Aims And Objectives: Predicting caries risk in children can be done by identifying caries risk factors. It is an important measure which contributes to best understanding of the cariogenic profile of the patient. Identification could be done by clinical examination and answering the questionnaire. We arrange the study to verify the questionnaire validation for predicting caries risk in children.
Materials And Methods: The study was conducted on 62 pairs of mothers and their children, aged between 3 and 5 years. The questionnaire consists of 10 questions concerning mothers' attitude and knowledge about oral health. The reliability and validity test is based on Cronbach's alpha and correlation coefficient value.
Results: All question are reliable (Cronbach's alpha = 0.873) and valid (Corrected item-total item correlation >0.4).
Conclusions: Five questionnaires of mother's attitude about oral health and five questionnaires of mother's knowledge about oral health are reliable and valid for predicting caries risk in children.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5502551 | PMC |
http://dx.doi.org/10.4103/jispcd.JISPCD_148_17 | DOI Listing |
Medicina (Kaunas)
December 2024
Department of Biochemistry, School of Dental Medicine, University of Belgrade, 11000 Belgrade, Serbia.
: Caries development is associated with poor oral hygiene, inadequate dietary habits, quantitative and qualitative food content, and a high level of bacterial plaque. Physical and chemical changes in saliva composition and particularly changes in its buffering capability play a significant role in caries development. This study aimed to determine the predictors of poor oral health among a sample of second-year dental students.
View Article and Find Full Text PDFBioengineering (Basel)
December 2024
Department of Conservative Dentistry & Endodontics, Narayana Dental College and Hospital, Nellore 523004, Andhra Pradesh, India.
Artificial intelligence (AI) is an area of computer science that focuses on designing machines or systems that can perform operations that would typically need human intelligence. AI is a rapidly developing technology that has grabbed the interest of researchers from all across the globe in the healthcare industry. Advancements in machine learning and data analysis have revolutionized oral health diagnosis, treatment, and management, making it a transformative force in healthcare, particularly in dentistry.
View Article and Find Full Text PDFChildren (Basel)
December 2024
Department of Pediatric Dentistry, Faculty of Dentistry, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Background/objectives: Obesity and dental caries are significant health issues affecting children worldwide. This study aims to investigate the prevalence of obesity and dental caries among kindergarten children in Saudi Arabia during the early implementation years of the Vision 2030 initiative. Specifically, it examines the obesity rates between public and private kindergartens and assesses the correlation between obesity and caries risk.
View Article and Find Full Text PDFChildren (Basel)
November 2024
Pediatric Dentistry Department, University Medicine of Greifswald, 17475 Greifswald, Germany.
Background: Nationally representative long-term data on caries in the primary dentition are rare but essential for determining the need for prevention and treatment. This research assessed the prevalence and trends of dental caries in 3-year-old children across Germany, with national data analyzed and compared with the corresponding data for 6-7-year-olds.
Methods: Data were extracted from the most recent German National Oral Health Survey in 2016.
Int J Paleopathol
January 2025
School of Archaeology and Ancient History, University of Leicester, United Kingdom. Electronic address:
Objective: To gain a more holistic understanding of oral health in the past by producing an 'Index of Oro-dental Disease' (IOD), incorporating multiple oro-dental diseases and accounting for differences in antemortem/postmortem alveolar bone and tooth loss.
Materials: UK Adult Dental Health Survey, 2009 anonymised dataset (N = 6206). Archaeological dental data from skeletal individuals from medieval and post-medieval Barton-upon-Humber, North Lincolnshire (N = 214, 1150-1855) and St James's Gardens Burial Ground, London (N = 281, 1789-1853).
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!