Social Patterning of Screening Uptake and the Impact of Facilitating Informed Choices: Psychological and Ethical Analyses

Screening for unsuspected disease has both possible benefits and harms for those who participate. Historically the benefits of participation have been emphasized to maximize uptake reflecting a public health approach to policy; currently policy is moving towards an informed choice approach involving giving information about both benefits and harms of participation. However, no research has been conducted to evaluate the impact on health of an informed choice policy. Using psychological models, the first aim of this study was to describe an explanatory framework for variation in screening uptake and to apply this framework to assess the impact of informed choices in screening. The second aim was to evaluate ethically that impact. Data from a general population survey (n = 300) of beliefs and attitudes towards participation in diabetes screening indicated that greater orientation to the present is associated with greater social deprivation and lower expectation of participation in screening. The results inform an explanatory framework of social patterning of screening in which greater orientation to the present focuses attention on the disadvantages of screening, which tend to be immediate, thereby reducing participation. This framework suggests that an informed choice policy, by increasing the salience of possible harms of screening, might reduce uptake of screening more in those who are more deprived and orientated to the present. This possibility gives rise to an apparent dilemma where an ethical decision must be made between greater choice and avoiding health inequality. Philosophical perspectives on choice and inequality are used to point to some of the complexities in assessing whether there really is such a dilemma and if so how it should be resolved. The paper concludes with a discussion of the ethics of paternalism

Combining equity and utilitarianism in a mathematical programming model

We discuss the problem of combining the conflicting objectives of equity and utilitarianism, for social policy making, in a single mathematical programming model. The definition of equity we use is the Rawlsian one of maximizing the minimum utility over individuals or classes of individuals. However, when the disparity of utility becomes too great, the objective becomes progressively utilitarian. Such a model is particularly applicable not only to health provision but to other areas as well. Building a mixed-integer/linear programming (MILP) formulation of the problem raises technical issues, because the objective function is nonconvex and the hypograph is not MILP representable in its initial form. We present a succinct formulation and show that it is “sharp” in the sense that its linear programming relaxation describes the convex hull of the feasible set (before extra resource allocation or policy constraints are added). We apply the formulation to a healthcare planning problem and show that instances of realistic size are easily solved by standard MILP software

Trajectory stratification of stochastic dynamics

We present a general mathematical framework for trajectory stratification for simulating rare events. Trajectory stratification involves decomposing trajectories of the underlying process into fragments limited to restricted regions of state space (strata), computing averages over the distributions of the trajectory fragments within the strata with minimal communication between them, and combining those averages with appropriate weights to yield averages with respect to the original underlying process. Our framework reveals the full generality and flexibility of trajectory stratification, and it illuminates a common mathematical structure shared by existing algorithms for sampling rare events. We demonstrate the power of the framework by defining strata in terms of both points in time and path-dependent variables for efficiently estimating averages that were not previously tractable