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Tri-Partite Diffusion of Disease, In...
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Banks, Patricia E.
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Tri-Partite Diffusion of Disease, Information and Behavior in Type II Diabetes.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Tri-Partite Diffusion of Disease, Information and Behavior in Type II Diabetes./
作者:
Banks, Patricia E.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:
129 p.
附註:
Source: Dissertations Abstracts International, Volume: 80-12, Section: B.
Contained By:
Dissertations Abstracts International80-12B.
標題:
Endocrinology. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13812706
ISBN:
9781392233191
Tri-Partite Diffusion of Disease, Information and Behavior in Type II Diabetes.
Banks, Patricia E.
Tri-Partite Diffusion of Disease, Information and Behavior in Type II Diabetes.
- Ann Arbor : ProQuest Dissertations & Theses, 2019 - 129 p.
Source: Dissertations Abstracts International, Volume: 80-12, Section: B.
Thesis (Ph.D.)--North Carolina Agricultural and Technical State University, 2019.
This item must not be sold to any third party vendors.
Type 2 diabetes mellitus (T2DM) affects over 7.2% of the U.S. population and costs associated with the disease exceed $245 billion (CDC, 2017). In the past decade, T2DM research has generated over one million articles, yet the dissemination and translation of this large body of research remain a public health challenge. An impediment to disseminating and translating T2DM research is that all persons receiving information do not have the same capability to understand the information received. Understanding and processing of health information can be improved by tailoring and targeting the amount and level of health information. However, existing epidemiological intervention research lacks metrics to guide distribution of appropriate amounts and levels of health information. Further, existing interventions rarely consider interaction of factors, such as socioeconomic status, age and education level, in combination with health communication or behavioral response to health information. To address the need in epidemiological intervention research and public health communication, the objective of this research is to examine communication strategies of tailored and targeted messaging in terms of health outcomes and equity. In this research, an agent-based simulation model that depicts the processes of T2DM progress, information distribution and processing and behavior change was developed and validated, and then used to examine the effects of communication strategies with age, education level and income. The simulation results reveal that communication strategy of tailored messaging and random messaging are more effective in increasing adoption of health communication messages and life expectancy (L.E.). In addition, income statistically significantly affects adoption of health behavior. This research introduced a novel tri-diffusion agent-based simulation model integrating disease progression, information processing and behavior change in the context of a non-communicable disease, i.e., T2DM. Additionally, the Gini correlation coefficient has been applied to assess the equity in terms of an intangible asset, i.e., health information. The evaluation results of health communication have met the need in epidemiological intervention research and public health communication. Further, understanding the impact of the interactions of key factors on health information communication and, indirectly, disease propagation, can provide insights to existing epidemiological trials and future research studies.
ISBN: 9781392233191Subjects--Topical Terms:
610914
Endocrinology.
Tri-Partite Diffusion of Disease, Information and Behavior in Type II Diabetes.
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Type 2 diabetes mellitus (T2DM) affects over 7.2% of the U.S. population and costs associated with the disease exceed $245 billion (CDC, 2017). In the past decade, T2DM research has generated over one million articles, yet the dissemination and translation of this large body of research remain a public health challenge. An impediment to disseminating and translating T2DM research is that all persons receiving information do not have the same capability to understand the information received. Understanding and processing of health information can be improved by tailoring and targeting the amount and level of health information. However, existing epidemiological intervention research lacks metrics to guide distribution of appropriate amounts and levels of health information. Further, existing interventions rarely consider interaction of factors, such as socioeconomic status, age and education level, in combination with health communication or behavioral response to health information. To address the need in epidemiological intervention research and public health communication, the objective of this research is to examine communication strategies of tailored and targeted messaging in terms of health outcomes and equity. In this research, an agent-based simulation model that depicts the processes of T2DM progress, information distribution and processing and behavior change was developed and validated, and then used to examine the effects of communication strategies with age, education level and income. The simulation results reveal that communication strategy of tailored messaging and random messaging are more effective in increasing adoption of health communication messages and life expectancy (L.E.). In addition, income statistically significantly affects adoption of health behavior. This research introduced a novel tri-diffusion agent-based simulation model integrating disease progression, information processing and behavior change in the context of a non-communicable disease, i.e., T2DM. Additionally, the Gini correlation coefficient has been applied to assess the equity in terms of an intangible asset, i.e., health information. The evaluation results of health communication have met the need in epidemiological intervention research and public health communication. Further, understanding the impact of the interactions of key factors on health information communication and, indirectly, disease propagation, can provide insights to existing epidemiological trials and future research studies.
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