2.50
Hdl Handle:
http://hdl.handle.net/10755/157636
Type:
Presentation
Title:
Fact or Fiction: The Assessment of Symptom Clusters Using SEM
Abstract:
Fact or Fiction: The Assessment of Symptom Clusters Using SEM
Conference Sponsor:Western Institute of Nursing
Conference Year:2009
Author:Sousa, Karen H., RN, PhD
P.I. Institution Name:University of Colorado Denver, College of Nursing
Title:Professor
Contact Address:13120 East 19th Ave., Denver, CO, 80045, USA
Contact Telephone:720-854-8883
Co-Authors:Paula Meek, Professor
Purpose: The purpose of this presentation is to demonstrate a method for evaluating symptom clusters using Structural Equation Modeling. Background: Structural Equation Modeling is a statistical methodology that takes a confirmatory approach to the multivariate analysis of variables. It is a comprehensive process for testing hypotheses about relationships among measured and latent variables. The Sign and Symptom Checklist for Persons with HIV Disease (SSC-HIV ), developed by Holzemer and colleagues, provides the operational definition for the measurement model representing symptom clusters for persons living with HIV . Measurement models define the relations between the observed variable, represented by individual symptoms, and the unobserved constructs or cluster themes. The SSC-HIV suggests that there are six symptom clusters represented by 26 measured symptoms. Participants: The sample is 917 men, primarily male, diagnosed with AIDS and had complete data on the symptoms of interest. Methods: SEM was used to test the hypothesized relationships and suggested a second-order factor structure. Analysis was conducted using MPLUS and the estimator used to estimate the model was weighted least square parameter (WLSM). This estimator uses a diagonal weight matrix with robust standard errors and a meanadjusted chi-square test statistic. It is appropriate for categorical data which reflects the level of measurement of the symptom data, present or not present. Several goodness of fit indices were used for assessing the model fit. Results: This analysis confirmed the six symptom clusters hypothesized by Holzemer and colleagues. The data were explained by the six first-order factors (RMSEA=.036, SRMR= .061, CFI=.99). Implications: Symptom management is an important outcome for nursing practice and is integral to evaluating the efficacy of nursing interventions. The use of valid conceptual models provides the context to guide the development of appropriate strategies for care. Using SEM demonstrated that the SSC-HIV is a valid measure of clusters of HIV-related symptoms. SEM is useful for confirming symptom clusters, which provides the context to assist individuals living with HIV-AIDS to attain an optimal quality of life. Implications and strategies regarding SEM as a methodological strategy will be discussed.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Western Institute of Nursing

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleFact or Fiction: The Assessment of Symptom Clusters Using SEMen_GB
dc.identifier.urihttp://hdl.handle.net/10755/157636-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Fact or Fiction: The Assessment of Symptom Clusters Using SEM</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Western Institute of Nursing</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2009</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Sousa, Karen H., RN, PhD</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">University of Colorado Denver, College of Nursing</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Professor</td></tr><tr class="item-address"><td class="label">Contact Address:</td><td class="value">13120 East 19th Ave., Denver, CO, 80045, USA</td></tr><tr class="item-phone"><td class="label">Contact Telephone:</td><td class="value">720-854-8883</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">karen.sousa@ucdenver.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Paula Meek, Professor</td></tr><tr><td colspan="2" class="item-abstract">Purpose: The purpose of this presentation is to demonstrate a method for evaluating symptom clusters using Structural Equation Modeling. Background: Structural Equation Modeling is a statistical methodology that takes a confirmatory approach to the multivariate analysis of variables. It is a comprehensive process for testing hypotheses about relationships among measured and latent variables. The Sign and Symptom Checklist for Persons with HIV Disease (SSC-HIV ), developed by Holzemer and colleagues, provides the operational definition for the measurement model representing symptom clusters for persons living with HIV . Measurement models define the relations between the observed variable, represented by individual symptoms, and the unobserved constructs or cluster themes. The SSC-HIV suggests that there are six symptom clusters represented by 26 measured symptoms. Participants: The sample is 917 men, primarily male, diagnosed with AIDS and had complete data on the symptoms of interest. Methods: SEM was used to test the hypothesized relationships and suggested a second-order factor structure. Analysis was conducted using MPLUS and the estimator used to estimate the model was weighted least square parameter (WLSM). This estimator uses a diagonal weight matrix with robust standard errors and a meanadjusted chi-square test statistic. It is appropriate for categorical data which reflects the level of measurement of the symptom data, present or not present. Several goodness of fit indices were used for assessing the model fit. Results: This analysis confirmed the six symptom clusters hypothesized by Holzemer and colleagues. The data were explained by the six first-order factors (RMSEA=.036, SRMR= .061, CFI=.99). Implications: Symptom management is an important outcome for nursing practice and is integral to evaluating the efficacy of nursing interventions. The use of valid conceptual models provides the context to guide the development of appropriate strategies for care. Using SEM demonstrated that the SSC-HIV is a valid measure of clusters of HIV-related symptoms. SEM is useful for confirming symptom clusters, which provides the context to assist individuals living with HIV-AIDS to attain an optimal quality of life. Implications and strategies regarding SEM as a methodological strategy will be discussed.</td></tr></table>en_GB
dc.date.available2011-10-26T20:03:35Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T20:03:35Z-
dc.description.sponsorshipWestern Institute of Nursingen_GB
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