Journal of abnormal psychology最新文献

Posttraumatic stress disorder (PTSD) researchers have increasingly used psychological network models to investigate PTSD symptom interactions, as well as to identify central driver symptoms. It is unclear, however, how generalizable such results are. We have developed a meta-analytic framework for aggregating network studies while taking between-study heterogeneity into account and applied this framework in the first-ever meta-analytic study of PTSD symptom networks. We analyzed the correlational structures of 52 different samples with a total sample size of n = 29,561 and estimated a single pooled network model underlying the data sets, investigated the scope of between-study heterogeneity, and assessed the performance of network models estimated from single studies. Our main findings are that: (a) We identified large between-study heterogeneity, indicating that it should be expected for networks of single studies to not perfectly align with one-another, and meta-analytic approaches are vital for the study of PTSD networks. (b) While several clear symptom-links, interpretable clusters, and significant differences between strength of edges and centrality of nodes can be identified in the network, no single or small set of nodes that clearly played a more central role than other nodes could be pinpointed, except for the symptom "amnesia" that was clearly the least central symptom. (c) Despite large between-study heterogeneity, we found that network models estimated from single samples can lead to similar network structures as the pooled network model. We discuss the implications of these findings for both the PTSD literature as well as methodological literature on network psychometrics. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Substance use and addiction are prominent global health concerns and are associated with abnormalities in reward sensitivity. Reward sensitivity and approach motivation are supported by a fronto-striatal neural circuit including the orbitofrontal cortex (OFC), ventral striatum (VS), and dorsal striatum (DS). Although research highlights abnormalities in reward neural circuitry among individuals with problematic substance use, questions remain about whether such use arises from excessively high, or excessively low, reward sensitivity. This study examined whether reward-related brain function predicted subsequent substance use course. Participants were 79 right-handed individuals (M_age = 21.52, SD = 2.19 years), who completed a monetary incentive delay (MID) fMRI task, and follow-up measures assessing substance use frequency and impairment. The average duration of the follow-up period was 9.1 months. Regions-of-interest analyses focused on the reward anticipation phase of the MID. Decreased activation in the VS during reward anticipation predicted increased substance use frequency at follow-up. Decreased DS activation during reward anticipation predicted increased substance use frequency at follow-up, but this finding did not pass correction for multiple comparisons. Analyses adjusted for relevant covariates, including baseline substance use and the presence or absence of a lifetime substance use disorder prior to MRI scanning. Results support the reward hyposensitivity theory, suggesting that decreased reward-related brain function is a risk factor for increased substance use. Results have implications for understanding the pathophysiology of problematic substance use and highlight the importance of the fronto-striatal reward circuit in the development and maintenance of addiction. (PsycInfo Database Record (c) 2021 APA, all rights reserved).