AIMC Topic: Psychiatric Status Rating Scales

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Evaluating the Efficacy of AI-Based Interactive Assessments Using Large Language Models for Depression Screening: Development and Usability Study.

JMIR formative research
BACKGROUND: The evolution of language models, particularly large language models, has introduced transformative potential for psychological assessment, challenging traditional rating scale methods that have dominated clinical practice for over a cent...

Smartwatch-Derived Digital Phenotypes Relate to Psychopathology Dimensions in Patients With Psychotic Spectrum Disorders: Longitudinal Observational Study.

JMIR mental health
BACKGROUND: Digital phenotyping refers to the objective measurement of human behavior via devices such as smartphones or watches and constitutes a promising advancement in personalized medicine. Digital phenotypes derived from heart rate, mobility, o...

Development of the Screen for Child Anxiety Related Emotional Disorders (SCARED) optimal short scale for Chinese children and adolescents: based on FasterRisk machine learning modeling.

BMC public health
BACKGROUND: Although the Screen for Child Anxiety Related Emotional Disorders (SCARED) is a widely used tool for assessing anxiety, its 41-item format makes it a time-intensive method for identifying children and adolescents at high risk of anxiety. ...

Decoding depression: Event related potential dynamics and predictive neural signatures of depression severity.

Journal of affective disorders
Depression is a heterogeneous disorder marked by disruptions in cognitive and affective processing. While self-reported measures and clinical interviews remain the diagnostic standard, integrating objective neurophysiological markers could enhance as...

Evaluating the Chinese versions of delirium assessment scales: a diagnostic systematic review.

BMC psychiatry
BACKGROUND: The purpose of this study is to examine the validity, reliability and methodological quality of delirium scales that have been translated and adapted in China using quality assessment tools.

AI-driven analyzes of open-ended responses to assess outcomes of internet-based cognitive behavioral therapy (ICBT) in adolescents with anxiety and depression comorbidity.

Journal of affective disorders
OBJECTIVE: Although patients prefer describing their problems using words, mental health interventions are commonly evaluated using rating scales. Fortunately, recent advances in natural language processing (i.e., AI-methods) yield new opportunities ...

Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection.

BMC psychiatry
OBJECTIVE: To develop a stratified screening tool through machine learning approaches for the Center for Epidemiologic Studies Depression Scale (CES-D-20) while maintaining diagnostic accuracy, addressing the efficiency limitations in large-scale app...

Enhancing prediction of major depressive disorder onset in adolescents: A machine learning approach.

Journal of psychiatric research
Major Depressive Disorder (MDD) is a prevalent mental health condition that often begins in adolescence, with significant long-term implications. Indicated prevention programs targeting adolescents with mild symptoms have shown efficacy, yet the meth...