Cognitive vulnerability to depression: A comparison of the weakest link,keystone and additive models

Multiple theories of cognitive vulnerability to depression have been proposed, each focusing on different aspects of negative cognition and utilising different measures of risk. Various methods of integrating such multiple indices of risk have been examined in the literature, and each demonstrates some promise. Yet little is known about the interrelations among these methods, or their incremental validity in predicting changes in depression. The present study compared three integrative models of cognitive vulnerability: the additive, weakest link, and keystone models. Support was found for each model as predictive of depression over time, but only the weakest link model demonstrated incremental utility in predicting changes in depression over the other models. We also explore the correlation between these models and each model's unique contribution to predicting onset of depressive symptoms.     

Cognitive and Interpersonal Vulnerability to Suicidal Ideation: A Weakest Link Approach

In contrast with traditional models of risk for suicidal ideation that combine multiple vulnerability components into one composite measure, weakest link perspectives posit that individuals are as vulnerable as their most vulnerable component (or “weakest link”). Such a perspective has been applied to depression, but has not been evaluated with respect to suicidal ideation. Thus, the goal of the present study was to apply a weakest link perspective to the study of suicidal ideation. We hypothesized that an individual’s “weakest link” among vulnerability components from the hopelessness theory (HT) and interpersonal psychological theory of suicide (IPTS) would interact with high levels of stress to predict increases in suicidal ideation over a 6-week period better than the traditional conceptualizations of HT or IPTS. Participants were 171 college students who completed measures of cognitive vulnerability, stress, and suicidal ideation twice over a period of 6 weeks. Bayesian regression analyses supported our hypotheses. The data fit the weakest link model using HT and IPTS components better than traditional conceptualizations of HT and IPTS. This study implies that weakest link models from depression may be useful in understanding which individuals are most vulnerable to experiencing suicidal ideation in the context of stress.     

Dimensional personality traits and the prediction of DSM-IV personality disorder symptom counts in a nonclinical sample

The third edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-III; APA, 1980) set forth a categorical system of personality psychopathology that is composed of discrete personality disorders (PDs), each with a distinct set of diagnostic criteria. Although this system is widely accepted and highly influential, alternative dimensional approaches to capturing personality psychopathology have been proposed. Three dimensional models of personality have garnered particular attention-the Five-Factor Model (FFM; Costa & McCrae, 1992), the Seven-Factor Psychobiological Model of Temperament and Character (Seven-Factor Model; Cloninger, Svrakic, & Przybeck, 1993); and the 18-factor model of personality pathology (18-factor model; Livesley, 1986). Although the personality traits from each of these models has been examined in relation to the ten personality disorders in the DSM-IV, no study has examined the comparative and incremental validity of these models in predicting PD symptoms for these ten disorders. Using self-report instruments that measure these models and the ten DSM-IV PDs, correlation and linear regression analyses indicate that traits from all three models had statistically significant associations with PD symptom counts. Hierarchical regressions revealed that the 18-factor model had incremental predictive validity over the FFM and Seven-Fac-tor Model in predicting symptom counts for all ten DSM-IV PDs. The FFM had incremental predictive validity over the Seven-Factor Model model for all ten disorders and the Seven-Factor was able to add incremental predictive validity over the 18-factor model for five of the ten PDs and for eight of the ten disorders relative to the FFM.     

Modeling caregiver adaptation over time: the longitudinal impact of behavior problems

Although cross-sectional research has established the link between care demands and various indicators of caregiver adaptation, few studies have examined the impact of care recipients' problematic behavior over time. The present analysis determines the importance of behavior problems when predicting rates of change in subjective stressors (role overload and role captivity) and depression. Using 4-wave longitudinal data (N = 137) on dementia caregivers, the authors fit individual growth curve models for care demands (i.e., behavior problems, activities of daily living dependencies, and cognitive impairment), subjective stressors, and depression. Subsequent structural equation models found that increases in behavior problems were most likely to predict increases in role overload. The findings emphasize the deleterious long-term impact of behavior problems on individuals' emotional adaptation to caregiving.     

