Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes

Network analysis reveals how specific emotions relate to social connection in anxiety and depression, identifying hope, joy, sadness, and love as central to these relationships.

Temporal patterns in finger tapping predict task-unrelated thought. Higher Hurst exponent values associated with lower mind-wandering probability across metronome conditions.

Longitudinal study reveals disorder-specific coping pathways: perceived constraints drive depression via avoidance, while anxiety involves multiple coping routes.

Study shows that specific mental health symptoms predict how people use flexible reasoning when making complex inferences, with alterations in goal-directed decision-making as a key mechanism.

Neural fMRI patterns predict treatment response in depression and anxiety through emotion regulation pathways, offering insights for precision medicine approaches.

Repeated exposure with brief support modestly improves self-appraisal in children with social anxiety disorder, though distorted self-evaluation persists as a core clinical feature.

Phenomenological study examining AI companions' role in emotion regulation support for university students with social anxiety, identifying benefits and technological dependence risks.

Longitudinal study shows dysfunctional metacognitive beliefs predict interpersonal distress trajectories independent of parental bonds, interpersonal style, depression and anxiety, suggesting new.

Study validates cognitive distortion architecture in Russian discourse using AI analysis of 249,414 social media texts, identifying 443,447 distortion instances across 18 categories with stable.

Longitudinal study examining how neural vulnerability markers predict stress-related emotional variability in adolescents using polyconnectomic depression risk scoring.