AIMC Topic: Surveys and Questionnaires

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From digital disruption to mental health: the impact of AI-induced educational anxiety on teacher well-being in the era of smart education.

BMC public health
BACKGROUND: In the context of artificial intelligence (AI) profoundly reshaping the educational ecosystem, teachers, as core drivers of the intelligent education era, are facing unprecedented opportunities and mental health challenges. Although AI de...

AI chatbots as 'pocket doctors': intimate health support for young women in Lebanon.

BMC public health
BACKGROUND: In conservative societies such as Lebanon and the broader Middle East and North Africa region, gynecological and intimate health issues are heavily stigmatized, limiting young women's access to care due to fear of judgment, privacy concer...

Evaluating the Accuracy of the Frysian Questionnaire for Differentiation of Musculoskeletal Complaints for Triage of Musculoskeletal Diseases: Algorithm Development and Validation Study.

JMIR medical informatics
BACKGROUND: Inflammatory rheumatic diseases (IRDs) affect 5% of the general population, whereas 35% of the population experiences musculoskeletal concerns. IRDs cause early disability, reduced life expectancy, and considerable health care costs. Earl...

Using machine learning to predict student outcomes for early intervention and formative assessment.

Scientific reports
The increasing importance of early prediction of student performance has led to research into machine learning models that can be used to assess student outcomes more accurately.This study focused on developing a predictive model based on machine lea...

Perceptions and Intentions to Use Generative AI Among First-Year Medical Students in Japan: Cross-Sectional Survey Study.

JMIR medical education
An April 2025 survey of 118 first-year Japanese medical students found high use of generative artificial intelligence (84.7%) but limited formal learning (49.2%), with strong learning interest yet neutral assignment use, indicating a need for structu...

From dry eye to depression: a machine learning-based framework for predicting adolescent mental health.

BMC medical informatics and decision making
BACKGROUND: Adolescent depression is a major public health concern. Physical health indicators are rarely included in risk tools. We examined whether adding dry eye disease (DED) to psychosocial and behavioral factors improves prediction of depressiv...

Leveraging industry 4.0 technologies for healthcare innovation and efficiency.

PloS one
This study investigates the specific impacts of Industry 4.0 technologies-such as artificial intelligence, Internet of Things (IoT), and data-driven automation-on collaboration, communication, service efficiency, and organizational performance within...

Demographic influences on trust in artificial intelligence across cognitive domains: A statistical perspective.

PloS one
As artificial intelligence (AI) systems become increasingly integrated into decision-making across various sectors, understanding public trust in these systems is more crucial than ever. This study presents a quantitative analysis of survey data from...

Factors contributing to differences in physical activity levels in (pre)frail older adults living in rural areas of China.

PloS one
INTRODUCTION: Physical Activity (PA) is essential for enhancing the physical function of pre-frail and frail older adults. However, among this group, PA-levels vary significantly. Identifying the factors contributing to these differences could suppor...

Robot or human? Manoeuvring switching intention after robot service failure.

PloS one
This study attempts to scrutinise tourists' switching intentions towards human service after a robot service failure, with the zone of tolerance and trust on stance in technology as moderators. The study adopts the unified theory of acceptance and us...