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.

BackgroundPrior studies have revealed the relationships between impulsivity and social media addiction (SMA) and between impulsivity and problematic smartphone use (PSU) based on total scores on standardized self-report scales. However, there has been a lack of studies exploring how the dimensions of impulsivity and components of SMA or PSU are interrelated. The present study aimed to investigate the structural relationships between the dimensions of impulsivity and components of SMA and PSU and determine the critical bridge node using network analysis.MethodsA total of 325 healthy adults aged 18–36 years participated in the study. SMA and PSU were assessed using the Bergen Social Media Addiction Scale (BSMAS) and Smartphone Application-Based Addiction Scale (SABAS), respectively. Impulsivity was measured by the Barratt Impulsiveness Scale Version 11 (BIS-11). Network analysis was used to construct an SMA-Impulsivity network and a PSU-Impulsivity network. Bridge centrality (bridge expected influence, BEI) was estimated to identify influential bridge nodes.ResultsIn addition to relationships within each community, network analysis revealed that the dimensions of impulsivity were closely associated with the components of SMA and PSU. Particularly, I2 “motor impulsivity” had a relatively strong connection with SMA3 “mood modification” and SMA4 “relapse” in the SMA-Impulsivity network, and with PSU2 “conflict” and PSU5 “withdrawal” in the PSU-Impulsivity network. Moreover, I2 “motor impulsivity” was identified as the most critical bridge node in both networks.ConclusionThese findings demonstrate potential pathways between different dimensions of impulsivity and the components of SMA and PSU, providing new evidence relevant to understanding the underlying mechanisms that account for how highly impulsive individuals develop SMA and PSU, and highlight the critical bridge node—motor impulsivity—that may be a promising and effective target for the prevention and treatment of SMA and PSU.

Prior studies have focused on single-target anodal transcranial direct current stimulation (tDCS) over the right inferior frontal gyrus (rIFG) or pre-supplementary motor area (pre-SMA) to improve response inhibition in healthy individuals. However, the results are contradictory and the effect of multitarget anodal stimulation over both brain regions has never been investigated. The present study aimed to investigate the behavioral and neurophysiological effects of different forms of anodal high-definition tDCS (HD-tDCS) on improving response inhibition, including HD-tDCS over the rIFG or pre-SMA and multitarget HD-tDCS over both areas. Ninety-two healthy participants were randomly assigned to receive single-session (20 min) anodal HD-tDCS over rIFG + pre-SMA, rIFG, pre-SMA, or sham stimulation. Before and immediately after tDCS intervention, participants completed a stop-signal task (SST) and a go/nogo task (GNG). Their cortical activity was recorded using functional near-infrared spectroscopy (fNIRS) during the go/nogo task. The results showed multitarget stimulation produced a significant reduction in stop-signal reaction time (SSRT) relative to baseline. The pre-to-post SSRT change was not significant for rIFG, pre-SMA, or sham stimulation. Further analyses revealed multitarget HD-tDCS significantly decreased SSRT in both the high-performance and low-performance subgroups compared with the rIFG condition which decreased SSRT only in the low-performance subgroup. Only the multitarget condition significantly improved neural efficiency as indexed by lower △oxy-Hb after stimulation. In conclusion, the present study provides important preliminary evidence that multitarget HD-tDCS is a promising avenue to improve stimulation efficacy, establishing a more effective montage to enhance response inhibition relative to the commonly used single-target stimulation.

This study aimed to explore the mediating and moderating effects of resilience and perseverance on pilots’ self-efficacy and capability of handling special situations. Using cluster sampling, 251 pilots’ self-efficacy, special flight situation handling capability, resilience and perseverance were assessed using standardized scales. Pilots with high self-efficacy can improve their resilience to enhance their capability to handle special situations. An analysis was performed that included perseverance in the mediation model, and results showed that the influence of self-efficacy on special situation handling through resilience was moderated by perseverance. The relations between self-efficacy and special flight situation handling capability present a moderated mediation model. A pilot’s capability of handling special situations, ensuring flight safety and combat capability may be enhanced by improving their self-efficacy, resilience, and perseverance.

BackgroundProblematic smartphone use (PSU) is associated with both anxiety and depression. However, the relationships between components of PSU and symptoms of anxiety or depression have not been investigated. Hence, the aim of this study was to closely examine the relationships between PSU and anxiety and depression to identify the pathological mechanisms underpinning those relationships. A second aim was to identify important bridge nodes to identify potential targets for intervention.MethodsSymptom-level network structures of PSU and anxiety, and PSU and depression were constructed to investigate the connections between the variables and evaluate the bridge expected influence (BEI) of each node. Network analysis using data from 325 Chinese healthy college students was performed.ResultsFive strongest edges appeared within the communities in both the PSU-anxiety and PSU-depression networks. The “Withdrawal” component had more connections with symptoms of anxiety or depression than any other PSU node. In particular, the edges between “Withdrawal” and “Restlessness” and between “Withdrawal” and “Concentration difficulties” were the strongest cross-community edges in the PSU-anxiety network and PSU-depression network, respectively. Furthermore, “Withdrawal” had the highest BEI in the PSU community in both networks.ConclusionsThese findings provide preliminary evidence of the pathological pathways linking PSU with anxiety and depression, with “Withdrawal” linking PSU with both anxiety and depression. Hence, “Withdrawal” may be a potential target for preventing and intervening in cases of anxiety or depression.