Abstract

Improving human wellbeing is a major focus of international environmental and sustainable development policy. However, clearly defined measures of wellbeing are needed as an empirical base for the formulation and evaluation of policies. Despite conceptual progress towards agreement of universally relevant dimensions of wellbeing, consensus is still lacking on how to translate these dimensions into locally appropriate indicators to measure wellbeing in different contexts. This paper focuses on three interrelated challenges associated with this knowledge gap: (1) navigating trade-offs between complexity versus simplicity of concept; (2) integrating top-down and bottom-up perspectives; (3) ensuring a cost-effective and flexible approach suitable for different policy contexts. We contribute to filling this gap by developing a step-by-step Wellbeing Indicator Selection Protocol (WISP) for measuring wellbeing. The protocol integrates perspectives through an interdisciplinary mixed methods design that includes cross-validation between quantitative approaches of redundancy analysis and statistical modelling and qualitative approaches of focus groups and thematic analysis. In this way we promote a pragmatic approach suitable for a range of social and environmental contexts. We tested WISP in rural Tanzania, identifying 111 candidate wellbeing indicators. This list was simplified to a subset of 19 indicators that retained 91 % of measured variation among all wellbeing indicators. The simplified list was representative of both a multidimensional concept of wellbeing and the diversity of opinions sampled. We conclude that the protocol provides practical, statistically validated guidance to support the design of wellbeing assessments, maintaining coherence between universal theory and local realities.

Highlights

  • Improving human wellbeing has become a major goal of international environmental and sustainable development policy (UNDP (United Nations Development Programme), 2015; CBD (Convention on Biological Diversity), 2016)

  • To assess the practical utility of the protocol, we provide an example of its use in rural Tanzania (Supplementary material S1)

  • 1 Continuous to categorical transformation, 2 log transformation, 3 Site-speciic indicator, 4 Gender-speciic indicator. %D = percentage deviance explained in human wellbeing index (HWI) by each indicator in the inal GLM. r2 =

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Summary

Introduction

Improving human wellbeing has become a major goal of international environmental and sustainable development policy (UNDP (United Nations Development Programme), 2015; CBD (Convention on Biological Diversity), 2016). There remains ongoing debate about how wellbeing should be conceptualised and measured (Dasgupta, 2001; OECD (Organisation for Economic Cooperation and Development), 2013). These high-level policy goals have largely fallen short in terms of the persistence of extreme poverty, increasing inequality and environmental degradation (Fehling et al, 2013; Allen et al, 2018; McGregor, 2018). Measurable indicators of wellbeing are needed to improve achievement of policy goals by (1) providing an evidence-base to track progress towards a more inclusive society (Brende and Bent, 2015; Costanza et al, 2014; Hicks et al, 2016), and (2) highlighting social issues requiring attention and adaptive action (Brown and Westaway, 2011). We adopt a deinition developed by the Wellbeing in Developing Countries research group, which deines wellbeing as ‘a state of being with others, which arises where human needs are met, where one can act meaningfully to pursue one’s goals and where one can enjoy a satisfactory quality of life’ (Gough and McGregor, 2007)

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