Digital outcome measures in orofacial myofunctional therapy

Objective: To examine how digital outcome measures may strengthen assessment in orofacial myofunctional therapy (OMT) and to propose a practical framework for moving the field beyond observer-dependent reporting toward auditable, clinically anchored endpoints suitable for telepractice. Data sources: Recent direct and adjacent literature was prioritized, with emphasis on studies and reviews addressing OMT, telepractice, web-based structured assessment, facial video analysis, clinical acoustic markers, instrumented swallowing technologies, digital swallowing care, and governance issues related to automated audiovisual data. Eligibility criteria: Evidence was retained when it clarified at least one of three questions: which OMT domains are most amenable to digital capture; which adjacent methods are plausibly transferable to OMT assessment; and which methodological conditions are required for digital endpoints to improve reproducibility rather than merely add technical novelty. Methods of synthesis: This critical narrative review was updated through March 2026. Direct OMT studies and adjacent rehabilitation literature were appraised separately and synthesized through a three-tier evidence model linked to an endpoint-construction pathway: clinical target, elicited task, acquisition conditions, variable extraction, clinical anchoring, and reproducibility testing. Main findings: Direct evidence supports structured telepractice workflows, web-enabled assessment scaffolds, and longitudinal patient-reported monitoring; however, it does not yet establish a validated core set of digital OMT endpoints. Adjacent literature provides firmer methodological support for disciplined video-derived facial variables, constrained signal interpretation, clinically benchmarked instrumentation, and explicit governance procedures. The most defensible near-term targets are lip competence and oral resting posture, facial symmetry and movement coordination, task-evoked perioral dynamics, swallowing-adjacent behavior, and longitudinal patient-reported monitoring. Conclusion: Progress will depend less on expanding digital feature inventories than on prospectively testing small, condition-sensitive endpoint sets under controlled acquisition, transparent analytical pipelines, explicit clinical anchors, and reproducibility checks across raters, sessions, devices, and sites.