Test of the demands, supports-constraints framework in predicting psychological distress amongst Australian public sector employees

This paper describes the demands, supports-constraints framework originally articulated by Payne (1979) for predicting psychological distress, and reports the results of an empirical study involving 2452 white-collar, public sector employees in Australia. The study uses hierarchical regression to test for the interaction effects of the demands and constraints variables, having applied suitable controls for instance by including trait anxiety and removing curvilinear effects. The results reveal little evidence of an interactive effect but moderately strong main effects and modest support for the value of controlling for curvilinear effects. Trait anxiety is shown to have a strong effect on psychological distress and considerably reduces the size of the relationship between demands, supports-constraints and psychological distress when statistically controlled for. However, it still accounts for 18.7% of the variance when entered last in the regression and it is recommended that its effects be explored in all studies of stress that rely on self-report data.     

Exploring the dynamics of racial food security gaps in the United States

Review of Economics of the Household - Household-level food insecurity is one of the largest public health concerns facing millions of people in the United States today. Although recent work has...     

Recursive expected utility and the separation of attitudes towards risk and ambiguity: an experimental study

We use the multiple price list method and a recursive expected utility theory of smooth ambiguity to separate out attitude towards risk from that towards ambiguity. Based on this separation, we investigate if there are differences in agent behaviour under uncertainty over gain amounts vis-a-vis uncertainty over loss amounts. On an aggregate level, we find that (i) subjects are risk averse over gains and risk seeking over losses, displaying a “reflection effect” and (ii) they are ambiguity neutral over gains and are mildly ambiguity seeking over losses. Further analysis shows that on an individual level, and with respect to both risky and ambiguous prospects, there is limited incidence of a reflection effect where subjects are risk/ambiguity averse (seeking) in gains and seeking (averse) in losses, though this incidence is higher for ambiguous prospects. A very high proportion of such cases of reflection exhibit risk (ambiguity) aversion in gains and risk (ambiguity) seeking in losses, with the reverse effect being significantly present in the case of risk but almost absent in case of ambiguity. Our results suggest that reflection across gains and losses is not a stable individual characteristic, but depends upon whether the form of uncertainty is precise or ambiguous, since we rarely find an individual who exhibits reflection in both risky and ambiguous prospects. We also find that correlations between attitudes towards risk and ambiguity were domain dependent.      

Estimation and Classification of BOLD Responses Over Multiple Trials

In this article, we model functional magnetic resonance imaging (fMRI) data for event-related experiment data using a fourth degree spline to fit voxel specific blood oxygenation level-dependent (BOLD) responses. The data are preprocessed for removing long term temporal components such as drifts using wavelet approximations. The spatial dependence is incorporated in the data by the application of 3D Gaussian spatial filter. The methodology assigns an activation score to each trial based on the voxel specific characteristics of the response curve. The proposed procedure has a capability of being fully automated and it produces activation images based on overall scores assigned to each voxel. The methodology is illustrated on real data from an event-related design experiment of visually guided saccades (VGS).     

Socioeconomic determinants of the intra-family status of wives in rural India: Analysis and empirical evidence

Relying on a structured survey of 117 wives in four rural villages in the Midnapore District of West Bengal, this article investigates the influence on the intra-family status of wives of variables that may increase the bargaining power of wives in their family. Saveral indicators of status are considered and investigated using the ANOVA technique and probit analysis. The main hypothesis considered is whether the results support bargaining theories of the intra-household status of wives or the view that gender status is primarily determined in Indian society by social customs and the patriarchal structure of society. Given the overall patriarchal structure of Indian society, the results indicate that bargaining theories are at best only marginally relevant. Situations that result in greater bargaining power for wives in Western societies do not necessarily do so in north India given the total pervasiveness of its patriarchal society. Research for this paper benefited from a grant by the Australian Research Committee     

The importance of knowing the affective meaning of job demands revisited

This paper starts with the assumption that when people are asked to describe the level of demands they face at work, it cannot be assumed that those demands are necessarily stressful, even if they are rated as strong or high demands. Thirty demand questions were designed for use with a sample of 2,253 public sector employees in Western Australia. As well as rating frequency of demand the respondents were asked to rate their level of dissatisfaction with the demand. For only 16 of the demands was there a correlation high enough to assume that the demand might be a stressor. Having demonstrated this, the rest of the paper compares different ways of combining the two scores to predict the level of psychological distress as measured by the General Health Questionnaire (GHQ12). The results support the claim in the title, that it is important to know the affective meaning of job demands.     

The plan of enrichment designs for dealing with high placebo response

To deal with high placebo response in clinical trials for psychiatric and other diseases, different enrichment designs, such as the sequential parallel design, two‐way enriched design, and sequential enriched design, have been proposed and implemented recently. Depending on the historical trial information and the trial sponsors' resources, detailed design elements are needed for determining which design to adopt. To assist in making more suitable decisions, we perform evaluations for selecting required design elements in terms of power optimization and sample size planning. We also discuss the implementation of the interim analysis related to its applicability.     

Hypothesis testing, power and sample size determination for between group comparisons in fMRI experiments

Modern methods for imaging the human brain, such as functional magnetic resonance imaging (fMRI) present a range of challenging statistical problems. In this paper, we first develop a large sample based test for between group comparisons and use it to determine the necessary sample size in order to obtain a target power via simulation under various alternatives for a given pre-specified significance level. Both testing and sample size calculations are particularly critical for neuroscientists who use these new techniques, since each subject is expensive to image.     

The Lack of Memory Property in the Density Form for the Bivariate Setup

The lack of memory property is a characterizing property of the exponential distribution in the continuous domain. In the bivariate setup different generalizations of the same are available in terms of survival function. We extend this lack of memory property in terms of bivariate probability density function and examine its characterization properties. In this process the density version of the lack of memory property can be interlinked with conditionally specified exponential distribution, bivariate reciprocal coordinate subtangent of the density curve and a few other derived measures.     

The Effects of Misconceptions on the Properties of Friedman's Test

Friedman's test is a widely used rank-based alternative to the analysis of variance (ANOVA) F-test for identifying treatment differences in a randomized complete block design. Many texts provide incomplete or misleading information about when Friedman's test may be appropriately applied. We discuss the assumptions needed for the test and common misconceptions. We show via simulation that when the variance or skew of the treatment distributions differ, application of Friedman's test to detect differences in treatment location can result in Type I error probabilities larger than the nominal α, and even when α is unaffected, the power of the test can be less than expected.