Experienced Well-Being and Compliance Behaviour: New Applications of Quality of Life theories, Using AI and RealTime Data

Abstract

The study of well-being has continued to evolve significantly over the past three decades, extending the foundational progress documented by Diener et al. (1999) through advances in measurement, cross-national surveys, and the emergence of high-frequency, real-time indicators. One of the most pressing issues in contemporary well-being research is the intersection between experienced well-being measures and societal compliance, especially in times of uncertainty. Effective crisis response depends not only on well-designed policies but also on how populations emotionally interpret uncertainty and respond behaviourally. This paper introduces a framework in which experienced well-being indicators are repositioned as behavioural inputs that shape compliance with public health interventions. Drawing on interdisciplinary theories, we argue that emotional readiness plays a critical role in driving prosocial behaviour during times of crisis. Using a macro-panel at the country–day level dataset and applying XGBoost and SHAP, we examine how dynamic, within-country features, both structural and subjective, predict compliance with COVID-19 vaccination policy. Results show that general trust and happiness are among the strongest predictors of compliance, often rivalling or exceeding traditional factors like GDP per capita or healthcare spending. Our findings show experienced well-being indicators not only predict compliance within countries but also have cross-national relevance, providing a foundation for more psychologically informed policy design. We propose that policymakers integrate these emotional indicators into crisis response systems to improve behavioural effectiveness and public cooperation.