Abstract
ABSTRACT
Background: Anxiety and fear are dominant themes in dentistry, particularly among children, which can persist into adulthood. Dental anxiety patients are challenging for dentists, So we should recognize dental anxiety in children as early as possible to plan the appropriate behavior guidance technique and perform successful dental treatment instilling positive behavior in the child.
Objectives: To assess the reliability and validity of the innovative RMS Digital Child Dental Anxiety Scale (RMS-DCDAS) in measuring children’s dental anxiety before visiting the dentist.
Material and methods: A prospective observational cross-sectional study using an innovative mobile application RMS-Digital Child Dental Anxiety Scale (RMS-DCDAS) incorporating artificial intelligence was developed and targeted children in private schools of Khorfakkan, Sharjah, UAE. A total of 520 children aged between 6 and 12 years, were randomly divided into reliability and validity
groups. A total of 287 children were included in the reliability group, they answered the eight questions of RMS-DCDAS and were recalled after two weeks for the retest. While 233 children in the validity group, were asked to answer 2 scales RMS-DCDAS and MCDASf in the same visit. The children in the validity groups were asked to choose the scales they liked the most.
Statistical analysis: Internal consistency of the RMS-DCDAS was assessed statistically using Cronbach's Alpha and the test-retest was evaluated using Paired t-test, and Spearman’s correlation coefficient. Construct validity of RMS-DCDAS was obtained by correlating the scale with MCDASf using Spearman’s correlation coefficient.
Results: The internal consistency of RMS-DCDAS was reliable (a=0.743). No significant difference was seen in questions no. 1, 2, 3, 5, and 8. However, there was a significant difference seen in the test-retest score with questions no. 4 (local anesthesia), 6 (extraction), and 7 (general anesthesia). Spearman's coefficient showed an overall strong correlation. For validity, Spearman's coefficient correlation showed a very strong correlation in all the questions between RMS DCDAS and MCDASf scores (0.909). When RMS-DCDAS scores were examined for validity with MCDASf by paired t-test, no significant difference was seen in any of the questions.
Conclusions: The findings of the present study suggest that the innovative RMS-DCDAS is reliable and valid that can be used as a new tool to assess children’s dental anxiety.
Keywords: Anxiety Scale, Artificial Intelligence, Anxiety in children, Dental anxiety, Digital Anxiety Scale, RMS-DCDAS, RMS-Digital Child Dental Anxiety Scale, MCDASf.
