Individual Differences in Testosterone Predict Persistence in Men

Persistence is an important predictor of future successes. The present research addresses the relationship between testosterone and persistence in men. One hundred eighteen men were randomly assigned to win or lose a competitive number tracing task against a confederate or complete the task alone in a non‐competitive control condition. Saliva samples were collected prior to and after the competition or control conditions. Participants were then given a maximum time of 30 min to spend attempting to solve unsolvable puzzles, with the option to quit at any time. In contrast to our prediction, changes in testosterone concentrations in response to the competitive interaction did not predict persistence behaviour. However, individual differences in testosterone concentrations (pre‐competition/non‐competition) were positively correlated with persistence. These findings are the first to examine associations between neuroendocrine function and persistence behaviour in people and suggest that testosterone should also be considered when predicting persistence‐related outcomes. Copyright © 2014 European Association of Personality Psychology     

Confirmatory factor analysis of the Machiavellian Personality Scale

According to Christie and Geis (1970), Machiavellianism predisposes one to self-interested behavior, manipulation, and deceit often at the expense of others. The measurement of Machiavellianism began with the Mach IV (Christie & Geis, 1970), which has long suffered from an indeterminant factor structure and poor reliability. Dahling, Whitaker, and Levy (2009) developed the Machiavellian Personality Scale (MPS) to address these shortcomings. In the current examination of the MPS, a four-factor structure is supported with confirmatory factor analysis, but the relationships in a full structural equation model between the four subscales and the criterion of empathy is problematic in that some MPS subscales are negative, some positive, and some unrelated to empathy. Additionally, reliability issues arose with the MPS as have historically occurred with the Mach IV. The four subscales of the MPS appear to act as suppressors of each other, further complicating the predictive relationship between Machiavellianism and other variables.     

Further evidence for a bifactor solution for the Consideration of Future Consequences Scale: Measurement and conceptual implications

The Consideration of Future Consequences construct has been found to relate meaningfully to several positive outcomes in temporal research. Researchers have proposed 1-factor, 2-factor, and bifactor solutions to the Consideration of Future Consequences Scale (CFCS). Using 313 British University undergraduates, we tested four competing models: (a) a 12-item unidimensional model, (b) a model fitted for two uncorrelated factors (CFC-Immediate and CFC-Future), (c) a model fitted for two correlated factors (CFC-I and CFC-F), and (d) a bifactor model. Results supported the bifactor model, suggesting that the two hypothesized factors are better understood as grouping factors. Accordingly, the present study supports the CFCS as a unidimensional global future orientation measure. These results have important implications for the study of future orientation using the CFCS. Researchers using the CFCS are encouraged to examine a bifactor solution for the scores.     

Initial development and validity evidence for the processes of change in Psychological Skills Training Questionnaire

ObjectivesThe purpose of this study was to create and provide validity evidence for the Processes of Change in Psychological Skills Training Questionnaire (PCPSTQ).DesignThe current study used a cross-sectional research design.MethodsFive hundred fifty nine NCAA Division I, professional, and Olympic level athletes participated in the current study. To create the PCPSTQ, an initial pool of 114 items was generated by the research team. After a content validity process, 65 items were retained for analysis. Exploratory structural equation modeling was used as an analytic strategy to identify the most appropriate factor structure for the PCPSTQ. Decisions about the most appropriate model were made using multiple fit indices. To examine the construct validity of the PCPSTQ, a series of one-way ANOVAs were conducted to examine differences in processes of change use across stage of change.ResultsIn the current study, validity evidence provided support for a 7-factor process of change measure (χ² = 325.84, p < .001; Comparative Fit Index = .971; Tucker Lewis Index = .945; Root Mean Square Error of Approximation = .037; Standard Root Mean Square Residual = .020). Results also supported the construct validity of the scale as a significant difference in process of change use across stage of change was reported for all seven processes.ConclusionsResults of the current study support the factor structure and construct validity of the PCPSTQ. It appears that the processes of behavior change reported across multiple behavior change domains might also be viable for sport psychology professionals.     

