Indicate how the bias would affect the measure of association. Would it be under estimated, or over estimated or unchanged.
Persons diagnosed as HIV positive or negative were interviewed about their number of lifetime sexual partners. The interview occurred after they were told their HIV status.
2. A cohort study looked at the association of exposure to PCBs in the workplace and the occurrence of cancer over 20 years. At the 10-year follow up, 15% of the original participants could not be located to assess their disease status.
3. In a clinical trial of a new drug, the intervention group reviewed the medicine and outcomes were assessed by a doctor working for the pharmaceutical company. The placebo group received the placebo and outcomes were assessed by a doctor from the local community hospital.
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For the following study descriptions, describe potential bias(es) most likely to be present. Indicate how the bias would affect the measure of association (would it be underestimated, overestimated or unchanged, or direction unknown
Persons diagnosed as HIV positive or negative were interviewed about their number of lifetime sexual partners. The interviews occurred after they were told their HIV status
To determine how bias would affect the measure of association in each scenario, we need to consider the potential biases involved.
1. In the first scenario, where persons diagnosed as HIV positive or negative were interviewed about their number of lifetime sexual partners, bias could potentially arise if individuals who are HIV positive underreport their number of sexual partners due to stigma or judgment. This could result in an underestimation of the measure of association between HIV status and number of sexual partners, as the true association may be larger than what is observed.
2. In the second scenario, a cohort study is being conducted to investigate the association between exposure to PCBs in the workplace and the occurrence of cancer over 20 years. However, at the 10-year follow-up, 15% of the original participants could not be located to assess their disease status. This loss to follow-up introduces the possibility of selection bias. If those lost to follow-up have a different likelihood of developing cancer compared to those who stayed in the study, it could potentially lead to an over or underestimation of the measure of association, depending on the characteristics of the participants lost.
3. The third scenario involves a clinical trial of a new drug, where the intervention group received the medicine and outcomes were assessed by a doctor working for the pharmaceutical company. On the other hand, the placebo group received the placebo, and outcomes were assessed by a doctor from the local community hospital. This scenario introduces potential biases due to differential assessment methods. If the doctors evaluating the outcomes have different standards or motivations, it could lead to an over or underestimation of the measure of association between the new drug and its outcomes.
Overall, in each scenario, biases have the potential to affect the measure of association. However, the direction and magnitude of the bias cannot be definitively determined without further information or analysis.