Showing papers in "Journal of Abnormal Psychology in 2019"
TL;DR: Cultural trends contributing to an increase in mood disorders and suicidal thoughts and behaviors since the mid-2000s, including the rise of electronic communication and digital media and declines in sleep duration, may have had a larger impact on younger people, creating a cohort effect.
Abstract: Drawing from the National Survey on Drug Use and Health (NSDUH; N = 611,880), a nationally representative survey of U.S. adolescents and adults, we assess age, period, and cohort trends in mood disorders and suicide-related outcomes since the mid-2000s. Rates of major depressive episode in the last year increased 52% 2005-2017 (from 8.7% to 13.2%) among adolescents aged 12 to 17 and 63% 2009-2017 (from 8.1% to 13.2%) among young adults 18-25. Serious psychological distress in the last month and suicide-related outcomes (suicidal ideation, plans, attempts, and deaths by suicide) in the last year also increased among young adults 18-25 from 2008-2017 (with a 71% increase in serious psychological distress), with less consistent and weaker increases among adults ages 26 and over. Hierarchical linear modeling analyses separating the effects of age, period, and birth cohort suggest the trends among adults are primarily due to cohort, with a steady rise in mood disorder and suicide-related outcomes between cohorts born from the early 1980s (Millennials) to the late 1990s (iGen). Cultural trends contributing to an increase in mood disorders and suicidal thoughts and behaviors since the mid-2000s, including the rise of electronic communication and digital media and declines in sleep duration, may have had a larger impact on younger people, creating a cohort effect. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
681 citations
TL;DR: Critically examine several issues with the use of the most popular centrality indices in psychological networks: degree, betweenness, and closeness centrality, and conclude that betweenness and closness centrality seem especially unsuitable as measures of node importance.
Abstract: Centrality indices are a popular tool to analyze structural aspects of psychological networks. As centrality indices were originally developed in the context of social networks, it is unclear to what extent these indices are suitable in a psychological network context. In this article we critically examine several issues with the use of the most popular centrality indices in psychological networks: degree, betweenness, and closeness centrality. We show that problems with centrality indices discussed in the social network literature also apply to the psychological networks. Assumptions underlying centrality indices, such as presence of a flow and shortest paths, may not correspond with a general theory of how psychological variables relate to one another. Furthermore, the assumptions of node distinctiveness and node exchangeability may not hold in psychological networks. We conclude that, for psychological networks, betweenness and closeness centrality seem especially unsuitable as measures of node importance. We therefore suggest three ways forward: (a) using centrality measures that are tailored to the psychological network context, (b) reconsidering existing measures of importance used in statistical models underlying psychological networks, and (c) discarding the concept of node centrality entirely. Foremost, we argue that one has to make explicit what one means when one states that a node is central, and what assumptions the centrality measure of choice entails, to make sure that there is a match between the process under study and the centrality measure that is used. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
438 citations
TL;DR: Comparisons of bifactor models to alternatives using fit indices may be misleading and call into question the evidentiary meaning of previous studies that identified the b ifactor model as superior based on fit.
Abstract: Structural models of psychopathology provide dimensional alternatives to traditional categorical classification systems. Competing models, such as the bifactor and correlated factors models, are typically compared via statistical indices to assess how well each model fits the same data. However, simulation studies have found evidence for probifactor fit index bias in several psychological research domains. The present study sought to extend this research to models of psychopathology, wherein the bifactor model has received much attention, but its susceptibility to bias is not well characterized. We used Monte Carlo simulations to examine how various model misspecifications produced fit index bias for 2 commonly used estimators, WLSMV and MLR. We simulated binary indicators to represent psychiatric diagnoses and positively skewed continuous indicators to represent symptom counts. Across combinations of estimators, indicator distributions, and misspecifications, complex patterns of bias emerged, with fit indices more often than not failing to correctly identify the correlated factors model as the data-generating model. No fit index emerged as reliably unbiased across all misspecification scenarios. Although, tests of model equivalence indicated that in one instance fit indices were not biased-they favored the bifactor model, albeit not unfairly. Overall, results suggest that comparisons of bifactor models to alternatives using fit indices may be misleading and call into question the evidentiary meaning of previous studies that identified the bifactor model as superior based on fit. We highlight the importance of comparing models based on substantive interpretability and their utility for addressing study aims, the methodological significance of model equivalence, as well as the need for implementation of statistical metrics that evaluate model quality. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
88 citations
University of Pittsburgh1, Boston Children's Hospital2, University of Washington3, University of South Carolina4, Yale University5, University of Calgary6, University of California, Los Angeles7, Kennedy Krieger Institute8, Johns Hopkins University9, Harvard University10, University of Miami11, University of California, Davis12, Glenrose Rehabilitation Hospital13, University of Alberta14, Boston University15, University of Minnesota16, Hebrew University of Jerusalem17
TL;DR: Overall and item-level performance on the gross (GM) and fine motor (FM) subscales of the Mullen Scales of Early Learning administered at 6 months to a large, geographically diverse sample of HR infants with varying developmental outcomes was examined.
