We propose and test a new model for predicting multiple quantitative measures of well-being globally at the country level based on the United Nations Human Development Index (HDI), income inequality (Net Gini), and National Happiness Index (NHI; U.N. Sustainable Development Solutions Network world survey of life satisfaction). HDI consists of per-capita Gross National Income (economic well-being), average life expectancy (proxy for health well-being), and educational attainment (capabilities well-being). Using data on 105 countries representing 95% of the world’s population, a history of grassroots activism (Global Non-violent Action Database), civil liberties and political rights (Freedom Score), political and fiscal decentralization, and voter participation (Institute for Democracy and Electoral Assistance) correlate with HDI and NHI. Citizen volunteering (Gallup Civic Engagement Index) predicts only NHI. In multivariate analyses, Freedom Score is the most robust predictor of all well-being measures, including income equality. Fiscal decentralization and voter turnout also predict HDI and NHI, controlling for other influences. Based on prior analyses in the Global Development of Applied Community Studies project, implications and recommendations are discussed for developing community human research and professional resources across 12 disciplines in countries where they are needed based on social justice, citizenship, well-being, inequality, human rights, and other development challenges. We recommend individual and community-level and qualitative analyses of the above predictors’ relationships with these same conceptualizations of well-being, as well as consideration of other social, cultural and political variables and their effect on well-being.

Data on 105 countries from the Global Development of Applied Community Studies project and a geographic information system (ArcGIS) were used to map and identify spatial patterns in the international growth of community psychology, as measured by professional associations and conferences, graduate and undergraduate programs and courses, and publications. Our primary aim was to analyze the field's global development, emphasizing professional training and research products, in the context of geographic proximity and theories of knowledge transfer and knowledge spillover. The results of Hot Spot Analysis and Cluster and Outlier Analysis spatially confirmed our hypothesis, revealing statistically significant hot spots of the strength of community psychology in the countries sharing borders. Hierarchical regression analysis found that the strength of community psychology in neighboring countries significantly predicted the development of community psychology beyond the influence of population size, Human Development Index, freedom score, and a history of grassroots activism. Implications for theory, research, and international professional and student exchanges are discussed.

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