Integrated decision-making about housing, energy and wellbeing: a qualitative system dynamics model.

BACKGROUND: The UK government has an ambitious goal to reduce carbon emissions from the housing stock through energy efficiency improvements. This single policy goal is a strong driver for change in the housing system, but comes with positive and negative "unintended consequences" across a broad range of outcomes for health, equity and environmental sustainability. The resulting policies are also already experiencing under-performance through a failure to consider housing as a complex system. This research aimed to move from considering disparate objectives of housing policies in isolation to mapping the links between environmental, economic, social and health outcomes as a complex system. We aimed to support a broad range of housing policy stakeholders to improve their understanding of housing as a complex system through a collaborative learning process. METHODS: We used participatory system dynamics modelling to develop a qualitative causal theory linking housing, energy and wellbeing. Qualitative interviews were followed by two interactive workshops to develop the model, involving representatives from national and local government, housing industries, non-government organisations, communities and academia. RESULTS: More than 50 stakeholders from 37 organisations participated. The process resulted in a shared understanding of wellbeing as it relates to housing; an agreed set of criteria against which to assess to future policy options; and a comprehensive set of causal loop diagrams describing the housing, energy and wellbeing system. The causal loop diagrams cover seven interconnected themes: community connection and quality of neighbourhoods; energy efficiency and climate change; fuel poverty and indoor temperature; household crowding; housing affordability; land ownership, value and development patterns; and ventilation and indoor air pollution. CONCLUSIONS: The collaborative learning process and the model have been useful for shifting the thinking of a wide range of housing stakeholders towards a more integrated approach to housing. The qualitative model has begun to improve the assessment of future policy options across a broad range of outcomes. Future work is needed to validate the model and increase its utility through computer simulation incorporating best quality data and evidence. Combining system dynamics modelling with other methods for weighing up policy options, as well as methods to support shifts in the conceptual frameworks underpinning policy, will be necessary to achieve shared housing goals across physical, mental, environmental, economic and social wellbeing.

Health intervention in social context: understanding social networks and neighbourhood.

Recruiting lay people from the neighbourhoods of target communities as Community Health Educators (CHEs) is an increasingly popular strategy for health interventions in the UK. CHEs are assumed to have a distinct advantage in reaching 'difficult to reach' groups by virtue of their network membership. However, results obtained from a recent intervention study [Chiu (2002). Straight talking: Communicating breast screening information in primary care. Leeds: Nuffield Institute for Health, University of Leeds] raised concerns about the much-asserted efficacy of networks and suggested that neighbourhood was a contextual factor that would potentially affect the results of health interventions. In addition, it suggested that the concept of social networks and other related concepts i.e. 'social embeddedness', 'social capital', and 'neighbourhoods' that underpin CHE interventions needed to be better understood. In order to examine these concepts in relation to CHE interventions, we conducted a pilot study involving 53 CHEs (26 White, 27 Black and Minority Ethnic) in seven health organisations across the UK. The CHEs took part in focus group interviews to explore their perceptions of social networks and neighbourhood. Quantitative information on their personal networks was also mapped using three proformas. This paper explores CHEs' networks with a specific focus on the concept of 'social embeddedness' and the effect of neighbourhood. Implications of these findings on the effectiveness of intervention are discussed.