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Abstract

Patient engagement in their care process, vis-à-vis self-management programs is an important element of the patient's longitudinal care plan, where the patient is encouraged and expected to achieve self-efficacy in the self-management of the disease through a regime of educational and behavioral modification strategies. To ensure the effectiveness of self-management programs, it is important that the proposed self-management interventions are (a) personalized to the unique needs and constraints of the patient; (b) based on sound theoretical health models; (c) based on validated health and behavior assessment tools to determine the patient's physical and behavioral dispositions; and (d) readily accessible to the patient through a ubiquitous medium, such as smart phones or the web. In this paper, we present a novel personalized self-management framework that delivers personalized health educational interventions to empower, educate and engage patients/individuals through self-observation, barrier identification, goal setting and action planning to achieve behavioral self-efficacy and self-regulation so that individuals can self-manage their condition. Our personalized self-management framework is guided by Social Cognition Theory, whereby have ensured that self-management programs for chronic disease management not just focus on changing the patient's awareness of the disease, rather they focus on enhancing the ability of the patient to make the right choices to achieve effective disease management. We present a three-stage personalized self-management framework that comprises: Stage 1: A high-level characterization of an individual with respect to a specific health outcome using validated assessment tools; Stage 2: A behavioral categorization of the individual based on his/her levels of self-efficacy, motivation and self-regulation, etc.; Stage 3: Use the personalized profile of the individual to tailor generic educational and self-management to develop a personalized self-management program that comprises personalized strategies to counter the challenges and barriers faced by the individual to achieving positive self-efficacy and self-regulation which in turn will lead to positive health outcomes. Our personalized self-management framework features (a) a novel self-management oriented individual profiling mechanism that takes into account both the health and psychosocial characteristics of an individual to generate his/her holistic profile; (b) a semantic web based knowledge model that captures the theoretical foundations of the SCT in terms of a Self-Management Program Personalization (SPP) ontology; (c) a semantic web based personalization tool that uses a logic-based execution engine that reasons over the SPP ontology, based on an individual's profile, to generate personalized self-management interventions; and (d) a mobile messaging platform to deliver the personalized self-management interventions and to monitor the patient's compliance using smart phones. We take a semantic web approach in designing the personalization approach whereby we have developed the SPP ontology to (a) model the theoretical framework of SCT in terms of SCT concepts; (b) model health assessment tools; (c) model the personalization rules that integrate the health and SCT models with the educational messages to generate a personalized self-management program. We have demonstrated the novel integration of health models, educational content and behavior change strategies to design self-management programs for cardiac risk factors, where the program is delivered through a mobile app.

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/content/papers/10.5339/qfarf.2013.BIOP-0128
2013-11-20
2019-10-17
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http://instance.metastore.ingenta.com/content/papers/10.5339/qfarf.2013.BIOP-0128
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