The magnitude and variability of sex differences in vocational interests were examined in the present meta-analysis for Holland's (1959, 1997) categories (Realistic, Investigative, Artistic, Social, Enterprising, and Conventional), Prediger's (1982) Things-People and Data-Ideas dimensions, and the STEM (science, technology, engineering, and mathematics) interest areas. Technical manuals for 47 interest inventories were used, yielding 503,188 respondents. Results showed that men prefer working with things and women prefer working with people, producing a large effect size (d = 0.93) on the Things-People dimension. Men showed stronger Realistic (d = 0.84) and Investigative (d = 0.26) interests, and women showed stronger Artistic (d = -0.35), Social (d = -0.68), and Conventional (d = -0.33) interests. Sex differences favoring men were also found for more specific measures of engineering (d = 1.11), science (d = 0.36), and mathematics (d = 0.34) interests. Average effect sizes varied across interest inventories, ranging from 0.08 to 0.79. The quality of interest inventories, based on professional reputation, was not differentially related to the magnitude of sex differences. Moderators of the effect sizes included interest inventory item development strategy, scoring method, theoretical framework, and sample variables of age and cohort. Application of some item development strategies can substantially reduce sex differences. The present study suggests that interests may play a critical role in gendered occupational choices and gender disparity in the STEM fields.

The current meta-analysis investigated the extent to which personality traits changed as a result of intervention, with the primary focus on clinical interventions. We identified 207 studies that had tracked changes in measures of personality traits during interventions, including true experiments and prepost change designs. Interventions were associated with marked changes in personality trait measures over an average time of 24 weeks (e.g., d = .37). Additional analyses showed that the increases replicated across experimental and nonexperimental designs, for nonclinical interventions, and persisted in longitudinal follow-ups of samples beyond the course of intervention. Emotional stability was the primary trait domain showing changes as a result of therapy, followed by extraversion. The type of therapy employed was not strongly associated with the amount of change in personality traits. Patients presenting with anxiety disorders changed the most, and patients being treated for substance use changed the least. The relevance of the results for theory and social policy are discussed. (PsycINFO Database Record

In this article we present the development and validation of two new measures of psychological well-being: the Comprehensive Inventory of Thriving (CIT) and the Brief Inventory of Thriving (BIT). These measures were developed with two specific goals in mind: (1) to measure a broad range of psychological well-being constructs and represent a holistic view of positive functioning; and (2) to predict important health outcomes that are useful for researchers and health practitioners. The CIT includes 18 subscales with 54 items in total, covering a broad range of well-being components. The BIT has 10 items in total and can serve as an indicator of psychological well-being and a brief screening tool of mental health. The new measures were evaluated in five samples of a total of 3,191 US participants with diverse demographics. The CIT and BIT had excellent psychometric properties and exhibited convergent validity with existing measures of psychological well-being and discriminant validity with measures of ill-being. Both measures contributed over and above existing measures of psychology well-being in predicting a variety of health outcomes, including self-reported and objective health status, physical functioning, and health behaviors. In addition, we showed the relative importance of thriving compared to ill-being for health outcomes and the benefits of assessing individuals' positive functioning beyond ill-being. Potential uses of the new measures are discussed.

This paper integrates the rapidly growing literatures on the individual and organizational factors that contribute to women’s career equality. We organize studies into three research perspectives: career preference, gender bias, and work-family explanations. These literatures diverge on whether women “opt out” or are “pushed out” of leadership positions in organizations. Further, the interconnectedness of these “pushes” and “pulls” and micro-macro linkages are not well-integrated. This creates a lack of clarity about what scholars should study and what practices organizations should implement. We define women’s career equality as an individual and organizational phenomenon involving the degree to which women (a) have equal access to and participation in career opportunities, and (b) experience equal intrinsic and extrinsic work and nonwork outcomes compared to men. We bridge the interdisciplinary divides by developing an integrative multi-level model of women’s career equality. We propose that individuals’ career perceptions and experiences are embedded in social contexts reflecting the climate for gender inclusion and interact with these contexts to shape women’s career equality outcomes. The climate for gender inclusion has three dimensions: fairness, leveraging talent, and workplace support. We identify coalescing themes to stimulate future research, including attention to national socio-economic influences, improving metrics and measurement of gender inclusion climate, multi-level career equality outcomes, a joint focus on implicit and explicit bias, and designing cross-disciplinary interventions for experiments. In order to foster theory-based research that is linked to practice, we suggest implementing and scientifically evaluating comprehensive workplace interventions that integrate perspectives and levels.

The degree of women's underrepresentation varies by STEM fields. Women are now overrepresented in social sciences, yet only constitute a fraction of the engineering workforce. In the current study, we investigated the gender differences in interests as an explanation for the differential distribution of women across sub-disciplines of STEM as well as the overall underrepresentation of women in STEM fields. Specifically, we meta-analytically reviewed norm data on basic interests from 52 samples in 33 interest inventories published between 1964 and 2007, with a total of 209,810 male and 223,268 female respondents. We found gender differences in interests to vary largely by STEM field, with the largest gender differences in interests favoring men observed in engineering disciplines (d = 0.83–1.21), and in contrast, gender differences in interests favoring women in social sciences and medical services (d = −0.33 and −0.40, respectively). Importantly, the gender composition (percentages of women) in STEM fields reflects these gender differences in interests. The patterns of gender differences in interests and the actual gender composition in STEM fields were explained by the people-orientation and things-orientation of work environments, and were not associated with the level of quantitative ability required. These findings suggest potential interventions targeting interests in STEM education to facilitate individuals' ability and career development and strategies to reform work environments to better attract and retain women in STEM occupations.

This paper investigates the interplay of family background and individual differences, such as personality traits and intelligence (measured in a large US representative sample of high school students; N = 81,000) in predicting educational attainment, annual income, and occupational prestige eleven years later. Specifically, we tested whether individual differences followed one of three patterns in relation to parental SES when predicting attained status: (a) the independent effects hypothesis (i.e., individual differences predict attainments independent of parental SES level), (b) the resource substitution hypothesis (i.e., individual differences are stronger predictors of attainments at lower levels of parental SES), and (c) the Matthew effect hypothesis (i.e., “the rich get richer,” individual differences are stronger predictors of attainments at higher levels of parental SES). We found that personality traits and intelligence in adolescence predicted later attained status above and beyond parental SES. A standard deviation increase in individual differences translated to up to 8 additional months of education, $4,233 annually, and more prestigious occupations. Furthermore, although we did find some evidence for both the resource substitution and the Matthew effect hypotheses, the most robust pattern across all models supported the independent effects hypothesis. Intelligence was the exception, where interaction models were more robust. Finally, we found that although personality traits may help compensate for background disadvantage to a small extent, they do not usually lead to a “full catch up” effect, unlike intelligence. This was the first longitudinal study of status attainment to test interactive models of individual differences and background factors.

Despite their significance to both individuals and organizations, interests are often misunderstood, and their predictive power is often overlooked. In this article, we discuss the nature of interests, describe several key features of interests, and, contrary to the received knowledge of many, explain how interests can be used to predict career and educational choice, performance, and success. Finally, we discuss the continuity of interests across the life span and explain how evidence of stability supports conceptualizations of interests as being distinct dispositions rather than simply extensions or workplace instantiations of basic personality traits.

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