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Browsing Gobierno by Subject "Adaptive Calibration Model"
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Item Influence of Childhood Environment on Risky Decision-Making in Adulthood: A Life History Theory and Adaptive Calibration Model Approach(Universidad del Desarrollo. Facultad de Gobierno, 2026) Guzmán Lavín, Eugenio José; Polo Rodrigo, PabloThis dissertation examines how distinct dimensions of childhood adversity—specifically environmental harshness (resource scarcity) and unpredictability (environmental instability)—relate to risk-taking behavior in adulthood. Grounded in Life History Theory and the Adaptive Calibration Model, the study explores whether early environmental conditions calibrate behavioral responses to uncertainty, and whether these effects depend on contextual, individual, and task-related factors. Across two empirical studies, the research employs behavioral measures of risk-taking, including the Balloon Analogue Risk Task (BART) and a lottery-based decision paradigm. Study 1 investigates the direct and moderated associations between childhood environments and adult risk propensity, considering life-history trade-offs and current environmental conditions. Study 2 extends this framework by incorporating acute stress manipulation and examining attachment orientations as a mediating mechanism, while also testing for nonlinear relationships. Overall, findings do not support a consistent or domain-general association between childhood adversity and adult risk-taking. Instead, results reveal heterogeneous and context-dependent patterns, with effects varying according to stress conditions, task structure, and individual differences. Evidence of nonlinear relationships further suggests that simple linear models may obscure important variability across levels of adversity. These findings contribute to a more nuanced understanding of risk-taking as a flexible and context-sensitive behavior, shaped by the interaction between early-life experiences and current environmental demands. The dissertation highlights the importance of integrating evolutionary frameworks with experimental approaches to better capture the complexity of human decision-making.