The Correlation Mechanism between Future Thinking and Problematic Network Use: An Analysis Based on Network Models

Qi Huaiyuan; Li Jiangyong; Wang Junyi; Luo Yangmei

doi:10.16719/j.cnki.1671-6981.20250216

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Journal of Psychological Science ›› 2025, Vol. 48 ›› Issue (2) : 435-446. DOI: 10.16719/j.cnki.1671-6981.20250216

Social, Personality & Organizational Psychology

The Correlation Mechanism between Future Thinking and Problematic Network Use: An Analysis Based on Network Models

Qi Huaiyuan, Li Jiangyong, Wang Junyi, Luo Yangmei

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Abstract

With the increasing use of internet devices, the prevalence of problematic internet use (PIU) has steadily increased. PIU is a clinical psychological disorder resulting from excessive internet use, with global prevalence rates ranging from 12.6% to 67.5%. PIU increases the risk of academic difficulties, negative emotions, sleep disturbances, and aggressive behaviors. It is also associated with a disregard for long-term future considerations. Future thinking, a psychological process that involves planning and predicting future scenarios, is closely linked to the development of PIU. It encompasses psychological experiences of future scenarios, self-perception, and cognitive processing of future values and emotions. A deficiency in future thinking may lead individuals to overlook the long-term consequences of internet use, thereby increasing the risk of excessive use. The future-oriented cognition model suggests that clear future expectations lead to activities like simulation, prediction, and planning, which can enhance long-term consideration and self-control. Thus, having clear expectations about future events can enhance individuals'consideration of long-term impacts, making them more likely to reflect on the potential academic, social, and health-related risks of PIU, and promoting goal-directed behavior and self-control to mitigate current excessive internet use. However, current research on the relationship between future thinking and PIU remains limited, with most existing studies focusing on the association between individual variables and PIU. The development of PIU involves complex interactions among multiple aspects of future thinking. Therefore, understanding the interplay between different components of future thinking and PIU is crucial for developing effective interventions to mitigate PIU.
This study analyzed data from 2,685 undergraduate students across eight universities in China. The cognitive components of future thinking (i.e., episodic future thinking, future self-continuity, and delay discounting), the emotional component (i.e., anticipatory pleasure), and the individual difference component (i.e., time perspective) were measured, along with the degree of PIU. Network analysis was employed to examine the complex relationships between these variables, and simulation intervention algorithms were used to identify potential intervention targets. Spearman correlations were first calculated to generate a heat map of the correlation matrix. Network analysis was then performed with 18 factors, including PIU sub-dimensions, as nodes, using a regularized partial correlation glasso network model. Finally, an Ising network model was constructed to simulate the effects of node changes on PIU and to identify key intervention targets. The NodeIdentifyR algorithm simulated 5,000 participants, applying two types of interventions to each node in the network: (1) Alleviating intervention, which reduced the node’s original parameter values by two standard deviations to simulate improved performance, and (2) Aggravating intervention, which increased the node’s original parameter values by two standard deviations to simulate worsened performance. The “sum score” indicator was used to assess the overall effect of each intervention on the three sub-symptoms of PIU.
The results indicated that (1) Multiple dimensions of future thinking (i.e., episodic future thinking, future self-continuity, delay discounting, and anticipatory pleasure) and future positivity were significantly negatively correlated with PIU and acted as protective factors. (2) In the network model, time perspective was identified as a distal factor for PIU, with future thinking serving as a mediating factor between time perspective and PIU. (3) Clarity of anticipation was found to be the most effective intervention target for preventing the worsening of PIU symptoms, while vividness of the future self was identified as the best intervention target for improving PIU symptoms.
These findings highlight the importance of understanding the complex interactions that contribute to PIU. By focusing on the most influential ones, as identified by simulation algorithms, interventions can be more targeted and effective. Addressing key factors such as the clarity of future expectations and vividness of future self-image can help individuals better understand the long-term effects of internet use, leading to improved self-control and reduced impulsive behaviors. Training people to think more clearly about future scenarios and strengthening their connection to their future selves can help reduce PIU symptoms and prevent excessive internet use in the long term.

Key words

problematic internet use / future thinking / time perspective / network analysis methods / simulation intervention

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Qi Huaiyuan, Li Jiangyong, Wang Junyi, Luo Yangmei. The Correlation Mechanism between Future Thinking and Problematic Network Use: An Analysis Based on Network Models[J]. Journal of Psychological Science. 2025, 48(2): 435-446 https://doi.org/10.16719/j.cnki.1671-6981.20250216

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