L’enfance et l’adolescence in situ : facteurs environnementaux facilitateurs et inhibiteurs de troubles cognitifs et comportementaux

The definition of mental health associates three fundamental variables: biological variables, psychological variables and environmental variables. In this article, we will focus on environmental variables that inhibit and facilitate cognitive and behavioural disorders in childhood and adolescence. Environmental psychology considers the interrelations between human and environment in its spatial, social and chronological dimensions and considers it as a characterized and undissociated system. We will bring to mind social and physical environmental variables with which children and adolescents interact frequently and, through a literature review, we will enlighten environmental variables that are susceptible to induce behavioural disorders and psychological variables that modulate children's and adolescent's relations to environment. We then suggest possible outcomes of this approach in clinical practice as well as in terms of therapeutic applications in child psychology and psychiatry. Finally, we evoke the necessity of taking in account neurobiological fields in order to outline a model of human development integrating the three variables that define mental health.     

The temporal stability of some Rorschach features

One hundred nonpatient adults, screened for evidence of personality disorganization, were retested after a three-year interval to study the temporal consistency of the Rorschach. In general, the correlational analysis for 19 basic variables studied, and a directionality analysis for five ratios, illustrate a considerable sturdiness over time. It is postulated that these variables can be separated into situational related indices (state variables), and more stable scores indicative of durable response styles (trait variables), based on the assumption that variables with lower correlations would identify state variables, while the higher correlations would signify the trait features. Nine of the 19 variables yield retest correlations in excess of.     

A MULTIDIMENSIONAL APPROACH FOR EVALUATING VARIABLES IN ORGANIZATIONAL RESEARCH AND PRACTICE

One of the most difficult tasks facing industrial-organizational psychologists is evaluating the importance of variables, especially new variables, to be included in the prediction of some outcome. When multiple regression is used, common practices suggest evaluating the usefulness of new variables by showing incremental validity beyond the set of existing variables. This approach assures that the new variables are not statistically redundant with this existing set, but this approach attributes any shared criterion-related validity to the existing set of variables and none to the new variables. More importantly, incremental validity alone fails to answer the question directly about the importance of variables included in a regression model—arguably the more important statistical concern for practitioners. To that end, the current article reviews 2 indices of relative importance, general dominance weights and relative weights, which may be used to complement incremental validity evidence and permit organizational decision makers to make more precise and informed decisions concerning the usefulness of predictor variables. We illustrate our approach by reanalyzing the correlation matrices from 2 published studies.     

When can information from ordinal scale variables be integrated?

Many theoretical constructs of interest to psychologists are multidimensional and derive from the integration of several input variables. We show that input variables that are measured on ordinal scales cannot be combined to produce a stable weakly ordered output variable that allows trading off the input variables. Instead a partial order is obtained in which the amount of ordering depends on the number and nature of the input variables and the relationship between them. However, if trade-offs are excluded, it is still possible to obtain a weak order using lexicographic ordering of the input variables. An implication is that psychological processes that integrate information from different input variables and that produce consistent output require that the input variables be measured on more than ordinal scales. A further implication is that the level of measurement of the input variables affects the kind of psychological model that can be applied to the process.     

DO SITUATIONAL VARIABLES ACT AS SUBSTANTIVE CAUSES OF RELATIONSHIPS BETWEEN INDIVIDUAL DIFFERENCE VARIABLES? TWO LARGE-SCALE TESTS OF “COMMON CAUSE” MODELS

James, Demaree, Mulaik, and Ladd (1992) proposed that situational variables may act as substantive ("common") causes of relationships between individual difference variables as well as statistical artifacts (i.e., measurement unreliability) associated with these variables, thus invalidating assumptions of current validity generalization/meta-analysis procedures. In this investigation, we report the results of two large-scale studies designed to test hypothesized relationships derived from two "common cause" models. Study 1 examines relationships between store-level organizational climate variables and employee satisfaction and performance variables for 33,097 sales personnel in 537 retail stores. Study 2 investigates relationships between store-level situational constraints and customer service perception and shopping variables for 31,611 customers from 564 retail stores. The results of these studies did not support the proposition that situational variables act as substantive causes of correlations among the respective employee and customer variables or the variances and reliabilities of these variables. The implications of these findings for meta-analyses in applied psychology as well as the generalizability of the findings are discussed.     

