JMIR Publications

ABSTRACT

Background:

Preventative self-care can reduce dental disease that disproportionately burdens vulnerable populations. Personalized Digital Oral Self-Care Behavioral Interventions offer a promising solution. However, the success of these digital interventions depends on tooth-brushing data collection e-platforms attuned to the needs and preferences of vulnerable communities.

Objective:

To assess the usability and feasibility of the Remote Oral Behaviors Assessment System (ROBAS) which has been adapted to address the unique requirements of socioeconomically disadvantaged minority individuals.

Methods:

A cohort of 53 participants, exclusively consisting of Latino (n=31, 58%) and Black (n=22, 42%) individuals with no prior experience using electric toothbrushes, utilized ROBAS over four months Beyond evaluating ROBAS's technical performance, extensive feedback was gathered to gauge users' experiences, viewpoints, and overall contentment. The System Usability Scale (SUS) served as a primary metric for assessing user satisfaction and acceptability.

Results:

ROBAS exhibited largely reliable and consistent data-gathering capabilities. Participant contentment was comparable to that of commonly used digital devices and technologies. A substantial portion of users indicated a willingness to financially invest in ROBAS, continue its utilization, and endorse it to acquaintances. While some reservations about privacy were expressed, these did not correlate with specific participant traits. Users valued ROBAS's ability to monitor brushing habits but called for refinements, especially in Wi-Fi and application connectivity. Recommendations for system improvements encompassed enhanced app functionality, individualized coaching, more comprehensive brushing data, and the addition of flossing activity tracking

Conclusions:

The research highlights ROBAS's promise as a digital platform for unobtrusively tracking daily oral self-care activities in marginalized communities. The system proved to be both feasible, evidenced by its stable and accurate data capture of brushing behaviors, and user-friendly, as reflected by strong System Usability Scale scores and positive user feedback. Influential factors for its uptake included ease of learning and operation, and feedback provided.