Classification of sub-populations for quantitative risk assessment based on awareness and perception: A...

Private well users in Ontario are responsible for protective actions, including source maintenance, treatment, and submitting samples for laboratory testing. However, low participation rates are reported, thus constituting a public health concern, as risk mitigation behaviours can directly reduce exposure to waterborne pathogens. The current study examined the combined effects of socio-demographic profile, experience(s), and "risk domains" (i.e., awareness, attitudes, risk perceptions and beliefs) on behaviours, and subsequently classified private well users in Ontario based on cognitive factors. A province-wide online survey (n = 1228) was employed to quantify Ontario well owners' awareness, perceptions, and behaviours in relation to their personal groundwater supply and local contamination sources. A scoring protocol for four risk domains was developed. Two-step cluster analysis was used to classify respondents based on individual risk domain scores. Logistic regression was employed to identify key variables associated with cluster membership (i.e., profile analysis). Overall, 1140 survey respondents were included for analyses. Three distinct clusters were identified based on two risk domains; groundwater awareness and source risk perception. Profile analyses indicate "low awareness and source risk perception" (Low A/SRP) members were more likely male, while "low awareness and moderate source risk perception" (Low A/Mod SRP) members were more likely female and bottled water users. Well users characterised as "high awareness and source risk perception" (High A/SRP) were more likely to report higher educational attainment and previous well water testing. Findings illustrate that socio-cognitive clusters and their components (i.e., demographics, awareness, attitudes, perceptions, experiences, and protective actions) are distinct based on the likelihood, frequency, and magnitude of waterborne pathogen exposures (i.e., risk-based). Risk-based clustering, when incorporated into quantitative microbial risk assessment, enables the development of effective risk management and communication initiatives that are demographically focused and tailored to specific sub-groups.