青少年情绪弹性的影响因素研究

影响青少年情绪弹性的个体变量主要包括性别、年龄等背景变量和其他心理变量。研究对830名中学生的情绪弹性进行了调查,结果表明,性别与年龄变量对青少年情绪弹性不产生实质性影响,说明青少年情绪弹性具有相对稳定的心理特性;心理弹性、人格特质、情绪调节能力及自我效能与青少年情绪弹性存在显著相关,并对后者产生显著的预测效应;负性情绪认知调节能力和神经质是影响青少年情绪弹性的两个主要心理变量,神经质还以负性情绪认知调节能力为中介变量对青少年情绪弹性产生间接影响。     

The effect of affine transformation on redundancy analysis

Canonical redundancy analysis provides an estimate of the amount of shared variance between two sets of variables and provides an alternative to canonical correlation. The proof that the total redundancy is equal to the average squared multiple correlation coefficient obtained by regressing each variable in the criterion set on all variables in the predictor set is generalized to the case in which there are a larger number of criterion than predictor variables. It is then shown that the redundancy for the criterion set of variables is invariant under affine transformation of the predictor variables, but not invariant under transformation of the criterion variables.     

African Americans' Educational Expectations: Longitudinal Causal Models for Women and Men

The long‐term educational development of African American adolescents was investigated using a national longitudinal sample. The dependent variable was the highest level of education that participants ever expected to achieve. These expectations were assessed when participants were 2 years beyond high school. Background variables and family variables were assessed when students were in the 8th grade. High school behavior variables were assessed when students were high school seniors. Path models revealed differing processes for women and men. Overall, effects of early academic performance variables were strongest, followed by effects of family variables and high school behavior variables. Implications for theory and practice are included.     

The effect of personality variables in the prediction of the execution of different prospective memory tasks in the laboratory

The study of prospective memory (ProM), the remembering of the delayed execution of intentions, has been growing in recent years, and we know quite a bit about the cognitive variables that affect it. But the performance of a task depends on personality variables as well as on cognitive ones, and the role of personality variables in ProM has only been partially studied, the results being less conclusive. We sought to address two main objectives: (1) to quantify the joint influence of cognitive and personality variables on three ProM tasks in the laboratory (two based on events and the other on time), and (2) to identify the personality profiles of those who perform well in these three ProM tasks as opposed to those who do not. The cognitive and personality variables were evaluated with two sessions of 157 participants. The 16 PF-5 was applied (Cattell, Cattell & Cattell, 1993) and other cognitive variables were measured. With the data obtained, we ran several regression analyses to determine how some cognitive variables (sustained attention, verbal fluency, interference, retrospective memory, selective attention) and personality factors (tested using the 16 PF-5) can help to explain the variance in the performance of prospective memory tasks. Our results show that the contribution of personality predictor variables is moderate and smaller than that of the cognitive variables for predicting the execution of ProM tasks in the laboratory. Furthermore the intervention of the personality variables differs depending on the ProM tasks used. Global self-control and rule-consciousness were the personality variables that contributed the most in the prediction of the scores in the ProM tasks that were used.     

The relationship between self-concept and selected academic and personal factors

One-hundred sixty-five high school students were the subjects in a study to determine if selected personal and academic variables were predictive of self-concept scores. The full model was moderately predictive of self-esteem, accounting for approximately 46% of the variance of the criterion variable. Also, it was found that, as a subset of variables, both academic and personal variables made a significant, unique contribution to the prediction of self-concept scores. Of the eleven independent variables used in this study, it was noted that grade point average, extracurricular activities, health, and home life individually made a unique contribution to the prediction of self-concept scores. These four variables also were found to be significantly correlated with self-concept. Other independent variables found to be significantly correlated with self-concept were: parents married and parents divorced. However, these variables were not considered as making a unique contribution to the prediction of self-concept.     

