Lori Anderson Snyder

Occupational safety: Application of the job demand–control-support model

The utility of the job demand-control-support (JDCS) model for explaining psychological and physical well-being has been documented in a variety of settings. The current studys purpose was to assess the effectiveness of the JDCS model for predicting occupational safety well-being criteria (i.e., workplace injuries) based on two studies that employed samples of union blue-collar workers from two different regions of the United States. The JDCS models buffer hypotheses were evaluated using hierarchical linear modeling. Both studies showed significant interactions between situational constraints and safety control to predict workplace injuries such that safety control buffered the negative effects of situational constraints. No significant three-way interaction between situational constraints, safety control, and safety climate on workplace injuries was found for either study. The implications of the present findings for both the JDCS model and occupational safety research are discussed.

The underreporting gap in aggressive incidents from geriatric patients against certified nursing assistants.

Staff in the health care industry experience workplace aggression at a much higher rate than the general workforce. However, a large proportion of aggressive incidents go unreported, and the source of many of these incidents is patients. This study investigates aggressive incidents from patients against certified nursing assistants (CNAs; n = 76) in a sample of six geriatric care facilities. The results indicate that CNAs experienced a median of 26 aggressive incidents over the course of the 2-week study and that approximately 95% of these incidents were not reported to the facility. The present study also empirically examines reasons why nursing staff decide to report incidents. Finally, this study reveals that the experience of aggression from patients is related to subsequent organizational commitment, job satisfaction, and intent to leave the job.

The Relationship Between Sleep and Work: A Meta-Analysis.

Sleep has tremendous importance to organizations because of its relationship with employee performance, safety, health, and attitudes. Moreover, sleep is a malleable behavior that may be improved by individual and organizational changes. Despite the consequential and modifiable nature of sleep, little consensus exists regarding its conceptualization, and how the choice of conceptualization may impact relationships with organizational antecedents and outcomes. To offer a stronger foundation for future theory and research about employee sleep, this study calculated meta-analytic correlations of sleep quality and sleep quantity from 152 primary studies of sleep among workers in organizations. Analyses revealed that both sleep quality and sleep quantity associated negatively with workload and a number of health, attitudinal, and affective outcomes. Despite their conceptual similarity, notable differences existed in sleep quality and sleep quantity in terms of their relationships to many different correlates. Generally, the relationships between sleep quality and the examined correlates were stronger for variables that reflected perceptions. Moderator analyses showed that relationships between sleep quality and quantity may be affected by measurement method and the number of self-report items used, while there is little evidence of the effect of measurement time frame. Findings from this first meta-analytic investigation of the occupational sleep literature have implications for the development of theory about relationships between sleep and work, the measurement of sleep, the identification of organizational correlates of sleep, and the design of interventions intended to improve employee sleep.

WORKPLACE AGGRESSION AND VIOLENCE AGAINST INDIVIDUALS AND ORGANIZATIONS: CAUSES, CONSEQUENCES, AND INTERVENTIONS

This chapter examines aggression at work perpetrated by individual insiders by bringing together streams of research that have often been examined separately. A comparison of the similarities and differences of aggression toward individuals, such as verbal abuse or physical attack, and aggression toward organizations, such as embezzlement or work slowdowns, is shown to provide important insights about the causes and consequences of workplace aggression. We propose a comprehensive model based on the integration of prior theoretical treatments and empirical findings. The model attempts to offer a framework to systematically examine psychological and organizational mechanisms underlying workplace aggression, and to explain the reasons why workplace violence policies and procedures sometimes fail. A set of research propositions is also suggested to assist in achieving this end in future research.

Personnel Selection of Information Technology Workers: The People, the Jobs, and Issues for Human Resource Management

The impetus for this paper was the recognition, based on recent surveys and our own experiences, that organizations face special challenges when designing and validating selection procedures for information technology (IT) workers. The history of the IT industry, the nature of IT work, and characteristics of IT workers converge to make the selection of IT workers uniquely challenging. In this paper, we identify these challenges and suggest means of addressing them. We show the advantages offered by the modern view of validation that endorses a wide spectrum of probative information relevant to establishing the job relatedness and business necessity of IT selection procedures. Finally, we identify the implications of these issues for industrial/organizational psychologists, human resource managers, and managers of IT workers.

Bayesian SEM for Specification Search Problems in Testing Factorial Invariance

ABSTRACT Specification search problems refer to two important but under-addressed issues in testing for factorial invariance: how to select proper reference indicators and how to locate specific non-invariant parameters. In this study, we propose a two-step procedure to solve these issues. Step 1 is to identify a proper reference indicator using the Bayesian structural equation modeling approach. An item is selected if it is associated with the highest likelihood to be invariant across groups. Step 2 is to locate specific non-invariant parameters, given that a proper reference indicator has already been selected in Step 1. A series of simulation analyses show that the proposed method performs well under a variety of data conditions, and optimal performance is observed under conditions of large magnitude of non-invariance, low proportion of non-invariance, and large sample sizes. We also provide an empirical example to demonstrate the specific procedures to implement the proposed method in applied research. The importance and influences are discussed regarding the choices of informative priors with zero mean and small variances. Extensions and limitations are also pointed out.

Math Self-Efficacy and STEM Intentions: A Person-Centered Approach

Research pertaining to STEM interest and persistence continues to be a top priority in the educational research arena. The current study employed a person-centered approach to examine the impact of math self-efficacy and various distal predictors, such as individuals’ demographic information, beliefs about math, and social group identification, on STEM interest and intentions. Specifically, we conducted a latent profile analysis (LPA), thereby inferring three homogeneous subgroups of individuals or latent classes from their response patterns on the 18-item sources of math self-efficacy measure. Our analyses showed that individuals’ ethnicity, implicit theories of math ability, and other group orientation were predictive of class membership (Mastery, Moderate, and Unconfident). We also found that there were significant differences in interest in STEM subjects, interest in STEM activities, individuals’ majors, and retention grade point average across the three latent classes. Our findings support the importance of math self-efficacy in choice of major as well as overall academic performance regardless of whether a student is in a STEM field or a non-STEM field.