Evaluating Food Policy Councils Using Structural Equation Modeling

At least 282 Food Policy Councils (FPCs) are currently working to improve access to healthy foods in their communities by connecting food system sectors, gathering community input, and advising food policy. Empirical research on FPCs is limited. This study empirically evaluates FPCs to better understand the relationships between Organizational Capacity, Social Capital, and Council Effectiveness by testing a FPC Framework adapted from Allen and colleagues (2012). Members of all FPCs in the U.S., Canada, and Native American Tribes and First Nations were invited to complete the Food Policy Council Self‐Assessment Tool (FPC‐SAT). Structural equation modeling was used to test the FPC Framework. Three hundred and fifty‐four FPC members from 95 councils completed the FPC‐SAT. After slight modification, a revised FPC Framework was a good fit with the data (χ² = 40.085, df = 24, p‐value = .021, comparative fit index = 0.988, Tucker Lewis index = 0.982, root mean squared error of approximation = 0.044, p‐close = .650). A moderation analysis revealed that community context influences the relationship between Social Capital and Council Effectiveness within the FPC Framework. The FPC Framework can guide capacity building interventions and FPC evaluations. The empirically tested framework can help FPCs efficiently work toward achieving their missions and improving their local food system.     

Applying social cognitive career theory to predict interests and choice goals in statistics among Spanish psychology students

This study investigated the usefulness of social cognitive career theory—SCCT (Lent, Brown, and Hackett, 1994) in predicting interests and goals relating to statistics among psychology students. The participants were 1036 Spanish students who completed measurements of statistics-related mastery experiences, self-efficacy, outcome expectations, interests and goals/intentions. Structural equation modeling (including multi-group analysis) was used to test the fit of the hypothesized models to the data. Results indicated support for SCCT as a way to predict students' interests in statistics and their intentions of engaging in academic or professional activities where statistics is used. Collectively, the predictors accounted for 50% of the variance in interests and for 77% of the variance in goals. Implications both for future research on SCCT and for intervention in statistics education are discussed.     

Development of behavioural regulation in Do and Don't contexts among behaviourally inhibited Chinese children

Behavioural inhibition influences the development of behavioural regulation in early childhood. Previous studies have mainly focused on the relationship between inhibition and regulation in the Don't context (e.g., inhibitory control), while few have investigated this relationship in the Do context (e.g., task persistence). This longitudinal study examined the effect of temperamental inhibition on behavioural regulation during both the Do and Don't contexts in 112 Chinese preschoolers. At 3.5 years of age, children's behavioural inhibition was assessed by behavioural observation and parental report, and then at 4.5 years of age, their regulatory behaviours were measured in the following two challenging contexts: Do [locked box (LB)] and Don't [toy inhibition (TI)]. In each task, children were randomly assigned to either a high‐ or a low‐incentive condition designed to vary the value of a given goal. Results suggested that higher inhibition was associated with poorer regulation (lower task persistence) in both conditions of the Do context (LB), whereas in the Don't context (TI) highly inhibited children showed better regulation (less violation behaviours) in the low‐incentive condition than they did in the high‐incentive condition. The results highlight the context characteristics and goal incentive as important factors for behavioural regulation development in inhibited children in China.     

血铅对儿童发展的影响及其特点

铅具有很强的神经发育毒性,即使是低水平的铅暴露也会对个体发展产生消极的影响.本文综述了铅对个体影响的研究,这些研究表明铅导致个体产生生理缺陷、认知能力下降及社会情绪性障碍等症状,对处在生长发育重要时期的儿童影响更长远.已有研究发现,血铅对儿童的影响具有持久性的特点,而且血铅的危害很难通过螯合作用的干预得到改善.医疗干预及相关研究显示,积极避免铅接触是预防儿童铅中毒的最有效策略.本文为将来探讨血铅如何影响儿童认知、情绪社会性和脑发育提出了研究方向.     

On the Computation of the RMSEA and CFI from the Mean-And-Variance Corrected Test Statistic with Nonnormal Data in SEM

A new type of nonnormality correction to the RMSEA has recently been developed, which has several advantages over existing corrections. In particular, the new correction adjusts the sample estimate of the RMSEA for the inflation due to nonnormality, while leaving its population value unchanged, so that established cutoff criteria can still be used to judge the degree of approximate fit. A confidence interval (CI) for the new robust RMSEA based on the mean-corrected (“Satorra-Bentler”) test statistic has also been proposed. Follow up work has provided the same type of nonnormality correction for the CFI (Brosseau-Liard & Savalei, 2014). These developments have recently been implemented in lavaan. This note has three goals: a) to show how to compute the new robust RMSEA and CFI from the mean-and-variance corrected test statistic; b) to offer a new CI for the robust RMSEA based on the mean-and-variance corrected test statistic; and c) to caution that the logic of the new nonnormality corrections to RMSEA and CFI is most appropriate for the maximum likelihood (ML) estimator, and cannot easily be generalized to the most commonly used categorical data estimators.