Towards a decision support system for health promotion in nursing

Aims. This study was designed to investigate what type of models, techniques and data are necessary to support the development of a decision support system for health promotion practice in nursing. Specifically, the research explored how interview data can be interpreted in terms of Concept Networks...

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Veröffentlicht in:Journal of advanced nursing 2003-07, Vol.43 (2), p.170-180
Hauptverfasser: Caelli, Kate, Downie, Jill, Caelli, Terry
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container_title Journal of advanced nursing
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creator Caelli, Kate
Downie, Jill
Caelli, Terry
description Aims. This study was designed to investigate what type of models, techniques and data are necessary to support the development of a decision support system for health promotion practice in nursing. Specifically, the research explored how interview data can be interpreted in terms of Concept Networks and Bayesian Networks, both of which provide formal methods for describing the dependencies between factors or variables in the context of decision‐making in health promotion. Background. In nursing, the lack of generally accepted examples or guidelines by which to implement or evaluate health promotion practice is a challenge. Major gaps have been identified between health promotion rhetoric and practice and there is a need for health promotion to be presented in ways that make its attitudes and practices more easily understood. New tools, paradigms and techniques to encourage the practice of health promotion would appear to be beneficial. Concept Networks and Bayesian Networks are techniques that may assist the research team to understand and explicate health promotion more specifically and formally than has been the case, so that it may more readily be integrated into nursing practice. Methods. As the ultimate goal of the study was to investigate ways to use the techniques described above, it was necessary to first generate data as text. Textual descriptions of health promotion in nursing were derived from in‐depth qualitative interviews with nurses nominated by their peers as expert health promoting practitioners. Findings. The nurses in this study gave only general and somewhat vague outlines of the concepts and ideas that guided their practice. These data were compared with descriptions from various sources that describe health promotion practices in nursing, then examples of a Conceptual Network and a representative Bayesian Network were derived from the data. Conclusions. The study highlighted the difficulty in describing health promotion practice, even among nurses recognized for their expertise in health promotion. Nevertheless, it indicated the data collection and analysis methods necessary to explicate the cognitive processes of health promotion and highlighted the benefits of using formal conceptualization techniques to improve health promotion practice.
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This study was designed to investigate what type of models, techniques and data are necessary to support the development of a decision support system for health promotion practice in nursing. Specifically, the research explored how interview data can be interpreted in terms of Concept Networks and Bayesian Networks, both of which provide formal methods for describing the dependencies between factors or variables in the context of decision‐making in health promotion. Background. In nursing, the lack of generally accepted examples or guidelines by which to implement or evaluate health promotion practice is a challenge. Major gaps have been identified between health promotion rhetoric and practice and there is a need for health promotion to be presented in ways that make its attitudes and practices more easily understood. New tools, paradigms and techniques to encourage the practice of health promotion would appear to be beneficial. Concept Networks and Bayesian Networks are techniques that may assist the research team to understand and explicate health promotion more specifically and formally than has been the case, so that it may more readily be integrated into nursing practice. Methods. As the ultimate goal of the study was to investigate ways to use the techniques described above, it was necessary to first generate data as text. Textual descriptions of health promotion in nursing were derived from in‐depth qualitative interviews with nurses nominated by their peers as expert health promoting practitioners. Findings. The nurses in this study gave only general and somewhat vague outlines of the concepts and ideas that guided their practice. These data were compared with descriptions from various sources that describe health promotion practices in nursing, then examples of a Conceptual Network and a representative Bayesian Network were derived from the data. Conclusions. The study highlighted the difficulty in describing health promotion practice, even among nurses recognized for their expertise in health promotion. Nevertheless, it indicated the data collection and analysis methods necessary to explicate the cognitive processes of health promotion and highlighted the benefits of using formal conceptualization techniques to improve health promotion practice.