Deinstitutionalization has resulted in a large and growing population of individuals with mental retardation (MR) living in community-based systems. Persons with MR comprise an extremely vulnerable population who must rely on the judgments of others for access to health care and assistance with daily living. Consequently, residential agency directors are routinely required to make health care service decisions on behalf of their clients. In a pilot study, proxy decision making was found to affect the provision of appropriate health care services for individuals with MR and, in some situations, resulted in a delay or even denial of health care. Discrepancies were particularly evident when health care providers suggested a lesser quality of health care for individuals with MR, based upon their perceptions of a lesser quality of life. Few studies have addressed proxy decision making, and there is little knowledge to guide decisions, particularly for a stigmatized population such as individuals with MR. The goals of the proposed study are to: 1) elucidate the components of proxy decision making for individuals with MR and assess the extent the individual with MR is included in the decision-making process; 2) test and validate the application of health care decision case scenarios with provider agencies for individuals with MR across the Commonwealth of Pennsylvania; and 3) model proxy health care decision making for individuals with MR using conjoint analysis. The proposed study offers an innovative method for analyzing proxy decision making, i.e., conjoint analysis, to describe how study participants are currently making decisions. With knowledge of how health care decisions are made for those with MR, the health care community will be better able to interact with the complex array of service agencies that determine care for those with MR. Findings from this study will provide a framework to guide the education of health care professionals, and heighten sensitivity to the needs of those with MR. Improved communication will lead to better quality decision making and improved care for this fragile population. [unreadable] [unreadable] [unreadable]