Effects of Sleep Deprivation on Performance: A Meta-Analysis

Matthew Haines

Summary:

                This meta-analysis attempts to make the distinction that sleep deprivation has a negative effect on performance. The authors focused the scope of the meta-analysis to include cognitive performance, motor performance, and mood. The meta-analysis included studies conducted from 1984-1992 and the study had to examine the effects of either partial sleep deprivation, long-term sleep deprivation, and short-term sleep deprivation. The studies were also categorized based on complexity and duration of the task, whether it be cognitive or negative. The study concluded that sleep deprivation caused a performance level decrease 1.37 standard deviations from the mean. This study also showed that the mean performance of sleep deprived subjects was in the 9^th percentile of subjects that were not sleep deprived.  These findings aid the validity of studies that show sleep deprivation has a negative effect on performance. This finding contradicts most of the findings being put out by introductory psychology books.

Critique:

                This study is an extensive analysis of sleep studies conducted from 1984-1992 and it does a good job of highlighting the different aspects of sleep deprivation. The authors try to address all confounding variables to increase the meta-analysis’s validity and they do a good job of collecting a decent sample size. However, I would like to see a more in-depth analysis into the data. It would help increase the validity of the study even more to explain how the data was normalized, if they accounted for variability, or if the conducted a study that delved into the variables more explicitly. 

https://watermark.silverchair.com/sleep-19-4-318.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAAfUwggHxBgkqhkiG9w0BBwagggHiMIIB3gIBADCCAdcGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMSiRuKuQxQ1JiDcYtAgEQgIIBqClI0H_1aoKooCIA-78IBxJb9JsvkgeDp05a4Ur6vqTU1hy72RbpFhsCeVfrAu0CpO90JinWXPNYPUxRvkHUssFwT0dGNm1D2o18cjhgmZteflWJ9juRfmVlh89tPO17WEaMjCu0nCY_ZhU3nxn9qeEuerkTUHe3m0L0Ot_gm5FapOghGvKdkkXVpmZuviE5MavNx698xtQTVCFd_e3VrNZ2SfvHO5LJa_3Smv7XjAr-SWO1F3U4sL9IXfc1ROLaERtlqsH02_Dn5hMPW74aRlLZUPQY3uiwkGacIOkK6i5HoH6MwgRWikeIaXqIOOXuq5l_34OmvNlW6uPVYDwKbXdLFzfjuLuTnkQP-awD6SznsPIKZeYlpdVh7mhCYl_isGhEM7U5tQmz6FbPtxHS2I1s23tsgrpX8ukZrl_0kMq2u4MK7vFCCURcuVP7EKC7WLFG04iVPdUfw3P5WSwge3zyKjhMY95e8w4ML-V6ALJntxdmry77n-bJKRJVtveh-6gsdWz5l4lANEz0x19dNrBLpDTQIkvMS0qDe3QecukM2q2kHlkd9Z8