Peer influence, Frontostriatal connectivity, and delay discounting in African American emerging adults

How and when is academic stress associated with mobile phone addiction? The roles of psychological distress, peer alienation and rumination

BACKGROUND

Mobile phone addiction has a high detection rate among adolescents and is thought to be related to academic stress. However, the underlying mechanisms in this relation were still unclear. The present study tested the mediating role of psychological distress and the moderating roles of peer alienation and rumination in the relationship between academic stress and mobile phone addiction.

METHODS

A total of 742 middle school students were recruited to complete measures of academic stress, psychological distress, mobile phone addiction, peer alienation, rumination, and demographic variables. Regression-based statistical mediation and moderation were conducted using the PROCESS macro for SPSS.

RESULTS

The results indicated that academic stress was significantly and positively associated with mobile phone addiction, and this link could be mediated by psychological distress. Moreover, this indirect effect was moderated by both peer alienation and rumination. Specifically, the mediating effect of psychological distress was stronger for adolescents with higher levels of peer alienation or adolescents with higher levels of rumination, as well as those with both higher levels of peer alienation and rumination.

CONCLUSION

The findings of this study enrich our understanding of how and for whom academic stress is correlated with mobile phone addiction. Education experts and parents should pay special attention to adolescents suffering from academic stress, especially those with higher peer alienation and rumination, and help them get rid of mobile phone addiction.

Spontaneous neural activity in the three principal networks underlying delay discounting: a resting-state fMRI study

Delay discounting, the decline in the subjective value of future rewards over time, has traditionally been understood through a tripartite neural network model, comprising the valuation, cognitive control, and prospection networks. To investigate the applicability of this model in a resting-state context, we employed a monetary choice questionnaire to quantify delay discounting and utilized resting-state functional magnetic resonance imaging (rs-fMRI) to explore the role of spontaneous brain activity, specifically regional homogeneity (ReHo), in influencing individual differences in delay discounting across a large cohort (N = 257). Preliminary analyses revealed a significant negative correlation between delay discounting tendencies and the ReHo in both the left insula and the right hippocampus, respectively. Subsequent resting-state functional connectivity (RSFC) analyses, using these regions as seed ROIs, disclosed that all implicated brain regions conform to the three principal networks traditionally associated with delay discounting. Our findings offer novel insights into the role of spontaneous neural activity in shaping individual variations in delay discounting at both regional and network levels, providing the first empirical evidence supporting the applicability of the tripartite network model in a resting-state context.

The Resting-State Neural Network of Delay Discounting

Delay discounting is a common phenomenon in daily life, which refers to the subjective value of a future reward decreasing as a function of time. Previous studies have identified several cortical regions involved in delay discounting, but the neural network constructed by the cortical regions of delay discounting is less clear. In this study, we employed resting-state functional magnetic resonance imaging (RS-fMRI) to measure the spontaneous neural activity in a large sample of healthy young adults and used the Monetary Choice Questionnaire to directly measure participants’ level of delay discounting. To identify the neural network of delay discounting at rest, we used an individual difference approach to explore brain regions whose spontaneous activities were related to delay discounting across the whole brain. Then, these brain regions served as seeds to identify the neural network of delay discounting. We found that the fractional amplitude of low-frequency fluctuations (fALFF) of the left insula were positively correlated to delay discounting. More importantly, its connectivity to the anterior cingulate cortex was read out for participants’ behavioral performance in the task of delay discounting. In short, our study provides empirical evidence that insula-anterior cingulate cortex connectivity may serve as a part of the neural network for delay discounting.