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Aim And Objectives: In the preoperative period, non-pharmacological methods such as multimedia applications and visual and audio technological tools are used to reduce children's fear and anxiety levels and to distract their attention to create a more enjoyable experience. One of these innovative technologies having attracted attention recently is augmented reality technology. The study was aimed investigating the effects of reading an augmented reality storybook on fear and anxiety levels of children in the age group of 7-12 years in the preoperative period.

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The Transformative Role of Artificial Intelligence in Dentistry: A Comprehensive Overview. Part 1: Fundamentals of AI, and its Contemporary Applications in Dentistry.

Int Dent J

March 2025

Department of Restorative Dentistry, College of Dentistry, Ajman University, Ajman, United Arab Emirates; Centre of Medical and Bio-allied Health Sciences Research, Ajman University, Ajman, United Arab Emirates.

Artificial intelligence (AI) holds immense promise in revolutionising dentistry, spanning, diagnostics, treatment planning and educational realms. This narrative review, in two parts, explores the fundamentals and the multifaceted potential of AI in dentistry. The current article explores the profound impact of AI in dentistry, encompassing diagnostic tools, treatment planning, and patient care.

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Introduction: Breaking bad news (BBN) is a distressing yet essential task in medicine, imposing emotional strain on both physicians and patients. Crucially, effective BBN relies on both verbal and nonverbal communication, which can be impaired by elevated stress associated with the task. Efficient teaching of communication skills continues to present a challenge, and the role of stress management in BBN encounters remains largely overlooked.

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Introduction: Despite the crucial importance of effective AFS in resource-limited settings, such settings remain comparatively underserved and underrepresented in terms of resource-setting-specific guidance and research. Further practical contextualization and application of current AFS best practices is thus necessary.

Areas Covered: A panel of leading experts from diverse countries (India, Nigeria, Spain, and the US) was brought together to provide recommendations for practical and effective implementation of AFS in resource-limited settings.

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Background: To demonstrate the application and utility of geostatistical modelling to provide comprehensive high-resolution understanding of the population's protective immunity during a pandemic and identify pockets with sub-optimal protection.

Methods: Using data from a national cross-sectional household survey of 6620 individuals in the Dominican Republic (DR) from June to October 2021, we developed and applied geostatistical regression models to estimate and predict Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) spike (anti-S) antibodies (Ab) seroprevalence at high resolution (1 km) across heterogeneous areas.

Results: Spatial patterns in population immunity to SARS-CoV-2 varied across the DR.

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