This happens when the diagnostic approach is related to knowledge of the subject's prior exposure to a putative cause (e.g. taking a certain drug, being exposed in an outbreak etc [2]).

Example: let's suppose that a case-control study is conducted to test if oral contraceptives (OC) are a risk factor for endometrial cancer. A group of cases and an equal number of controls are selected. Cases are selected at GP (family doctor) surgeries. Cases who use OC may be more likely to be offered screening for endometrial cancer either systematically or because of a side-effect of OC (breakthrough bleeding). The chance of undertaking detection of endometrial cancer is therefore higher among OC users than among other cases i.e. the use of OC may cause the search for endometrial cancer (by causing symptomless patients to bleed) rather than causing the cancer itself. The result is that a higher proportion of cases report using OC, with an overestimation of 'a', leading to an overestimation of the odds ratio.

Sackett [2] describes this example, where an innocent exposure may become a suspect, if, rather than causing a disease, it causes a sign or symptom which precipitates a search for a disease, as 'unmasking (detection signal) bias'.