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Health behavior change in advance care planning: An agent-based model

Ernecoff, Natalie C. (2015) Health behavior change in advance care planning: An agent-based model. Master's Thesis, University of Pittsburgh. (Unpublished)

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Significance: A practical and ethical challenge in advance care planning research is controlling and intervening on human behavior. Additionally, observing dynamic changes in advance care planning (ACP) behavior proves difficult, though tracking changes over time is important for intervention development. Agent-based modeling (ABM) allows researchers to integrate complex behavioral data about advance care planning behaviors and thought processes into a controlled environment that is more easily alterable and observable. Literature to date has not addressed how best to motivate individuals, increase facilitators and reduce barriers associated with ACP. We aimed to build an ABM that accurately reflects: 1) the rates at which individuals complete the ACP process, 2) how individuals respond to barriers, facilitators, and behavioral variables 3) the interactions between these variables, 4) suggests -future -public health interventions and validation studies.
Methods: We developed an ABM of the ACP -decision making process. We integrated into this dynamic model the barriers, facilitators, and other behavioral variables - that -agents encounter as they move- through the Transtheoretical Model’s stages of change.
Findings: We successfully incorporated ACP barriers, facilitators, and other behavioral variables into our ABM, forming a plausible representation of ACP behavior and decision-making. In addition, the resulting distributions across the stages of change replicated those found in the literature, with approximately half of participants in the action-maintenance stage in both the model and the literature.
Public Health Implications: Our ABM is the first of its kind to outline potential intervention points for behavior change in the context of ACP. The ABM approach to ACP is a useful method for representing dynamic social and experiential influences on the decision making process. This model could be used in the future to test structural interventions (e.g. increasing access to ACP materials in primary care clinics) theoretically before implementation. Future studies can expand on this by gathering longitudinal, individual-level data and integrating it into the ABM for a more comprehensive representation of decision-making patterns with respect to ACP.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Ernecoff, Natalie C.nce4@pitt.eduNCE4
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairKeane, Christophercrkcity@pitt.eduCRKCITY
Committee MemberAlbert, Stevensmalbert@pitt.eduSMALBERT
Committee MemberWhite, Douglaswhitedb@upmc.eduDBW13
Date: 28 January 2015
Date Type: Publication
Defense Date: 6 October 2014
Approval Date: 28 January 2015
Submission Date: 24 November 2014
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 52
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Behavioral and Community Health Sciences
Degree: MPH - Master of Public Health
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: advance directive, living will, computer model, behavioral model
Date Deposited: 28 Jan 2015 14:58
Last Modified: 19 Dec 2016 14:42


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