Abstract: Research has identified early appearing differences in gross and fine motor abilities in infants at heightened risk (HR) for autism spectrum disorder (ASD) because they are the younger siblings of children with ASD, and it suggests that such differences may be especially apparent among those HR infants themselves eventually diagnosed with ASD. The present study examined overall and item-level performance on the gross (GM) and fine motor (FM) subscales of the Mullen Scales of Early Learning (MSEL) administered at 6 months to a large, geographically diverse sample of HR infants with varying developmental outcomes (ASD, elevated ADOS without ASD, low ADOS without ASD) and to infants with low ASD risk (low risk [LR]). We also explored whether motor abilities assessed at 6 months predicted ASD symptom severity at 36 months. FM (but not GM) performance distinguished all 3 HR groups from LR infants with the weakest performance observed in the HR-Elevated ADOS children, who exhibited multiple differences from both LR and other HR infants in both gross and fine motor skills. Finally, 6-month FM (but not GM) scores significant predicted 36-month ADOS severity scores in the HR group; but no evidence was found of specific early appearing motor signs associated with a later ASD diagnosis. Vulnerabilities in infants' fine and gross motor skills may have significant consequences for later development not only in the motor domain but in other domains. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
82 citations
TL;DR: These data are consistent with prior work in adults linking depression, episodic memory, emotion regulation, life stress/adversity, and hippocampal volume in adults and suggest similar relations are evident as early as adolescence when memory systems are under development.
Abstract: Depression in adults is associated with deficits in a number of cognitive domains, however it remains less clear how early in development theses deficits can be detected in early onset depression. There are several different hypotheses about the links between cognitive function and depression. For example, it has been argued that executive function deficits contribute to emotion regulation difficulties, which in turn increase risk for depression. Further, it has been suggested that some cognitive deficits, such as episodic memory, may reflect hippocampal abnormalities linked to both depression and episodic memory. We examined these questions in adolescents participating in a longitudinal study of preschool onset depression. We measured cognitive function at adolescence using the National Institutes of Health toolbox (vocabulary, processing speed, executive function, working memory and episodic memory), and examined relationships of cognitive deficits to depression, emotion regulation, life stress and adversity, as well as hippocampal volume trajectories over three imaging assessments starting at school age. Depression related deficits in episodic memory were found. Youths with either current and past depression showed episodic memory deficits even after controlling for other psychopathology and family income. Depression severity, emotion dysregulation, and life stress/adversity all predicted episodic memory impairment, as did smaller intercepts and slopes of hippocampal growth over time. Modest relationships of depression to hippocampal volume and strong relationships between emotion regulation and both episodic memory and hippocampal volume were found. These data are consistent with prior work in adults linking depression, episodic memory, emotion regulation, life stress/adversity, and hippocampal volume in adults and suggest similar relations are evident as early as adolescence when memory systems are under development. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
71 citations
TL;DR: It is suggested that it should no longer be assumed that clinically anxious individuals are characterized by selective attention toward threat, because meta-analytical evidence that clinical anxiety is characterized by threat-related attention bias is thin.
Abstract: Considerable effort and funding have been spent on developing Attention Bias Modification (ABM) as a treatment for anxiety disorders, theorized to exert therapeutic effects through reduction of a tendency to orient attention toward threat. However, meta-analytical evidence that clinical anxiety is characterized by threat-related attention bias is thin. The largest meta-analysis to date included dot-probe data for n = 337 clinically anxious individuals. Baseline measures of biased attention obtained in ABM RCTs form an additional body of data that has not previously been meta-analyzed. This article presents a meta-analysis of threat-related dot-probe bias measured at baseline for 1,005 clinically anxious individuals enrolled in 13 ABM RCTs. Random-effects meta-analysis indicated no evidence that the mean bias index (BI) differed from zero (k = 13, n = 1005, mean BI = 1.8 ms, SE = 1.26 ms, p = .144, 95% confidence interval [-0.6, 4.3]. Additional Bayes factor analyses also supported the point-zero hypothesis (BF10 = .23), whereas interval-based analysis indicated that mean bias in clinical anxiety is unlikely to extend beyond the 0 to 5 ms interval. Findings are discussed with respect to strengths (relatively large samples, possible bypassing of publication bias), limitations (lack of control comparison, repurposing data, specificity to dot-probe data), and theoretical and practical context. We suggest that it should no longer be assumed that clinically anxious individuals are characterized by selective attention toward threat. Clinically anxious individuals enrolled in RCTs for Attention Bias Modification are not characterized by threat-related attention bias at baseline. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
70 citations
TL;DR: Prevention programs that reduce perceived pressure to be thin and thin-ideal internalization among early adolescent girls with these factors should reduce eating disorder onset, as well as downstream risk factors that are also aversive (e.g., body dissatisfaction and negative affect).
Abstract: Prospective studies have identified risk factors that predict future onset of eating disorders, but none has provided a test of the temporal sequencing of the emergence of risk factors hypothesized in a multivariate etiologic model of eating disorder development. Using data from an 8-year prospective study of 496 adolescent girls, we first conducted receiver operator characteristic plots to identify cut-points for each risk factor that optimally predicted future onset of threshold or subthreshold bulimia nervosa, binge eating disorder, and purging disorder. We then used growth curve models to estimate the age at which each participant crossed the disorder-predictive cutpoint for each risk factor, or if they did not, during follow-up, permitting a test of whether the risk factors emerged in the sequence hypothesized in the Dual Pathway etiologic model. Overall, 47% of the 51 youth who showed onset of one of these eating disorders first showed emergence of disorder-predictive levels of perceived pressure to be thin and/or thin-ideal internalization, before showing onset of disorder-predictive levels of body dissatisfaction, before showing onset of disorder-predictive levels of dieting and/or negative affect, before showing onset of the eating disorder; another 29% had one of these steps out of order or did not cross one step in this model. Youth who did not show onset of an eating disorder were significantly less likely to cross the disorder-predictive cut-points for each risk factor or to conform to the sequence of risk factor emergence hypothesized in this model. Results provide novel support for the temporal sequencing of risk factor emergence hypothesized in this multivariate etiologic model and suggest that prevention programs that reduce perceived pressure to be thin and thin-ideal internalization among early adolescent girls with these factors should reduce eating disorder onset, as well as downstream risk factors that are also aversive (e.g., body dissatisfaction and negative affect). (PsycINFO Database Record (c) 2019 APA, all rights reserved).
