Trajectory Design and Analytic Methods for the Study of Human Response to Chronic Illness and Care Systems

2.50
Hdl Handle:
http://hdl.handle.net/10755/304403
Category:
Abstract
Type:
Presentation
Title:
Trajectory Design and Analytic Methods for the Study of Human Response to Chronic Illness and Care Systems
Author(s):
Docherty, Sharron; Brandon, Debra
Lead Author STTI Affiliation:
Beta Epsilon
Author Details:
Sharron Docherty, PhD, CPNP, doche002@mc.duke.edu; Debra Brandon, PhD, RN, FAAN;
Abstract:

Session presented on: Friday, July 26, 2013

Purpose: People with chronic illnesses and their families experience multiple symptoms and/or disabilities and their responses cross multiple measurement domains, from genetic, biologic, through psychosocial, behavioral, and environmental.  The Adaptive Leadership (AL) framework provides a compelling and effective conceptual lens through which to view the challenges that individuals face as it allows examination of phenomena that are multilevel, dynamic, unpredictable, and highly context dependent.  Research approaches that best address the vital questions in this field also require dynamic designs and analytic methods that allow us to identify patterns across levels of functioning and place a high value on the role and timing of dynamic interactions. The purpose of this paper is to present a range of trajectory design methods that can be used in synergy with the AL framework for the study of chronic illness and care systems.

Methods: We will describe key trajectory design methods that cross levels of analysis capturing interactions between genetic, physiologic, behavioral, and environmental factors

Results: These methods, including person-oriented, case-based, longitudinal mixed-method designs capture stability, change, and development. They are useful for complex, inhomogeneous, and multifaceted datasets that are often generated in studies of humans in chronic illness situations. Data inhomogeneity in this field is created because the phenomena of interest often requires various temporal and spatial scales, which cross a range of responses, and include both textual and numerical data that may be either continuous or discrete. In contrast to variable-oriented approaches, these analysis methods search for patterns, trends, or typologies in trajectories of response. Visualization is a key component of these novel methods in which patterns are identified across trajectories of data around a case (individual, dyad, system).

Conclusion: Trajectory design methods allow for the exploration of data, create portraits of response, and enhance insights to generate hypotheses.

Keywords:
trajectory science methods; chronic illness; adaptive leadership
Repository Posting Date:
22-Oct-2013
Date of Publication:
22-Oct-2013
Conference Date:
2013
Conference Name:
24th International Nursing Research Congress
Conference Host:
Sigma Theta Tau International, the Honor Society of Nursing
Conference Location:
Prague, Czech Republic
Description:
24th International Nursing Research Congress Theme: Bridge the Gap Between Research and Practice Through Collaboration. Held at the Hilton Prague Hotel.
Note:
This is an abstract-only submission. If the author has submitted a full-text item based on this abstract, you may find it by browsing the Virginia Henderson Global Nursing e-Repository by author. If author contact information is available in this abstract, please feel free to contact him or her with your queries regarding this submission.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_GB
dc.type.categoryAbstracten_GB
dc.typePresentationen_GB
dc.titleTrajectory Design and Analytic Methods for the Study of Human Response to Chronic Illness and Care Systemsen_GB
dc.contributor.authorDocherty, Sharronen_GB
dc.contributor.authorBrandon, Debraen_GB
dc.contributor.departmentBeta Epsilonen_GB
dc.author.detailsSharron Docherty, PhD, CPNP, doche002@mc.duke.edu; Debra Brandon, PhD, RN, FAAN;en_GB
dc.identifier.urihttp://hdl.handle.net/10755/304403-
dc.description.abstract<p>Session presented on: Friday, July 26, 2013</p><b>Purpose: </b>People with chronic illnesses and their families experience multiple symptoms and/or disabilities and their responses cross multiple measurement domains, from genetic, biologic, through psychosocial, behavioral, and environmental.  The Adaptive Leadership (AL) framework provides a compelling and effective conceptual lens through which to view the challenges that individuals face as it allows examination of phenomena that are multilevel, dynamic, unpredictable, and highly context dependent.  Research approaches that best address the vital questions in this field also require dynamic designs and analytic methods that allow us to identify patterns across levels of functioning and place a high value on the role and timing of dynamic interactions. The purpose of this paper is to present a range of trajectory design methods that can be used in synergy with the AL framework for the study of chronic illness and care systems. <p><b>Methods: </b>We will describe key trajectory design methods that cross levels of analysis capturing interactions between genetic, physiologic, behavioral, and environmental factors <p><b>Results: </b>These methods, including person-oriented, case-based, longitudinal mixed-method designs capture stability, change, and development. They are useful for complex, inhomogeneous, and multifaceted datasets that are often generated in studies of humans in chronic illness situations. Data inhomogeneity in this field is created because the phenomena of interest often requires various temporal and spatial scales, which cross a range of responses, and include both textual and numerical data that may be either continuous or discrete. In contrast to variable-oriented approaches, these analysis methods search for patterns, trends, or typologies in trajectories of response. Visualization is a key component of these novel methods in which patterns are identified across trajectories of data around a case (individual, dyad, system). <p><b>Conclusion: </b>Trajectory design methods allow for the exploration of data, create portraits of response, and enhance insights to generate hypotheses.en_GB
dc.subjecttrajectory science methodsen_GB
dc.subjectchronic illnessen_GB
dc.subjectadaptive leadershipen_GB
dc.date.available2013-10-22T20:35:10Z-
dc.date.issued2013-10-22-
dc.date.accessioned2013-10-22T20:35:10Z-
dc.conference.date2013en_GB
dc.conference.name24th International Nursing Research Congressen_GB
dc.conference.hostSigma Theta Tau International, the Honor Society of Nursingen_GB
dc.conference.locationPrague, Czech Republicen_GB
dc.description24th International Nursing Research Congress Theme: Bridge the Gap Between Research and Practice Through Collaboration. Held at the Hilton Prague Hotel.en_GB
dc.description.noteThis is an abstract-only submission. If the author has submitted a full-text item based on this abstract, you may find it by browsing the Virginia Henderson Global Nursing e-Repository by author. If author contact information is available in this abstract, please feel free to contact him or her with your queries regarding this submission.en_GB
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