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APA Journal of Abnormal Psychology

Identifying highly influential nodes in the complicated grief network.Open in a New Window

The network approach to psychopathology conceptualizes mental disorders as networks of mutually reinforcing nodes (i.e., symptoms). Researchers adopting this approach have suggested that network topology can be used to identify influential nodes, with nodes central to the network having the greatest influence on the development and maintenance of the disorder. However, because commonly used centrality indices do not distinguish between positive and negative edges, they may not adequately assess the nature and strength of a node’s influence within the network. To address this limitation, we developed 2 indices of a node’s expected influence (EI) that account for the presence of negative edges. To evaluate centrality and EI indices, we simulated single-node interventions on randomly generated networks. In networks with exclusively positive edges, centrality and EI were both strongly associated with observed node influence. In networks with negative edges, EI was more strongly associated with observed influence than was centrality. We then used data from a longitudinal study of bereavement to examine the association between (a) a node’s centrality and EI in the complicated grief (CG) network and (b) the strength of association between change in that node and change in the remainder of the CG network from 6- to 18-months postloss. Centrality and EI were both correlated with the strength of the association between node change and network change. Together, these findings suggest high-EI nodes, such as emotional pain and feelings of emptiness, may be especially important to the etiology and treatment of CG. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

 

Clinical and personality traits in emotional disorders: Evidence of a common framework.Open in a New Window

Certain clinical traits (e.g., ruminative response style, self-criticism, perfectionism, anxiety sensitivity, fear of negative evaluation, and thought suppression) increase the risk for and chronicity of emotional disorders. Similar to traditional personality traits, they are considered dispositional and typically show high temporal stability. Because the personality and clinical-traits literatures evolved largely independently, connections between them are not fully understood. We sought to map the interface between a widely studied set of clinical and personality traits. Two samples (N = 385 undergraduates; N = 188 psychiatric outpatients) completed measures of personality traits, clinical traits, and an interview-based assessment of emotional-disorder symptoms. First, the joint factor structure of these traits was examined in each sample. Second, structural equation modeling was used to clarify the effects of clinical traits in the prediction of clinical symptoms beyond negative temperament. Third, the incremental validity of clinical traits beyond a more comprehensive set of higher-order and lower-order personality traits was examined using hierarchical regression. Clinical and personality traits were highly correlated and jointly defined a 3-factor structure—Negative Temperament, Positive Temperament, and Disinhibition—in both samples, with all clinical traits loading on the Negative Temperament factor. Clinical traits showed modest but significant incremental validity in explaining symptoms after accounting for personality traits. These data indicate that clinical traits relevant to emotional disorders fit well within the traditional personality framework and offer some unique contributions to the prediction of psychopathology, but it is important to distinguish their effects from negative temperament/neuroticism. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

 

Attentional bias temporal dynamics in remitted depression.Open in a New Window

Theory implicates attentional bias (AB) or dysregulated attentional processing of emotional information in the recurrence of major depressive episodes. However, empirical study of AB among remitted depressed patients is limited in scope and has yielded mixed findings. Mixed findings may be accounted for by how the field has conceptualized and thereby studied AB. We propose that a novel temporal dynamic process perspective on AB may help disambiguate extant findings and elucidate the nature of AB in remitted depression. Thus, we reexamined Dot Probe data among remitted depressed patients (RMD; n = 328) and nondepressed controls (NDC; n = 82) that previously yielded null effects when AB was quantified by means of the traditional aggregated mean bias score (Vrijsen et al., 2014). We reanalyzed data using a novel computational approach that extracts a series of bias estimations from trial to trial (Zvielli, Bernstein, & Koster, 2015). Key features of these dynamic process signals revealed moderate to excellent reliability relative to the traditional aggregated mean bias scores. These features of AB dynamics—specifically temporal variability in AB including AB toward and away from emotional stimuli—were significantly elevated among RMDs relative to NDCs. Moreover, among RMDs, a greater number of past depressive episodes were associated with elevation in these features of AB dynamics. Effects were not accounted for by residual depressive symptoms or social anxiety symptoms. Findings indicate that dysregulation in attentional processing of emotional information reflected in AB dynamics may be key to depression vulnerability. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

 

Reduced model-based decision-making in schizophrenia.Open in a New Window

Individuals with schizophrenia have a diminished ability to use reward history to adaptively guide behavior. However, tasks traditionally used to assess such deficits often rely on multiple cognitive and neural processes, leaving etiology unresolved. In the current study, we adopted recent computational formalisms of reinforcement learning to distinguish between model-based and model-free decision-making in hopes of specifying mechanisms associated with reinforcement-learning dysfunction in schizophrenia. Under this framework, decision-making is model-free to the extent that it relies solely on prior reward history, and model-based if it relies on prospective information such as motivational state, future consequences, and the likelihood of obtaining various outcomes. Model-based and model-free decision-making was assessed in 33 schizophrenia patients and 30 controls using a 2-stage 2-alternative forced choice task previously demonstrated to discern individual differences in reliance on the 2 forms of reinforcement-learning. We show that, compared with controls, schizophrenia patients demonstrate decreased reliance on model-based decision-making. Further, parameter estimates of model-based behavior correlate positively with IQ and working memory measures, suggesting that model-based deficits seen in schizophrenia may be partially explained by higher-order cognitive deficits. These findings demonstrate specific reinforcement-learning and decision-making deficits and thereby provide valuable insights for understanding disordered behavior in schizophrenia. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

