Development of a Artificial Intelligence Dental Anxiety Scale (AI -CDAS) For Children: Validation And Reliability

Area of Science:

• Pediatric Dentistry
• Psychometric Evaluation
• Artificial Intelligence in Healthcare

Background:

• Assessing pediatric dental anxiety is challenging with traditional patient-based scales.
• There is a need for reliable and valid tools to quantify dental anxiety in children.
• Artificial Intelligence offers potential for developing innovative assessment methods.

Purpose of the Study:

• To evaluate the psychometric properties (validity and reliability) of the Artificial Intelligence Child Dental Anxiety Scale (AI-CDAS).
• To establish AI-CDAS as a dependable tool for detecting dental anxiety in pediatric patients.
• To assess the correlation between AI-CDAS and a validated facial affective scale.

Main Methods:

• A study involving 100 outpatients aged 3-9 years was conducted.
• Dental anxiety was measured using the AI-CDAS with a facial response set.
• AI-CDAS scores were compared against the Colored Version of the Modified Facial Affective Scale.

Main Results:

• The AI-CDAS demonstrated good reliability and validity.
• Significant correlations were observed between AI-CDAS and the Colored Version of the Modified Facial Affective Scale.
• The AI-CDAS proved to be a reliable measure for assessing children's dental anxiety.

Conclusions:

• The Artificial Intelligence Child Dental Anxiety Scale (AI-CDAS) is a valid and reliable instrument for assessing pediatric dental anxiety.
• AI-CDAS can assist dentists in routinely evaluating dental anxiety in children.
• Self-report measures like AI-CDAS are easy to administer and provide valuable insights into patient experiences.