66 citations
TL;DR: Depression symptoms, including sadness, self-dislike, pessimism, feelings of punishment, and indecision were most important for attention bias for sad stimuli, and no reliable symptom predictors were identified.
Abstract: Cognitive models of depression posit that negatively biased self-referent processing and attention have important roles in the disorder. However, depression is a heterogeneous collection of symptoms and all symptoms are unlikely to be associated with these negative cognitive biases. The current study involved 218 community adults whose depression ranged from no symptoms to clinical levels of depression. Random forest machine learning was used to identify the most important depression symptom predictors of each negative cognitive bias. Depression symptoms were measured with the Beck Depression Inventory-II. Model performance was evaluated using predictive R-squared (Rpred2), the expected variance explained in data not used to train the algorithm, estimated by 10 repetitions of 10-fold cross-validation. Using the self-referent encoding task (SRET), depression symptoms explained 34% to 45% of the variance in negative self-referent processing. The symptoms of sadness, self-dislike, pessimism, feelings of punishment, and indecision were most important. Notably, many depression symptoms made virtually no contribution to this prediction. In contrast, for attention bias for sad stimuli, measured with the dot-probe task using behavioral reaction time (RT) and eye gaze metrics, no reliable symptom predictors were identified. Findings indicate that a symptom-level approach may provide new insights into which symptoms, if any, are associated with negative cognitive biases in depression. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
60 citations
TL;DR: A metascientific review of the EST literature indicated that power and replicability estimates were concerningly low across almost all ESTs, and individually, some ESTs scored poorly across multiple metrics, with Strong ESTs failing to continuously outperform their Modest counterparts.
Abstract: Empirically supported treatments (or therapies; ESTs) are the gold standard in therapeutic interventions for psychopathology. Based on a set of methodological and statistical criteria, the APA has assigned particular treatment-diagnosis combinations EST status and has further rated their empirical support as Strong, Modest, and/or Controversial. Emerging concerns about the replicability of research findings in clinical psychology highlight the need to critically examine the evidential value of EST research. We therefore conducted a metascientific review of the EST literature, using clinical trials reported in an existing online APA database of ESTs, and a set of novel evidential value metrics (i.e., rates of misreported statistics, statistical power, R-Index, and Bayes Factors). Our analyses indicated that power and replicability estimates were concerningly low across almost all ESTs, and individually, some ESTs scored poorly across multiple metrics, with Strong ESTs failing to continuously outperform their Modest counterparts. Lastly, we found evidence of improvements over time in statistical power within the EST literature, but not for the strength of evidence of EST efficacy. We describe the implications of our findings for practicing psychotherapists and offer recommendations for improving the evidential value of EST research moving forward. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
54 citations
TL;DR: Findings corroborate previous findings that enhancement motives are most predictive of outcomes in the college population and highlight the importance of considering within-subject variance in drinking motives.
Abstract: Between-subjects literature has established that trait-like negative mood predicts coping motives, which predict alcohol-related problems and that trait-like positive mood predicts mood enhancement motives, which then predict alcohol consumption. However, there is considerable within-person variation in drinking motives, and the relationship between mood, motives, and alcohol outcomes must be more closely examined at a daily level. The current study used ecological momentary assessment (EMA) to measure mood, motives, alcohol use, and alcohol consequences in 101 college drinkers over a 15-day period. At the between-subjects level, positive mood predicted enhancement motives, which in turn predicted alcohol consumption and consequences. Negative mood predicted coping motives, which were associated with only alcohol-related consequences. At the within-subjects level, daily anxious and depressed mood were associated with endorsing coping motives, but coping motives were not associated with alcohol consumption or problems. Positive mood was associated with enhancement motives, which was associated with both daily alcohol consumption and problems. These results corroborate previous findings that enhancement motives are most predictive of outcomes in the college population and highlight the importance of considering within-subject variance in drinking motives. The relationships between mood, motives, and alcohol outcomes differ when examined as between-subjects versus within-subject constructs. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
48 citations
TL;DR: Results suggest interoception may represent a shared transdiagnostic vulnerability that underlies atypical emotional processing in a variety of disparate clinical populations but that current operationalization and measurement of interoceptive awareness continues to create confusion and inconsistency in the literature.
Abstract: Alexithymia-a trait associated with difficulties understanding one's own emotions-is theorized to stem from deficits in interoceptive awareness, or the ability to detect, accurately monitor, and regulate internal bodily processes. The present meta-analysis analyzed all studies that empirically examined the relationship between alexithymia and interoceptive awareness. Across 66 independent samples (N = 7,146), alexithymia had a small, negative correlation with interoceptive awareness (r = -.162, p = .001, 95% CI [-.252, -.068]), but additional analyses revealed that the strength and directionality of this association was heavily influenced by the specific interoceptive awareness components measured (e.g., interoceptive accuracy vs. sensibility) and the methods used to measure interoceptive awareness (e.g., objective vs. self-report measures). The strength of this relationship was also moderated by diagnosis of participants such that alexithymia was moderately associated with interoceptive awareness in samples with psychiatric and developmental disorders, but the relationship was nonsignificant in healthy, typically developing samples. Results suggest interoception may represent a shared transdiagnostic vulnerability that underlies atypical emotional processing in a variety of disparate clinical populations but that current operationalization and measurement of interoceptive awareness continues to create confusion and inconsistency in the literature. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: Results implicate AS and IU as risk factors for the maladaptive decisional correlates of Pavlovian generalization and suggest that established associations between these traits and clinical anxiety may derive, in part, from their enhancement of mal Adaptive APIC-G.
