Machine Learning Overview

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Types of Machine Learning Algorithms

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An Integrated Framework for Solving Email Management Problems with Unsupervised Machine Learning Techniques and Artificial Neural Networks

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Dictive Factors of Dental Anxiety in Adult Patients at a Tertiary Dental Hospital in Nigeria: Dictive Factors of Dental Anxiety in Adult Patients at a Tertiary Dental Hospital in Nigeria

Objective: This study was designed to assess the prevalence and associated factors of dental anxiety among adult patients attending a tertiary dental hospital in Nigeria, while also identifying potential predictors of dental anxiety. Method:  A total of 177 adult dental patients completed a self -administered questionnaire comprising socio-demographic information and other information relating to medical conditions, pain, health insurance coverage, previous dental visits and self-perception of oral health. Dental anxiety was assessed with the Modified dental anxiety scale. Result: The prevalence of dental anxiety was 10.73% (MDAS=19-25) with overall severity mean score of 13.36±3.41. Age and sex were associated with the level of dental anxiety (p-values of 0.027 and 0.007 respectively). Moreover, age, sex and level of education were associated with mean anxiety levels (p-values of 0.043, 0.009 and 0.015 respectively). Previous dental visits and self-perception of oral health were associated with dental anxiety (p-values of 0.034 and < 0.001 respectively). Sex, marital status, previous dental visits and self-oral health perception were predictors of high dental anxiety (p-values of 0.028, 0.019, 0.033 and 0.001 respectively). Conclusion: Demographic factors, previous dental visits and self-perception of oral health are associated with dental anxiety. Predictors of high dental anxiety are sex, marital status, previous dental visits and self-oral health perception