The roles of behavioral inhibition/activation systems and impulsivity in problematic smartphone use: A network analysis

Abstract

BackgroundBehavioral inhibition/activation systems (BIS/BAS) and impulsivity are associated with problematic smartphone use (PSU). However, no studies to date have explored how the subdomains of BIS/BAS and the dimensions of impulsivity relate to the components of PSU in a joint framework. This study aimed to examine the relationships between the three constructs at a fine-grained level and identify the central nodes and bridge nodes of their relationships using network analysis.MethodsA regularized partial correlation network of PSU, BIS/BAS, and impulsivity communities was estimated to investigate the connections between variables and determine the expected influence and bridge expected influence for each variable based on data from 325 Chinese adults. PSU, BIS/BAS, and impulsivity were assessed using the Smartphone Application-Based Addiction Scale (SABAS), BIS/BAS scales, and Barratt Impulsiveness Scale-Version 11 (BIS-11), respectively.ResultsIn addition to connections within each community, network analysis revealed that there were connections between different communities, especially connections to PSU. I2 “motor impulsivity” was strongly associated with PSU2 “conflict” and PSU6 “relapse”; BASR “BAS-reward responsiveness” was strongly associated with PSU5 “withdrawal.” Nodes BASR “BAS-reward responsiveness” and PSU6 “relapse” were the most central variables, while nodes BASR “BAS-reward responsiveness” and I2 “motor impulsivity” were the strongest bridge variables.ConclusionThe connections between the subdomains of BIS/BAS and the components of PSU and between the dimensions of impulsivity and the components of PSU may be particularly important in the development and maintenance of PSU. The central variables identified here, along with the bridge variables, could be promising and effective targets for the prevention and intervention of PSU.

The Relationships Between Suicidal Ideation, Meaning in Life, and Affect: a Network Analysis

“…Moreover, this study can be considered an important first primary investigation to the identifications of those interconnected variables in a fine-grained level, that may lead to suicidal ideation and then to potential suicide, which may provide ideas and inspiration for similar research in the future. Regarding the clinical implications, central nodes are critical for activating or inhibiting other nodes and contribute greatly to the development and maintenance of the overall network (Borsboom, 2017;Borsboom and Cramer, 2013;Robinaugh et al, 2016), and interventions targeting the central nodes could disrupt the entire network and mitigate the severity of mental problems, facilitating the treatment and prevention (Cai et al, 2022;Guo et al, 2022a;Haws et al, 2022;. In our study, search for meaning in life, sleep, despair, and positive affect were identified as central nodes; therefore, intervention strategies that alleviate search for meaning in life, sleep problems, and despair and strengthen positive affect are potential ways to reduce suicidal ideation.…”

“…In the present study, we conducted a network analysis of dimension-level meaning in life, affect, and suicidal ideation. Network analysis is an emerging data-driven approach to examine and visualize interactions between symptoms or non-symptoms (Beard et al, 2016;Borsboom, 2017;Borsboom and Cramer, 2013;Guo et al, 2022a). From a network theory perspective, mental disorders emerge from active interactions between symptoms or non-symptoms, rather than just passive reflections of latent variable (Borsboom, 2017;McNally, 2016).…”

“…This approach is distinct from the latent variable model and will shed new light on the underlying mechanisms of the formation and maintenance of suicidal ideation. Network analysis also provides centrality indices to determine central nodes that activate all other nodes and exert great influence on the overall network (Borsboom, 2017;Byrne et al, 2021;Guo et al, 2022a), and assesses bridge centrality indices to determine bridge nodes that are critical to maintaining the co-occurrence of variables and transmitting the influence of one variable on another (Guo et al, 2022a, b;Jones et al, 2021;Yuan et al, 2022). To date, the dimension-level network of meaning in life, affect, and suicidal ideation has not been studied.…”

Network analysis of affect, emotion regulation, psychological capital, and resilience among Chinese males during the late stage of the COVID-19 pandemic

“…According to network analysis theory, psychological constructs can be considered as a network emerging from interactions between different components (dimensions or items), in which nodes represent interacting components of constructs and edges represent correlation pathways between these components (49)(50)(51). Network analysis can graphically delineate these interactions to provide insights into the psychopathological mechanisms and develop targeted intervention strategies (52). Network analysis can also provide meaningful indices to evaluate the roles the nodes play in the network (53).…”

“…For example, the bridge expected influence (BEI) index is used to assess the influence of a given node on nodes of other psychological constructs. BEI can help to determine the bridge nodes that play important roles in maintaining the co-occurrence of constructs (54), which may be useful to inform interventions (52,(54)(55)(56). Network analysis has been applied in prior studies on psychological resilience.…”