</description><identifier>ISSN: 0309-2402</identifier><identifier>EISSN: 1365-2648</identifier><identifier>DOI: 10.1046/j.1365-2648.2003.02691.x</identifier><identifier>PMID: 12834375</identifier><language>eng</language><publisher>Oxford, UK: Blackwell Science Ltd</publisher><subject>Bayes Theorem ; Bayesian analysis ; Bayesian networks ; Clinical Nursing Research ; Concept analysis ; concept networks ; Decision Making ; Decision support systems ; Decision Support Systems, Clinical ; Development ; Female ; Health promotion ; Health Promotion - organization &amp; administration ; Humans ; Interviews as Topic ; Nurse Practitioners ; Nurses ; Nursing ; Nursing Care - methods ; Pilot Projects</subject><ispartof>Journal of advanced nursing, 2003-07, Vol.43 (2), p.170-180</ispartof><rights>Copyright Blackwell Science Ltd. 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This study was designed to investigate what type of models, techniques and data are necessary to support the development of a decision support system for health promotion practice in nursing. Specifically, the research explored how interview data can be interpreted in terms of Concept Networks and Bayesian Networks, both of which provide formal methods for describing the dependencies between factors or variables in the context of decision‐making in health promotion. Background. In nursing, the lack of generally accepted examples or guidelines by which to implement or evaluate health promotion practice is a challenge. Major gaps have been identified between health promotion rhetoric and practice and there is a need for health promotion to be presented in ways that make its attitudes and practices more easily understood. New tools, paradigms and techniques to encourage the practice of health promotion would appear to be beneficial. Concept Networks and Bayesian Networks are techniques that may assist the research team to understand and explicate health promotion more specifically and formally than has been the case, so that it may more readily be integrated into nursing practice. Methods. As the ultimate goal of the study was to investigate ways to use the techniques described above, it was necessary to first generate data as text. Textual descriptions of health promotion in nursing were derived from in‐depth qualitative interviews with nurses nominated by their peers as expert health promoting practitioners. Findings. The nurses in this study gave only general and somewhat vague outlines of the concepts and ideas that guided their practice. These data were compared with descriptions from various sources that describe health promotion practices in nursing, then examples of a Conceptual Network and a representative Bayesian Network were derived from the data. Conclusions. The study highlighted the difficulty in describing health promotion practice, even among nurses recognized for their expertise in health promotion. 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This study was designed to investigate what type of models, techniques and data are necessary to support the development of a decision support system for health promotion practice in nursing. Specifically, the research explored how interview data can be interpreted in terms of Concept Networks and Bayesian Networks, both of which provide formal methods for describing the dependencies between factors or variables in the context of decision‐making in health promotion. Background. In nursing, the lack of generally accepted examples or guidelines by which to implement or evaluate health promotion practice is a challenge. Major gaps have been identified between health promotion rhetoric and practice and there is a need for health promotion to be presented in ways that make its attitudes and practices more easily understood. New tools, paradigms and techniques to encourage the practice of health promotion would appear to be beneficial. Concept Networks and Bayesian Networks are techniques that may assist the research team to understand and explicate health promotion more specifically and formally than has been the case, so that it may more readily be integrated into nursing practice. Methods. As the ultimate goal of the study was to investigate ways to use the techniques described above, it was necessary to first generate data as text. Textual descriptions of health promotion in nursing were derived from in‐depth qualitative interviews with nurses nominated by their peers as expert health promoting practitioners. Findings. The nurses in this study gave only general and somewhat vague outlines of the concepts and ideas that guided their practice. These data were compared with descriptions from various sources that describe health promotion practices in nursing, then examples of a Conceptual Network and a representative Bayesian Network were derived from the data. Conclusions. The study highlighted the difficulty in describing health promotion practice, even among nurses recognized for their expertise in health promotion. Nevertheless, it indicated the data collection and analysis methods necessary to explicate the cognitive processes of health promotion and highlighted the benefits of using formal conceptualization techniques to improve health promotion practice.</abstract><cop>Oxford, UK</cop><pub>Blackwell Science Ltd</pub><pmid>12834375</pmid><doi>10.1046/j.1365-2648.2003.02691.x</doi><tpages>11</tpages></addata></record>
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subjects Bayes Theorem
Bayesian analysis
Bayesian networks
Clinical Nursing Research
Concept analysis
concept networks
Decision Making
Decision support systems
Decision Support Systems, Clinical
Development
Female
Health promotion
Health Promotion - organization & administration
Humans
Interviews as Topic
Nurse Practitioners
Nurses
Nursing
Nursing Care - methods
Pilot Projects
title Towards a decision support system for health promotion in nursing
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