Abstract: Generalization of Pavlovian fear to safe stimuli resembling conditioned-danger cues (CS+) is a widely accepted conditioning correlate of clinical anxiety. Though much of the pathogenic influence of such generalization may lie in the associated avoidance, few studies have assessed maladaptive avoidance decisions associated with Pavlovian generalization. Lab-based assessments of this process, here referred to as aversive Pavlovian-instrumental covariation during generalization (APIC-G), have recently begun. The current study represents a next step in this line of work by conducting the first examination of anxiety-related dimensions of personality that may exacerbate APIC-G. Specifically, we test anxiety sensitivity (AS) and intolerance of uncertainty (IU) as moderators of relations between Pavlovian generalization and maladaptive avoidance decisions in 102 undergraduate students with wide-ranging levels of IU and AS. Results indicate a facilitative effect of AS on this APIC-G process, with AS strengthening relations between Pavlovian generalization and maladaptive generalized avoidance whether operationalizing Pavlovian generalization with psychophysiological (fear-potentiated startle) or behavioral measures. Additionally, IU was found to facilitate APIC-G when indexing Pavlovian generalization with behavioral but not fear-potentiated startle measures. Moderating effects of AS were most pronounced for stimulus classes bearing the highest resemblance to CS+, whereas effects of IU were most pronounced for the stimulus class with the highest level of threat ambiguity. Results implicate AS and IU as risk factors for the maladaptive decisional correlates of Pavlovian generalization and suggest that established associations between these traits and clinical anxiety may derive, in part, from their enhancement of maladaptive APIC-G. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: Structural neuroimaging and self-report data are used to generate neuroanatomical profiles (NAPs) of FFM traits and psychopathology indices composed of the thickness, surface area, and gray matter volume of each region in the Desikan atlas, suggesting that similar neuroanAtomical correlates underlie specific personality traits and symptoms of psychopathology.
Abstract: Although personality traits have been linked to internalizing and externalizing psychopathology, the extent to which these traits and psychopathological phenotypes share a common neuroanatomical structure is unclear. To address this gap, we used structural neuroimaging and self-report data from 1101 participants in the Human Connectome Project to generate neuroanatomical profiles (NAPs) of FFM traits and psychopathology indices composed of the thickness, surface area, and gray matter volume of each region in the Desikan atlas, then used a profile matching approach to compare the absolute similarity of the FFM trait NAPs and psychopathology index NAPs. These analyses indicated that the NAPs derived from Neuroticism and Extraversion demonstrated medium to large positive and negative absolute similarities to the NAPs of internalizing psychopathology, respectively. Similarly, the NAPs of Agreeableness and Conscientiousness showed medium to large negative relations with the NAPs of antisocial behavior and substance use, respectively. These results suggest that similar neuroanatomical correlates underlie specific personality traits and symptoms of psychopathology, providing support for dimensional models that incorporate personality traits into the etiology and manifestation of psychopathology. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: Data suggest that prior reports of aberrant EBDM in schizophrenia patients are related to both cognitive function and individual differences in negative symptoms, and even within the subset of patients who successfully used reward and probability information to guide effort expenditure, higher levels of negative symptoms related to motivation and avolition were associated with greater effort aversion during the task.
Abstract: Schizophrenia is associated with amotivation and reduced goal-directed behavior, which have been linked to poor functional outcomes. Motivational deficits in schizophrenia are often measured using effort-based decision-making (EBDM) paradigms, revealing consistent alterations in effort expenditure relative to controls. Although these results have generally been interpreted in terms of decreased motivation, the ability to use trial-by-trial changes in reward magnitude or probability of receipt to guide effort allocation may also be affected by cognitive deficits. To date, it remains unclear whether altered performance in EBDM primarily reflects deficits in motivation, cognitive functioning, or both. We applied a newly developed computational modeling approach to the analysis of EBDM data from two previously collected samples comprising 153 patients and 105 controls to determine the extent to which individuals did or did not use available information about reward and probability to guide effort allocation. Half of the participants with schizophrenia failed to incorporate information about reward and probability when making effort-expenditure decisions. The subset of patients who exhibited difficulties using reward and probability information were characterized by greater impairments across measures of cognitive functioning. Interestingly, even within the subset of patients who successfully used reward and probability information to guide effort expenditure, higher levels of negative symptoms related to motivation and avolition were associated with greater effort aversion during the task. Taken together, these data suggest that prior reports of aberrant EBDM in schizophrenia patients are related to both cognitive function and individual differences in negative symptoms. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: The results provide further evidence of deficits during reward anticipation in individuals with schizophrenia, particularly for those with severe negative symptoms, and some evidence for worse reward learning among those with greater negative symptoms.
