Title: Personalized sleep bruxism management through phenotyping: A pilot study of whatsApp delivered behavioral coaching
Abstract:
Background: Sleep bruxism is a multifactorial behavior with heterogeneous presentations that often overlap with sleep-disordered breathing, stress-related muscle tension, and hyperarousal/insomnia. Current approaches to bruxism management rarely account for this heterogeneity, which limits the effectiveness of generic interventions. To address this gap, we designed a brief phenotyping questionnaire and algorithm that assigns participants to one of three archetypes: AIR (breathing-related airflow limitation), EARTH (stress-related muscle tension and psychological load), or WATER (sleep-related hyperarousal and insomnia features). Each archetype is mapped to a tailored six-week behavioral coaching program delivered via WhatsApp, targeting the predominant mechanism contributing to bruxism in that subgroup.
Methods: Fifty-five participants were assigned to AIR (n=4), EARTH (n=34), or WATER (n=17) cohorts via the algorithm. Each participant was enrolled in a WhatsApp-based community for their archetype and received daily educational modules and behavioral exercises. In addition to baseline and week-6 outcome surveys, participants completed daily symptom trackers monitoring jaw pain, fatigue, sleep quality, and headaches. Outcomes will be measured via baseline and week-6 self-reported symptom questionnaires covering bruxism frequency, jaw pain, sleep quality, insomnia symptoms, perceived stress, and breathing difficulties, with weekly short-form check-ins on key symptoms and perceived helpfulness. Classification validity will be assessed through cluster analysis of participants' self-reported symptoms, participant-rated fit of their assigned archetype, and algorithm sensitivity analyses. Intervention efficacy will be valuated using within-participant pre–post comparisons for each cohort, focusing on the outcomes most relevant to their assigned archetype (e.g., stress and jaw pain for EARTH, sleep
quality for WATER). Due to the small size of the AIR group, results will be reported descriptively.
Results: Data collection is ongoing. Planned analyses will describe baseline symptom distinctions across archetypes, longitudinal trends from daily trackers, engagement and adherence, and pre–post effect sizes within each cohort. Particular attention will be given to identifying whether symptom trajectories align with the theoretical mechanisms underpinning each archetype (e.g., stress reduction in EARTH, improved sleep continuity in WATER).
Conclusions: This pilot will provide early validation of a rapid phenotyping algorithm for sleep bruxism and explore the feasibility and potential efficacy of tailored digital behavioral coaching. The integration of daily symptom tracking offers a unique opportunity to assess both intervention responsiveness and classification robustness. Findings will guide refinement of the algorithm, content optimization, and the design of an integrated digital health platform combining wearable data, coaching, symptom tracking, and peer support
