We will investigate, from the community perspective, the contextual factors influencing uptake of the exposure reduction practices tested in WP2. Data will be collected from children (aged 5-12), their carers (parents/guardians and teachers) and other key in-formants (agency practitioners) in regions of varying socioeconomic status within each city.

1) Mask preferences and Learning behaviours:  Focus group discussions (FGDs) will be conducted in each city to explore children’s preferences for different styles of facemasks. Feeding into WP7, the FGDs will also be used to ask from whom the children learn from at different ages; preferred media (e.g. booklets, internet, videos, plays); ages at which children have agency in different domains; and what guidance they have already received from NGO/GOs (if any) and perceptions of the usefulness of received information.

2) Cultural drivers influencing behaviour change: The most promising exposure reduction practices in each city will be analysed further, to gain a depth of understanding of the contextual factors which might influence uptake, using a mixed methods approach combining both qualitative data from interviews with teachers, parents/guardians and their children and quantitative data from questionnaire surveys (with carers). The two types of data will be used to validate each other and create a solid foundation for informing the design of the uptake interventions that will be evaluated in WP7.

The ‘Behaviour Change Wheel’ (BCW) [Michie et al. 2011], implemented in many studies, will form the analytical framework for the interviews and surveys. At its hub, the BCW has a model of behaviour, known as COM-B, which describes behaviour as consisting of Capability (e.g., knowledge, skills), Opportunity (e.g., sociocultural influences, environmental context, resources), and Motivation (e.g., goals and intentions, beliefs about consequences). The model is used to identify how to best achieve behaviour change. For example, if lack of capability is a barrier to uptake of a practice then a different type of uptake intervention (e.g., education, training) would be needed compared to if the barrier is lack of opportunity (e.g., enablement, environmental restructuring) or motivation (e.g., persuasion, incentivisation).

Sample sizes for the interviews and questionnaire surveys will be informed by considerations of saturation of themes and statistical power. A maximum variation approach will be used to recruit a diverse sample of respondents, allowing us to compare the opinions and perspectives of people of different demographics. The findings will provide insights into the contextual variants of the types of interventions and supporting policies that would be expected to be effective. For example, we will compare samples obtained from urban areas in Indonesia (Bandung) and Nepal (Kathmandu) which both suffer from severe PAP, yet have different cultures and climates which could impact the motivation, capability and opportunity to protect. Our contextually-sensitive approaches to data analysis will include thematic analysis of the interview data to identify patterns of meaning across different contexts, from a descriptive and exploratory orientation. To complement these qualitative insights, the quantitative survey analysis will adopt statistical approaches underpinned by regression analysis (e.g. structural equation modelling (SEM)), to quantify the contributions of contextual factors in shaping the determinants of behaviour change.

The Behaviour Change Wheel. Michie et al. 2011, Implementation Sci. 6:42.