Failing to examine differences between and among people

The second type of bias identified by Burke and Eichler arises when we ignore or are insensitive to the position people occupy in hierarchies and the impact of location on health and well-being. For example, if we develop a reproductive health program for woman and ignore the needs of women with disabilities or women who have experienced sexual abuse or violence, the program will only be useful and appropriate for specific groups. Failing to recognize differences can lead us to generalize information from dominant groups when it does not apply or to assume that groups are uniform when they contain important differences. Similarly, research that “uses only one sex, one race or non-disabled people and presents its findings as if they were applicable to everybody is over-generalizing” [1] and runs the risk of causing harm.

In the case of hip and knee replacements, some studies suggest that rates of osteoarthritis – the primary reason for surgery of this kind – are different for diverse groups of women and men. The researchers found that women have twice the rate of osteoarthritis as men; women of colour have higher rates of knee osteoarthritis than white women; and individuals with lower income and fewer years of education have higher rates of arthritis than those with higher income and more education. In other words, if we assume that everyone faces the same risk of osteoarthritis and has the same need for hip or knee surgery, we will disadvantage specific populations.

Source: [1] Burke, M.A., & Eichner, M. (2006). The BIAS FREE Framework a practical tool for identifying and eliminating social biases in health research. Geneve. Switzerland: Global Forum for Health Research, p.9.,

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