Baojuan Ye, Qi Dai
International Journal of Mental Health Promotion, Vol.27, No.6, pp. 809-822, 2025, DOI:10.32604/ijmhp.2025.065246
（This article belongs to the Special Issue: Latent Profile Analysis in Mental Health Research: Exploring Heterogeneity through Person Centric Approach)
Abstract Objectives: Positive family functioning (FF) is critical for adolescent development, yet only a few studies have examined this developmental trajectory pathway. This study aimed to identify different types of FF development trajectories during junior high school students, investigate their influence on social avoidance (SA), and further examine the mediating role of preference for solitude (PS) between them. Methods: A three-wave longitudinal study was used with six-month intervals. Questionnaire data were collected from 436 junior high school students in Jiangxi Province, China. Participants ranged in age from 11 to 14 years old (Mean = 12.89 years,… More >

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ARTICLE

Possible Classifications of Social Network Addiction: A Latent Profile Analysis of Chinese College Students
Lin Luo, Junfeng Yuan, Yanling Wang, Rui Zhu, Huilin Xu, Siyuan Bi, Zhongge Zhang
International Journal of Mental Health Promotion, Vol.27, No.6, pp. 863-876, 2025, DOI:10.32604/ijmhp.2025.064385
（This article belongs to the Special Issue: Latent Profile Analysis in Mental Health Research: Exploring Heterogeneity through Person Centric Approach)
Abstract Objectives: Social Network Addiction (SNA) is becoming increasingly prevalent among college students; however, there remains a lack of consensus regarding the measurement tools and their optimal cutoff score. This study aims to validate the 21-item Social Network Addiction Scale-Chinese (SNAS-C) in its Chinese version and to determine its optimal cutoff score for identifying potential SNA cases within the college student population. Methods: A cross-sectional survey was conducted, recruiting 3387 college students. Latent profile analysis (LPA) and receiver operating characteristic (ROC) curve analysis were employed to establish the optimal cutoff score for the validated 21-item SNAS-C. Results:… More >

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Latent Profile Analysis in Mental Health Research: Exploring Heterogeneity through Person Centric Approach

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