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

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.

Authors

Publication Details

Journal
International Journal of Mental Health Promotion
Published
2025-01-01
DOI
https://doi.org/10.32604/ijmhp.2025.058503
Citations
4
Primary Topic
Social Media and Politics
Type
article
Field-Weighted Citation Impact
15.46
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Gordon L. Flett, Xiu‐Mei Chen, Rui Liu, I‐Hua Chen et al.
4 citations
International Journal of Mental Health Promotion
Social Media and Politics
15.46
article

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

Gordon L. Flett, Xiu‐Mei Chen, Rui Liu, I‐Hua Chen, Jianlong Wang, Ming‐Ju Huang
article en
4 citations

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.

International Journal of Mental Health PromotionVol. 27(2)
Openalex Percentile: Top 2%
Social Media and Politics
15.46
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.