2.50
Hdl Handle:
http://hdl.handle.net/10755/153906
Type:
Presentation
Title:
Evaluation of Systematic Attrition Related to Experimental Interventions
Abstract:
Evaluation of Systematic Attrition Related to Experimental Interventions
Conference Sponsor:Sigma Theta Tau International
Conference Year:2010
Author:Roberts, Beverly L., RN, PhD
P.I. Institution Name:University of Florida
Title:Professor
Co-Authors:Bryan A. Weber, ARNP, PhD
21st INRC [Research Presentation] Purpose: To compare univariate statistics, survival analysis and Cox regression to identify systematic attrition related to experimental interventions. Univariate statistics assess differences in drop outs groups.  Survival analyses provide information about the cumulative probability of attrition over time while Cox regression assesses potential factors affecting the probability of attrition over time. Methods: To illustrate this, an example from a study of the effects of a 12-week muscle strengthening exercise on recovery after hospitalization for a medical event was used.  The 68 men and 152 women (mean age=78 years) were randomly assigned to exercise or a control conditions.  Data was collected 24 hours before discharge and 1, 2, 4, 6, 8 and 12 weeks later.  Results: Attrition was 49% and 51% in the exercise and control groups, respectively.  There were no significant differences in survival time (cumulative occurrence of withdrawing from the study) or hazard ratio (risk of dropping out at each time point) (p>.76 for chi squared).  Univariate comparisons of attrition status revealed that those who remained in the study had significantly a lower length of stay than those who dropped (5.53 and 6.61, respectively, t(218)=2.18, p=.03).  There were no significant differences in attrition status for gender, treatment in ICU, and malnutrition.  In contrast to these univariate differences, Cox regression revealed that age and treatment in ICU were significant contextual predictors of attrition (p<.04) while gender, malnutrition, and length of stay were not significant.  Experimental status did not explain significantly more to the probability of attrition.  Conclusion: Unlike univariate comparisons of attrition, survival analysis and Cox regression provide information about systematic differences in the cumulative probability attrition over time.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Sigma Theta Tau International

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleEvaluation of Systematic Attrition Related to Experimental Interventionsen_GB
dc.identifier.urihttp://hdl.handle.net/10755/153906-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Evaluation of Systematic Attrition Related to Experimental Interventions</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Sigma Theta Tau International</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2010</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Roberts, Beverly L., RN, PhD</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">University of Florida</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Professor</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">robertsb@ufl.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Bryan A. Weber, ARNP, PhD</td></tr><tr><td colspan="2" class="item-abstract">21st INRC [Research Presentation] Purpose: To compare univariate statistics, survival analysis and Cox regression to identify systematic attrition related to experimental interventions. Univariate statistics assess differences in drop outs groups.&nbsp; Survival analyses provide information about the cumulative probability of attrition over time while Cox regression assesses potential factors affecting the probability of attrition over time.&nbsp;Methods: To illustrate this, an example from a study of the effects of a 12-week muscle strengthening exercise on recovery after hospitalization for a medical event was used.&nbsp; The 68 men and 152 women (mean age=78 years) were randomly assigned to exercise or a control conditions.&nbsp; Data was collected 24 hours before discharge and 1, 2, 4, 6, 8 and 12 weeks later.&nbsp; Results: Attrition was 49% and 51% in the exercise and control groups, respectively.&nbsp; There were no significant differences in survival time (cumulative occurrence of withdrawing from the study) or hazard ratio (risk of dropping out at each time point) (p&gt;.76 for chi squared).&nbsp; Univariate comparisons of attrition status revealed that those who remained in the study had significantly a lower length of stay than those who dropped (5.53 and 6.61, respectively, t(218)=2.18, p=.03).&nbsp; There were no significant differences in attrition status for gender, treatment in ICU, and malnutrition.&nbsp; In contrast to these univariate differences, Cox regression revealed that age and treatment in ICU were significant contextual predictors of attrition (p&lt;.04) while gender, malnutrition, and length of stay were not significant.&nbsp; Experimental status did not explain significantly more to the probability of attrition.&nbsp; Conclusion: Unlike univariate comparisons of attrition, survival analysis and Cox regression provide information about systematic differences in the cumulative probability attrition over time.</td></tr></table>en_GB
dc.date.available2011-10-26T12:36:07Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T12:36:07Z-
dc.description.sponsorshipSigma Theta Tau Internationalen_GB
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