The Role of Personality Traits, Attachment Style, and Satisfaction With Relationships in the Subjective Well-Being of Americans, Portuguese, and Mozambicans

• Main Author: Galinha, Iolanda Costa
• Publication Date: 2012
• Other Authors: Oishi, Shigehiro, Pereira, Cícero Roberto, Wirtz, Derrick, Esteves, Francisco
• Format: Article
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/10451/22912
• topic: Personalidade; Personality; Bem-estar subjectivo; Subjective well-being; Relacionamentos; Relationships

Personality traits, attachment security, and satisfaction with relationships are each important predictors of subjective well-being (SWB). However, no studies have included these predictors together to analyze the unique contribution of each to SWB. Furthermore, most studies are empirically based in Western/industrialized societies, and few studies include African countries. This article addresses the unique contribution of extroversion, neuroticism, attachment security, and satisfaction with relationships to SWB across three samples of 1,574 university students: 497 from North Carolina (United States of America), 544 from Maputo (Mozambique), and 533 from Lisbon (Portugal). Structural equation modeling analysis showed that in the American sample, emotional stability was a more important predictor of global SWB than satisfaction with relationships. In the Mozambican sample, satisfaction with relationships was far more important as a predictor of SWB than emotional stability. In the Portuguese sample, emotional stability and satisfaction with relationships were equally important predictors of SWB. The main difference between the three samples was the contribution of satisfaction with relationships to SWB. Similarities between the three samples include the low or nonsignificant contributions of extroversion and attachment to SWB, above and beyond the contribution of satisfaction with relationships and neuroticism, suggesting they may be sharing variance in the prediction of SWB.