Pathways, predictors and paradoxes of illbeing and wellbeing Insights from a UK Biobank Study

Wellbeing and illbeing are influenced by a variety of biopsychosocial factors, yet prior research has neglected a focus on pathways and potential for non-linearity. Here we aimed to: (1) identify predictors and pathways to wellbeing and illbeing; (2) clarify the specific functional forms of their association; and (3) integrate these findings to develop a more nuanced understanding of the pathways leading to wellbeing and illbeing. PLS-SEM and Bayesian regression were used to analyse associations among heart rate variability (HRV), meaning oriented behaviour (MOB), resilience, social connectedness, and adversity in relation to wellbeing and illbeing using data from the UK Biobank (n=8,047). HRV directly enhanced wellbeing and also mediated these effects through MOB, which subsequently amplified resilience and social connectedness, indirectly increasing wellbeing as well as reducing illbeing. Social connectedness was also found to positively moderate the relationship between MOB and wellbeing (as well as illbeing). Findings identified HRV and MOB as key upstream determinants of mental health, while non-linear modelling was found to be essential for better understanding the pathways to and relationships between wellbeing and illbeing.