Identifying Cognitive and Interpersonal Predictors of Adolescent Depression

Emerging research has begun to examine cognitive and interpersonal predictors of stress and subsequent depression in adolescents. This research is critical as cognitive and interpersonal vulnerability factors likely shape expectations, perspectives, and interpretations of a given situation prior to the onset of a stressor. In the current study, adolescents (n?=?157; boys=64, girls=93), ages 12 to 18, participated in a 6-month, multi-wave longitudinal study examining the impact of negative cognitive style, self-criticism, and dependency on stress and depression. Results of time-lagged, idiographic multilevel analyses indicate that depressogenic attributional styles (i.e., composite score and weakest link approach) and self-criticism predict dependent interpersonal, but not noninterpersonal stress. Moreover, the occurrence of stress mediates the relationship between cognitive vulnerability and depressive symptoms over time. At the same time, self-criticism predicts above and beyond depressogenic attributional styles (i.e., composite and weakest link approach). In contrast to our hypotheses, dependency does not contribute to the occurrence of stress, and additionally, no gender differences emerge. Taken together, the findings suggest that self-criticism may be a particularly damaging vulnerability factor in adolescence, and moreover, it may warrant greater attention in the context of psychotherapeutic interventions.     

Depression as a predictor of perceived social support and demand: a componential approach using a prospective sample of older adults

This study examined the relationship of the cognitive, mood, and somatic components of depression on perceptions of social support and social demand among older adults (n = 851) over two years. Factor-analyses confirmed the factor structure of our multicomponential model of depression. Results supported our proposal that interpersonal specificity, as measured by depressive cognition about self and others, is important to predicting changes in perceived support and demand over time. Each component of depression was related to social support and social demand cross-sectionally, whereas only the cognitive component of depression predicted changes in support and demand prospectively. Future research should consider the pathways linking depressive cognition to perceived support and demand.     

Depression and Anxiety: Integrating the Tripartite and Cognitive Content-Specificity Assessment Models

The cognitive content-specificity hypothesis proposes that depression and anxiety can be discriminated on the basis of unique cognitive profiles. Alternatively, the Tripartite model suggests that, although depression and anxiety share a general distress factor, anhedonia is a characteristic of depression with anxious arousal a characteristic of anxiety. Past research devoted to integrating these two models has been limited in a number of ways. To remedy these limitations, this study attempted to assess the complete Tripartite model and used a multidimensional cognitive assessment tool to handle the heterogeneity of anxious cognitive content. Results on data collected from 411 clients seeking services at a university counseling center suggested that a one-to-one mapping between Tripartite dimensions and cognitive content was possible. Further, variables from each model simultaneously explained unique variance in depression and anxiety ratings.     

Depression as a mediator of negative cognitive style and hopelessness in stress generation

Over the past 20 years, there has been considerable interest in the role of cognitive factors in the stress generation process. Generally, these studies find that depressed individuals, or individuals at cognitive risk for depression, are more likely to experience stressful life events that are in part influenced by their own characteristics and behaviours (i.e., negative dependent events). However, there is still much to be learnt about the mediators of these effects. For example, does the development of depression symptoms explain why individuals at cognitive risk for depression experience increased negative dependent events? Or, is it that increases in cognitive risk explain why depressed individuals experience increased negative dependent events? To explore these questions, a short‐term prospective study was conducted with 209 college students who were given measures of depression, depressogenic risk factors (i.e., negative cognitive style and hopelessness), and negative dependent events at two time points 6 weeks apart. Support was found for three models: (1) depression symptoms mediated the relationship between negative cognitive style and negative dependent events; (2) depression symptoms mediated the relationship between hopelessness and negative dependent events; and (3) first hopelessness and then depression symptoms mediated the relationship between negative cognitive style and negative dependent events in a multiple‐step model. In contrast, the reverse models were not confirmed, suggesting specificity in the direction of the mediational sequence.     

