The Adaptive PERMA Framework: Reconceptualizing Well-Being as Dynamic and Context-Responsive

Well-being research has long sought to identify what enables human flourishing, with frameworks like PERMA providing structured approaches to understanding psychological well-being components. However, existing frameworks conceptualize well-being as relatively stable individual differences measured at discrete time points, an approach that cannot capture rapid fluctuations characteristic of digital environments where well-being responds to continuous social feedback, algorithmically-curated content, and frequent context switching.This paper introduces the Adaptive PERMA Framework (APF), which reconceptualizes well-being as a dynamic, temporally evolving system. By integrating foundational well-being theory with computational psychology methods, APF addresses gaps through three core mechanisms: bidirectional feedback loops, adaptive weighting, and state-dependent transitions. Unlike prior extensions adding new PERMA dimensions, APF explicitly models how well-being evolves in digitally-mediated contexts where psychological states fluctuate rapidly. This enables predictive modeling of well-being trajectories, provides a theoretical foundation for adaptive interventions, and advances understanding of how digital environments shape human flourishing.