Development of the psychopathological vulnerability index for screening at-risk youths: a Rasch model approach

Yujing Liao; Haitao Shen; Wenjie Duan; Shanshan Cui; Chunxiu Zheng; Rong Liu; Yawen Jia

doi:10.1038/s44184-024-00106-6

Development of the psychopathological vulnerability index for screening at-risk youths: a Rasch model approach

Npj Ment Health Res. 2024 Dec 2;3(1):60. doi: 10.1038/s44184-024-00106-6.

Authors

Yujing Liao^#¹, Haitao Shen^#², Wenjie Duan^#³, Shanshan Cui⁴, Chunxiu Zheng⁴, Rong Liu⁵, Yawen Jia⁶

Affiliations

¹ Social and Public Administration School, East China University of Science and Technology, Shanghai, China.
² Institute of Marxism, East China University of Science and Technology, Shanghai, China.
³ Social and Public Administration School, East China University of Science and Technology, Shanghai, China. duan.w@outlook.com.
⁴ The Office of Student Services, East China University of Science and Technology, Shanghai, China.
⁵ Student Counseling and Mental Health Center, East China University of Science and Technology, Shanghai, China.
⁶ School of Journalism and Communication, Nanchang University, Nanchang, China.

^# Contributed equally.

PMID: 39623039
DOI: 10.1038/s44184-024-00106-6

Abstract

Accumulating research on mental health emphasizes the general factor of psychopathology (p-factor) that unites various mental health issues. This study develops a psychopathological vulnerability assessment for youths, evaluating its psychometric properties and clinical utility. An umbrella review conceptualized multifactor psychopathological vulnerability, leading to a 57-item pool. A total of 11,224 individuals participated in this study. The resulting 22-item psychopathological vulnerability index (PVI) fitted the unidimensional Rasch model, demonstrating a person separation reliability of 0.78 and a Cronbach's alpha of 0.84. Cut-off points of 11 and 5, derived from latent class analysis, were used to distinguish vulnerable and high-protection populations. The PVI's concurrent and predictive hit rates ranged from 36.00% to 53.57% in clinical samples. The PVI concretized the vulnerability-stress model for identifying at-risk youths and may facilitate universal interventions by integrating the theoretical foundations of bifactor S-1 models with key symptoms from network models for theoretically grounded approaches.

Grants and funding

Grant 23ZR1415000/the Natural Science Foundation of Shanghai