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How culturally wise psychological interventions can help reduce poverty

Public and global health

November 13, 2025

  • Date (DD-MM-YYYY)

    20-11-2025 to 20-11-2026

    Available on-demand until 20th November 2026

  • Cost

    Free

  • Education type

    Publication

  • CPD subtype

    On-demand

Description

Poverty is characterized by multidimensional economic, social, and psychological constraints that undermine people’s agency to pursue new opportunities and shape their life outcomes. How can interventions best support the agency of low-income individuals and, in so doing, boost poverty-reduction efforts? We theorize and find that agency interventions are effective when designed to be “culturally wise,” i.e., attuned to the model of agency predominant in a cultural context. Focusing on low-income women in rural Niger, Study 1 finds that local mental models of economic success primarily reflect interdependence, grounded in relational factors like advancing social harmony, respectfulness, and collective benefits. As evidenced by data from a United States sample, this contrasts with a more independent model common in the West grounded in personal factors like self-initiative. Study 2 finds empirical support for relational factors (e.g., subjective social standing) in addition to self-oriented personal factors (e.g., self-efficacy) as mechanisms of women’s economic advancement in a highly effective multifaceted poverty reduction program. Study 3 reports a field experiment with program participants (n = 2,628) to compare a Western-derived personal agency intervention and a culturally wise relational agency intervention each to a control. Only relational agency caused significant improvements in economic outcomes over 12 mo, as well as in some personal and relational outcomes. By contrast, personal agency showed limited effects, shifting only personal outcomes. These findings reveal the promise of research at the intersection of social and cultural psychology, behavioral science, and development economics to help address global poverty.

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