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Development of an obesity management ontology based on the nursing process for the mobile-device domain.

Kim HY, Park HA, Min YH, Jeon E - J. Med. Internet Res. (2013)

Bottom Line: The relationship linking concepts were "part of", "instance of", "derives of", "derives into", "has plan", "followed by", and "has intention".The concepts and relationships were formally represented using Protégé.We have developed an ontology for representing obesity management with the nursing process as a foundation of ontology.

View Article: PubMed Central - HTML - PubMed

Affiliation: College of Nursing, Eulji University, Daejeon, Republic of Korea.

ABSTRACT

Background: Lifestyle modification is the most important factor in the management of obesity. It is therefore essential to enhance client participation in voluntary and continuous weight control.

Objective: The aim of this study was to develop an obesity management ontology for application in the mobile-device domain. We considered the concepts of client participation in behavioral modification for obesity management and focused on minimizing the amount of information exchange between the application and the database when providing tailored interventions.

Methods: An obesity management ontology was developed in seven phases: (1) defining the scope of obesity management, (2) selecting a foundational ontology, (3) extracting the concepts, (4) assigning relationships between these concepts, (5) evaluating representative layers of ontology content, (6) representing the ontology formally with Protégé, and (7) developing a prototype application for obesity management.

Results: Behavioral interventions, dietary advice, and physical activity were proposed as obesity management strategies. The nursing process was selected as a foundation of ontology, representing the obesity management process. We extracted 127 concepts, which included assessment data (eg, sex, body mass index, and waist circumference), inferred data to represent nursing diagnoses and evaluations (eg, degree of and reason for obesity, and success or failure of lifestyle modifications), and implementation (eg, education and advice). The relationship linking concepts were "part of", "instance of", "derives of", "derives into", "has plan", "followed by", and "has intention". The concepts and relationships were formally represented using Protégé. The evaluation score of the obesity management ontology was 4.5 out of 5. An Android-based obesity management application comprising both agent and client parts was developed.

Conclusions: We have developed an ontology for representing obesity management with the nursing process as a foundation of ontology.

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Related in: MedlinePlus

The Health Avatar Project model.
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figure1: The Health Avatar Project model.

Mentions: The prototype application consisted of two parts: an agent avatar and a client avatar as described in the Figure 1. The agent avatar as a knowledge base was developed using an XML schema made from the obesity management ontology including 37 classes and 90 individuals in Protégé. The XML schema was translated into database schema with 11 tables for assessment, diagnosis, and outcome identification. In addition, classes such as diagnosis, implementation, and evaluation in XML were converted into Java classes with methods to call recommendations according to data entered, which were linked to database. The client avatar as a user interface consisted of 41 screens to collect client’s health data and deliver recommendations provided from the agent avatar. With JDK (Java development kit) 1.7.0, Eclipse having ADT (Android Development Tool) Plugin for Eclipse, and the Android SDK platform 4.0.3, the client avatar and the agent avatar were integrated. Figure 5 is a screen shot providing one of tailored recommendations.


Development of an obesity management ontology based on the nursing process for the mobile-device domain.

Kim HY, Park HA, Min YH, Jeon E - J. Med. Internet Res. (2013)

The Health Avatar Project model.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC3713932&req=5

figure1: The Health Avatar Project model.
Mentions: The prototype application consisted of two parts: an agent avatar and a client avatar as described in the Figure 1. The agent avatar as a knowledge base was developed using an XML schema made from the obesity management ontology including 37 classes and 90 individuals in Protégé. The XML schema was translated into database schema with 11 tables for assessment, diagnosis, and outcome identification. In addition, classes such as diagnosis, implementation, and evaluation in XML were converted into Java classes with methods to call recommendations according to data entered, which were linked to database. The client avatar as a user interface consisted of 41 screens to collect client’s health data and deliver recommendations provided from the agent avatar. With JDK (Java development kit) 1.7.0, Eclipse having ADT (Android Development Tool) Plugin for Eclipse, and the Android SDK platform 4.0.3, the client avatar and the agent avatar were integrated. Figure 5 is a screen shot providing one of tailored recommendations.

Bottom Line: The relationship linking concepts were "part of", "instance of", "derives of", "derives into", "has plan", "followed by", and "has intention".The concepts and relationships were formally represented using Protégé.We have developed an ontology for representing obesity management with the nursing process as a foundation of ontology.

View Article: PubMed Central - HTML - PubMed

Affiliation: College of Nursing, Eulji University, Daejeon, Republic of Korea.

ABSTRACT

Background: Lifestyle modification is the most important factor in the management of obesity. It is therefore essential to enhance client participation in voluntary and continuous weight control.

Objective: The aim of this study was to develop an obesity management ontology for application in the mobile-device domain. We considered the concepts of client participation in behavioral modification for obesity management and focused on minimizing the amount of information exchange between the application and the database when providing tailored interventions.

Methods: An obesity management ontology was developed in seven phases: (1) defining the scope of obesity management, (2) selecting a foundational ontology, (3) extracting the concepts, (4) assigning relationships between these concepts, (5) evaluating representative layers of ontology content, (6) representing the ontology formally with Protégé, and (7) developing a prototype application for obesity management.

Results: Behavioral interventions, dietary advice, and physical activity were proposed as obesity management strategies. The nursing process was selected as a foundation of ontology, representing the obesity management process. We extracted 127 concepts, which included assessment data (eg, sex, body mass index, and waist circumference), inferred data to represent nursing diagnoses and evaluations (eg, degree of and reason for obesity, and success or failure of lifestyle modifications), and implementation (eg, education and advice). The relationship linking concepts were "part of", "instance of", "derives of", "derives into", "has plan", "followed by", and "has intention". The concepts and relationships were formally represented using Protégé. The evaluation score of the obesity management ontology was 4.5 out of 5. An Android-based obesity management application comprising both agent and client parts was developed.

Conclusions: We have developed an ontology for representing obesity management with the nursing process as a foundation of ontology.

Show MeSH
Related in: MedlinePlus