1,291 research outputs found
Work engagement, job design and the role of the social context at work: Exploring antecedents from a relational perspective
Relational resources are now recognised as significant factors in workplaces and increasing attention is being given to the motivational impact of giving in addition to receiving social support. Our study builds on this work to determine the role of such relational mechanisms in work engagement, a concept that simultaneously captures drive and well-being. Data from 182 midwives from two maternity hospitals revealed a best-fit model where perceived supervisor support, social support from peers, prosocial impact on others and autonomy explained 52% of variance in work engagement. Perceived prosocial impact acted as a significant partial mediator between autonomy and work engagement. This study provides evidence for the importance of perceived prosocial impact and the role of immediate supervisors in facilitating work engagement in midwifery. Results highlight the value of relational resources and suggest their explicit inclusion in current models of work engagement
From social context and resilience to performance through job satisfaction: A multilevel study over time
Giving the crucial role of organizational context in shaping individual attitudes and behaviors at work, in this research we studied the effects of collective work-unit Perceptions of Social Context (PoSC) on individual work resilience and two key individual outcomes: job satisfaction and job performance as rated by the supervisor. We theorized that collective PoSC act as antecedents of individual variables, and that individual job satisfaction mediates the relationship between collective PoSC and job performance, and between work resilience and job performance over time. A sample of 305 white-collar employees, clustered in 67 work-units, participated in the study. Hierarchical linear modeling highlighted that collective PoSC are significant related to individual work resilience. Moreover, results showed that individual job satisfaction fully mediates the relationship between collective PoSC and individual job performance and the relationship between individual work resilience and individual job performance. At a practical level, results suggest that interventions on collective PoSC may increase work resilience, job satisfaction and job performance over time at the individual level
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Validation of a social cohesion theoretical framework: a multiple group SEM strategy
Social cohesion dates back to the end of the nineteenth century. Back then, society experienced epochal transformations, as are also happening nowadays. Whenever there are epochal changes, a social order (cohesion) matter arises. The paper provides a conceptual scheme of social cohesion identifying its constituent dimensions subdivided by three spheres (macro, meso, micro) and two perspectives (objective and subjective). The overarching aim is to test the validity of the operationalization of the social cohesion model provided. Firstly, we conducted an exploratory factor analysis introducing an approach implemented in Mplus named exploratory structural equation modeling that shows several useful characteristics. Afterward, through a structural equation modeling approach, we performed several confirmatory factor analyses adopting a multiple group SEM strategy in order to cross-validate the social cohesion model
Structural equation model testing and the quality of natural killer cell activity measurements
BACKGROUND: Browne et al. [Browne, MacCallum, Kim, Andersen, Glaser: When fit indices and residuals are incompatible. Psychol Methods 2002] employed a structural equation model of measurements of target cell lysing by natural killer cells as an example purportedly demonstrating that small but statistically significant ill model fit can be dismissed as "negligible from a practical point of view". METHODS: Reanalysis of the natural killer cell data reveals that the supposedly negligible ill fit obscured important, systematic, and substantial causal misspecifications. RESULTS: A clean-fitting structural equation model indicates that measurements employing higher natural-killer-cell to target-cell ratios are more strongly influenced by a progressively intrusive factor, whether or not the natural killer cell activity is activated by recombinant interferon γ (rIFN γ). The progressive influence may reflect independent rate limiting steps in cell recognition and attachment, spatial competition for cell attachment points, or the simultaneous lysings of single target cells by multiple natural killer cells. CONCLUSIONS: If the progressively influential factor is ultimately identified as a mere procedural impediment, the substantive conclusion will be that measurements of natural killer cell activity made at lower effector to target ratios are more valid. Alternatively, if the individual variations in the progressively influential factor are modifiable, this may presage a new therapeutic route to enhancing natural killer cell activity. The methodological conclusion is that, when using structural equation models, researchers should attend to significant model ill fit even if the degree of covariance ill fit is small, because small covariance residuals do not imply that the underlying model misspecifications are correspondingly small or inconsequential
Bias and heteroscedastic memory error in self-reported health behavior: an investigation using covariance structure analysis