Learning to visually perceive the relative mass of colliding balls in globally and locally constrained task ecologies

Novice observers differ from each other in the kinematic variables they use for the perception of kinetic properties, but they converge on more useful variables after practice with feedback. The colliding-balls paradigm was used to investigate how the convergence depends on the relations between the candidate variables and the to-be-perceived property, relative mass. Experiment 1 showed that observers do not change in the variables they use if the variables with which they start allow accurate performance. Experiment 2 showed that, at least for some observers, convergence can be facilitated by reducing the correlations between commonly used nonspecifying variables and relative mass but not by keeping those variables constant. Experiments 3a and 3b further demonstrated that observers learn not to rely on a particular nonspecifying variable if the correlation between that variable and relative mass is reduced.     

Predicting the lateral direction of deceptive and non-deceptive penalty kicks in football from the kinematics of the kicker

This study addresses the utility of the kinematics of penalty takers for goalkeepers in association football. Twelve professional and semi-professional players shot to one side of the goal with (deceptive condition) or without (non-deceptive condition) simulating a shot to the opposite side. The body kinematics of the penalty takers were registered with motion-capture apparatus. Correlation and regression techniques were used to determine the relation between the shot direction and aspects of the penalty taker’s kinematics at different moments. Several kinematic variables were strongly correlated with shot direction, especially those related to the lower part of the body. Some of these variables, including the angle of the non-kicking foot, acquired high correlations at time intervals that are useful to goalkeepers. Compound variables, here defined as linear combinations of variables, were found to be more useful than locally defined variables. Whereas some kinematic variables showed substantial differences in their relation to ball direction depending on deception, other kinematic variables were less affected by deception. Results are interpreted with the hypothesis of non-substitutability of genuine action. The study can also be interpreted as extending the correlation and regression methodology, often used to analyze variables defined at single moments, to the analysis of variables in a time continuous fashion.     

Forgotten variables in memory theory and research

Abstract

Memory research, like other scientific research, disregards many variables in order to bring the full force of the scientific method to bear on clearly important variables. The reasons why memory research attends to certain variables and disregards others emanate largely from theoretical assumptions that distinguish memory systems from other psychological systems, and that distinguish variables intrinsic to memory from those extrinsic to memory. Nevertheless, a number of these ‘forgotten’ variables affect memory performance. Regardless of past practice, it is a mistake for memory research to continue to ignore relevant variables. Doing so introduces measurement error that contaminates memory performance measures, and classification error that precludes the discovery of legitimate memory variables. It is proposed here that if forgotten memory variables are controlled, manipulated, and measured more extensively, then future memory research will have greater power and memory theories will have greater validity.     

Child resiliency in inner-city families affected by HIV: the role of family variables

This study examined the role of family variables in child resiliency within a sample of African-American, inner-city children whose mothers are HIV-infected. Variables from three dimensions of the family were included: family structural variables, maternal variables, and mother-child (parenting) variables. The participants were 82 children between the ages of 6 and 11 and their HIV-infected mothers. Correlational analyses indicated that resiliency was associated only with three parenting variables: parent-child relationship, parental monitoring, and parental structure in the home. Hierarchical regression analyses indicated a multiplicative relationship between parental monitoring and parent-child relationship and between parental monitoring and parental structure in the home, suggesting that parenting variables potentiate each other. Clinical implications of the findings are considered.     

How to Generate Non-normal Data for Simulation of Structural Equation Models

A procedure for generating non-normal data for simulation of structural equation models is proposed. A simple transformation of univariate random variables is used for the generation of data on latent and error variables under some restrictions for the elements of the covariance matrices for these variables. Data on the observed variables is then computed from latent and error variables according to the model. It is shown that by controlling univariate skewness and kurtosis on pre-specified random latent and error variables, observed variables can be made to have a relatively wide range of univariate skewness and kurtosis characteristics according to the pre-specified model. Univariate distributions are used for the generation of data which enables a user to choose from a large number of different distributions. The use of the proposed procedure is illustrated for two different structural equation models and it is shown how PRELIS can be used to generate the data.     