Abstract: Negative symptoms are a core clinical feature of schizophrenia that are only marginally responsive to current treatments. Recent work suggests that deficits in reinforcement learning and anticipatory responses to reward may be two mechanisms that help explain impairments in motivation in those with schizophrenia. The present study utilized a reinforcement-learning paradigm, which allowed us to examine both reward anticipation and reinforcement learning. Twenty-eight people with schizophrenia and 30 healthy controls completed a reinforcement-learning task while undergoing functional MRI. Participants with schizophrenia also completed a weeklong ecological momentary assessment protocol reporting anticipated motivation and pleasure in their daily activities. Unexpectedly, we found no significant group differences in performance or neural response in reinforcement learning. However, we found that poorer reward learning was associated with greater clinician ratings of negative symptoms and daily reports of anticipatory motivation and pleasure negative symptoms. In regards to anticipatory responses, we found that people with schizophrenia showed blunted activation in the anterior cingulate, insula, caudate, and putamen while anticipating reward. Further, blood oxygen level-dependent (BOLD) response in reward related regions during anticipation of reward was significantly related to both clinician-rated motivation and pleasure deficits as well as daily reports of motivation and pleasure. Our results provide further evidence of deficits during reward anticipation in individuals with schizophrenia, particularly for those with severe negative symptoms, and some evidence for worse reward learning among those with greater negative symptoms. Moreover, our findings suggest that these deficits show important relationships with emotional and motivational functioning in everyday life. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: The present results suggest that emphasizing speed in experimental instructions may lead to a better neural differentiation between patients with OCD and healthy controls which has important implications for the use of the ERN as a risk indicator.
Abstract: Hyperactive error monitoring is a robust neurocognitive characteristic in obsessive-compulsive disorder (OCD). Yet, relatively little is known about the flexibility and potential moderators of error monitoring in OCD. The current study investigates error monitoring in 30 healthy participants and 28 patients with OCD using a flanker task in 2 conditions either emphasizing speed or accuracy. Results indicate that no group difference is observable in error-related negativity (ERN) under the accuracy-focused condition. Both groups show an ERN attenuation in the speed condition; however, this reduction is larger in healthy controls leading to pronounced group differences in the speed-focused condition. Similarly, receiver operating characteristic analyses yield an area under the curve (AUC) of .62 in the accuracy-focused condition, whereas under speed instruction an AUC of .85 suggests a marked increase in classification accuracy. Behavioral results and results from a drift-diffusion model of decision making indicate a more cautious response strategy and less adaptability to experimental manipulations in OCD. Overall, results suggest that the observed increases in error-related neural activity in OCD might stem from a reduced flexibility and diminished ability to disengage from an accuracy-oriented, error-avoidant response style. Further, the present results suggest that emphasizing speed in experimental instructions may lead to a better neural differentiation between patients with OCD and healthy controls which has important implications for the use of the ERN as a risk indicator. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: It is suggested that vocal expression fails to modulate across changing affective states in individuals with active SMI symptoms, this lack of modulation may be commonly associated with many SMI Symptoms, and vocal analysis can accommodate temporal dynamics.
Abstract: Acoustic analysis of vocal expression offers a potentially inexpensive, unobtrusive, and highly sensitive biobehavioral measure of serious mental illness (SMI)-related issues. Despite literature documenting its use for understanding SMI, prior studies have largely ignored that vocal expression is highly dynamic within individuals over time. We employed ambulatory vocal assessment from SMI outpatients to understand links between vocal expression, SMI symptoms, and affective states. Vocal samples were analyzed using a validated acoustic analysis protocol. Overall, vocal expression was not directly related to SMI symptoms but changed as a function of state and state by symptom interactions. The results suggest that (a) vocal expression fails to modulate across changing affective states in individuals with active SMI symptoms, (b) this lack of modulation may be commonly associated with many SMI symptoms, and (c) vocal analysis can accommodate temporal dynamics. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: Stress sensitization is demonstrated in predicting depression following normative forms of SLEs and stress generation effects for both depression and anxiety using a multilevel modeling approach.
Abstract: Associations between stressful life events (SLEs) and internalizing psychopathology are complex and bidirectional, involving interactions among stressors across development to predict psychopathology (i.e., stress sensitization) and psychopathology predicting greater exposure to SLEs (i.e., stress generation). Although stress sensitization and generation theoretical models inherently focus on within-person effects, most previous research has compared average levels of stress and psychopathology across individuals in a sample (i.e., between-person effects). The present study addressed this gap by investigating stress sensitization and stress generation effects in a multiwave, prospective study of SLEs and adolescent depression and anxiety symptoms. Depression, anxiety, and SLE exposure were assessed every 3 months for 2 years (8 waves of data) in a sample of adolescents (n = 382, aged 11 to 15 at baseline). Multilevel modeling revealed within-person stress sensitization effects such that the association between within-person increases in SLEs and depression, but not anxiety, symptoms were stronger among adolescents who experienced higher average levels of SLEs across 2 years. We also observed within-person stress generation effects, such that adolescents reported a greater number of dependent-interpersonal SLEs during time periods after experiencing higher levels of depression at the previous wave than was typical for them. Although no within-person stress generation effects emerged for anxiety, higher overall levels of anxiety predicted greater exposure to dependent-interpersonal SLEs. Our findings extend prior work by demonstrating stress sensitization in predicting depression following normative forms of SLEs and stress generation effects for both depression and anxiety using a multilevel modeling approach. Clinical implications include an individualized approach to interventions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: The results suggest that neural processing reward and loss plays a crucial role in depressogenic stress generation, and a significant indirect effect of the RewP on follow-up depression through dependent, but not independent, life stress.
