Abstract

Empirical ethics inquiry works from the notion that stakeholder perspectives are necessary for gauging the ethical acceptability of human studies and assuring that research aligns with societal expectations. Although common, studies involving different populations often entail comparisons of trends that problematize the interpretation of results. Using graphical model selection - a technique aimed at transcending limitations of conventional methods - this report presents data on the ethics of clinical research with two objectives: (1) to display the patterns of views held by ill and healthy individuals in clinical research as a test of the study's original hypothesis and (2) to introduce graphical model selection as a key analytic tool for ethics research.In this IRB-approved, NIH-funded project, data were collected from 60 mentally ill and 43 physically ill clinical research protocol volunteers, 47 healthy protocol-consented participants, and 29 healthy individuals without research protocol experience. Respondents were queried on the ethical acceptability of research involving people with mental and physical illness (i.e., cancer, HIV, depression, schizophrenia, and post-traumatic stress disorder) and non-illness related sources of vulnerability (e.g., age, class, gender, ethnicity). Using a statistical algorithm, we selected graphical models to display interrelationships among responses to questions.Both mentally and physically ill protocol volunteers revealed a high degree of connectivity among ethically-salient perspectives. Healthy participants, irrespective of research protocol experience, revealed patterns of views that were not highly connected.Between ill and healthy protocol participants, the pattern of views is vastly different. Experience with illness was tied to dense connectivity, whereas healthy individuals expressed views with sparse connections. In offering a nuanced perspective on the interrelation of ethically relevant responses, graphical model selection has the potential to bring new insights to the field of ethics.

View details for PubMedID 25961066

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