Resilience in the Face of Maternal Psychopathology and Adverse Life Events

Maternal psychopathology has long been recognized as a risk factor for psychopathology in offspring; however, some resilient youth achieve a favorable outcome in the presence of maternal psychopathology. We identified factors that predicted resilience among youth who were exposed to adverse life events, and also examined whether the same factors protected youth against maternal psychopathology and adverse life events. Main and interaction effects of child and family factors were examined employing cross-sectional data from a household probability sample of 1285 youth aged 9 through 17 collected at four sites. On average, children exhibited a greater degree of resilience when they had higher IQ, closer parental monitoring, better family functioning, higher educational aspiration, and were female. Interaction between maternal psychopathology and IQ was significant, and there was a trend between maternal psychopathology and gender. A higher IQ is a protective factor against both maternal psychopathology and adverse life events; whereas being a girl seems to be a protective factor against maternal psychopathology, but not adverse life events.     

A comparison between three and five factor models of Pakistani personality data

The Eysenck Personality Questionnaire-Revised (EPQ-R), the Eysenck Personality Profiler Short Version (EPP-S), and the Big Five Inventory (BFI-V4a) were administered to 135 postgraduate students of business in Pakistan. Whilst Extraversion and Neuroticism scales from the three questionnaires were highly correlated, it was found that Agreeableness was most highly correlated with Psychoticism in the EPQ-R and Conscientiousness was most highly correlated with Psychoticism in the EPP-S. Principal component analyses with varimax rotation were carried out. The analyses generally suggested that the five factor model rather than the three-factor model was more robust and better for interpretation of all the higher order scales of the EPQ-R, EPP-S, and BFI-V4a in the Pakistani data. Results show that the superiority of the five factor solution results from the inclusion of a broader variety of personality scales in the input data, whereas Eysenck's three factor solution seems to be best when a less complete but possibly more important set of variables are input.     

高校毕业生择业焦虑问卷的跨地区验证和比较

对高校毕业生择业焦虑问卷的结构进行必要的修订和跨地区验证。使用修订后的问卷对内蒙古、陕西、山东、广东等四省区7所大学的1458名2007届毕业生进行调查,考察不同地区毕业生择业焦虑状况。结果表明:修订后的问卷具有较好的心理测量学指标和跨地区普遍适用性;不同地区高校毕业生的择业焦虑在4个维度和问卷总分上均存在显著差异。说明问卷的修订是有效的,可用于不同地区毕业生择业焦虑的测量和心理教育效果的评定;地区间的经济、文化、教育水平的差距可能是导致毕业生择业焦虑差异的主要因素。     

Predicting counterproductive work behavior from the interaction of personality traits

Much attention has been given to enhancing the prediction of counterproductive work behavior (CWB), with a particular focus on the relationship between the five factor model of personality and CWB. Several scholars have advocated for a more complex view of this relationship, and rather than focusing simply on main effects, to examine the interaction of personality traits in predicting employee behavior. In consideration of the traits most strongly related to CWB, we examined the interaction between: (1) conscientiousness and emotional stability, (2) agreeableness and emotional stability, and (3) conscientiousness and agreeableness on CWB directed at individuals (CWB-I) and the organization (CWB-O). Results from a multi-national sample illustrate the interaction of traits increases the prediction of CWB over and above a single trait approach. The interactions suggest employees perform the least CWB when they are high on both traits (in the respective trait pairings), but low levels on either trait relate to increased CWB, and at levels comparable to individuals low on both traits. We conclude research on personality and CWB would benefit from an interactive approach as it allows for greater prediction of CWB-O and CWB-I, which is important in light of the organizational and interpersonal consequences of employee misbehavior.     

农村选民选举行为的结构特征

以云南省两个县八个自然村的 2 62名选民为被试 ,采用心理测量原理与技术探讨了农村选民选举行为的结构特征。结果表明 ,政见取向由“政策效应”、“民生意识”、“村民权益”和“监督机制”4个因素构成 ,非政见取向由“候选人身份”、“候选人德能”、“选民社会关系”、“候选人背景”、“选民自我利益”、“选民自我权利”和“政党意见”7个因素构成。经检验 ,由此构成的农村选举行为问卷具有较高的内部一致性 ,问卷项目具有较高的区分度。文章讨论了农村选民选举行为的结构特征及其意义。     

Comparison of women engineers who persist in or depart from engineering

The current research examined differences between women engineers who persisted in an engineering career versus those who left engineering using a combination of two prominent theories of career change: social cognitive career theory (SCCT, Lent, Brown & Hackett, 1994; 2002) and integrated model of career change (Rhodes & Doering, 1983). The two groups of women did not differ in three domains of self-confidence or outcome expectations (engineering tasks, navigating organizational climate, or multiple roles), in vocational interests, or in workplace barriers. Women who continue in engineering do differ from those who leave in their experience of workplace supports and their levels of occupational commitment. Engineering turnover intentions and occupational commitment emerged as the two key variables that explained 33.4% of the variance in persistence in engineering careers. We discuss the implications of the results in terms of theoretical development and practical implications for organizations.     