 

High resolution examination of the role of sleep disturbance in predicting functioning and psychotic symptoms in schizophrenia: A novel experience sampling study.Open in a New Window

Sleep disturbance is common in schizophrenia, but its role in predicting functioning and psychotic symptoms has yet to be rigorously examined. The purpose of this study was to conduct a prospective, high-resolution examination of the relationship between nightly sleep and next-day functioning and psychotic symptoms in people with a diagnosis of schizophrenia. Experience sampling methodology was integrated with actigraphy and sleep diaries across 7 days in 22 patients with a diagnosis of schizophrenia. Momentary assessments of mood, psychotic symptoms, and functioning were gathered at 5 points each day following pseudorandom schedules. Multilevel modeling was performed to evaluate the links between variables. Objective and subjective sleep disturbance predicted reduced next-day functioning, which remained significant after controlling for psychotic symptom severity. Increased sleep fragmentation and reduced subjective and objective sleep efficiency predicted greater next-day auditory hallucinations, whereas increased objective sleep fragmentation and reduced subjective sleep quality predicted greater paranoia and delusions of control. Negative affect on awakening mediated a proportion of these relationships (range: 17.9–57.3%). For the first time, we show that sleep disturbance is a predictor of next-day impaired functioning and psychotic symptom severity in people with a diagnosis of schizophrenia. Therefore, interventions targeting sleep may have the potential to directly and indirectly enhance functional and symptomatic recovery in those experiencing psychosis. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

 

The reciprocal predictive relationship between high-risk personality and drinking: An 8-wave longitudinal study in early adolescents.Open in a New Window

In youth, maladaptive personality traits such as urgency (the tendency to act rashly when highly emotional) predict early onset alcohol consumption. In adults, maladaptive behaviors, including substance use, predict negative personality change. This article reports on a test of hypothesized maladaptive, reciprocal prediction between youth drinking and the trait of urgency. In a sample of 1,906 youth assessed every 6 months from the spring of 5th grade through the spring of 8th grade, and again in the spring of 9th grade, the authors found such reciprocal prediction. Over each 6 month and then 12 month time lag, urgency predicted increased subsequent drinking. In addition, over 6 of the 7 time lags, drinking behavior predicted subsequent increases in urgency. During early adolescence, maladaptive personality and dysfunctional behavior each led to increases in the other. The results of this process include cyclically increasing risk for youth drinking and may include increasing risk for the multiple maladaptive behaviors predicted by the trait of urgency. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

 

A multimethod examination of negative behaviors during couples interactions and problem drinking trajectories.Open in a New Window

Models of alcohol use disorder (AUD) are increasingly conceptualizing social and relationship factors as being critical to the understanding of problem drinking. Close relationships involving conflict have been a particular research focus, and partners’ expressions of negative emotion are theorized to affect drinking among those with AUD. Although it has long been presumed that behaviors during couples interactions influence drinking—and this assumption has informed many modern treatments for AUD—this hypothesis has not been directly tested. We bring multiple methods to bear on this question, combining laboratory-based behavioral observation with a longitudinal design. Forty-eight individuals with AUD (probands), together with their partners, completed a laboratory-based conflict interaction. Their behavior was coded with the Rapid Marital Interaction Coding System. Longitudinal follow-ups of drinking behaviors were completed at 6 and 12 months. Results showed that, above and beyond the proband’s own behaviors, partner negative behaviors moderated probands’ drinking trajectories, with drinkers whose partners displayed higher levels of hostility at baseline reporting slower declines in frequency of drinking, heavy episodic drinking, and alcohol problems over time and higher levels of drinking, heavy episodic drinking, and alcohol problems at follow-up. Results emphasize the importance of considering close relationships in the study of AUD and further indicate the utility of combining multiple methods in alcohol research. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

 

Latent-variable modeling of brain gray-matter volume and psychopathy in incarcerated offenders.Open in a New Window

Advanced statistical modeling has become a prominent feature in psychological science and can be a useful approach for representing the neural architecture linked to psychopathology. Psychopathy, a disorder characterized by dysfunction in interpersonal-affective and impulsive-antisocial domains, is associated with widespread neural abnormalities. Several imaging studies suggest that underlying structural deficits in paralimbic regions are associated with psychopathy. Although these studies are useful, they make assumptions about the organization of the brain and its relevance to individuals displaying psychopathic features. Capitalizing on statistical modeling, in the present study (N = 254), we used latent-variable methods to examine the structure of gray-matter volume in male offenders, and assessed the latent relations between psychopathy and gray-matter factors reflecting paralimbic and nonparalimbic regions. Results revealed good fit for a 4-factor gray-matter paralimbic model and these first-order factors were accounted for by a superordinate paralimbic “system” factor. Moreover, a superordinate psychopathy factor significantly predicted the paralimbic, but not the nonparalimbic factor. The latent-variable paralimbic model, specifically linked with psychopathy, goes beyond understanding single brain regions within the system and provides evidence for psychopathy-related gray-matter volume reductions in the paralimbic system as a whole. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

