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Assessing a Smartphone App (AICaries) That Uses Artificial Intelligence to Detect Dental Caries in Children and
Jin Xiao1, Jiebo Luo2, Oriana Ly-Mapes1
1Eastman Institute for Oral Health, University of Rochester, Rochester, NY, United States.
Insights
Parents can use the AICaries smartphone app for early detection of childhood cavities. This AI-powered tool helps parents identify early childhood caries (ECC) and access crucial information for prevention.
Area of Science:
- Digital health interventions
- Artificial intelligence in healthcare
- Pediatric oral health
Background:
- Early childhood caries (ECC) is a prevalent chronic disease affecting millions globally, particularly low-income US children.
- ECC leads to significant health issues and reduced quality of life, often diagnosed late due to limited access to dental care.
- Smartphone apps offer a promising avenue for patient-driven early detection and risk management of ECC.
Purpose of the Study:
- To refine and evaluate the usability of AICaries, an AI-powered smartphone application for parents to detect dental caries in children.
- Employ a community-based participatory research strategy to enhance the app's effectiveness.
Main Methods:
- A two-step qualitative study design was used to assess app usability and parent feedback.
- Step 1 involved 10 parent-child pairs for usability testing and app refinement.
- Step 2 included unmoderated field testing with 32 parent-child pairs to evaluate feasibility, acceptability, and image quality.
Main Results:
- The study is funded by the National Institute of Dental and Craniofacial Research.
- IRB approval was obtained, and the study launched in August 2021, with data collection concluding in March 2022.
Conclusions:
- The AICaries app empowers parents to detect ECC early using smartphones, facilitating timely treatment.
- Parents can utilize the app to gain knowledge on reducing caries risk in children.
- Study data will inform a future clinical trial on the real-world impact of AICaries on ECC prevention.
Background:
Early childhood caries (ECC) is the most common chronic childhood disease, with nearly 1.8 billion new cases per year worldwide. ECC afflicts approximately 55% of low-income and minority US preschool children, resulting in harmful short- and long-term effects on health and quality of life. Clinical evidence shows that caries is reversible if detected and addressed in its early stages. However, many low-income US children often have poor access to pediatric dental services. In this underserved group, dental caries is often diagnosed at a late stage when extensive restorative treatment is needed. With more than 85% of lower-income Americans owning a smartphone, mobile health tools such as smartphone apps hold promise in achieving patient-driven early detection and risk control of ECC.
Objective:
This study aims to use a community-based participatory research strategy to refine and test the usability of an artificial intelligence-powered smartphone app, AICaries, to be used by children's parents/caregivers for dental caries detection in their children.
Methods:
Our previous work has led to the prototype of AICaries, which offers artificial intelligence-powered caries detection using photos of children's teeth taken by the parents' smartphones, interactive caries risk assessment, and personalized education on reducing children's ECC risk. This AICaries study will use a two-step qualitative study design to assess the feedback and usability of the app component and app flow, and whether parents can take photos of children's teeth on their own. Specifically, in step 1, we will conduct individual usability tests among 10 pairs of end users (parents with young children) to facilitate app module modification and fine-tuning using think aloud and instant data analysis strategies. In step 2, we will conduct unmoderated field testing for app feasibility and acceptability among 32 pairs of parents with their young children to assess the usability and acceptability of AICaries, including assessing the number/quality of teeth images taken by the parents for their children and parents' satisfaction.
Results:
The study is funded by the National Institute of Dental and Craniofacial Research, United States. This study received institutional review board approval and launched in August 2021. Data collection and analysis are expected to conclude by March 2022 and June 2022, respectively.
Conclusions:
Using AICaries, parents can use their regular smartphones to take photos of their children's teeth and detect ECC aided by AICaries so that they can actively seek treatment for their children at an early and reversible stage of ECC. Using AICaries, parents can also obtain essential knowledge on reducing their children's caries risk. Data from this study will support a future clinical trial that evaluates the real-world impact of using this smartphone app on early detection and prevention of ECC among low-income children.
International Registered Report Identifier (Irrid):
PRR1-10.2196/32921.
