Identifying subtypes in persons, situations and person-situation interactions: Categorical latent state-trait modelling approaches

The latent state-trait theory posits that a psychological construct may reflect stable influences specific to a person (i.e., trait), ephemeral influences from situations (i.e., state), and interactions between them (i.e., state-trait interactions). Researchers conventionally apply mixture modelling to explore heterogeneity in variables by identifying homogenous classes with respect to the measured variable, yet rarely distinguishing between person- and situation-specific classes. The current study introduces novel categorical latent state-trait models to identify subgroups in states and traits, quantifying the effects of person-specific classes, situation-specific classes, and person-situation interactions. The proposed models are applied to an empirical dataset. We discuss statistical inference, effect size measures, and model visualization for the proposed models. Based on realistic parameter values from the empirical dataset, preliminary simulation studies were conducted to investigate models' performances. Bayesian estimation in the proposed models allows flexible testing of a wide range of hypotheses related to state, trait, and interaction effects. We discuss limitations and future directions.

Disorder-specific versus transdiagnostic cognitive mechanisms in anxiety and depression: Machine-learning-based prediction of symptom severity

INTRODUCTION

Psychiatric evaluation of anxiety and depression is currently based on self-reported symptoms and their classification into discrete disorders. Yet the substantial overlap between these disorders as well as their within-disorder heterogeneity may contribute to the mediocre success rates of treatments. The proposed research examines a new framework for diagnosis that is based on alterations in underlying cognitive mechanisms. In line with the Research Domain Criteria (RDoC) approach, the current study directly compares disorder-specific and transdiagnostic cognitive patterns in predicting the severity of anxiety and depression symptoms.

METHODS

The sample included 237 individuals exhibiting differing levels of anxiety and depression symptoms, as measured by the STAI-T and BDI-II. Random Forest regressors were used to analyze their performance on a battery of six computerized cognitive-behavioral tests targeting selective and spatial attention, expectancy, interpretation, memory, and cognitive control biases.

RESULTS

Unique anxiety-specific biases were found, as well as shared anxious-depressed bias patterns. These cognitive biases exhibited relatively high fitting rates when predicting symptom severity (questionnaire scores common range 0-60, MAE = 6.03, RMSE = 7.53). Interpretation and expectancy biases exhibited the highest association with symptoms, above all other individual biases.

LIMITATIONS

Although internal validation methods were applied, models may suffer from potential overfitting due to sample size limitations.

CONCLUSION

In the context of the ongoing dispute regarding symptom-centered versus transdiagnostic approaches, the current study provides a unique comparison of these two views, yielding a novel intermediate approach. The results support the use of mechanism-based dimensional diagnosis for adding precision and objectivity to future psychiatric evaluations.

Trajectory of Nostalgia in Emerging Adulthood

We examined the change and stability of nostalgia in emerging adulthood. We followed 327 students through their 4 university years with six assessments. Nostalgia demonstrated moderate rank stability (r = .25-.79). A Trait-State-Occasion model analysis indicated that the stable trait component, slowing-change trait component, and state component explained 37% to 43%, 10% to 27%, and 29% to 49% of variation in nostalgia on specific occasions, respectively. Longitudinal multilevel analysis revealed that the mean nostalgia level declined across university years. Greater intensity of negative life events at the start of university was associated with higher initial nostalgia and slower decline of it, while the emotion intensified when experiencing more negative life events. Nostalgia in emerging adulthood displays moderate stability, with negative life events contributing to the shape of its trajectory.

Changes in Anxiety and Depression Symptoms Predict Sexual Risk Behaviors Among Young Men Living in Dar es Salaam, Tanzania

Young men are important targets in HIV prevention in Tanzania and throughout sub-Saharan Africa. Anxiety and depression are common among youth and may be important predictors of HIV risk behaviors; evidence of these relationships in high-risk populations is needed. Using baseline and 1 year follow-up assessments from an HIV prevention trial we assessed the association between changes in symptoms of anxiety and depression and follow-up sexual risk behaviors (condom use and sexual partner concurrency) controlling for baseline sexual risk behaviors among 1113 male members of social groups known as "camps" in Dar es Salaam, Tanzania. Anxiety and depression were measured using the HSCL-25 and condom use and sexual partner concurrency were assessed through self-report. In separate models, increases in anxiety and depression were associated with sexual partner concurrency and with lower levels of condom use. In a combined model, both anxiety and depression appeared to independently affect concurrency but only depression was independently associated with condom use, with the association between anxiety and condom use being likely attributable to covariance with depression symptoms. The results of this study indicate the importance of screening and providing treatment for depression and anxiety disorders in high HIV-prevalence contexts, and the need to develop effective HIV prevention interventions targeting young men living with anxiety and depression.

Distinguishing transient versus stable aspects of depression in New Zealand Pacific Island children using Generalizability Theory

BACKGROUND

The distinction between temporary versus enduring or state/trait aspects of depression is important. More precise distinction would improve understanding of the aetiology of depression and those aspects most amenable to intervention thus identifying more homogeneous, dynamic targets for clinical trials. Generalizability Theory has been proposed as useful for disentangling state and trait components of psychopathology.

METHODS

We applied Generalizability Theory to determine the relative contributions of temporary and enduring aspects of depression in a widely used screening measure of depression the - 10-item Children's Depression Inventory (CDI-10; Kovacs, 1985). Participants were children of Pacific Island descent living in New Zealand (n = 668). Data were collected at ages - 9, 11, and 14 years.

RESULTS

The CDI-10 demonstrated acceptable generalizability across occasions (G = 0.79) with about one third of variance in total scores attributed to temporary and two thirds to more enduring aspects of depression. There were no other significant sources of error variance. Two items were identified as more sensitive than the remaining eight to more dynamic symptoms.

LIMITATIONS

Studies with briefer test-retest intervals are warranted. Use of this Pacific Island cohort limits generalizability of findings to other cultures and ethnicities. No data were collected on whether participants had received intervention for depression.

CONCLUSIONS

While the CDI-10 reliably measures both stable and transient aspects of depression in children, the scale does not permit clear distinction between them. We advocate application of Generalizability Theory for developing state/trait depression measures and determining which existing measures are most suitable for capturing modifiable features of depression.

Using Multigroup-Multiphase Latent State-Trait Models to Study Treatment-Induced Changes in Intra-Individual State Variability: An Application to Smokers' Affect

Sometimes, researchers are interested in whether an intervention, experimental manipulation, or other treatment causes changes in intra-individual state variability. The authors show how multigroup-multiphase latent state-trait (MG-MP-LST) models can be used to examine treatment effects with regard to both mean differences and differences in state variability. The approach is illustrated based on a randomized controlled trial in which N = 338 smokers were randomly assigned to nicotine replacement therapy (NRT) vs. placebo prior to quitting smoking. We found that post quitting, smokers in both the NRT and placebo group had significantly reduced intra-individual affect state variability with respect to the affect items calm and content relative to the pre-quitting phase. This reduction in state variability did not differ between the NRT and placebo groups, indicating that quitting smoking may lead to a stabilization of individuals' affect states regardless of whether or not individuals receive NRT.