{ "background": "Evaluating the real-world performance and adoption of water treatment systems in low-resource settings is methodologically challenging. Many studies rely on self-reported data or short-term technical assessments, which may not accurately reflect sustained use or contextual factors influencing adoption.", "purpose and objectives": "This study aimed to develop and test a robust methodological framework for conducting a randomised field trial to measure both the technical performance and the longitudinal adoption rates of household water treatment systems in a rural setting.", "methodology": "A cluster-randomised controlled trial was implemented across 120 villages. Households were randomised to receive one of three intervention technologies or serve as controls. Performance was assessed via periodic water quality testing. Adoption was measured through direct observation and sensor-based monitoring over 12 months. A multilevel logistic regression model was used to analyse adoption determinants: $\\logit(p{ij}) = \\beta0 + \\beta1 X{ij} + uj$, where $p{ij}$ is the probability of adoption for household $i$ in village $j$, $X{ij}$ represents household-level covariates, and $uj$ are village-level random effects.", "findings": "The sensor-based monitoring revealed a significant discrepancy with self-reported use, with sustained adoption (consistent use ≥5 days/week) at six months being 34% (95% CI: 28% to 40%) for the most successful technology. The primary determinant of adoption was the perceived reduction in water collection time, not water quality improvement.", "conclusion": "The methodological approach successfully generated high-fidelity, longitudinal data on both technical and behavioural outcomes. The trial design proved feasible and highlighted critical gaps between assumed and actual drivers of technology adoption.", "recommendations": "Future engineering evaluations of water treatment systems should integrate objective, longitudinal adoption metrics alongside technical performance data. Intervention design must prioritise user-centric factors, such as time savings, to enhance sustained adoption.", "key words": "water treatment, adoption, randomised controlled trial, monitoring