RESUMO
BACKGROUND: A reconceptualised global strategy is key as nations begin to shift from crisis management to medium- and long-term planning to rebuild and strengthen their economic, social and public health systems. Efforts towards measuring, modelling, and forecasting Mental Wealth could serve as the catalyst for this reconceptualization. The Mental Wealth approach builds systemic resilience through investments which promote collective cognitive and emotional wellbeing. This paper presents the theoretical foundations for Mental Wealth. It presents, for the first time, literature across the disciplines of health and social sciences, economics, business, and humanities to underpin the development of an operational metric of Mental Wealth. DISCUSSION: An approach which embeds social and psychological dimensions of prosperity, alongside the economic, is needed to inform the effective allocation of investments in the post-pandemic world. The authors advocate for a transdisciplinary framework of Mental Wealth to be applied in innovating population-level policy interventions to address the growing challenges brought on by COVID-19. Mental Wealth highlights the value generated by the deployment of collective mental assets and supporting social infrastructure. In order to inform this position, a review of the literature on the concepts underpinning Mental Wealth is presented, limitations of current measurement tools of mental and social resources are evaluated, and a framework for development of a Mental Wealth metric is proposed. CONCLUSION: There are challenges in developing an operational Mental Wealth metric. The breadth of conceptual foundations to be considered is extensive, and there may be a lack of agreement on the appropriate tools for its measurement. While variability across current measurement approaches in social resources, wellbeing and mental assets contributes to the difficulty creating a holistic and generic metric, these variations are now clearer. The operationalisation of the Mental Wealth metric will require comprehensive mapping of the elements to be included against the data available.