DIAGNOSTIC SELF‐TESTING: AUTONOMOUS CHOICES AND RELATIONAL RESPONSIBILITIES

Diagnostic self‐testing devices are being developed for many illnesses, chronic diseases and infections. These will be used in hospitals, at point‐of‐care facilities and at home. Designed to allow earlier detection of diseases, self‐testing diagnostic devices may improve disease prevention, slow the progression of disease and facilitate better treatment outcomes. These devices have the potential to benefit both the individual and society by enabling individuals to take a more proactive role in the maintenance of their health and by helping society improve health and reduce health costs. However, the full implications of future home‐based diagnostic technology for individuals and society remain unclear due to their novelty. We argue that the development of diagnostic tools, especially for home use, will heighten a number of ethical challenges. This paper will explore some of the ethical implications of home‐based self‐testing diagnostic devices for the autonomous and relational dimensions of the person. This will be facilitated by examining the impact of diagnostic devices for individual autonomy, for the delivery of accurate diagnosis and for the personal significance of the information for the user. The latter will be examined using Charles Taylor's view of personhood and his emphasis on human agency and interpretation. While the ethical issues are not necessarily new, the development of home‐based self‐testing diagnostic devices will make issues regarding autonomy, accuracy of information and personal significance more and more demanding. This will be the case particularly when an individual's autonomous choices come into conflict with the person's relational responsibilities.     

Conditional Quadratic Discrimination in the Identification of Biological Markers for Disease Screening

Conditional multivariate normal density functions are used to construct conditional quadratic discriminant functions that adjust for covariate differences between disease groups. An expected actual error rate for the conditional discriminant function is defined. The purpose of this paper is to use the conditional quadratic discriminant function and its misolassification error rate in order to help determine if a set of discriminators is a good biological marker for disease screening. The conditional quadratic discriminant analysis is illustrated using data from two alcoholism classification problems. It is shown how the discriminant functions can identify a set of variables that can be used as biological markers.