 

Theory of mind is not theory of emotion: A cautionary note on the Reading the Mind in the Eyes Test.Open in a New Window

The ability to represent mental states (theory of mind [ToM]) is crucial in understanding individual differences in social ability and social impairments evident in conditions such as autism spectrum disorder (ASD). The Reading the Mind in the Eyes Test (RMET) is a popular measure of ToM ability, validated in part by the poor performance of those with ASD. However, the RMET requires recognition of facial emotion, which is impaired in those with alexithymia, which frequently co-occurs with ASD. Thus, it is unclear whether the RMET indexes emotion recognition, associated with alexithymia, or ToM, associated with ASD. We therefore investigated the independent contributions of ASD and alexithymia to performance on the RMET. ASD and alexithymia-matched control participants did not differ on RMET performance, whereas ASD participants demonstrated impaired performance on an alternative test of ToM, the Movie for Assessment of Social Cognition (MASC). Furthermore, alexithymia, but not ASD diagnosis, significantly influenced RMET performance but did not affect MASC performance. These results suggest that the RMET measures emotion recognition rather than ToM ability and support the alexithymia hypothesis of emotion-related deficits in ASD. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

 

Current evolutionary adaptiveness of psychiatric disorders: Fertility rates, parent−child relationship quality, and psychiatric disorders across the lifespan.Open in a New Window

This study sought to evaluate the current evolutionary adaptiveness of psychopathology by examining whether these disorders impact the quantity of offspring or the quality of the parent–child relationship across the life span. Using the National Comorbidity Survey, this study examined whether DSM–III–R anxiety, posttraumatic stress, depressive, bipolar, substance use, antisocial, and psychosis disorders predicted later fertility and the quality of parent–child relationships across the life span in a national sample (N = 8,098). Using latent variable and varying coefficient models, the results suggested that anxiety in males and bipolar pathology in males and females were associated with increased fertility at younger ages. The results suggested almost all other psychopathology was associated with decreased fertility in middle to late adulthood. The results further suggested that all types of psychopathology had negative impacts on the parent–child relationship quality (except for antisocial pathology in males). Nevertheless, for all disorders, the impact of psychopathology on both fertility and the parent–child relationship quality was affected by the age of the participant. The results also showed that anxiety pathology is associated with a high-quantity, low-quality parenting strategy followed by a low-quantity, low-quality parenting strategy. Further, the results suggest that bipolar pathology is associated with an early high-quantity and a continued low-quality parenting strategy. Posttraumatic stress, depression, substance use, antisocial personality, and psychosis pathology are each associated with a low-quantity, low-quality parenting strategy, particularly in mid to late adulthood. These findings suggest that the evolutionary impact of psychopathology depends on the developmental context. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

 

Unreliability as a threat to understanding psychopathology: The cautionary tale of attentional bias.Open in a New Window

[Correction Notice: An Erratum for this article was reported online in Journal of Abnormal Psychology on Sep 1 2016 (see record 2016-41990-001). In the original article, there was an error in the Author Note. It incorrectly stated, “Development of the MacBrain Face Stimulus Set was overseen by Nim Tottenham and supported by the Jonathan D. Huppert and Catherine T. MacArthur Foundation Research Network on Early Experience and Brain Development.” It should have stated, “Development of the MacBrain Face Stimulus Set was overseen by Nim Tottenham and supported by the John D. and Catherine T. MacArthur Foundation Research Network on Early Experience and Brain Development.” The online version of this article has been corrected.] The use of unreliable measures constitutes a threat to our understanding of psychopathology, because advancement of science using both behavioral and biologically oriented measures can only be certain if such measurements are reliable. Two pillars of the National Institute of Mental Health’s portfolio—the Research Domain Criteria (RDoC) initiative for psychopathology and the target engagement initiative in clinical trials—cannot succeed without measures that possess the high reliability necessary for tests involving mediation and selection based on individual differences. We focus on the historical lack of reliability of attentional bias measures as an illustration of how reliability can pose a threat to our understanding. Our own data replicate previous findings of poor reliability for traditionally used scores, which suggests a serious problem with the ability to test theories regarding attentional bias. This lack of reliability may also suggest problems with the assumption (in both theory and the formula for the scores) that attentional bias is consistent and stable across time. In contrast, measures accounting for attention as a dynamic process in time show good reliability in our data. The field is sorely in need of research reporting findings and reliability for attentional bias scores using multiple methods, including those focusing on dynamic processes over time. We urge researchers to test and report reliability of all measures, considering findings of low reliability not just as a nuisance but as an opportunity to modify and improve upon the underlying theory. Full assessment of reliability of measures will maximize the possibility that RDoC (and psychological science more generally) will succeed. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
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