This study examined the utility of social cognitive career theory (SCCT; R. W. Lent, S. D. Brown, & G. Hackett, 1994) in predicting engineering interests and major choice goals among women and men and among students at historically Black and predominantly White universities. Participants (487 students in introductory engineering courses at 3 universities) completed measures of academic interests, goals, self-efficacy, outcome expectations, and environmental supports and barriers in relation to engineering majors. Findings indicated that the SCCT-based model of interest and choice goals produced good fit to the data across gender and university type. Implications for future research on SCCT's choice hypotheses, and particularly for the role of environmental supports and barriers in the choice of science and engineering fields, are discussed.

Central variables of social cognitive theory were adapted to forge an integrative model of well-being, which was designed to offer greater utility for therapeutic and self-directed change efforts than the dominant personality view of well-being. The authors present 2 studies using versions of the social cognitive model to predict domain-specific and overall life satisfaction. In both studies-one nomothetic, the other idiographic in measurement approach-findings indicated that satisfaction in particular life domains is predicted by domain-specific social cognitive variables (e.g., self-efficacy, perceived goal progress, environmental resources). Domain satisfaction in valued life domains also explained unique variance in overall life satisfaction, even after controlling for trait positive affectivity or extraversion. Implications for theory, research, and counseling aimed at well-being promotion and maintenance are discussed.

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Lent (2004) posited a model of domain-specific and overall life satisfaction in which social-cognitive variables (self-efficacy, outcome expectations, environmental supports, and perceived goal progress) play key roles. In this study, the authors examined the relation of these variables to academic satisfaction. Participants were 153 engineering students. Results of structural equation modeling analyses indicated that the social-cognitive model fit the data well overall and that each of the predictors, except for outcome expectations, explained unique variation in students’ academic satisfaction. The authors consider the implications of the findings for further research and practice on academic and work satisfaction.

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