A comparative assessment of the factor structures and psychometric properties of the GHQ-12 and the GHQ-20 based on data from a Finnish population-based sample

The General Health Questionnaire (GHQ) is a self-report questionnaire designed to identify psychological distress. Psychometric properties of two versions of GHQ-12 and GHQ-20 were assessed in a large population-based sample of Finnish twins, ages 22 to 27 (n= 4580). Participants were randomized into two subgroups, namely Twin1 (n= 2294) and Twin2 (n= 2286). The GHQ-12 data were assessed using Confirmatory Factor Analysis (CFA). The factor structure of the GHQ-20 was first assessed with Exploratory Factor Analysis (EFA) in the Twin1 dataset, and the results obtained were then subjected to CFA in Twin1 and Twin2 datasets. The CFA of the GHQ-12 indicated that the best fit and the simplest solution were provided by the three-factor solution in both subpopulations. Analyses of the GHQ-20 suggested that the four-factor structure was superior to the three-factor model. This result is also theoretically justifiable. Compared to the 12-item version, GHQ-20 provides additional fourth factor of anhedonia, suggesting some discriminative power.     

On structural equation modeling with data that are not missing completely at random

A general latent variable model is given which includes the specification of a missing data mechanism. This framework allows for an elucidating discussion of existing general multivariate theory bearing on maximum likelihood estimation with missing data. Here, missing completely at random is not a prerequisite for unbiased estimation in large samples, as when using the traditional listwise or pairwise present data approaches. The theory is connected with old and new results in the area of selection and factorial invariance. It is pointed out that in many applications, maximum likelihood estimation with missing data may be carried out by existing structural equation modeling software, such as LISREL and LISCOMP. Several sets of artifical data are generated within the general model framework. The proposed estimator is compared to the two traditional ones and found superior.The research of the first author was supported by grant No. SES-8312583 from the National Science Foundation and by a Spencer Foundation grant. We wish to thank Chuen-Rong Chan for drawing the path diagram.     

Application of the bootstrap methods in factor analysis

A Monte Carlo experiment is conducted to investigate the performance of the bootstrap methods in normal theory maximum likelihood factor analysis both when the distributional assumption is satisfied and unsatisfied. The parameters and their functions of interest include unrotated loadings, analytically rotated loadings, and unique variances. The results reveal that (a) bootstrap bias estimation performs sometimes poorly for factor loadings and nonstandardized unique variances; (b) bootstrap variance estimation performs well even when the distributional assumption is violated; (c) bootstrap confidence intervals based on the Studentized statistics are recommended; (d) if structural hypothesis about the population covariance matrix is taken into account then the bootstrap distribution of the normal theory likelihood ratio test statistic is close to the corresponding sampling distribution with slightly heavier right tail.This study was carried out in part under the ISM cooperative research program (91-ISM · CRP-85, 92-ISM · CRP-102). The authors would like to thank the editor and three reviewers for their helpful comments and suggestions which improved the quality of this paper considerably.     

The TRAMS: The Team-Referent Attributions Measure in Sport

ObjectivesTo provide initial evidence for the construct, concurrent, and predictive validity of the Team-Referent Attributions Measure in Sport (the TRAMS).DesignCross-sectional in Studies 1 and 2, and multiple time points in Study 3.MethodStudy 1 required participants (N = 500) to complete the TRAMS for their “least successful” and “most successful” performances in the preceding three months. In Study 2, after performance, participants (N = 515) completed the TRAMS and the Causal Dimension Scale for Teams (CDS-T; Greenlees et al., 2005). Study 3 required participants (N = 165) to complete a measure of pre-competition collective-efficacy prior to performance (Day 1, Time 1), the TRAMS following performance (Day 1, Time 2), and a measure of subsequent collective-efficacy prior to subsequent performance (Day 7–9, Time 3).ResultsStudy 1 supported the factor structure of the TRAMS across least successful and most successful conditions. Study 2 provided further support for the factor structure of the TRAMS, together with evidence of concurrent validity with subscales of the CDS-T. Study 3 revealed, following team defeat, interactions between controllability and generalisability dimensions: Controllability had a significant effect upon subsequent collective-efficacy when causes of team defeat were also perceived to generalise across situations and/or across teams. Following team victory, stable attributions were positively associated with subsequent collective-efficacy.ConclusionsThis article provides initial evidence for the validity of the TRAMS and demonstrates for team-referent attributions the theoretical advantages of examining a broader conceptualisation of generalisability attributions and interactive effects of attributions.