Abstract: Blunted reward sensitivity and life stress are each depressogenic. Additionally, individuals with clinical and psychosocial vulnerabilities are prone to experience or evoke dependent life stressors (e.g., interpersonal conflict) that, in turn, increase depression risk. However, no previous study has investigated the role of neural vulnerability factors in generating life stress. Therefore, the current study investigated whether a neural measure of reward sensitivity prospectively predicts the generation of life stress, which in turn mediates effects of these neural processes on subsequent depression. Participants were 467 never-depressed adolescent girls. Using event-related potentials, neural sensitivity to the difference between monetary reward and loss (the Reward Positivity [RewP]) was assessed at baseline. Negative life events were assessed twice via interview over the ensuing 18 months, yielding an index of total life stress over the follow-up period. A self-report dimensional measure of depression symptoms was administered at baseline and follow-up. After accounting for baseline age, depression, and race, a blunted RewP predicted greater dependent, but not independent, life stress over the follow-up. Mediation analyses revealed a significant indirect effect of the RewP on follow-up depression through dependent, but not independent, life stress. Our results suggest that neural processing reward and loss plays a crucial role in depressogenic stress generation. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: It was found that the higher the rank of the coplayer, the stronger the negative emotions reported by participants and the more they opted for the individual option, which led to lower gains in this group.
Abstract: Depression significantly affects interpersonal functioning. Social avoidance may play an important role in depression, limiting opportunities and social skills acquisition, contributing to the maintenance of social difficulties. In the last few years, the need for studying social interactions using interactive tasks has been highlighted. This study investigated social avoidance in unmedicated depressed (n = 26) and matched healthy control (n = 26) participants, using a novel computerized social decision-making task (the TEAM task). In this task, participants choose between a social option (playing in a team with a coplayer) and an individual option (playing alone). Although the social option is more profitable from a material point of view, it can also be challenging because of social comparison and guilt feelings for failing the team. It was found that the higher the rank of the coplayer, the stronger the negative emotions (shame, guilt) reported by participants and the more they opted for the individual option. Depressed participants reported significantly less positive (happiness) and more negative (shame, guilt, disappointment) feelings regarding the task. Importantly, depressed participants chose the individual option significantly more often than controls, which led to lower gains in this group. Furthermore, as the task progressed, controls selected the individual option less often, whereas depressed participants selected the individual option more often. Our findings illustrate the importance of social avoidance in depression and how this behavior can lead to negative consequences. They also highlight the role of social comparison and guilt-related processes in underlying social avoidance in depression. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: This study provides a new method for testing escape decision making and does so using a computational cognitive model, allowing it to precisely index processes underlying suicidal and related behaviors.
Abstract: Suicide is a leading cause of death worldwide. Despite decades of clinical and theoretical accounts that suggest that suicidal thoughts and behaviors are efforts to escape painful emotions, little prior research has examined decision making involved in escaping aversive states. We compared the performance of 85 suicidal participants to 44 nonsuicidal psychiatric patients on a novel reinforcement learning task with choices to make either active (i.e., "go") or passive responses (i.e., "no-go") to either escape or avoid an aversive stimulus. We used a computational cognitive model to isolate decision-making biases. We hypothesized that suicidal participants would exhibit a relatively elevated bias for making active responses to escape an aversive state and would show worse performance when escape required a passive response (i.e., "doing nothing" to escape). Our hypotheses were supported: The computational model revealed that suicidal participants exhibited a higher bias for an active response to escape compared with nonsuicidal psychiatric controls, suggesting that this finding was not just the result of the presence of psychopathology. The bias parameter also accounted for unique variance in predicting group status among several constructs previously related to suicidal thoughts and behaviors. This study provides a new method for testing escape decision making and does so using a computational cognitive model, allowing us to precisely index processes underlying suicidal and related behaviors. Future research examining escape decision making from a computational perspective could help link neural processes or environmental stressors to suicidal thoughts or behaviors. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: Regression results demonstrated that aspect-level analyses generated substantial increases in predictive power over the FI-FFM Extraversion domain score, establishing the value of examining relations with extraversion at the aspect level.
Abstract: Extraversion shows both negative and positive associations with psychopathology. Previous work in this area has focused largely on either a broad higher order extraversion domain score or on specific lower-order extraversion facets. The goal of this study was to explicate how two intermediate aspects of the trait-communal extraversion and agentic extraversion-relate to psychopathology. We examined these relations using the Communal Extraversion (e.g., enjoy spending time with people, would describe myself as cheerful, like places that are crowded and exciting) and Agentic Extraversion (e.g., speak my mind, take charge in a group of people, like the sensation of going really fast) scales from the Faceted Inventory of the Five-Factor Model (FI-FFM; Watson, Nus, & Wu, 2019). As expected, Communal Extraversion generally showed negative associations with psychopathology; it had particularly strong links to indicators of internalizing, including depression symptoms (correlations generally ranged from -.40 to -.60) and various forms of social dysfunction (most correlations ranged from -.35 to -.60). In marked contrast, Agentic Extraversion tended to have positive associations with psychopathology; it displayed particularly substantial links to indicators of mania, narcissism/narcissistic personality disorder, and traits related to externalizing (correlations generally ranged from .25 to .50). Regression results demonstrated that aspect-level analyses generated substantial increases in predictive power over the FI-FFM Extraversion domain score. This basic pattern of results replicated over time, across gender, and across both self-rated and interview-based indicators of psychopathology. These findings establish the value of examining relations with extraversion at the aspect level. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: This work provides a comprehensive evaluation of interpersonal problems by enlisting several large samples to estimate a set of latent variable candidate models, covering the spectrum of purely dimensional, hybrid, and purely categorical approaches.
