Other Titles
Circadian Disorders: Advancing the Science of Sleep
Abstract
Session presented on Thursday, July 21, 2016:
Background: Insomnia is a common complaint in the modern societies; however, it remains underdiagnosed and undertreated. Although screening tools including Insomnia Severity Index (ISI), Athens Insomnia Scale (AIS), and Pittsburg Sleep Quality Index (PSQI) are widely used for identifying insomnia, the diagnostic properties of have yet to be summarized in a systematic manner. Aim: The aim of the current study was to estimate and to compare the diagnostic accuracy of the ISI, AIS, and PSQI in identifying insomnia.
Method: We perform a systematic search in electronic databases including EMBASE, PubMed, PsycINFO, CINAHL, and Chinese Electronic Periodic Services from their inception to until May 20, 2015.
Summary: Sensitivity, specificity, and diagnostic odds ratios (DOR) against a reference standard were calculated for each study. The revised Quality Assessment of Diagnostic Accuracy Studies was used to assess the quality of each included study. All analyses were conducted using Stata 14.0, with midas and metandi user-written commands, SAS 9.0.2,with Proc Mixed module, and Review Manager 5.3. Random effects bivariate model was used for analyses.
Results: We included 19 studies with a total of 4693 participants in data analyses. The summary estimates for the ISI, AIS, and PSQI in identifying insomnia in the studies were as follows: 88% (95% confidence interval CI = 0.79+/-0.93), 91% (0.87+/-0.93) and 94% (0.86+/-0.98); specificity: 85% (0.68+/-0.94), 87% (0.68+/-0.95) and 76% (0.64+/-0.85); and DORs: 41.93 (8.77+/-200.33), 67.7 (23.4+/-196.1) and 53 (15.5+/-186.2), respectively. No significant difference was observed regarding the pooled sensitivity, specificity, and DORs among the ISI, AIS, and PSQI (all P > 0.05).
Conclusions: The current evidence indicates that the ISI, AIS, and PSQI are comparable and useful instruments for identifying insomnia in terms of diagnostic properties. Moreover, after comparisons of the diagnostic properties, sleep domains and feasibility of the scales revealed that the AIS is the strongest and most appropriate among the three instruments.
Sigma Membership
Lambda Beta at-Large
Type
Presentation
Format Type
Text-based Document
Study Design/Type
N/A
Research Approach
N/A
Keywords:
Diagnostic Meta Analysis, Insomnia, Accuracy
Recommended Citation
Chiu, Hsiao-Yean and Tsai, Pei-Shan, "Diagnostic accuracy of insomnia screening tools: A meta-analysis" (2016). INRC (Congress). 239.
https://www.sigmarepository.org/inrc/2016/presentations_2016/239
Conference Name
27th International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Cape Town, South Africa
Conference Year
2016
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record.
All permission requests should be directed accordingly and not to the Sigma Repository.
All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Acquisition
Proxy-submission
Diagnostic accuracy of insomnia screening tools: A meta-analysis
Cape Town, South Africa
Session presented on Thursday, July 21, 2016:
Background: Insomnia is a common complaint in the modern societies; however, it remains underdiagnosed and undertreated. Although screening tools including Insomnia Severity Index (ISI), Athens Insomnia Scale (AIS), and Pittsburg Sleep Quality Index (PSQI) are widely used for identifying insomnia, the diagnostic properties of have yet to be summarized in a systematic manner. Aim: The aim of the current study was to estimate and to compare the diagnostic accuracy of the ISI, AIS, and PSQI in identifying insomnia.
Method: We perform a systematic search in electronic databases including EMBASE, PubMed, PsycINFO, CINAHL, and Chinese Electronic Periodic Services from their inception to until May 20, 2015.
Summary: Sensitivity, specificity, and diagnostic odds ratios (DOR) against a reference standard were calculated for each study. The revised Quality Assessment of Diagnostic Accuracy Studies was used to assess the quality of each included study. All analyses were conducted using Stata 14.0, with midas and metandi user-written commands, SAS 9.0.2,with Proc Mixed module, and Review Manager 5.3. Random effects bivariate model was used for analyses.
Results: We included 19 studies with a total of 4693 participants in data analyses. The summary estimates for the ISI, AIS, and PSQI in identifying insomnia in the studies were as follows: 88% (95% confidence interval CI = 0.79+/-0.93), 91% (0.87+/-0.93) and 94% (0.86+/-0.98); specificity: 85% (0.68+/-0.94), 87% (0.68+/-0.95) and 76% (0.64+/-0.85); and DORs: 41.93 (8.77+/-200.33), 67.7 (23.4+/-196.1) and 53 (15.5+/-186.2), respectively. No significant difference was observed regarding the pooled sensitivity, specificity, and DORs among the ISI, AIS, and PSQI (all P > 0.05).
Conclusions: The current evidence indicates that the ISI, AIS, and PSQI are comparable and useful instruments for identifying insomnia in terms of diagnostic properties. Moreover, after comparisons of the diagnostic properties, sleep domains and feasibility of the scales revealed that the AIS is the strongest and most appropriate among the three instruments.