This article revisits and further investigates the extent to which scope insensitivity in helping contexts can be reduced by the unit asking (UA) method. UA is an intervention that first asks people to help one unit and then asks for willingness to help multiple units. In 3 studies (N = 3,442), participants took on the role of policymakers to allocate help (motivation to help and willingness to pay) to local aid projects. They underwent either UA or a control condition (in which they stated their willingness to help only to the multiple units). Against expectations, the first 2 studies found a reversed UA effect for helping motivation, such that help decreased when participants were in the UA condition. However, the third study found a UA effect for helping motivation when participants made the sequential assessments within one project (when the individual unit belonged to the multiple units-group), rather than between projects (when the individual unit belonged to another group). Thus, our results suggest that the 2 assessments critical for the UA method should be done within the same project rather than between 2 projects to successfully reduce scope insensitivity. Further, the age of the unit (child or adult), the number of the unit(s), the composition of the group (homogeneous or heterogeneous), and the size of the group did not substantially reduce scope insensitivity with UA.

Fifty to eighty-five percent of schizophrenic patients are impaired on ocular pursuit paradigms. However, results regarding the relatives are more discordant. The aim of this study was to investigate whether eye movement disorders could be a vulnerability marker of schizophrenia.

This paper introduces a new framework for modelling the joint development over time of mortality rates in a pair of related populations with the primary aim of producing consistent mortality forecasts for the two populations. The primary aim is achieved by combining a number of recent and novel developments in stochastic mortality modelling, but these, additionally, provide us with a number of side benefits and insights for stochastic mortality modelling. By way of example, we propose an Age-Period-Cohort model which incorporates a mean-reverting stochastic spread that allows for different trends in mortality improvement rates in the short-run, but parallel improvements in the long run. Second, we fit the model using a Bayesian framework that allows us to combine estimation of the unobservable state variables and the parameters of the stochastic processes driving them into a single procedure. Key benefits of this include dampening down of the impact of Poisson variation in death counts, full allowance for paramater uncertainty, and the flexibility to deal with missing data. The framework is designed for large populations coupled with a small sub-population and is applied to the England & Wales national and Continuous Mortality Investigation assured lives males populations. We compare and contrast results based on the two-population approach with single-population results.