Abstract: Interpersonal problems are key transdiagnostic constructs in psychopathology. In the past, investigators have neglected the importance of operationalizing interpersonal problems according to their latent structure by using divergent representations of the construct: (a) computing scores for severity, agency, and communion ("dimensional approach"), (b) classifying persons into subgroups with respect to their interpersonal profile ("categorical approach"). This hinders cumulative research on interpersonal problems, because findings cannot be integrated both from a conceptual and a statistical point of view. We provide a comprehensive evaluation of interpersonal problems by enlisting several large samples (Ns = 5,400, 491, 656, and 712) to estimate a set of latent variable candidate models, covering the spectrum of purely dimensional (i.e., confirmatory factor analysis using Gaussian and nonnormal latent t-distributions), hybrid (i.e., semiparametric factor analysis), and purely categorical approaches (latent class analysis). Statistical models were compared with regard to their structural validity, as evaluated by model fit (corrected Akaike's information criterion and the Bayesian information criterion), and their concurrent validity, as defined by the models' ability to predict relevant external variables. Across samples, the fully dimensional model performed best in terms of model fit, prediction, robustness, and parsimony. We found scant evidence that categorical and hybrid models provide incremental value for understanding interpersonal problems. Our results indicate that the latent structure of interpersonal problems is best represented by continuous dimensions, especially when one allows for nonnormal latent distributions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: Registration helps clinical researchers in thinking through tensions between bandwidth and fidelity that surround recruiting participants, defining clinical phenotypes, handling comorbidity, treating missing data, and analyzing rich and complex data.
Abstract: Clinical scientists can use a continuum of registration efforts that vary in their disclosure and timing relative to data collection and analysis. Broadly speaking, registration benefits investigators by offering stronger, more powerful tests of theory with particular methods in tandem with better control of long-run false positive error rates. Registration helps clinical researchers in thinking through tensions between bandwidth and fidelity that surround recruiting participants, defining clinical phenotypes, handling comorbidity, treating missing data, and analyzing rich and complex data. In particular, registration helps record and justify the reasons behind specific study design decisions, though it also provides the opportunity to register entire decision trees with specific endpoints. Creating ever more faithful registrations and standard operating procedures may offer alternative methods of judging a clinical investigator's scientific skill and eminence because study registration increases the transparency of clinical researchers' work. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: GAMIs may result in greater conformity to societal expectations regarding binary gender norms, thus decreasing discrimination, rejection, victimization, and nonaffirmation, and increased alignment of physical characteristics and gender identity may increase self-esteem.
Abstract: Transgender and gender nonconforming (TGNC) individuals are at heightened risk for psychological distress, including social anxiety (SA). The current study aimed to examine whether gender-affirming medical interventions (GAMIs) are associated with lower SA among TGNC individuals. Two hundred ninety-one transfeminine and 424 transmasculine participants completed the Trans Health Survey, which assessed SA and interest in or utilization of GAMIs (genital surgery, chest surgery, hormone use, speech therapy, tracheal shave or Adam's apple removal, hair removal). Transfeminine individuals who had completed genital surgery, chest surgery, tracheal shave or Adam's apple removal, hair removal, hormone treatment, or speech therapy reported lower SA than those planning to undergo the intervention, and those who had completed genital or chest surgery reported lower SA than those considering it. Transmasculine individuals who had completed chest surgery, a hysterectomy, or used hormones reported lower SA than those who were planning to do so, and those who had completed genital surgery had lower SA than those considering it. Among those expressing interest, utilization of GAMIs is associated with less SA. GAMIs may result in greater conformity to societal expectations regarding binary gender norms, thus decreasing discrimination, rejection, victimization, and nonaffirmation. Increased alignment of physical characteristics and gender identity may increase self-esteem. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: BPD patients exhibit increased punishment behavior during fair, “favorable” social exchanges, which they tend to perceive as less fair than controls, and may be biased toward underestimating positive feedback from others.
Abstract: This study evaluated whether the impairment in cooperation that characterizes individuals with borderline personality disorder (BPD) can be explained by the difficulty to use emotion regulation strategies and to accurately perceive the fairness of others' behavior. Forty-one patients with BPD and 41 sex and age matched healthy controls (HC) played the responder's role in a Modified Ultimatum Game during which they were asked to apply 3 different emotion regulation strategies: look, distancing, and reappraisal. Offer rejection rates were used as an index of punishment behavior. After the experiment, participants also rated the degree of perceived equity of the offers after receiving fair and unfair offers. Reappraisal was effective in decreasing punishment behaviors for unfair offers in both the BPD and HC groups. By contrast, BPD patients displayed a different behavior than HC when making decisions upon fair offers, independently from the regulation strategies adopted. In fact, they rejected higher rates of fair offers than HC. Further, BPD patients judged fair offers as less fair than HC. This indicates an altered judgment and decision making on fair interpersonal exchanges. In conclusion, BPD patients exhibit increased punishment behavior during fair, "favorable" social exchanges, which they tend to perceive as less fair than controls. Thus, BPD patients may be biased toward underestimating positive feedback from others. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: The findings confirmed the diagnostic bias between African Americans and White individuals though there were no differences on clinician symptom ratings and Moderation analysis suggests that behaviorally based measures impact the relationship between race and diagnosis; however, this was largely unsupported for race and clinical symptom ratings.
