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Accumulating evidence suggests that alterations in inflammatory biomarkers are important in depression. However, previous meta-analyses disagree on these associations, and errors in data extraction may account for these discrepancies.
PubMed/MEDLINE, Embase, PsycINFO, and the Cochrane Library were searched from database inception to 14 January 2020. Meta-analyses of observational studies examining the association between depression and levels of tumor necrosis factor-α (TNF-α), interleukin 1-β (IL-1β), interleukin-6 (IL-6), and C-reactive protein (CRP) were eligible. Errors were classified as follows: incorrect sample sizes, incorrectly used standard deviation, incorrect participant inclusion, calculation error, or analysis with insufficient data. We determined their impact on the results after correction thereof.
Errors were noted in 14 of the 15 meta-analyses included. Across 521 primary studies, 118 (22.6%) showed the following errors: incorrect sample sizes (20 studies, 16.9%), incorrect use of standard deviation (35 studies, 29.7%), incorrect participant inclusion (7 studies, 5.9%), calculation errors (33 studies, 28.0%), and analysis with insufficient data (23 studies, 19.5%). After correcting these errors, 11 (29.7%) out of 37 pooled effect sizes changed by a magnitude of more than 0.1, ranging from 0.11 to 1.15. The updated meta-analyses showed that elevated levels of TNF- α, IL-6, CRP, but not IL-1β, are associated with depression.
These findings show that data extraction errors in meta-analyses can impact findings. Efforts to reduce such errors are important in studies of the association between depression and peripheral inflammatory biomarkers, for which high heterogeneity and conflicting results have been continuously reported.
This study aimed to explore the relationship between online game addiction and aggression, self-control, and narcissistic personality traits, which are known as the psychological characteristics linked to “at-risk” populations for online game addiction.
A total of 1471 online game users (males 82.7%, females 17.3%, mean age 21.30 ± 4.96) participated in this study and were asked to complete several self-report measures using an online response method. Questionnaires included demographic information and game use-related characteristics of the samples, the online game addiction scale (modified from Young's Internet addiction scale), the Buss–Perry aggression questionnaire, a self-control scale, and the narcissistic personality disorder scale.
Our results indicated that aggression and narcissistic personality traits are positively correlated with online game addiction, whereas self-control is negatively correlated with online game addiction (p < 0.001). In addition, a multiple regression analysis revealed that the extent of online game addiction could be predicted based on the person's narcissistic personality traits, aggression, self-control, interpersonal relationship, and occupation. However, only 20% of the variance in behavioral consequences was explained with the model.
An interesting profile has emerged from the results of this study, suggesting that certain psychological characteristics such as aggression, self-control, and narcissistic personality traits may predispose some individuals to become addicted to online games. This result will deepen our understanding of the “at-risk” population for online game addiction and provide basic information that can contribute to developing a prevention program for people who are addicted to online games.
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