Antecedents of employees' mental health—The role of career and work satisfaction

It was hypothesized that individual and situational variables, as a whole, will show stronger relationships with work-related attitudes than with mental health indices. Work-related attitudes, on the other hand, were expected to contribute more strongly to mental health than the individual and situational variables. Results obtained from two groups of staff professionals and retail store managers, using primarily questionnaire data, supported these hypotheses. Career and work satisfaction emerged as the strongest contributors to mental health. Situational variables such as job characteristics, supervisory style, and pay related more strongly to the attitudinal variables than to mental health. This pattern suggests that career and work satisfaction may serve as intervening variables in the relationship between situational variables and mental health.     

Using Principal Components as Auxiliary Variables in Missing Data Estimation

To deal with missing data that arise due to participant nonresponse or attrition, methodologists have recommended an “inclusive” strategy where a large set of auxiliary variables are used to inform the missing data process. In practice, the set of possible auxiliary variables is often too large. We propose using principal components analysis (PCA) to reduce the number of possible auxiliary variables to a manageable number. A series of Monte Carlo simulations compared the performance of the inclusive strategy with eight auxiliary variables (inclusive approach) to the PCA strategy using just one principal component derived from the eight original variables (PCA approach). We examined the influence of four independent variables: magnitude of correlations, rate of missing data, missing data mechanism, and sample size on parameter bias, root mean squared error, and confidence interval coverage. Results indicate that the PCA approach results in unbiased parameter estimates and potentially more accuracy than the inclusive approach. We conclude that using the PCA strategy to reduce the number of auxiliary variables is an effective and practical way to reap the benefits of the inclusive strategy in the presence of many possible auxiliary variables.     

Approach and Avoidance Temperament as Basic Dimensions of Personality

ABSTRACT This research comprises 6 studies designed to examine approach and avoidance temperament as basic dimensions of personality. In Study 1, we developed direct measures of approach and avoidance temperament. In Study 2, we demonstrated that the approach and avoidance temperament variables are not epiphenomena of response biases. In Study 3, we documented the test‐retest stability of the temperament variables. In Study 4, we documented that approach and avoidance temperament are separate from other like‐valenced variables and may be construed as the core of these variables. In Study 5, we documented that approach and avoidance temperament are separate from chronic promotion and prevention foci. In Study 6, we distinguished the temperament variables from achievement goal variables and documented the temperament variables as antecedents of achievement goals and achievement goals as proximal predictors of performance. Approach and avoidance temperament are discussed as an ideal foundation for a strong, enduring structure of personality.     

Redundancy analysis for qualitative variables

Redundancy analysis (also called principal components analysis of instrumental variables) is a technique for two sets of variables, one set being dependent of the other. Its aim is maximization of the explained variance of the dependent variables by a linear combination of the explanatory variables. The technique is generalized to qualitative variables; it then gives implicitly a simultaneous optimal scaling of the dependent, qualitative variables. Examples are taken from the Dutch Life Situation Survey 1977, using Satisfaction with Life and Happiness as dependent variables. The analysis leads to one well-being scale, defined by the explanatory variables Marital status, Schooling, Income and Activity.The views expressed in this paper are those of the author and do not necessarily reflect the policies of the Netherlands Central Bureau of Statistics.     

Sex and sex-typing effects on computer attitudes and aptitude

Previous research has supported a sex difference favoring males on computer-related variables. This study examines the potential mediating effects of psychological sex typing on computer variables. One hundred twenty-five undergraduates were administered measures assessing sex typing, computer experience, computer attitudes, computer self-efficacy, and computer aptitude. When the effects of specific computer experience and sex-typing variables were removed using analyses of covariance, male/female comparisons on computer aptitude and self-efficacy variables were no longer significant. Participant sex as well as masculinity and several computer experience variables were significant in the computer attitude analysis.