When we see the word "bias," many of us think about issues like discrimination, racism, and sexism. In research, there are lots of examples of how racial and gender bias (conscious and unconscious) have resulted in detrimental outcomes for marginalized communities. As such, we must always be aware of and correct how our social biases influence our work.
Other lesser-known biases can also create problems for even the most experienced analysts. For nonprofits interested in using data for strategizing, evaluation, and advocacy, it is essential to understand the different types of bias and how to avoid them. These mistakes can "misinform decision-making processes, leading to ineffective interventions, policies, or therapies." Since no one wants that, this article covers four types of biases, how they can appear in a nonprofit's work, and ways to reduce biases in the future.
Types of bias
Selection bias
Selection bias occurs when some groups of people who should be a part of a research project are left out of the process, intentionally or unintentionally. For example, imagine an executive director who wants staff feedback for an upcoming strategic planning session. She creates a survey to get ideas for what topics to cover at the meeting. However, she only sends the survey to senior staff and directors, assuming they can speak for the entire staff. That's a selection bias error – by only including high-level staff, she will miss out on ideas from the rest of the employees that could be critical for the organization's growth and development.
Response bias
Response bias occurs when we ask questions in ways that influence people to give false responses. One way this happens is when questions are complex or confusing. For instance, questions that include a lot of jargon or unfamiliar acronyms can make it difficult for people to give a proper answer. And as we know, the nonprofit sector loves acronyms!
Also, response bias sometimes occurs when a person wants to give a socially appropriate response. Let's take a client feedback example. If a program staff member is interviewing a participant and asks them if they enjoyed the program, the client may be inclined to respond "yes" to be agreeable, even if their experience was not good. The power dynamics may be such that the participant does not want to risk upsetting the staff member, so they give a false answer to keep the peace. That's bad news for the client, as they don't feel comfortable expressing their concerns, and bad news for program staff, who will miss essential feedback that could strengthen their services in the future.
Procedural bias
Procedural biases occur when something about the data collection process influences the results. For instance, program leaders may be tempted to mandate that participants complete a feedback survey. However, this isn't always the best idea - people may fill out the survey as quickly as possible to get through it without taking the time to think through their answers.
This bias can also occur if people do not have enough time to complete a survey. For instance, if the executive director from the earlier example sends the survey one day before the strategic planning meeting, a few things will probably happen:
Some staff will rush through the survey.
Some staff won't have time to fill it out
The executive director will not have enough time to analyze the results before the session.
That's too many potential errors to make a survey worthwhile!
Confirmation bias
Confirmation bias occurs when we think we already know the answers to our questions, choose data that fits our conclusions, and ignore anything that doesn't fit (consciously or unconsciously). In my opinion, confirmation bias is one of the most dangerous biases, especially for advocacy organizations. In my previous life as a policy analyst, I saw situations where organizations chose a policy they wanted to advocate for and then worked backward to find data supporting their position. However, they never considered any evidence that contradicted their position. Without considering contrary data, organizations risk advocating for policies that could have unintended consequences for the populations they are trying to help.
How do we get rid of bias?
Unfortunately, no research project is bias-free. Despite our best efforts, there are sometimes limitations, resource restrictions, or simply blind spots that prevent us from doing "perfect" work. However, the first step in reducing biases is being aware of them and correcting them as we go.
Morgia Research Services has extensive experience collaborating with clients to identify potential biases in needs assessments, program evaluations, and other types of nonprofit research work. Need help with your next project? Click the button below to schedule a free 45-minute consultation call with us today!
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