Anxiety & Stress

Preliminary investigation of an artificial intelligence-based cognitive behavioral therapy training tool.

We developed an asynchronous online cognitive behavioral therapy (CBT) training tool that provides artificial intelligence- (AI-) enabled feedback to learners across eight CBT skills. We sought to evaluate the technical reliability and to ascertain how practitioners would use the tool to inform product iteration and future deployment. We conducted a single-arm 2-week field trial among behavioral h...

The influence of generative artificial intelligence on creative cognition of design students: a chain mediation model of self-efficacy and anxiety.

INTRODUCTION: This study investigated the role of generative Artificial Intelligence (AI) in enhancing the creative cognition of design students, examining the mediating effects of self-efficacy and anxiety reduction.

Development of a machine learning-based multivariable prediction model for the naturalistic course of generalized anxiety disorder.

BACKGROUND: Generalized Anxiety Disorder (GAD) is a chronic condition. Enabling the prediction of individual trajectories would facilitate tailored ma...

Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records.

BACKGROUND: Depression and anxiety are prevalent mental health conditions among individuals with type 2 diabetes mellitus (T2DM), who exhibit unique v...

Functional Disability and Psychological Impact in Headache Patients: A Comparative Study Using Conventional Statistics and Machine Learning Analysis.

: Recent research has focused on exploring the relationships between various factors associated with headaches and understanding their impact on indiv...

Identifying Neuro-Inflammatory Biomarkers of Generalized Anxiety Disorder from Lymphocyte Subsets Based on Machine Learning Approaches.

INTRODUCTION: Activation of the inflammatory response system is involved in the pathogenesis of generalized anxiety disorder (GAD). The purpose of thi...

Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat ( L.).

Phytochromes are essential photoreceptors in plants that sense red and far-red light, playing a vital role in regulating plant growth and development ...

Physalis Calyx seu Fructus relieves chicken intestinal damage to heat via improving the antioxidant ability.

Heat-stress-induced oxidative and inflammatory responses were important factors contributing to chicken intestinal damage. The purpose of this study w...

Musicians and researchers: two creative professions striving to improve heart health through music.

Musicians and researchers are creative professions that share many similarities. They both aim to bring joy and progress to humanity. In recent decade...

Brain mapping, biomarker identification and using machine learning method for diagnosis of anxiety during emotional face in preschool children.

BACKGROUND: Due to the importance and the consequences of anxiety, the goals of the current study are brain mapping, biomarker identification and the ...

Automated classification of stress and relaxation responses in major depressive disorder, panic disorder, and healthy participants via heart rate variability.

BACKGROUND: Stress is a significant risk factor for psychiatric disorders such as major depressive disorder (MDD) and panic disorder (PD). This highli...

Prediction of health anxiety using resting-state functional near-infrared spectroscopy and machine learning.

BACKGROUND: The role of cortical networks in health anxiety remain poorly understood. This study aimed to develop a predictive model for health anxiet...

Predicting 28-day all-cause mortality in patients admitted to intensive care units with pre-existing chronic heart failure using the stress hyperglycemia ratio: a machine learning-driven retrospective cohort analysis.

Chronic heart failure (CHF) poses a significant threat to human health. The stress hyperglycemia ratio (SHR) is a novel metric for accurately assessin...

Understanding the impacts of drought on peanuts L.): exploring physio-genetic mechanisms to develop drought-resilient peanut cultivars.

Peanut is a vital source of protein, particularly in the tropical regions of Asian and African countries. About three-quarters of peanut production oc...

Key risk factors of generalized anxiety disorder in adolescents: machine learning study.

Adolescents worldwide are increasingly affected by mental health disorders, with anxiety disorders, including Generalized Anxiety Disorder (GAD), bein...

Machine learning prediction of anxiety symptoms in social anxiety disorder: utilizing multimodal data from virtual reality sessions.

INTRODUCTION: Machine learning (ML) is an effective tool for predicting mental states and is a key technology in digital psychiatry. This study aimed ...

Personalized stress optimization intervention to reduce adolescents' anxiety: A randomized controlled trial leveraging machine learning.

Anxiety symptoms are among the most prevalent mental health disorders in adolescents, highlighting the need for scalable and accessible interventions....

Differential gray matter correlates and machine learning prediction of abuse and internalizing psychopathology in adolescent females.

Childhood abuse represents one of the most potent risk factors for the development of psychopathology during childhood, accounting for 30-60% of the r...

Stress Monitoring in Pandemic Screening: Insights from GSR Sensor and Machine Learning Analysis.

This study investigates the impact of patient stress on COVID-19 screening. An attempt was made to measure the level of anxiety of individuals underta...

Machine learning and confirmatory factor analysis show that buprenorphine alters motor and anxiety-like behaviors in male, female, and obese C57BL/6J mice.

Buprenorphine is an opioid approved for medication-assisted treatment of opioid use disorder. Used off-label, buprenorphine has been reported to contr...