Ross E. McKinney Jr , Heather H. Pierce
In the pursuit of truth in scientific evaluation, objectivity of the researcher is assumed, but in reality, interpreting research data requires judgment and interpretation. That 2 scientists can analyze the same data set and come to different conclusions is a reflection of the subjective elements that illustrate both the complexity of science and the potential for bias to influence reported outcomes. As one potential source of bias, a conflict of interest exists when professional judgment concerning some primary interest or responsibility is affected by a secondary interest or responsibility.1 Because all human beings have interests beyond their primary duties (eg, self-interest), conflicts of interest are ubiquitous and the evaluation of their potential effect is a matter of assessing the probable degree to which bias might have influenced the conduct of research or interpretation of data. The policies, rules, investigations, and scholarship on conflicts of interest have largely focused on financial conflicts of interest, with ongoing debates as to whether the definition of conflict of interest appropriately or disproportionately relies on financial relationships as a proxy indicator of bias. More comprehensive strategies for mitigating bias, regardless of whether it has been observed, can effectively supplement targeted responses to identified financial conflicts of interest.
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