AIMC Topic: Anxiety
Clear Filters Showing 61 to 70 of 187 articles
Predictive modelling of stress, anxiety and depression: A network analysis and machine learning study.
The British journal of clinical psychology
Jun 25, 2024
OBJECTIVE: This study assessed predictors of stress, anxiety and depression during the COVID-19 pandemic using a large number of demographic, COVID-19 context and psychological variables.
Predicting Depression, Anxiety, and Their Comorbidity among Patients with Breast Cancer in China Using Machine Learning: A Multisite Cross-Sectional Study.
Depression and anxiety
Jun 21, 2024
Depression and anxiety are highly prevalent among patients with breast cancer. We tested the capacity of personal resources (psychological resilience, social support, and process of recovery) for predicting depression, anxiety, and comorbid depressio...
Evaluation of future nurses' knowledge, attitudes and anxiety levels about artificial intelligence applications.
Journal of evaluation in clinical practice
Jun 18, 2024
RATIONALE: Evaluating future nurses' perspectives on artificial intelligence, determining their missing or incorrect information on the subject and determining their anxiety levels are of great importance in terms of providing science and technology-...
Implementation of Anxiety UK's Ask Anxia Chatbot Service: Lessons Learned.
JMIR human factors
Jun 17, 2024
Chatbots are increasingly being applied in the context of health care, providing access to services when there are constraints on human resources. Simple, rule-based chatbots are suited to high-volume, repetitive tasks and can therefore be used effec...
Use of Machine Learning Algorithms Based on Text, Audio, and Video Data in the Prediction of Anxiety and Posttraumatic Stress in General and Clinical Populations: A Systematic Review.
Biological psychiatry
Jun 10, 2024
Research in machine learning (ML) algorithms using natural behavior (i.e., text, audio, and video data) suggests that these techniques could contribute to personalization in psychology and psychiatry. However, a systematic review of the current state...
Machine learning identifies different related factors associated with depression and suicidal ideation in Chinese children and adolescents.
Journal of affective disorders
Jun 4, 2024
BACKGROUND: Depression and suicidal ideation often co-occur in children and adolescents, yet they possess distinct characteristics. This study sought to identify the different related factors associated with depression and suicidal ideation.
Evaluation of Biomechanical and Mental Workload During Human-Robot Collaborative Pollination Task.
Human factors
May 28, 2024
OBJECTIVE: The purpose of this study is to identify the potential biomechanical and cognitive workload effects induced by human robot collaborative pollination task, how additional cues and reliability of the robot influence these effects and whether...
Effects of midwifery and nursing students' readiness about medical Artificial intelligence on Artificial intelligence anxiety.
Nurse education in practice
May 24, 2024
BACKGROUND: Artificial intelligence technologies are one of the most important technologies of today. Developments in artificial intelligence technologies have widespread and increased the use of artificial intelligence in many areas. The field of he...
Study of a PST-trained voice-enabled artificial intelligence counselor for adults with emotional distress (SPEAC-2): Design and methods.
Contemporary clinical trials
May 18, 2024
BACKGROUND: Novel and scalable psychotherapies are urgently needed to address the depression and anxiety epidemic. Leveraging artificial intelligence (AI), a voice-based virtual coach named Lumen was developed to deliver problem solving treatment (PS...
Examining how gamers connect with their avatars to assess their anxiety: A novel artificial intelligence approach.
Acta psychologica
May 2, 2024
Research has supported that a gamer's attachment to their avatar can offer significant insights about their mental health, including anxiety. To assess this hypothesis, longitudinal data from 565 adult and adolescent participants (M = 29.3 years, SD ...
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