A network analysis of problematic smartphone use symptoms in a student sample

Abstract

Background and aimsPrevious research has established risk factors for problematic smartphone use (PSU), but few studies to date have explored the structure of PSU symptoms. This study capitalizes on network analysis to identify the core symptoms of PSU in a large sample of students.MethodsThis research investigated 26,950 grade 4 students (male = 13,271) and 11,687 grade 8 students (male = 5,739) using the smartphone addiction proneness scale (SAPS). The collected data were analyzed using a network analysis method, which can provide centrality indexes to determine the core symptoms of PSU. The two networks from the different groups were compared using a permutation test.ResultsThe results indicated that the core symptoms of students' problematic smartphone use were the loss of control and continued excessive use across the two samples.Discussion and conclusionsThese findings suggest that loss of control is a key feature of problematic smartphone use. The results also provide some evidence relevant to previous research from the perspective of network analysis and some suggestions for future treatment or prevention of students' problematic smartphone use.

Understanding juveniles’ problematic smartphone use and related influencing factors: A network perspective

“…This result may indicate that peer attitudes towards smartphone use and the parent-child relationship are both prominent in this network. For loss of control, our results extended research by Huang et al, (2020) that loss of control was still a core symptom of PSU, even when PSU was placed into a network full of other influencing factors. Therefore, we believe that the three factors and the core symptoms are the central variables connecting the whole network.…”

“…This scale has gained popularity among researchers (Lee & Ogbolu, 2018;Meeus, Eggermont, & Beullens, 2019). We used a revised Chinese version scale (Huang et al, 2020), which consists of 16 items and includes 4 dimensions: (1) disturbance of adaptive functions, (2) withdrawal, (3) tolerance, and (4) virtual life orientation. The higher the score is, the higher the tendency for PSU is.…”

“…The higher the score is, the higher the tendency for PSU is. In this research, Cronbach's a of the scale was 0.901, and the 16 items were considered the juveniles' 16 PSU symptoms (as suggested by Huang et al, 2020) when conducting network analysis. Based on the peer contagion hypothesis (Dishion & Tipsord, 2011) in which peer behavior, attitude, and pressure influence juveniles' behaviors, and the same is true of peer PSU, attitudes, and pressure for smartphone use.…”

“…Few researchers have attempted to explore the interactions of PSU. Rather, they have mainly focused on the inner symptoms of PSU (Andrade, Scatena, Martins, et al, 2020;Huang, Lai, Xue, Zhang, & Wang, 2020). For example, researchers have explored the central symptoms of PSU (Huang et al, 2020) or the validation of the smartphone addiction scale Andrade, Scatena, Martins, et al, 2020) from a network analysis perspective.…”

“…Rather, they have mainly focused on the inner symptoms of PSU (Andrade, Scatena, Martins, et al, 2020;Huang, Lai, Xue, Zhang, & Wang, 2020). For example, researchers have explored the central symptoms of PSU (Huang et al, 2020) or the validation of the smartphone addiction scale Andrade, Scatena, Martins, et al, 2020) from a network analysis perspective. In addition, several researchers have explored the interaction between Internet addiction and psychological symptoms from a network aspect (Andrade, Scatena, Bedendo, et al, 2020).…”