Self-control, smartphone addiction, negative attentional bias and insomnia symptoms among college students: a latent profile and network analysis.
- 1School of Nursing, Hubei University of Chinese Medicine, Wuhan, Hubei, China.
- 2School of Marxism, Hubei University of Chinese Medicine, Wuhan, Hubei, China.
- 3Hubei Shizhen Laboratory, Wuhan, Hubei, China.
Abstract
Insomnia symptoms are common among college students and may be associated with multiple psychological and behavioral characteristics. However, the relationships among self-control, smartphone addiction (SA), negative attentional bias, and insomnia symptoms remain unclear. This study aimed to identify latent profiles of self-control, SA, and negative attentional bias and further explore their network relationships with insomnia symptoms among college students. A cross-sectional survey was conducted among 1,597 Chinese college students. Latent profile analysis (LPA) was used to identify profiles based on self-control, SA, and negative attentional bias. Multivariable linear regression examined the associations between latent profile membership and Athens Insomnia Scale (AIS) scores. Network analysis was performed to identify central and bridge nodes, and the network comparison test (NCT) was used to compare network structures across latent profiles. Three latent profiles were identified: the Moderate Self-Control-Moderate SA and Negative Attention Profile (75.20%), the Low Self-Control-High SA and Negative Attention Profile (10.83%), and the High Self-Control-Low SA and Negative Attention Profile (13.96%). Compared with the High Self-Control-Low SA and Negative Attention Profile, the Moderate Self-Control-Moderate SA and Negative Attention Profile (B = 2.31, 95% CI: 1.75-2.86) and the Low Self-Control-High SA and Negative Attention Profile (B = 4.04, 95% CI: 3.27-4.81) were significantly associated with higher AIS scores (both p < 0.001). SA1 (Withdrawal behavior) had the highest expected influence (EI) in the overall network and across all three profiles, and also exhibited the highest bridge strength in the overall network. APNI-N (Negative attention) showed the second-highest bridge strength. After false discovery rate correction, the NCT showed no significant differences in either overall network structure or global strength across the three profiles. Three profiles of self-control, SA, and negative attentional bias were identified among college students and showed different associations with insomnia symptoms. Withdrawal behavior and negative attention emerged as important features of the psychological and behavioral network. These findings provide further insight into the joint patterns and interconnected characteristics associated with insomnia symptoms among college students.
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BibTeX
@article{zhang2026selfcontrol,
title = {{Self-control, smartphone addiction, negative attentional bias and insomnia symptoms among college students: a latent profile and network analysis.}},
author = {Xiaoming Zhang and Hanbin He and Bifa Zhu and Xinhong Zhu},
journal = {Frontiers in psychology},
year = {2026},
month = oct,
doi = {10.3389/fpsyg.2026.1976921},
url = {https://europepmc.org/article/MED/42953172},
note = {CC BY},
}
RIS
TY - JOUR
TI - Self-control, smartphone addiction, negative attentional bias and insomnia symptoms among college students: a latent profile and network analysis.
AU - Xiaoming Zhang
AU - Hanbin He
AU - Bifa Zhu
AU - Xinhong Zhu
PY - 2026
DA - 2026/10/14
JO - Frontiers in psychology
DO - 10.3389/fpsyg.2026.1976921
UR - https://europepmc.org/article/MED/42953172
AB - Insomnia symptoms are common among college students and may be associated with multiple psychological and behavioral characteristics. However, the relationships among self-control, smartphone addiction (SA), negative attentional bias, and insomnia symptoms remain unclear. This study aimed to identify latent profiles of self-control, SA, and negative attentional bias and further explore their network relationships with insomnia symptoms among college students. A cross-sectional survey was conducted among 1,597 Chinese college students. Latent profile analysis (LPA) was used to identify profiles based on self-control, SA, and negative attentional bias. Multivariable linear regression examined the associations between latent profile membership and Athens Insomnia Scale (AIS) scores. Network analysis was performed to identify central and bridge nodes, and the network comparison test (NCT) was used to compare network structures across latent profiles. Three latent profiles were identified: the Moderate Self-Control-Moderate SA and Negative Attention Profile (75.20%), the Low Self-Control-High SA and Negative Attention Profile (10.83%), and the High Self-Control-Low SA and Negative Attention Profile (13.96%). Compared with the High Self-Control-Low SA and Negative Attention Profile, the Moderate Self-Control-Moderate SA and Negative Attention Profile (B = 2.31, 95% CI: 1.75-2.86) and the Low Self-Control-High SA and Negative Attention Profile (B = 4.04, 95% CI: 3.27-4.81) were significantly associated with higher AIS scores (both p < 0.001). SA1 (Withdrawal behavior) had the highest expected influence (EI) in the overall network and across all three profiles, and also exhibited the highest bridge strength in the overall network. APNI-N (Negative attention) showed the second-highest bridge strength. After false discovery rate correction, the NCT showed no significant differences in either overall network structure or global strength across the three profiles. Three profiles of self-control, SA, and negative attentional bias were identified among college students and showed different associations with insomnia symptoms. Withdrawal behavior and negative attention emerged as important features of the psychological and behavioral network. These findings provide further insight into the joint patterns and interconnected characteristics associated with insomnia symptoms among college students.
SN - 1664-1078
ER -