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
JMIR Res Protoc 2021;10(10):e32921
doi:10.2196/32921
Keywords
artificial intelligence (204); smartphone app (56); mDentistry; dental caries (7); underserved population (1); mobile dentistry
Introduction
Early childhood caries (ECC) is by far the most common chronic childhood disease, with nearly 1.8 billion new cases per year worldwide 1-3. In the United States, it afflicts approximately 37% of all children aged 2-5 years but disproportionately affects up to 55% of low-income and minority children. Untreated ECC often leads to higher risk of caries lesions in permanent teeth, diminished oral health–related quality of life, hospitalizations and emergency room visits due to systemic infection, and even death 4,5. Hence, more innovative/effective preventive and treatment strategies are needed, particularly early detection of ECC.
The current biomedical approach to control the ECC pandemic has had limited success. Primarily, this approach focuses on individual-level restorative procedures rather than populationwide preventive strategies. Dental caries is localized destruction of dental hard tissues (enamel and dentin) by acidic by-products from the microbial fermentation of carbohydrates. In the early (subclinical) stages, such as white spot lesions on the tooth enamel surface, caries can be reversed. Many US preschool children from low-income families, however, often have poor access to pediatric dental services; limited dental access leave the underserved children in positions where dental caries is often diagnosed in later stages, thus requiring more extensive restorative treatments. Moreover, ECC is a multifactorial disease with host, microorganisms, diet, and oral hygiene practices as the factors that determine the risks 6-9. Children’s parents/caregivers need to be engaged around these risk factors and acquire skills to self-manage risk to reduce children’s risk for ECC.
To combat this ECC pandemic and overcome the barriers of lacking dental access among underserved children and lacking self-management awareness of these children’s caregivers, our long-term goal is to develop a first-of-its-kind artificial intelligence (AI)–powered smartphone app to be used by children’s parents, which offers patient-centered caries detection and caries risk management.
Smartphone apps have been successfully applied in managing individual behaviors and health conditions 10 such as smoking cessation, weight loss, medication adherence, and Parkinson disease progression monitoring 10-12. With 77% of all age American individuals 13 and more than 85% of lower-income mid-age American individuals 14,15 owning a smartphone, a smartphone app presents as a suitable and innovative way of providing oral health interventions. Recently, mobile dentistry has been brought up by researchers to promote oral health care at a broad population base 16,17; however, current oral health smartphone apps are limited in scope and audience. First, compared to the large amount of available medical health apps in the commercial app store, the number of apps that are oral health focused is minimal. Second, most of the available apps are designed for improving the efficiency of tooth brushing or helping users understand oral disease types and manifestation. There is no technology, much less any app, that can be used by parents for early detection of caries in their children. Furthermore, using AI to aid imaging recognition has been applied to improve disease diagnosis in many medical fields including oncology, ophthalmology, radiology, etc 18-21. However, modern dentistry has not used AI imaging technology for caries detection. To our knowledge, AICaries will be the first app using this technology in dentistry.
In summary, a patient-friendly smartphone app coupled with AI-powered caries detection holds promise in facilitating early clinical confirmation and treatment of ECC. Led by experts in AI imaging recognition, oral health, and mobile health (mHealth), this AICaries study will address the gap in research and clinical practice for ECC from the angle of disease early detection and self-management using mHealth tools.
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