Examining the Incremental Validity and Adverse Impact of Cognitive Ability and Conscientiousness on Job Performance

Using archival data from a large home improvement organization, the current study examined the incremental validity of conscientiousness over cognitive ability in predicting different performance criteria. Also, the study examined the effects of conscientiousness and cognitive ability on adverse impact. Results indicated that conscientiousness provided incremental validity over cognitive ability in the prediction of several performance criteria. Specifically, conscientiousness had the highest increases in validity over cognitive ability in the prediction of contextual performance factors (e.g., contextual performance, customer service orientation, dealing with others). However, the addition of conscientiousness failed to ameliorate the adverse impact associated with cognitive ability. In addition, limitations of the study and future directions of research are addressed.     

Mapping gray matter development: Implications for typical development and vulnerability to psychopathology

Recent studies with brain magnetic resonance imaging (MRI) have scanned large numbers of children and adolescents repeatedly over time, as their brains develop, tracking volumetric changes in gray and white matter in remarkable detail. Focusing on gray matter changes specifically, here we explain how earlier studies using lobar volumes of specific anatomical regions showed how different lobes of the brain matured at different rates. With the advent of more sophisticated brain mapping methods, it became possible to chart the dynamic trajectory of cortical maturation using detailed 3D and 4D (dynamic) models, showing spreading waves of changes evolving through the cortex. This led to a variety of time-lapse films revealing characteristic deviations from normal development in schizophrenia, bipolar illness, and even in siblings at genetic risk for these disorders. We describe how these methods have helped clarify how cortical development relates to cognitive performance, functional recovery or decline in illness, and ongoing myelination processes. These time-lapse maps have also been used to study effects of genotype and medication on cortical maturation, presenting a powerful framework to study factors that influence the developing brain.     

Predicting the effects of cellular-phone dialing on driver performance

Legislators, journalists, and researchers alike have recently directed a great deal of attention to the effects of cellular telephone (‘cell phone’) use on driver behavior and performance. This paper demonstrates how cognitive modeling can aid in understanding these effects by predicting the impact of cell-phone dialing in a naturalistic driving task. We developed models of four methods of cell-phone dialing and integrated these models with an existing driver model of steering and speed control. By running this integrated model, we generated a priori predictions for how each dialing method affects the accuracy of steering and speed control with respect to an accelerating and braking lead vehicle. The model predicted that the largest effects on driver performance arose for dialing methods with high visual demand rather than methods with long dialing times. We validated several of the model’s predictions with an empirical study in a fixed-based driving simulator.     

The Canberra Longitudinal Study: Design,Aims, Methodology,Outcomes and Recent Empirical Investigations

The first section of this paper describes methodology and major cognitive outcomes of the Canberra Longitudinal Study (CLS). This community study of 1045 Australians aged 70 years or over commenced in 1990. Participants were reassessed on three subsequent occasions. Its major themes were investigations of prevalence of dementia and depression, risk factors, inter-individual variability and instrument development. Over 60 papers arising from the study have been published.

The second section of this paper describes the use of a Factor of Curves (FOC) latent growth model to examine the existence of a common factor responsible for age-related deterioration in cognitive and non-cognitive processes. This analysis is a logical progression in a series of investigations using the Canberra Longitudinal Study into risk factors and correlates of cognitive change using structural equation modeling techniques. The FOC model is described and is used to explore the nature of an hypothesized common factor and to determine its relationship with age, gender, education, pre-morbid intelligence and to the ApoE genotype. Latent growth models were developed for each of reaction time, Symbol Letter Modalities Test (SLMT), Grip strength, self-reported Sensory disability and memory from three waves of data. Second-order latent level slope factors were established based on the individual factor growth curve models. Although a common factor model could be fitted to the data, there is little support that it represents a single common cause.     

