Assessing a Smartphone App (AICaries) That Uses Artificial Intelligence to Detect Dental Caries in Children and Provides Interactive Oral Health Education: Protocol for a Design and Usability Testing Study
BackgroundEarly 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 hea...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2021-10-01
|
| Series: | JMIR Research Protocols |
| Online Access: | https://www.researchprotocols.org/2021/10/e32921 |
| _version_ | 1797735576108007424 |
|---|---|
| author | Jin Xiao Jiebo Luo Oriana Ly-Mapes Tong Tong Wu Timothy Dye Nisreen Al Jallad Peirong Hao Jinlong Ruan Sherita Bullock Kevin Fiscella |
| author_facet | Jin Xiao Jiebo Luo Oriana Ly-Mapes Tong Tong Wu Timothy Dye Nisreen Al Jallad Peirong Hao Jinlong Ruan Sherita Bullock Kevin Fiscella |
| author_sort | Jin Xiao |
| collection | DOAJ |
| description |
BackgroundEarly 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.
ObjectiveThis 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.
MethodsOur 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.
ResultsThe 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.
ConclusionsUsing 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 |
| first_indexed | 2024-03-12T13:01:03Z |
| format | Article |
| id | doaj.art-0395c84018ef4485bf179e92257f2997 |
| institution | Directory Open Access Journal |
| issn | 1929-0748 |
| language | English |
| last_indexed | 2024-03-12T13:01:03Z |
| publishDate | 2021-10-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Research Protocols |
| spelling | doaj.art-0395c84018ef4485bf179e92257f29972023-08-28T19:34:43ZengJMIR PublicationsJMIR Research Protocols1929-07482021-10-011010e3292110.2196/32921Assessing a Smartphone App (AICaries) That Uses Artificial Intelligence to Detect Dental Caries in Children and Provides Interactive Oral Health Education: Protocol for a Design and Usability Testing StudyJin Xiaohttps://orcid.org/0000-0002-8776-2520Jiebo Luohttps://orcid.org/0000-0002-4516-9729Oriana Ly-Mapeshttps://orcid.org/0000-0002-0859-921XTong Tong Wuhttps://orcid.org/0000-0002-1175-9923Timothy Dyehttps://orcid.org/0000-0002-9801-4712Nisreen Al Jalladhttps://orcid.org/0000-0002-5990-8123Peirong Haohttps://orcid.org/0000-0002-2853-1562Jinlong Ruanhttps://orcid.org/0000-0003-0207-5463Sherita Bullockhttps://orcid.org/0000-0002-3727-8220Kevin Fiscellahttps://orcid.org/0000-0003-3613-8012 BackgroundEarly 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. ObjectiveThis 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. MethodsOur 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. ResultsThe 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. ConclusionsUsing 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)PRR1-10.2196/32921https://www.researchprotocols.org/2021/10/e32921 |
| spellingShingle | Jin Xiao Jiebo Luo Oriana Ly-Mapes Tong Tong Wu Timothy Dye Nisreen Al Jallad Peirong Hao Jinlong Ruan Sherita Bullock Kevin Fiscella Assessing a Smartphone App (AICaries) That Uses Artificial Intelligence to Detect Dental Caries in Children and Provides Interactive Oral Health Education: Protocol for a Design and Usability Testing Study JMIR Research Protocols |
| title | Assessing a Smartphone App (AICaries) That Uses Artificial Intelligence to Detect Dental Caries in Children and Provides Interactive Oral Health Education: Protocol for a Design and Usability Testing Study |
| title_full | Assessing a Smartphone App (AICaries) That Uses Artificial Intelligence to Detect Dental Caries in Children and Provides Interactive Oral Health Education: Protocol for a Design and Usability Testing Study |
| title_fullStr | Assessing a Smartphone App (AICaries) That Uses Artificial Intelligence to Detect Dental Caries in Children and Provides Interactive Oral Health Education: Protocol for a Design and Usability Testing Study |
| title_full_unstemmed | Assessing a Smartphone App (AICaries) That Uses Artificial Intelligence to Detect Dental Caries in Children and Provides Interactive Oral Health Education: Protocol for a Design and Usability Testing Study |
| title_short | Assessing a Smartphone App (AICaries) That Uses Artificial Intelligence to Detect Dental Caries in Children and Provides Interactive Oral Health Education: Protocol for a Design and Usability Testing Study |
| title_sort | assessing a smartphone app aicaries that uses artificial intelligence to detect dental caries in children and provides interactive oral health education protocol for a design and usability testing study |
| url | https://www.researchprotocols.org/2021/10/e32921 |
| work_keys_str_mv | AT jinxiao assessingasmartphoneappaicariesthatusesartificialintelligencetodetectdentalcariesinchildrenandprovidesinteractiveoralhealtheducationprotocolforadesignandusabilitytestingstudy AT jieboluo assessingasmartphoneappaicariesthatusesartificialintelligencetodetectdentalcariesinchildrenandprovidesinteractiveoralhealtheducationprotocolforadesignandusabilitytestingstudy AT orianalymapes assessingasmartphoneappaicariesthatusesartificialintelligencetodetectdentalcariesinchildrenandprovidesinteractiveoralhealtheducationprotocolforadesignandusabilitytestingstudy AT tongtongwu assessingasmartphoneappaicariesthatusesartificialintelligencetodetectdentalcariesinchildrenandprovidesinteractiveoralhealtheducationprotocolforadesignandusabilitytestingstudy AT timothydye assessingasmartphoneappaicariesthatusesartificialintelligencetodetectdentalcariesinchildrenandprovidesinteractiveoralhealtheducationprotocolforadesignandusabilitytestingstudy AT nisreenaljallad assessingasmartphoneappaicariesthatusesartificialintelligencetodetectdentalcariesinchildrenandprovidesinteractiveoralhealtheducationprotocolforadesignandusabilitytestingstudy AT peironghao assessingasmartphoneappaicariesthatusesartificialintelligencetodetectdentalcariesinchildrenandprovidesinteractiveoralhealtheducationprotocolforadesignandusabilitytestingstudy AT jinlongruan assessingasmartphoneappaicariesthatusesartificialintelligencetodetectdentalcariesinchildrenandprovidesinteractiveoralhealtheducationprotocolforadesignandusabilitytestingstudy AT sheritabullock assessingasmartphoneappaicariesthatusesartificialintelligencetodetectdentalcariesinchildrenandprovidesinteractiveoralhealtheducationprotocolforadesignandusabilitytestingstudy AT kevinfiscella assessingasmartphoneappaicariesthatusesartificialintelligencetodetectdentalcariesinchildrenandprovidesinteractiveoralhealtheducationprotocolforadesignandusabilitytestingstudy |