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Household water treatment (HWT) is a simple technology to tackle this issue of non-potable drinking water at household level. Unfortunately, studies have showed that people do not use it regularly which diminishes the impact of HWT on health. Our previous studies find that socio-environmental characteristics determines the water-related behavior via so-called psychosocial factors. However, there is a need to understand whether socio-environmental characteristics have similar effect on the psychosocial factors across regions and cultures. This comparative study aims to fill that knowledge gap. We follow Risk – Attitude – Norm – Ability - Self regulation (RANAS) theory to model inter-relationships between socio-environmental and psychosocial variables. Bayesian Belief Network (BBN) based model is used to model the relationship between socio-environmental characteristics, psychosocial factors, and the use of HWT. Principal component analysis (PCA) and cluster analysis (CA) are used to determine similarity of the condition probability table (CPT) between the various case studies. A CPT corresponds a psychosocial variable and measures the strength of relationships between on the psychosocial variable and selected socio-environmental characteristics (education level, relative wealth index, accessibility, and health problem) that it is conditioned by in the BBN. Four household interview datasets, i.e. four case studies, are used in the comparative analysis: two from Indonesia and others from Nepal and Chad. The PCA and CA analysis showed that two CPTs form Indonesia were quite similar to each other, while Nepal and Chad formed another cluster. However, the PCA scores explained 30.43% of the variance in the four datasets which implies that, socio-environmental characteristics have quite similar effect on shaping the people's perception regarding the adoption of HWT across different considered contexts. In general, better socio-environmental characteristics, e.g. better education or easier access to a product, result in higher levels of psychosocial factors, e.g. higher level of the perception of risk of getting health disease from drinking untreated water, resulting in higher probability of using HWT. Our results emphasize the importance of positive and supportive environment in order to change people's water-related behavior in developing countries. Keywords: water-related behavior, socio-environmental characteristics, psychosocial factors, cluster analysis, principal component analysis, cluster analysis. [ABSTRACT FROM AUTHOR]

About 20 Million (73%) people in Nepal still do not have access to safely managed drinking water service and 22 million (79%) do not treat their drinking water before consumption. Few studies have addressed the combination of socio-economic characteristics and psychosocial factors that explain such behaviour in a probabilistic manner. In this paper we present a novel approach to assess the usage of household water treatment (HWT), using data from 451 households in mid and far-western rural Nepal. We developed a Bayesian belief network model that integrates socio-economic characteristics and five psychosocial factors. The socio-economic characteristics of households included presence of young children, having been exposed to HWT promotion in the past, level of education, type of water source used, access to technology and wealth level. The five psychosocial factors capture households' perceptions of incidence and severity of water-borne infections, attitudes towards the impact of poor water quality on health, water treatment norms and the knowledge level for performing HWT. We found that the adoption of technology was influenced by the psychosocial factors norms, followed by the knowledge level for operating the technology. Education, wealth level, and being exposed to the promotion of HWT were the most influential socio-economic characteristics. Interestingly, households who were connected to a piped water scheme have a higher probability of HWT adoption compared to other types of water sources. The scenario analysis revealed that interventions that only target single socio-economic characteristics do not effectively boost the probability of HWT practice. However, interventions addressing several socio-economic characteristics increase the probability of HWT adoption among the target groups. [ABSTRACT FROM AUTHOR]