Attributional style and depressive symptoms in adolescents: an examination of the role of various indicators of cognitive vulnerability

This study focuses on the hopelessness theory to explain depressive symptoms in adolescents. The aim is to assess which dimensions of the attributional style (causal attribution, attribution of consequences, implications for the self, total score, and weakest link score) better moderate the impact of negative events on the increase of depressive symptoms. For this purpose, 856 Spanish adolescents (449 girls and 407 boys, ages between 14 and 17 years) were assessed at the beginning of the school year and at follow-up 6 months later. They completed measures of depressogenic cognitive style [Hankin, B. L., & Abramson, L. Y. (2002). Measuring cognitive vulnerability to depression in adolescents: Reliability, validity, and gender differences. Journal of Clinical Child and Adolescent Psychology, 31, 491-504], negative life events, and depressive symptoms. The results show that only the dimension of attribution of stable and global causes moderated the impact of the negative events on the increase of depression at follow-up. The results are discussed in terms of the meaning of the weakest link score and the construct of attributional style from a developmental perspective.     

Cognitive Development Masks Support for Attributional Style Models of Depression in Children and Adolescents

Attributional style models of depression in adults (Abramson et al. 1989, 1978) have been adapted for use with children; however, most applications do not consider that children's understanding of causal relations may be qualitatively different from that of adults. If children's causal attributions depend on children's level of cognitive development, then support for attributional models of depression in young people will vary with cognitive development. In this paper, a new measure of cognitive development, the Peabody Causal Reasoning Test (PCRT), is introduced to assess children's understanding of ability versus effort, task difficulty, and luck as causal factors. Analyses revealed that in 8- to 16-year-old children, failure to control for level of cognitive development suppressed empirical support for cognitive diathesis-stress models of depression. Statistically controlling for measures of cognitive development strengthened support for this model.     

抑郁症认知治疗理论及实践进展

认知治疗分化为认知行为与认知分析治疗两个流派。抑郁的贝克认知模型、归因模型、自我价值关联模型以及抑郁的注意过程等认知理论为认知治疗奠定了基础。认知行为治疗、认知行为分析系统心理治疗以及基于冥想的认知治疗等已经在实践中被较有力的临床证据检验。认知治疗在抑郁症的治疗中已显示出广泛的应用前景。     

Facial affect processing and depression susceptibility: cognitive biases and cognitive neuroscience

Facial affect processing is essential to social development and functioning and is particularly relevant to models of depression. Although cognitive and interpersonal theories have long described different pathways to depression, cognitive-interpersonal and evolutionary social risk models of depression focus on the interrelation of interpersonal experience, cognition, and social behavior. We therefore review the burgeoning depressive facial affect processing literature and examine its potential for integrating disciplines, theories, and research. In particular, we evaluate studies in which information processing or cognitive neuroscience paradigms were used to assess facial affect processing in depressed and depression-susceptible populations. Most studies have assessed and supported cognitive models. This research suggests that depressed and depression-vulnerable groups show abnormal facial affect interpretation, attention, and memory, although findings vary based on depression severity, comorbid anxiety, or length of time faces are viewed. Facial affect processing biases appear to correspond with distinct neural activity patterns and increased depressive emotion and thought. Biases typically emerge in depressed moods but are occasionally found in the absence of such moods. Indirect evidence suggests that childhood neglect might cultivate abnormal facial affect processing, which can impede social functioning in ways consistent with cognitive-interpersonal and interpersonal models. However, reviewed studies provide mixed support for the social risk model prediction that depressive states prompt cognitive hypervigilance to social threat information. We recommend prospective interdisciplinary research examining whether facial affect processing abnormalities promote-or are promoted by-depressogenic attachment experiences, negative thinking, and social dysfunction.     