BACKGROUND: Frequent use of self-reports for investigating recent and past behavior in medical research requires statistical techniques capable of analyzing complex sources of bias associated with this methodology. In particular, although decreasing accuracy of recalling more distant past events is commonplace, the bias due to differential in memory errors resulting from it has rarely been modeled statistically. METHODS: Covariance structure analysis was used to estimate the recall error of self-reported number of sexual partners for past periods of varying duration and its implication for the bias. RESULTS: Results indicated increasing levels of inaccuracy for reports about more distant past. Considerable positive bias was found for a small fraction of respondents who reported ten or more partners in the last year, last two years and last five years. This is consistent with the effect of heteroscedastic random error where the majority of partners had been acquired in the more distant past and therefore were recalled less accurately than the partners acquired more recently to the time of interviewing. CONCLUSIONS: Memory errors of this type depend on the salience of the events recalled and are likely to be present in many areas of health research based on self-reported behavior
Does the impact of osteoarthritis vary by age, gender and social deprivation? A community study using the International Classification of Functioning, Disability and Health
The aim of the study was to explore if the impact of osteoarthritis varies with respect to age, gender and social deprivation. Impact was defined as impairment, activity limitations and participation restriction (International Classification of Functioning, Disability and Health (ICF)). Investigating the functioning of the ICF model for subgroups is important both practically and theoretically. The sample comprised a community sample of 763 people diagnosed with osteoarthritis. Uncontaminated measures of the ICF constructs were developed using discriminant content validity from a pool of 134 items, including the WOMAC and SF-36. Multigroup Structural Equation Modelling was used to explore if the same pathways exist for subgroups of gender, age and social deprivation. Results: Different significant paths were found for gender and social deprivation: impairment did not predict participation restriction for women and those most deprived, whereas these paths were significant for men and those less deprived. No difference in the paths was found for age. The impact of osteoarthritis appears to vary with respect to gender and social deprivation but not age. This suggests both that osteoarthritis per se does not adequately explain the health outcomes observed and that different clinical approaches may be appropriate for people of different gender and levels of deprivation. Implications of Rehabilitation • The ICF model appears to vary with respect to gender and social deprivation for people with osteoarthritis. • The ICF model did not appear to vary with respect to age for people with osteoarthritis. • Different treatments and interventions for osteoarthritis may need to be targeted for specific gender and social deprivation groups
Investigating the interaction between the parking choice and holiday travel behavior
Parking is one of the key links between the urban planning and transportation operation. However, most studies in this field focus on the parking behavior on workdays, and the holiday parking is seldom investigated. This study analyzes the interaction between the parking choice and travel behavior in the holidays. Data were collected at Fragrant Hills and Beijing Botanical Garden during the Qingming Festival (Tomb-sweeping Days) in 2013. The structural equation modelling was applied to examine the causal effects and quantitative relationships between the parking choice and holiday travel behavior and identify the main influencing factors based on the activity analysis. The results show that the parking choice has a close relationship with holiday travel behavior, which is more than an explanatory variable for the travel behavior. Moreover, the parking space availability, parking charge, and walking distance have significant effects on holiday parking choice. In addition, the personal attributes and household characteristics are significant influencing factors for the parking choice and holiday travel behavior
Measuring measurement
Measurement connects the world of quantum phenomena to the world of classical
events. It plays both a passive role, observing quantum systems, and an active
one, preparing quantum states and controlling them. Surprisingly - in the light
of the central status of measurement in quantum mechanics - there is no general
recipe for designing a detector that measures a given observable. Compounding
this, the characterization of existing detectors is typically based on partial
calibrations or elaborate models. Thus, experimental specification (i.e.
tomography) of a detector is of fundamental and practical importance. Here, we
present the realization of quantum detector tomography: we identify the optimal
positive-operator-valued measure describing the detector, with no ancillary
assumptions. This result completes the triad, state, process, and detector
tomography, required to fully specify an experiment. We characterize an
avalanche photodiode and a photon number resolving detector capable of
detecting up to eight photons. This creates a new set of tools for accurately
detecting and preparing non-classical light.Comment: 6 pages, 4 figures,see video abstract at
http://www.quantiki.org/video_abstracts/0807244
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