Open Access

ARTICLE

Latent Profile Analysis: Mattering Concepts, Problematic Internet Use, and Adaptability in Chinese University Students

Jianlong Wang^1,#, Xiumei Chen^1,2,#, Muqi Huang³, Rui Liu³, I-Hua Chen^4,5,*, Gordon L. Flett^6,*

1 Faculty of Education, Qufu Normal University, Qufu, 273165, China
2 School of Information Engineering, Shandong Youth University of Political Science, Jinan, 250103, China
3 International College, Krirk University, Bangkok, 10700, Thailand
4 Chinese Academy of Education Big Data, Qufu Normal University, Qufu, 273165, China
5 Jiangxi Psychological Consultant Association, Nanchang, 330000, China
6 LaMarsh Centre for Child and Youth Research, Department of Psychology, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada

* Corresponding Authors: I-Hua Chen. Email: ; Gordon L. Flett. Email:
# These authors contributed to the work equally and should be regarded as co-first authors

(This article belongs to the Special Issue: Mattering in the Digital Era: Exploring Its Role in Internet Use Patterns and Mental Health Outcomes)

International Journal of Mental Health Promotion 2025, 27(2), 241-256. https://doi.org/10.32604/ijmhp.2025.058503

Received 13 September 2024; Accepted 18 December 2024; Issue published 03 March 2025

Abstract

Background: This study addresses the pressing need to understand the nuanced relationship between ‘mattering’—the perception of being significant to others—and problematic internet use (PIU) among university students. Unlike previous research that has primarily employed variable-centered approaches, this study first adopts a person-centered approach using Latent Profile Analysis (LPA) to identify distinct mattering profiles. Subsequently, through variable-centered analyses, these profiles are examined in relation to different types of PIU—specifically problematic social media use (PSMU) and problematic gaming (PG)—as well as adaptability. Methods: Data were collected from 3587 university students across 19 universities in China. Participants completed three mattering-related scales (General Mattering Scale, Anti-Mattering Scale, and Fear of Not Mattering Inventory), along with the Bergen Social Media Addiction Scale, the Internet Gaming Disorder Scale-Short Form, and the Nine-item Adaptability Scale. Results: A four-class model identified by LPA was optimally selected: Class 1 (high general mattering, low anti-mattering, low fear of not mattering), Class 2 (moderate levels), Class 3 (moderate general mattering, high anti-mattering, high fear of not mattering), and Class 4 (low general mattering, low fear of not mattering, moderate anti-mattering). Significant differences were found among these classes in both PIU types (PSMU: F = 139.66, p < 0.001; PG: F = 162.96, p < 0.001). The pattern of mean differences consistently showed: Class 3 > Class 2 > Class 4 > Class 1. Class 3 participants demonstrated the highest likelihood of meeting the addiction criteria, Class 2 showed moderate probability, while Classes 1 and 4 exhibited lower probabilities (χ² = 113.38 to 408.87, all p < 0.001). Additionally, Class 3 reported the lowest adaptability (F = 131.67, p < 0.001). Conclusion: This study reveals that the unique influence of three ways of assessing feelings of mattering and the fear of not mattering on university students’ PIU at the personal level, concluding that these factors are integral to understanding PIU among this demographic.

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Keywords

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Supplementary Material

Supplementary Material File

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