Behavioural Drivers of COVID-19 Vaccination and Antiviral Uptake in Australia: A Cross-Sectional Analysis Using the...

Objective: To identify demographic, clinical, and behavioural determinants of COVID-19 vaccination and antiviral uptake in Australia using the Capability, Opportunity, Motivation-Behaviour (COM-B) framework with psychometric validation and LASSO-enhanced variable selection. Methods: Cross-sectional analysis of the 2024 KAB BREATHE survey (n = 5177) of Australian adults, intentionally enriched for risk-stacked (more than 1 chronic condition). Primary outcomes included 2023/2024 COVID-19 booster receipt, future vaccine intentions, vaccine/antiviral beliefs and antiviral uptake. Predictors included demographics, chronic conditions, and domain-specific leave-one-out (LOO) COM-B scores standardised to mean = 0, SD = 1. COM-B domains were assessed using Cronbach's alpha. Univariate and multivariable logistic regression models were complemented by LASSO penalised logistic regression with 10-fold cross-validation. Results: Among 5177 Australian adults, the mean age was 51.5 years (SD 16.5), 61.4% (3179/5177) were female, and 70.3% (3638/5177) were classified as risk-stacked. Booster uptake declined sharply from 50.8% (2023) to 19.1% (2024). Cronbach's alpha showed poor internal consistency for Capability (α = 0.006) and Opportunity (α = -0.383) but was acceptable for full Motivation (α = 0.78). In adjusted models, age (aOR 1.02-1.03 per year), medically associated risk factors (aOR 1.66-3.51), and tertiary education (aOR 1.34-1.79) consistently predicted higher uptake and intention. Renting (aOR 0.59-0.78) and current employment (likely inversely associated with age) (aOR 0.73-0.83) were associated with lower uptake across all vaccine outcomes. Adding LOO COM-B scores substantially improved model fit (e.g., 2024 booster AUC 0.73→0.83); Motivation per SD was the strongest predictor (aOR 2.44-4.94 for vaccine outcomes, 1.52-2.49 for antivirals). LASSO models achieved CV-AUCs of 0.78-0.87. Among COVID-positive respondents (n = 2576), only 15.2% received antiviral treatment. Conclusions: Age, clinical risk, and socioeconomic factors, particularly housing tenure and employment status, are key drivers of COVID-19 preventive behaviours (either positively or negatively). The COM-B framework, when corrected for circular prediction and validated via Cronbach's alpha and LASSO, provides substantial explanatory value. Targeted interventions should address structural barriers faced by renters and younger, employed individuals while leveraging high motivation among older adults and clinically vulnerable groups. Implications for Public Health: These findings support a shift from knowledge-based campaigns towards equity-focused, multi-level public health strategies that address structural barriers to COVID-19 vaccination and antiviral access in Australia.