Berksonian bias, Pygmalion effect and Hawthorne effect
As these are difficult to understand and find examples of, i have compiled some info in easiest way i could. I hope it helps you all :)
Hawthorne effect: the alteration of behaviour by the subjects of a study due to their awareness of being observed.
Pygmalion effect: Investigator inadvertently conveys his high expectations to subjects, who then produce the expected result. A "self-fulfilling prophecy".
Berkson bias: usually occurs when cases and controls are selected from hospital inpatients.More specifically, when both the exposure and outcome affect the selection and leads to a false negative association.It looks confusing but just look at this example:
Consider an investigator studying a relation between diabetes and CHD.He goes to a hospital and gets a list of people admitted with CHD and he selects equal number of controls(inpatients not having CHD).
Let us create a 2x2 table here
Both diabetes and CHD are causes of hospitalisation.And we select our cases and controls from these hospitalised patients.The problem of choosing the control group(those who don't have CHD) from inpatients is that when compared to general public,the number of diabetics among the controls are much more(diabetes is a cause of hospitalisation). So that increases the value of b (exposed controls) with a corresponding decrease in d (not exposed controls) when compared to general population.
Odds ratio= ad/bc
So decrease in d and increase in b will cause a decreased odds ratio(decreased association) when compared to the value that would have been obtained if the study has been conducted in general population.Thus,here when exposure and result both affects selection,we get a decreased association.
Hawthorne effect: the alteration of behaviour by the subjects of a study due to their awareness of being observed.
Pygmalion effect: Investigator inadvertently conveys his high expectations to subjects, who then produce the expected result. A "self-fulfilling prophecy".
Berkson bias: usually occurs when cases and controls are selected from hospital inpatients.More specifically, when both the exposure and outcome affect the selection and leads to a false negative association.It looks confusing but just look at this example:
Consider an investigator studying a relation between diabetes and CHD.He goes to a hospital and gets a list of people admitted with CHD and he selects equal number of controls(inpatients not having CHD).
Let us create a 2x2 table here
CHD +
|
CHD -
|
|
Exposure (DM) +
|
a
|
b
|
Exposure (DM) -
|
c
|
d
|
Both diabetes and CHD are causes of hospitalisation.And we select our cases and controls from these hospitalised patients.The problem of choosing the control group(those who don't have CHD) from inpatients is that when compared to general public,the number of diabetics among the controls are much more(diabetes is a cause of hospitalisation). So that increases the value of b (exposed controls) with a corresponding decrease in d (not exposed controls) when compared to general population.
Odds ratio= ad/bc
So decrease in d and increase in b will cause a decreased odds ratio(decreased association) when compared to the value that would have been obtained if the study has been conducted in general population.Thus,here when exposure and result both affects selection,we get a decreased association.
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