behavior

Abstract Habits—automatic, cue‐triggered behaviors—constitute a substantial portion of daily actions and present powerful targets for interventions aimed at improving health, productivity, and well-being. However, extant habit-formation research is constrained by three key limitations: (1) reliance on self-report measures that conflate repetition with true automaticity, (2) short-term efficacy demonstrated primarily over 3–12-week intervals, and (3) siloed theoretical models that fail to integrate neural, contextual, and digital dimensions into a cohesive framework. To address these gaps, this paper (a) systematically reviews foundational and post-2020 empirical literature on habit formation and change, and (b) proposes the Integrated Multilevel Habit Change (IMHC) Model, a conceptual framework that (i) combines objective measurement with dual-process and COM-B theory, (ii) leverages micro-contextual “levers” and neurobiological insights, and (iii) employs adaptive algorithms to personalize cue timing and pacing.