Written by Vida Shafipour, Mahmood Moosazadeh, Yadollah Jannati, Fariba Shoushi
Parent Category: Year 2017, Volume 9
Category: Volume 9, Issue 3, March 2017
Background: Studies have shown that family members of patients in intensive care units experience high levels of anxiety. Contradictions in the results of the studies conducted regarding the effect of training on the anxiety level of such families, emphasize the necessity of employing other research methods to eliminate these ambiguities.
Objective: This study applied meta-analysis to determine the effect of training on the anxiety level of families with patients in the intensive care unit.
Methods: In order to find electronically published studies from 1990 to 2016, the articles published in journals indexed in the following databases were used: Elsevier, Scopus, ProQuest, ISI, Web of Science, PubMed, Google scholar and Cochrane. For data analysis Stata Software version 11 was used and the heterogeneity index of studies was determined through Cochran (Q) and I2. Due to the heterogeneity, the random effect model was used to estimate the difference between the standardized mean of anxiety.
Results: In this meta-analysis and systematic review article, eight articles were found to be eligible. The number of samples in the initial studies into a meta-analysis included 387 patients in the intervention group and 393 people in the control group. Standardized difference of the mean anxiety score in the intervention group was -0.329 (CI 95%: -0.756-0.099) units less than that of the control group, indicating that this effect was not statistically significant.
Conclusions: The results of this meta-analysis show that training will decline the anxiety level of a family with patients hospitalized in the intensive care unit, although the impact is not considerable.
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Keywords: Family, Anxiety, ICU, Education
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Deadline for submission: 7 March 2019, 16:00 (GMT)
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About the Instructor
Dr. Michael Borenstein, one of the authors of Introduction to Meta-Analysis, is widely recognized for his ability to make statistical concepts accessible to researchers as well as to statisticians. He has lectured widely on meta-analysis, including at the NIH, CDC, and FDA. Read more: