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Biomedical subjects

J G Ozbolt

Publications and source records attributed to J G Ozbolt.

5 recordsLinked to original sources

Psychophysiological processes of stress in chronic physical illness: a theoretical perspective.

This paper proposes a theoretical framework and conceptual model for clinicians and investigators working with people who have a chronic physical illness. The framework is based upon nursing theory and classical propositions from psychology and physiology. The major premise of the model is that individuals with limited psychosocial attributes and a preponderance of unmet basic needs are more likely to perceive events as threatening and experience a maladaptive stress response, such as heightened symptoms and acute exacerbations of their illness. Conversely, those with strong attributes and a perception of need satisfaction are more likely to view events as challenging, thus avoiding symptomatic discomfort and enhancing personal growth. Implications for nursing practice and research are addressed.

Adaptation, Psychological

Designing information systems for nursing practice: data base and knowledge base requirements of different organizational technologies.

One of the major causes of failure of information system design is the failure of developers to take into account the organizational environment, thereby leading to an unusable system. The first step in designing an effective system is to describe the user's view of the system, a view that incorporates how the system will help users to manage information in their particular organizational environment. For nurses involved in designing a nursing information system, a useful way of considering the organizational environment is provided by Perrow. The organizational technologies described by Perrow can be viewed as different models of nursing practice, each with particular requirements for a knowledge base and a data base. Nurses can identify the model that most closely corresponds to actual or desired nursing practice in their agencies and use the model's associated knowledge base and data base requirements as a guide to specifying the information system to be developed.

Artificial Intelligence

A proposed expert system for nursing practice. A springboard to nursing science.

The knowledge on which nursing practice is based comes largely from traditional sources, expert nurses passing on the wisdom of their experience to novices. Nursing research, although increasing, is usually parallel to nursing practice, and its findings, at best, are implemented only after long delays. Consequently, the most effective nursing responses to a particular client problem may be undiscovered or unknown. Nursing information systems reflect the nature and usage of nursing knowledge. They offer standard care plans, but the knowledge and decision structures for individualizing care remain exclusively in the mind of the nurse. Nurses may have great freedom to enter information into the information system, but the information is rarely retrievable in a form suitable for evaluation or research. Nursing practice, and the knowledge on which it is based, could be enhanced through the use of a novel expert system. This paper describes how such a system could be developed, with examples from the authors' prototype programs. Taxonomies of data, diagnoses, objectives, and interventions would make it possible to compare patients and to determine the relative effectiveness of nursing interventions. A built-in evaluation component would provide feedback and correction. Everyday nursing practice would become a field for research, and the knowledge gained from research would immediately be fed back into practice. In its development and in its implementation, this kind of system would help to build nursing science.

Computers