Sleep deprivation and sustained attention performance: integrating mathematical and cognitive modeling

A long history of research has revealed many neurophysiological changes and concomitant behavioral impacts of sleep deprivation, sleep restriction, and circadian rhythms. Little research, however, has been conducted in the area of computational cognitive modeling to understand the information processing mechanisms through which neurobehavioral factors operate to produce degradations in human performance. Our approach to understanding this relationship is to link predictions of overall cognitive functioning, or alertness, from existing biomathematical models to information processing parameters in a cognitive architecture, leveraging the strengths from each to develop a more comprehensive explanation. The integration of these methodologies is used to account for changes in human performance on a sustained attention task across 88 h of total sleep deprivation. The integrated model captures changes due to time awake and circadian rhythms, and it also provides an account for underlying changes in the cognitive processes that give rise to those effects. The results show the potential for developing mechanistic accounts of how fatigue impacts cognition, and they illustrate the increased explanatory power that is possible by combining theoretical insights from multiple methodologies.     

More than g: Evidence for the Incremental Validity of Performance-Based Assessments for Predicting Training Performance

Past research has consistently shown that tests measuring specific cognitive abilities provide little if any incremental validity over tests of general mental ability when predicting performance on the job. In this study, we suggest that the seeming lack of incremental validity may have been due to the type of content that has traditionally been assessed. Therefore, we hypothesised that incremental validity can be obtained using specific cognitive abilities that are less highly correlated with g and are matched to the tasks performed on the job. To test this, we examined a recently developed performance-based measure that assesses a number of cognitive abilities related to training performance. In a sample of 310 US Navy student pilots, results indicated that performance-based scores added sizeable incremental validity to a measure of g. The significant increases in R² ranged from .08 to .10 across criteria. Similar results were obtained after correcting correlations for range restriction, though the magnitude of incremental validity was slightly smaller (ΔR² ranged from .05 to .07).     

Cognitive and Interpersonal Vulnerabilities to Adolescent Depression: Classification of Risk Profiles for a Personalized Prevention Approach

Despite interest in psychosocial vulnerabilities to depression, little is known about reliable and valid individualized risk profiles that can be used to match individuals to evidence-based interventions for depression. This study investigated well-established cognitive and interpersonal vulnerabilities to depression among youth to discern an evidence-based risk classification approach which is being used in a personalized depression prevention randomized clinical trial. Data were drawn from a general community sample of adolescents (N?=?467; ages 10–16, mean 13.14, SD?=?1.62; 57% females) who were followed prospectively for 3 years. Youth completed measures of cognitive (negative cognitive style, dysfunctional attitudes, rumination) and interpersonal (support and conflict with peers and parents, excessive reassurance seeking, social competence, co-rumination) risks to depression, and then were followed longitudinally for onset of depression. Principal axis factor analyses showed that three latent factors--cognitive vulnerability, interpersonal support, and interpersonal conflict--optimally represented the structure of these risk factors. Clinically practical and meaningful cutoffs, based on tertile cut-off scores on cognitive and interpersonal risk measures, were used to categorize youth into relatively balanced high and low cognitive and interpersonal risk groups. These risk classification groups exhibited validity (AUC?>?0.70) by predicting prospective onsets of depressive episodes at 18-months follow-ups. These findings demonstrate a reliable and valid approach to synthesize psychosocial vulnerabilities to depression, specifically cognitive and interpersonal risks. Results are discussed in terms of using these risk classifications profiles to test personalized prevention of depression during adolescence.     

The Incremental Validity of Honesty–Humility Over Cognitive Ability and the Big Five Personality Traits

The present study examines the incremental validity of Honesty–Humility (H-H), a measure of the tendency to be fair and genuine in dealing with others, for supervisory ratings of job performance (including both task and contextual performance) over cognitive ability and the Big Five personality traits. Specifically, we explore the incremental validity of H-H in predicting contextual performance. Results based on 217 South Korean military officer candidates are consistent with previous conclusions that Conscientiousness is the strongest predictor of contextual performance and that cognitive ability is the strongest predictor of task performance. More important, our results reveal that H-H offers moderate incremental validity for contextual performance but no incremental validity for task performance over the effects of cognitive ability and the Big Five personality traits.