Exploring the determinants of household water treatment in Kabul: A COM-B model perspective in a low-income context

Abstract

Access to clean drinking water remains a major challenge in low- and middle-income countries, causing premature death from waterborne diseases, especially in water-insecure settings such as Afghanistan. While technologies and solutions for household-level water treatment exist, models to guide behaviour change for their adoption tend to stress psychological dimensions of behaviour with relatively little grounding in local expressions and contextual drivers of households’ water treatment behaviour in low- and middle-income countries.

Speaking to this challenge, our study explores factors influencing household water treatment in peri-urban Kabul, using the COM-B model (Capability, Opportunity, Motivation – Behaviour) as a guiding framework for analysis. We conducted semi-structured interviews with a purposive (maximally diverse) sample of 68 participants across two Kabul neighbourhoods to inform the framework. The data was collected from May to July 2021.

Our qualitative findings cover themes including water realities, common water storage and treatment practices, the process of navigating and negotiating water treatment, and discontinuities therein. Among others, this shows that residents’ everyday experiences with water are shaped by sensory quality indicators like smell and turbidity, but also illness experiences due to limited formal water information. The complex assemblage of factors shaping households’ navigation and negotiation of water treatment options included gender roles, household economics, technology availability, efficacy perceptions, and competing priorities. In addition, our qualitative data documents how the emergency-focused approach to water security by NGOs contributed occasionally to scepticism, trust erosion, and discontinuities in household water treatment methods.

Our study challenges the literature’s emphasis on psychological dimensions of water behaviour as similarly salient contextual factors include social dynamics, infrastructure, electricity disruptions, and the physical environment. We recommend that behaviourally-informed interventions should be tailored to the realities of underserved communities, for example by increasing community involvement, targeting affordable technologies resilient to disruptions, and addressing contextual barriers like infrastructure limitations.