mDentistry: A powerful tool to improve oral health of a broad population in the digital era

A Tele-detection and referral pAthways model for early childhood cariEs control- a protocol for a randomized factorial study: the TRACE study

BACKGROUND

Early childhood caries (ECC) is one of the most common childhood diseases affecting the primary teeth of children younger than 6 years of age. ECC progression can be reversed in the early stages although these lesions often go undetected. New approaches are needed to detect oral diseases at an early stage when they can be better controlled. The aim of the study is to assess the effectiveness of ECC tele-detection methods combined with referral pathways with and without user fee removal in controlling ECC.

METHODS

A randomized factorial trial will be used to compare two tele-dentistry detection methods for ECC (intraoral camera and smartphone camera) and two referral pathways (user fee removal versus conventional care). The study will recruit children younger than 6 years of age in marginalized communities in Alexandria, Egypt. The primary outcome is the percentage of teeth receiving indicated care, while the secondary outcomes are the oral health-related quality of life, acceptance of teledentistry by dentists, procedure time, and child cooperation. Two-way analysis of variance will be used to assess the effect of the two factors as between group variables on the outcomes after 6 and 12 months. The interaction between detection methods and referral pathways will also be assessed, and the effect of confounders will be controlled in a multivariable linear regression model.

DISCUSSION

The findings of this study have the potential to inform clinical practice and oral healthcare policies for ECC management. Successful tele-detection and referral pathways could be integrated into oral healthcare systems, leading to improved oral health outcomes for children.

TRIAL REGISTRATION

The trial has been registered on ClinicalTrials.gov in August 2023 (initial release) ID: NCT06019884.

Acceptance and Usability of an Innovative mDentistry eHygiene Model Amid the COVID-19 Pandemic Within the US National Dental Practice-Based Research Network: Mixed Methods Study

BACKGROUND

Amid the COVID-19 pandemic and other possible future infectious disease pandemics, dentistry needs to consider modified dental examination regimens that render quality care and ensure the safety of patients and dental health care personnel (DHCP).

OBJECTIVE

This study aims to assess the acceptance and usability of an innovative mDentistry eHygiene model amid the COVID-19 pandemic.

METHODS

This pilot study used a 2-stage implementation design to assess 2 critical components of an innovative mDentistry eHygiene model: virtual hygiene examination (eHygiene) and patient self-taken intraoral images (SELFIE), within the National Dental Practice-Based Research Network. Mixed methods (quantitative and qualitative) were used to assess the acceptance and usability of the eHygiene model.

RESULTS

A total of 85 patients and 18 DHCP participated in the study. Overall, the eHygiene model was well accepted by patients (System Usability Scale [SUS] score: mean 70.0, SD 23.7) and moderately accepted by dentists (SUS score: mean 51.3, SD 15.9) and hygienists (SUS score: mean 57.1, SD 23.8). Dentists and patients had good communication during the eHygiene examination, as assessed using the Dentist-Patient Communication scale. In the SELFIE session, patients completed tasks with minimum challenges and obtained diagnostic intraoral photos. Patients and DHCP suggested that although eHygiene has the potential to improve oral health care services, it should be used selectively depending on patients' conditions.

CONCLUSIONS

The study results showed promise for the 2 components of the eHygiene model. eHygiene offers a complementary modality for oral health data collection and examination in dental offices, which would be particularly useful during an infectious disease outbreak. In addition, patients being able to capture critical oral health data in their home could facilitate dental treatment triage and oral health self-monitoring and potentially trigger oral health-promoting behaviors.

Emerging Technologies of Three-Dimensional Printing and Mobile Health in COVID-19 Immunity and Regenerative Dentistry

The ongoing coronavirus disease 2019 (COVID-19) pandemic highlights the importance of developing point-of-care (POC) antibody tests for monitoring the COVID-19 immune response upon viral infection or following vaccination, which requires three key aspects to achieve optimal monitoring, including three-dimensional (3D)-printed POC devices, mobile health (mHealth), and noninvasive sampling. As a critical tissue engineering concept, additive manufacturing (AM, also known as 3D printing) enables accurate control over the dimensional and architectural features of the devices. mHealth refers to the use of portable digital devices, such as smartphones, tablet computers, and fitness and medical wearables, to support health, which facilitates contact tracing, and telehealth consultations during the pandemic. Compared with invasive biosample (blood), saliva is of great importance in the spread and surveillance of COVID-19 as a noninvasive diagnostic method for virus detection and immune status monitoring. However, investigations into 3D-printed POC antibody test and mHealth using noninvasive saliva are relatively limited. Further exploration of 3D-printed antibody POC tests and mHealth applications to monitor antibody production for either disease onset or immune response following vaccination is warranted. This review briefly describes the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and immune response after infection and vaccination, then discusses current widely used binding antibody tests using blood samples and enzyme-linked immunosorbent assays on two-dimensional microplates before focusing upon emerging POC technological platforms, such as field-effect transistor biosensors, lateral flow assay, microfluidics, and AM for fabricating immunoassays, and the possibility of their combination with mHealth. This review proposes that noninvasive biofluid sampling combined with 3D POC antibody tests and mHealth technologies is a promising and novel approach for POC detection and surveillance of SARS-CoV-2 immune response. Furthermore, as key concepts in dentistry, the application of 3D printing and mHealth was also included to facilitate the appreciation of cutting edge techniques in regenerative dentistry. This review highlights the potential of 3D printing and mHealth in both COVID-19 immunity monitoring and regenerative dentistry.

