Dental disease is one of the most common chronic diseases in the United States and exacts a substantial personal and societal toll. A large body of research links dental disease to poor oral hygiene behaviors such as inadequate brushing and flossing, but fails to explain adequately how these putative causal relationships arise or are mediated. Traditional retrospective self-reports are susceptible to numerous biases and lack the granularity and scientific rigor needed to rigorously test hypotheses about causal pathways. To solve the vexing challenges of oral behavior measurement, we have assembled a multidisciplinary team of scientists and engineers to develop a Remote Oral Behaviors Assessment System (ROBAS) that can provide objective, individual-level and ecologically-valid data on oral hygiene behaviors. Building on a strong body of research priors and innovative technologies developed by our team, our academic-industry partnership will build, test, refine and field-validate ROBAS in three sequential stages with their corresponding specific aims. In Stage 1, we will develop ROBAS by integrating a sensor-enabled toothbrush with a wrist actigraph and a data analytics system and then bench-test and iteratively refine it using computerized simulators and test subjects (Aim 1). In Stage 2, we will pilot-test ROBAS in a cohort of 32 healthy subjects to optimize its performance and usability in naturalistic settings (Aim 2). Data collected on the objective (precision, validity, reliability), subjective (user satisfaction, acceptability) and user performance parameters will be used to further refine ROBAS validity, reliability and functionality. In Stage 3, we will use a randomized, controlled, crossover study contrasting 60 at-risk (substance using) individuals with 60 comparable controls to evaluate ROBAS's capacity for longitudinal (6 months) assessment of oral health behaviors (OHBs) in naturalistic settings. Specifically, we will test ROBAS's clinical utility and incrementa validity over retrospective self-reports and Ecological Momentary Assessments (EMAs) (Aim 3). Additionally, we will use an articulated theoretical framework to investigate the associations among sociobehavioral determinants, OHBs (measured by self-reports, EMAs and ROBAS), and dental disease indicators (gingivitis and dental plaque) (Aim 4). Evaluating ROBAS in community subjects with different levels of risk for dental disease (substance users and non-users) will facilitate translatability of our research. The tightly coordinated academic-industry alliance will ensure rapid productization and availability of ROBAS (project deliverable). The ability to collect granular, ecologically-valid data for long periods of time will afford unprecedented opportunity to develop and rigorously test more sophisticated causal models of oral health behaviors and glean fundamental insights regarding behavior change processes. The paradigm shift from the conventional rescue- driven model of dental care to a proactive preventive approach, based on sensor-enabled behavioral analysis, has the potential to fundamentally transform the delivery of dental care. Equally important, the technological innovations of our project will have broad application in a variety of social, behavioral and clinical settings.
Most dental disease is caused by poor oral hygiene behaviors. To better understand why, how and when these faulty behaviors occur, the project will combine sensor-containing toothbrushes and wristwatches with mobile phones (mHealth) to develop an integrated Remote Oral Behaviors Assessment System (ROBAS) that captures behaviors as they occur. The ability to unobtrusively collect data on an individual's brushing and flossing patterns for long periods of time will allow scientists to better understand how poor hygiene behaviors produce dental disease. Clinicians and health systems will be able to identify individuals most at risk for dental disease and proactively assist them. Furthermore, ROBAS would serve as the building block for succeeding mHealth systems that engage and empower individuals through individualized feedback on proper oral hygiene practices, anticipate transitions to risky states, and deliver timely, evidence-based behavioral interventions.
|Bari, Rummana; Adams, Roy J; Rahman, Mahbubur et al. (2018) rConverse: Moment by Moment Conversation Detection Using a Mobile Respiration Sensor. Proc ACM Interact Mob Wearable Ubiquitous Technol 2:|
|Shetty, Vivek; Yamamoto, John; Yale, Kenneth (2018) Re-architecting oral healthcare for the 21st century. J Dent 74 Suppl 1:S10-S14|
|Hossain, Syed Monowar; Hnat, Timothy; Saleheen, Nazir et al. (2017) mCerebrum: A Mobile Sensing Software Platform for Development and Validation of Digital Biomarkers and Interventions. Proc Int Conf Embed Netw Sens Syst 2017:|