Psychosocial boundaries of digital well-being: Exploring smartphone addiction, information overload, and sense of belonging in mobile ecosystem

18/08/2026

AI Summary

Smartphone addiction increases information overload, which mediates most of the negative effect on users' sense of belonging.
High self-control buffers the addiction to overload pathway, while social media fatigue amplifies overload's erosion of belonging.
A neural network detects non-linear threshold effects and predicts belonging deficits accurately, yet performance comparisons are cautious due to small test set.

AI Summary

This study investigates how smartphone addiction undermines sense of belonging, treated here as one key dimension of the broader digital well-being construct rather than as digital well-being in full, through the mediating role of information overload, with self-control and social media fatigue as boundary conditions.

The results reveal that smartphone addiction significantly predicts information overload, which in turn erodes sense of belonging; information overload mediates the majority of the total effect.

Practically, it provides actionable insights for platform management through ethical design to reduce overload, organizational policy through digital boundary setting, and user behavior management through self-control training and fatigue mitigation.

Basic summary

Arch Psychiatr Nurs. 2026 Aug;63:152164. doi: 10.1016/j.apnu.2026.152164. Epub 2026 Jun 9.

ABSTRACT

In the digital era, mobile applications have become ubiquitous in China’s organizational and daily life, creating a condition in which constant connectivity coexists with social disconnection, posing critical challenges to user well-being management. This study investigates how smartphone addiction undermines sense of belonging, treated here as one key dimension of the broader digital well-being construct rather than as digital well-being in full, through the mediating role of information overload, with self-control and social media fatigue as boundary conditions. Based on a sample of 326 Chinese mobile app users, we adopt a mixed-methods approach integrating structural equation modeling (SEM) and a feed-forward neural network to test a moderated mediation model. The results reveal that smartphone addiction significantly predicts information overload, which in turn erodes sense of belonging; information overload mediates the majority of the total effect. Self-control buffers the addiction-to-overload link, while social media fatigue amplifies the overload-to-belonging erosion. The neural network model achieves high accuracy in predicting belonging deficits and uncovers non-linear threshold effects not modelled by the linear SEM specification. Because the predictive comparison rests on a small hold-out test set (n = 49), between-model performance differences are interpreted with caution. Theoretically, this study integrates Cognitive Load Theory, Self-Regulation Theory, and Conservation of Resources Theory to advance digital well-being research in management. Practically, it provides actionable insights for platform management through ethical design to reduce overload, organizational policy through digital boundary setting, and user behavior management through self-control training and fatigue mitigation.

PMID:42608091 | DOI:10.1016/j.apnu.2026.152164

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