Artificial intelligence-powered smartphone application, AICaries, improves at-home dental caries screening in children: Moderated and unmoderated usability test

Early Childhood Caries (ECC) is the most common childhood disease worldwide and a health disparity among underserved children. ECC is preventable and reversible if detected early. However, many children from low-income families encounter barriers to dental care. An at-home caries detection technology could potentially improve access to dental care regardless of patients' economic status and address the overwhelming prevalence of ECC. Our team has developed a smartphone application (app), AICaries, that uses artificial intelligence (AI)-powered technology to detect caries using children's teeth photos. We used mixed methods to assess the acceptance, usability, and feasibility of the AICaries app among underserved parent-child dyads. We conducted moderated usability testing (Step 1) with ten parent-child dyads using "Think-aloud" methods to assess the flow and functionality of the app and analyze the data to refine the app and procedures. Next, we conducted unmoderated field testing (Step 2) with 32 parent-child dyads to test the app within their natural environment (home) over two weeks. We administered the System Usability Scale (SUS) and conducted semi-structured individual interviews with parents and conducted thematic analyses. AICaries app received a 78.4 SUS score from the participants, indicating an excellent acceptance. Notably, the majority (78.5%) of parent-taken photos of children's teeth were satisfactory in quality for detection of caries using the AI app. Parents suggested using community health workers to provide training to parents needing assistance in taking high quality photos of their young child's teeth. Perceived benefits from using the AICaries app include convenient at-home caries screening, informative on caries risk and education, and engaging family members. Data from this study support future clinical trial that evaluates the real-world impact of using this innovative smartphone app on early detection and prevention of ECC among low-income children.

Assessment of an Innovative Mobile Dentistry eHygiene Model Amid the COVID-19 Pandemic in the National Dental Practice-Based Research Network: Protocol for Design, Implementation, and Usability Testing

BACKGROUND

Amid COVID-19, and other possible future infectious disease pandemics, dentistry needs to consider modified dental examination regimens that render quality care, are cost effective, and ensure the safety of patients and dental health care personnel (DHCP). Traditional dental examinations, which number more than 300 million per year in the United States, rely on person-to-person tactile examinations, pose challenges to infection control, and consume large quantities of advanced-level personal protective equipment (PPE). Therefore, our long-term goal is to develop an innovative mobile dentistry (mDent) model that takes these issues into account. This model supplements the traditional dental practice with virtual visits, supported by mobile devices such as mobile telephones, tablets, and wireless infrastructure. The mDent model leverages the advantages of digital mobile health (mHealth) tools such as intraoral cameras to deliver virtual oral examinations, treatment planning, and interactive oral health management, on a broad population basis. Conversion of the traditional dental examinations to mDent virtual examinations builds upon (1) the reliability of teledentistry, which uses intraoral photos and live videos to make diagnostic decisions, and (2) rapid advancement in mHealth tool utilization.

OBJECTIVE

In this pilot project, we designed a 2-stage implementation study to assess 2 critical components of the mDent model: virtual hygiene examination (eHygiene) and patient self-taken intraoral photos (SELFIE). Our specific aims are to (1) assess the acceptance and barriers of mDent eHygiene among patients and DHCP, (2) assess the economic impact of mDent eHygiene, and (3) assess the patient's capability to generate intraoral photos using mHealth tools (exploratory aim, SELFIE).

METHODS

This study will access the rich resources of the National Dental Practice-Based Research Network to recruit 12 dentists, 12 hygienists, and 144 patients from 12 practices. For aims 1 and 2, we will use role-specific questionnaires to collect quantitative data on eHygiene acceptance and economic impact. The questionnaire components include participant characteristics, the System Usability Scale, a dentist-patient communication scale, practice operation cost, and patient opportunity cost. We will further conduct a series of iterative qualitative research activities using individual interviews to further elicit feedback and suggestion for changes to the mDent eHygiene model. For aim 3, we will use mixed methods (quantitative and qualitative) to assess the patient's capability of taking intraoral photos, by analyzing obtained photos and recorded videos.

RESULTS

The study is supported by the US National Institute of Dental and Craniofacial Research. This study received "single" institutional review board approval in August 2021. Data collection and analysis are expected to conclude by December 2021 and March 2022, respectively.

CONCLUSIONS

The study results will inform the logistics of conducting virtual dental examinations and empowering patients with mHealth tools, providing better safety and preserving PPE amid the COVID-19 and possible future pandemics.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/32345.

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

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.