AIMC Topic: Surveys and Questionnaires

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Psychometric properties and Turkish adaptation of the artificial intelligence attitude scale (AIAS-4): evidence for construct validity.

BMC psychology
Artificial intelligence (AI) attitude scales can be used to better evaluate the benefit and drawback cons of AI. This article consists of two different studies examining attitudes towards AI. In Study I (N = 370), the four-item Artificial Intelligenc...

Artificial Intelligence and Qualitative Analysis of Emergency Department Telemental Health Care Implementation Survey.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
: Implementation of telemental health care in emergency departments (EDs) in the United States (U.S.) has been increasing. Artificial intelligence (AI) can augment traditional qualitative research methods; little is known about its efficiency and acc...

The AI-environment paradox: Unraveling the impact of artificial intelligence (AI) adoption on pro-environmental behavior through work overload and self-efficacy in AI learning.

Journal of environmental management
This study examines the complex relationships among artificial intelligence (AI) adoption in organizations, employee work overload, and pro-environmental behavior at work (PEBW), while examining the moderating role of self-efficacy in AI learning. Dr...

Pharmacy faculty and students perceptions of artificial intelligence: A National Survey.

Currents in pharmacy teaching & learning
INTRODUCTION: This study explores the perceptions, familiarity, and utilization of artificial intelligence (AI) among pharmacy faculty and students across the United States. By identifying key gaps in AI education and training, it highlights the need...

CLIP in medical imaging: A survey.

Medical image analysis
Contrastive Language-Image Pre-training (CLIP), a simple yet effective pre-training paradigm, successfully introduces text supervision to vision models. It has shown promising results across various tasks due to its generalizability and interpretabil...

Improving diagnosis-based quality measures: an application of machine learning to the prediction of substance use disorder among outpatients.

BMJ open quality
OBJECTIVE: Substance use disorder (SUD) is clinically under-detected and under-documented. We built and validated machine learning (ML) models to estimate SUD prevalence from electronic health record (EHR) data and to assess variation in facility-lev...

Trust and Acceptance Challenges in the Adoption of AI Applications in Health Care: Quantitative Survey Analysis.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) has potential to transform health care, but its successful implementation depends on the trust and acceptance of consumers and patients. Understanding the factors that influence attitudes toward AI is crucial ...

Unveiling sex difference in factors associated with suicide attempt among Chinese adolescents with depression: a machine learning-based study.

Journal of mental health (Abingdon, England)
BACKGROUND: Adolescents with depression are at heightened risk of suicide, with a distinct sex difference in suicidal behaviour observed. This study explores the sex-specific factors influencing suicide attempts among Chinese adolescents with depress...

Catenation between mHealth application advertisements and cardiovascular diseases: moderation of artificial intelligence (AI)-enabled internet of things, digital divide, and individual trust.

BMC public health
BACKGROUND: World Health Organization (WHO) identified noncommunicable diseases as the foremost risk to public health globally and the cause of approximately 80% of premature deaths. However, Cardiovascular diseases account for most of these prematur...