Abstract: There is evidence that African Americans are 2.4 times more likely to be diagnosed with a schizophrenia-spectrum diagnosis compared with White individuals, who are more likely to receive an affective diagnosis. The reason for these diagnostic discrepancies is unclear, however, 2 explanations have garnered attention: epigenetic differences and systematic error or bias in the diagnostic process. The latter is the focus of the present study and it is hypothesized that the bias involves cultural insensitivity on the part of the clinician. The present study has investigated bias-driven diagnostic disparities between African Americans and White individuals, by using traditional symptom rating scales, clinical diagnoses, and objective, behaviorally based measures. Data was aggregated from 3 separate studies conducted on outpatients (N = 251) with schizophrenia-spectrum or affective disorders. The present study used computationally derived acoustic markers of speech to tap hallmark negative symptoms (e.g., blunted affect or alogia) and behavioral-based markers of language failures to tap disorganization. Clinician symptom ratings were made using the Brief Psychiatric Rating Scale. Our findings confirmed the diagnostic bias between African Americans and White individuals though there were no differences on clinician symptom ratings. On the other hand, the computerized and behavioral measures revealed more speech disorder and less blunted affect in African Americans versus White individuals. Moderation analysis suggests that behaviorally based measures impact the relationship between race and diagnosis; however, this was largely unsupported for race and clinical symptom ratings. Further research is needed to disentangle normative variations from psychopathology. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: It is argued that this workflow will result in more transparent and easily shareable psychopathology research, eventually increasing and replicability reproducibility in the research field.
Abstract: Data analysis in psychopathology research typically entails multiple stages of data preprocessing (e.g., coding of physiological measures), statistical decisions (e.g., inclusion of covariates), and reporting (e.g., selecting which variables best answer the research questions). The complexity and lack of transparency of these procedures have resulted in two troubling trends: the central hypotheses and analytical approaches are often selected after observing the data, and the research data are often not properly indexed. These practices are particularly problematic for (experimental) psychopathology research because the data are often hard to gather due to the target populations (e.g., individuals with mental disorders), and because the standard methodological approaches are challenging and time consuming (e.g., longitudinal studies). Here, we present a workflow that covers study preregistration, data anonymization, and the easy sharing of data and experimental material with the rest of the research community. This workflow is tailored to both original studies and secondary statistical analyses of archival data sets. In order to facilitate the implementation of the described workflow, we have developed a free and open-source software program. We argue that this workflow will result in more transparent and easily shareable psychopathology research, eventually increasing and replicability reproducibility in our research field. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: Findings suggest that alterations in facial expressivity occur early in the pathogenesis of psychosis and provide evidence for the efficacy of higher resolution measures of facialexpressivity in psychosis research.
Abstract: Negative symptoms, such as blunted facial affect, are core features of psychotic disorders that predict poor functional outcome. However, it is unknown whether these impairments occur prior to the onset of psychosis. Understanding this phenomenon in the psychosis risk period has significant relevance for elucidating pathogenic processes, as well as potential for informing a viable new behavioral marker for broader social dysfunction and clinical course. The current study sought to determine the nature of facial expression deficits among individuals at clinical high-risk (CHR) for developing psychosis using a comprehensive approach, incorporating clinical interview ratings and automated facial expression coding analysis. A total of 42 CHR and 42 control participants completed clinical interviews and digitally taped segments were submitted into an automated, computerized tool to assess for 7 facial expressions (joy, anger, surprise, fear, contempt, disgust, sadness). Furthermore, relationships between facial expressions and social functioning and available scores on a psychosis conversion risk calculator from a total of 78 participants (39 CHR and 39 controls) were examined. Relationships between measures were also investigated (data was available for the Prodromal Inventory of Negative Symptoms among 33 CHR and 25 controls). Findings from clinical interview indicated that the CHR group exhibited elevated blunting. Furthermore, automated analyses showed that the CHR group displayed blunting in expressions of joy but surprisingly, increased anger facial expressions. Lastly, irregularities in facial expressions were related to decreased social functioning and increased psychosis conversion risk calculator scores, signaling heightened likelihood of conversion to psychosis. These findings suggest that alterations in facial expressivity occur early in the pathogenesis of psychosis and provide evidence for the efficacy of higher resolution measures of facial expressivity in psychosis research. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: Investigating the role of interpretation biases in the transgenerational transmission of depression risk in at-risk youth indicates that negative interpretation biases are present in youth at risk for depression, possibly representing a cognitive vulnerability for the development of depression.
Abstract: Children of parents with a history of depression have an increased risk of developing depression themselves. The present study investigated the role of interpretation biases (that have been found in adults and adolescents with depression but have rarely been examined in at-risk youth) in the transgenerational transmission of depression risk. Interpretation biases were assessed with two experimental tasks: Ambiguous Scenarios Task (AST) and Scrambled Sentences Task (SST) in 9-14-year-old children of parents with a history of depression (high risk; n = 43) in comparison to children of parents with no history of mental disorders (low risk; n = 35). Interpretation biases were also compared between the two groups of parents and relationships between children's and parents' bias scores were examined. As expected, we found more negative interpretation biases in high-risk children compared to low-risk children as well as in parents with a history of depression compared to never-depressed parents (assessed via the SST but not the AST). However, transgenerational correlations were only found for the AST. Our results indicate that negative interpretation biases are present in youth at risk for depression, possibly representing a cognitive vulnerability for the development of depression. Moreover, different measures of interpretation bias seemed to capture different aspects of biased processing with the more implicit measure (SST) being a more valid indicator of depressive processing. (PsycINFO Database Record (c) 2019 APA, all rights reserved).