2016
Wasif Hasan Baig; Samina Abidi; Syed Sibte Raza Abidi
An Ontological Model of Behaviour Theory to Generate Personalized Action Plans to Modify Behaviours Proceedings Article
In: Exploring Complexity in Health: An Interdisciplinary Systems Approach. 26th European Medical Informatics Conference (MIE2016), Munich, pp. 399-403, IOS Press, 2016.
Abstract | Links | BibTeX | Tags: Action Plans, Behaviour Modelling, Information Personalization, Ontology
@inproceedings{Baig2016b,
title = {An Ontological Model of Behaviour Theory to Generate Personalized Action Plans to Modify Behaviours},
author = {Wasif Hasan Baig and Samina Abidi and Syed Sibte Raza Abidi},
doi = {10.3233/978-1-61499-678-1-399},
year = {2016},
date = {2016-08-15},
booktitle = {Exploring Complexity in Health: An Interdisciplinary Systems Approach. 26th European Medical Informatics Conference (MIE2016), Munich},
volume = {228},
pages = {399-403},
publisher = {IOS Press},
series = {Studies in Health Technology and Informatics},
abstract = {Behavior change approaches aim to assist patients in achieving self-efficacy in managing their condition. Social cognitive theory (SCT) stipulates self-efficacy as a central element to behavior change and provides constructs to achieve self-efficacy guided by person-specific action plans. In our work, to administer behaviour change in patient with chronic conditions, our approach entails the computerization of SCT-based self-efficacy constructs in order to generate personalized action plans that are suitable to an individual's current care scenario. We have taken a knowledge management approach, whereby we have computerized the SCT-based self-efficacy constructs in terms of a high-level SCT knowledge model that can be operationalized to generate personalized behaviour change action plans. We have collected and computerized behavior change content targeting healthy living and physical activity. Semantic web technologies have been used to develop the SCT knowledge model, represented in terms of an ontology and SWRL rules. The ontological SCT model can inferred to generate personalized self-management action plans for a given patient profile. We present formative evaluation of the clinical correctness and relevance of the generated personalized action plans for a range of test patient profiles},
keywords = {Action Plans, Behaviour Modelling, Information Personalization, Ontology},
pubstate = {published},
tppubtype = {inproceedings}
}
Behavior change approaches aim to assist patients in achieving self-efficacy in managing their condition. Social cognitive theory (SCT) stipulates self-efficacy as a central element to behavior change and provides constructs to achieve self-efficacy guided by person-specific action plans. In our work, to administer behaviour change in patient with chronic conditions, our approach entails the computerization of SCT-based self-efficacy constructs in order to generate personalized action plans that are suitable to an individual's current care scenario. We have taken a knowledge management approach, whereby we have computerized the SCT-based self-efficacy constructs in terms of a high-level SCT knowledge model that can be operationalized to generate personalized behaviour change action plans. We have collected and computerized behavior change content targeting healthy living and physical activity. Semantic web technologies have been used to develop the SCT knowledge model, represented in terms of an ontology and SWRL rules. The ontological SCT model can inferred to generate personalized self-management action plans for a given patient profile. We present formative evaluation of the clinical correctness and relevance of the generated personalized action plans for a range of test patient profiles