AIMC Topic: Surveys and Questionnaires

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Validating Emotion Analysis on Social Media Text for Detecting Psychological Distress: A Cross-Sectional Survey.

Issues in mental health nursing
This study investigates the relationship between self-reported psychological distress and emotions in social media posts, using a deep learning-based emotion analysis model. A cross-sectional design was used, collecting data from Instagram and Thread...

Deep learning approach in undergraduate nursing students and their relationship with learning outcomes: A latent profile analysis.

Nurse education in practice
BACKGROUND: Deep learning approach plays a pivotal role in nursing education, equipping students with the critical thinking skills and knowledge necessary to address complex clinical challenges. However, nursing students exhibit diverse approaches to...

Integrating AI in medical education: a comprehensive study of medical students' attitudes, concerns, and behavioral intentions.

BMC medical education
BACKGROUND: To analyze medical students' perceptions, trust, and attitudes toward artificial intelligence (AI) in medical education, and explore their willingness to integrate AI in learning and teaching practices.

A thematic analysis of what Australians state would change their minds on climate change.

Scientific reports
What do Australians believe would change their current opinions about climate change? In this study, we used audience segmentation analysis through the Six Americas Short Survey to identify groups of climate opinion holders within a representative sa...

Investigating the factors affecting the intention to separate e-waste among mobile phone repairers in an emerging economy: A hybrid structural equation modelling and artificial neural network approach.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
The growing number of mobile phone users on a global scale has led to enormous amounts of electronic waste (e-waste) being generated annually. Insufficient knowledge of e-waste separation causes individuals to dispose of e-waste along with other wast...

Impact of using an AI scribe on clinical documentation and clinician-patient interactions in allied health private practice: perspectives of clinicians and patients.

Musculoskeletal science & practice
BACKGROUND: The burden associated with clinical documentation can negatively impact patient care and job satisfaction amongst allied health professionals (AHPs). Digital scribes based on artificial intelligence (AI) may address these issues, but this...

Federated Learning in radiomics: A comprehensive meta-survey on medical image analysis.

Computer methods and programs in biomedicine
Federated Learning (FL) has emerged as a promising approach for collaborative medical image analysis while preserving data privacy, making it particularly suitable for radiomics tasks. This paper presents a systematic meta-analysis of recent surveys ...

Knowledge and use, perceptions of benefits and limitations of artificial intelligence chatbots among Italian physiotherapy students: a cross-sectional national study.

BMC medical education
BACKGROUND: Artificial Intelligence (AI) Chatbots (e.g., ChatGPT, Microsoft Bing, and Google Bard) can emulate human interaction and may support physiotherapy education. Despite growing interest, physiotherapy students' perspectives remain unexplored...