Effects of decision strategy and number of openings on employment selection decisions

The purpose of this study was to explore the impact of two factors—decision strategy and the number of openings—on selection decisions. Two hundred graduate and undergraduate students participated in a human resource employment screening simulation. Decision strategy was varied by having candidates evaluate resumes and letters of application for 20 candidates one-at-a-time (sequentially) or all at once (simultaneously). The number of position openings was either one or three. Decision strategy affected the number of candidates accepted, acceptance threshold, and decision time. The number of openings affected selection decisions in the simultaneous but not the sequential context. Implications of these results for selection processes are discussed.     

Pathways to Problems – The Evolution of 'Pathology'

This paper describes a qualitative research study which compared accounts from interviews with families where difficulties had evolved into serious problems with those where an escalation into pathology has been avoided. These accounts confirm that family life is commonly seen to be problematic and stressful, particularly during transitional stages. Specifically, it appears that it is not simply the severity of the initial stresses and problems that distinguishes families, but the meanings that these evoke and the corresponding patterns of responses, especially the 'attempted solutions' that are set in motion. These responses, fuelled by external interventions, can launch families along pathological pathways. It is suggested that the meanings ascribed to difficulties and the ensuing responses are predominantly shaped and constrained by three factors: the dominant societally shared discourses of mental health and distress; the emotional resources and attachments of family members; and systemic interpersonal processes. Some therapeutic implications, especially the importance of assisting families to resist pathologizing processes are indicated.     

Effects of marital discord on the school behavior of children of schizophrenic,affectively disordered,and normal parents

An association between children's school behavior and two family variables, marital discord and parental psychopathology, has been consistently reported in the literature. However, the joint effects of each of these two familial factors has not been closely examined. The present report provides a further examination of the interrelationships among these three variables with particular emphasis on the effects of marital discord on children's school behavior in families with behaviorally disturbed parents. Marital discord was found to account for much of the association between having a parent with bipolar disorder or unipolar depression and problematic school behavior, but the same variable did not explain the relationship between having a schizophrenic parent and problems in school. The implications of these findings for interventions with the children of disturbed parents and for high-risk research are discussed.This research was supported by Grant MH21145 from the National Institute of Mental Health.     

Effects of self-monitoring and feedback on residential electricity consumption

Prior research has indicated that frequent feedback could reduce residential electricity consumption by 10% to 15%. However, because feedback was primarily given in written form, this procedure might not be practical. The present study evaluated a potentially more practical feedback procedure during peak-use periods with high electricity consuming households. The study was conducted during the winter in an upper-middle class neighborhood of almost identical, all-electric townhouses (N = 71) that averaged about 170 KWH per day per household for a monthly bill of over $200. Twelve households received daily written feedback. Sixteen households (self-monitoring) were taught to read their outdoor electricity meter and to record KWH used every day. A comparison group was composed of 14 households that had volunteered to participate and 29 others that had only given permission to have their meters read. During a 1-month period that the procedures were in effect, the feedback group reduced consumption by 13% and the self-monitoring group by about 7%. These reductions, relative to the comparison group, were maintained during an early spring 1-month follow-up period and, to a lesser extent, during a 6-week warm spring period. Self-monitoring participants were highly reliable and persistent meter readers. Reductions in electricity use were reported by households to be largely attributable to lowering of the heat thermostat, and large monetary and KWH savings were found. Techniques to make self-monitoring cost-effective important components of the self-monitoring procedure, methods to apply self-monitoring more broadly, and plans to combine behavioral procedures with physical technology are discussed.     

Issues in multivariate assessment of a large-scale behavioral program

Several social and research issues directly affected the development and implementation of multivariate assessment in a large community-based applied research program. Examples are drawn from experiences of the Preparation through Responsive Educational Programs Project for disruptive and skill deficient adolescents in suburban, rural, and urban junior high school settings, focusing on the assessment of academic and social skill development and long-term skill maintenance. The social context altered both project treatment and follow-up plans, requiring assessment of potentially unintended effects and decreasing consistency across sites. Future community acceptance of such programs may depend on the investigators' adaptation to diverse community pressures for program conduct and assessment and the measurement of phenomena that are not always directly observable.     

Distinguishing Between Latent Classes and Continuous Factors with Categorical Outcomes: Class Invariance of Parameters of Factor Mixture Models

Factor mixture models are latent variable models with categorical and continuous latent variables that can be used as a model-based approach to clustering. A previous article covered the results of a simulation study showing that in the absence of model violations, it is usually possible to choose the correct model when fitting a series of models with different numbers of classes and factors within class. The response format in the first study was limited to normally distributed outcomes. This article has 2 main goals, first, to replicate parts of the first study with 5-point Likert scale and binary outcomes, and second, to address the issue of testing class invariance of thresholds and loadings. Testing for class invariance of parameters is important in the context of measurement invariance and when using mixture models to approximate nonnormal distributions. Results show that it is possible to discriminate between latent class models and factor models even if responses are categorical. Comparing models with and without class-specific parameters can lead to incorrectly accepting parameter invariance if the compared models differ substantially with respect to the number of estimated parameters. The simulation study is complemented with an illustration of a factor mixture analysis of 10 binary depression items obtained from a female subsample of the Virginia Twin Registry.