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Working students face incredible demands on their time and resources, yet little research exists assessing the degree to which they are able to recover from their demands. The current study aimed to determine the extent to which different types of psychological detachment-detachment from work as well as detachment from school-contribute to the well-being of working students, and whether work can serve as an opportunity to recover from school and vice versa. An additional focus of the study was how perceived stress interacts with detachment both from school and from work to impact well-being. To investigate these questions, data were collected daily for 12 days from 268 undergraduate students who were also employed. Results revealed that neither psychological detachment from work nor from school is beneficial, with psychological detachment from work even having a negative relationship with vigor. However, perceived stress due to school did interact with psychological detachment from school, such that detachment had a stronger impact on vigor and fatigue on days when individuals experienced more stress. A key takeaway from this study is the need for future research on psychological detachment for working students to separate detachment from work and detachment from school. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

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With a specific focus on the Native American population, the current study investigated the structure of ethnic identity, measured by the Multigroup Ethnic Identity Measure, using a bifactor model across Native American (n = 307), Asian (n = 348), and White (n = 549) undergraduate students. We further investigated measurement invariance across ethnic groups that shared the same factor structure. The results indicated that ethnic identity can be modeled by a bifactor structure with a general factor and two group factors, affective pride and exploration, for Native American and Asian respondents but not White respondents. In addition, measurement invariance tests supported partial weak invariance between the Native American group and the Asian group. The current findings suggest that comparisons of ethnic identity scores across ethnic groups should be treated with caution.

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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.

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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. (PsycINFO Database Record

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BACKGROUND: Because the health care field is expected to be the fastest growing job field until 2020, an urgent need to focus on nurse retention exists. PURPOSE: The aim of this study was to examine the relationships between predictors of turnover (i.e., personal characteristics, role states, job characteristics, group/leader relations, organizational/environmental perceptions, attitudinal reactions) and turnover cognitions and intentions, as well as actual turnover among nurses, in an effort to determine the strongest predictors of voluntary turnover. METHODOLOGY: Meta-analysis was used to determine best estimates of the effect of predictors on turnover based on 106 primary studies of employed nurses. Meta-analyzed correlations were subjected to path analysis to establish the structural relationships among the study variables. FINDINGS: Supportive and communicative leadership, network centrality, and organizational commitment are the strongest predictors of voluntary turnover based on meta-analytic correlations. Additional variables that relate to nurse turnover intentions include job strain, role tension, work-family conflict, job control, job complexity, rewards/recognition, and team cohesion. PRACTICE IMPLICATIONS: The findings suggest that some factors, such as salary, are relatively less important in prediction of turnover. Administrators concerned about nurse turnover may more effectively direct resources toward altering certain job characteristics and work conditions in the effort to reduce voluntary turnover among nurses.

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OBJECTIVE: Occupational stress models suggest that the ability to understand, predict, and control stressful events minimizes their impact. This study examines the applicability of the stress antidote theory to the safety environment. Newly developed measures assess understanding why and how unsafe events occur, predicting the occurrence of unsafe events, and controlling unsafe events, and how these constructs relate to safety performance at work. In addition, the role of supervisor safety support is explored. PARTICIPANTS: 424 employees in the Facilities department at a large university. METHODS: Measures were developed based on existing literature and focus groups, and participants completed a survey about their safety experiences at work. RESULTS: Analyses conducted using structural equation modeling indicate that safety understanding, safety prediction, and safety control are related but distinct variables. Safety understanding affects safety performance through safety control, while supervisor support for safety affects safety performance both directly and indirectly through control. CONCLUSION: Lack of understanding of safety or inability to predict dangerous outcomes may be necessary but not sufficient to explain unsafe workplace behaviors. Employees' safety behaviors may be more directly influenced by the extent to which they have the power to control safety in their work environment.

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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 study's 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 model's 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.

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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.

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