detection bias

detection bias

[ditek′shən]
a potential artifact in epidemiological data caused by the use of a particular diagnostic technique or type of equipment. As an example, cancer rates may vary in different regions or periods, not because of an actual difference in the incidence of the disease but because of different diagnostic technologies.
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Second, only five trials report an adequate blinding process, it may have introduced performance bias and detection bias, in which the assessors are likely to have preferentially attributed injury occurrence to the control group.
To avoid detection bias, the researchers constructed a comparison group from the same database of 1,676 patients diagnosed with systemic sclerosis.
It is known to us that major advantages of RCTs to demonstrate causality include low risk of selective bias and minimized the influence of baseline confounding by randomly assigning the intervention, low risk of performance bias, or detection bias due to blinding.
Authors reported that all trials were at high risk of performance and detection bias due to no-blinding of participants and the self-assessing nature of the results, and accordingly downgraded all outcomes to reduced level of certainty.
In the standing position, one study reported a mean inter-beat interval detection bias of -2.
Assessment of detection bias focused on determining whether there were systematic differences between groups in how outcomes were determined.
When increases in breast cancer risk are seen in observational studies, the findings could be due to bias, and in this particular instance, detection bias.
11] This tool assesses selection bias, allocation bias, performance bias, detection bias, attrition bias and other bias.
The findings suggest that either all cholesterol drugs cause acute memory loss "or, perhaps more likely, that the association is the result of a detection bias," a higher likelihood of identifying memory problems in these patients because of increased physician contact, the study authors concluded.
This tool assesses risk of bias within the following domains: selection bias, performance bias, detection bias, attrition bias, reporting bias, and other bias.
The authors urged caution in interpreting the findings because of high or unclear risk of selection bias, detection bias, and attrition bias, and too little information was available for the authors to conduct subgroup analyses.
Such methodology would help clarify any age differences as they pertain to a negative or positive emotion detection bias.

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