How can you mitigate potential biases in a community needs assessment?

Biases are baked into the process of assessing community needs and flow from the perspectives we approach needs and the people who complete the assessment. While it's important to to control these biases, it is also important to acknowledge them. They often come in the form of the values that form our assessment questions and approaches. Ensuring that we hear from a broad variety of stakeholders is one way to collect information that will represent community interests. When we approach assessment using a participatory method (that's our preference), you understand that data itself is not the only goal. Participatory approaches create insights and action responses from those who participate.

Biases are tendencies or inclinations that influence our perspectives and decisions, often in an unconscious manner. They are significant in many aspects of life and work for several reasons: Influence on Decision-Making: Biases can impact decisions, leading to choices that may not be based on objective evaluation. In professional settings, this could affect hiring practices, performance evaluations, and strategic planning. Perception and Interpretation: Biases shape how individuals perceive and interpret information, potentially leading to misconceptions or misunderstandings about people, situations, or data. Social Interaction: In social settings, biases can influence how people interact with others from different backgrounds.

1. Value qualitative data along with quantitative data. Often, an over-reliance on quantitative data as "more rigorous" leaves out the depth of experience that is available in qualitative data. 2. Intentionally reach out to a variety of respondents - even if that means setting aside a part of your budget for alternate modes of contact or language access and accessibility as part of your planning. Consider who is being left out of the conversation and how their engagement with a community needs assessment could be limited exponentiating a lack of access of services. 3. Look for context. Examine the history, environment, local politics, etc. of a community to give context to any report on an organization to drive strategic actions.

Seek to match the demographics of the community in question with an advisory committee made of stakeholders from the community’s demographics. Any group’s authenticity and expertise will seek to match its demographics by definition where and with whom the group’s stakeholders reside, operate and serve. The essence of power and influence lives within a community’s demographics.

We all have biases, and no matter what lengths you go to, you will always have some, and that's okay. You can check your own biases by asking yourself questions to further analyze how you think, feel and what you believe about a particular person, group, place, or event. You can help counteract the effects of your bias by becoming aware that you have them, and be open and curious to evidence that does not support your bias. A strong tendency in research and in every day life is to discount or throw out any outliers or exceptions. Instead I would encourage you to be curious about what makes them so different and could this be representative of alternative explanations or viewpoints that you aren't currently considering.

Agreed, it's important that items like evaluations and assessments are based on samples that are representative of the groups that they will be used with. Otherwise, it leads to biased results.

One of the biggest biases we encounter in psychological research is samples of convenience or convenience sampling where the ease of access leads to the inclusion of a sliver of population which is not fairly or fully representative of the actual population. Handling such sampling biases should involve awareness of different types of possible biases that can emerge at very stage of a trial. Randomization is commonly used to balance out internal and external validity even though it is not foolproof at all times. If randomization is used then it should be backed by a sturdy design. Also, using something like the Jadad scale helps in establishing greater methodological accuracy.

I find it's always prudent to utilize validated quantifying methods in order to reduce bias. If you are seeking a new quantification method, seek to independently validate that.

This is not a comprehensive response as that would take more than 750 characters. To remove biases you must first understand the biases around the subject. There is no one size fits all. You also need to remove the outliers, which always skew the data points. That’s my 2cents.

There should definitely be clear understanding for data collection and progress monitoring. Anyone implementing a protocol should be properly trained to ensure fidelity.

Invite several colleagues with diverse backgrounds, experiences, and perspectives to review the report. Do not share with them your perspectives but genuinely ask them for their analysis of the data. Receive their feedback with an open mind and spirit of curiosity. Understand that your hypothesis may have been incorrect and that is ok. This is an exercise to learn about the community in order to address the needs.

We all have biases and acknowledging your biases about the data you are collecting and how you developed those biases is a helpful place to start. Then, we can critically examine our perceptions and understandings of what the data may be showing/telling you through proven methodologies such as triangulation, feedback, peer reviews, etc. Seeking diverse voices (quantitative and qualitative) and sources from those within the community and outside of the community help add perspective to what the data may be revealing as well.

The gold standard for reducing cultural bias is inclusion. Include people who reflect the community you are assessing the needs of in decision making roles at every level of the assessment process. The more diverse your assessment team is, the less likely you will be to fall into the trap of cultural bias. It’s essential to have people with real, lived experience of the challenges you are trying to address involved in identifying the root causes of those challenges; gaps in services, resources, and infrastructure; and a plan that is practical for the community in question. The people you serve are the experts in their own needs. Without them, you’re more likely to land on what I like to call “a solution looking for a problem to solve.”

It's important that tools are culturally sensitive. Otherwise, the results will be skewed and biased. They should be validated on the group they are being used with.

Begin as if you know nothing. I find it's the 'little knowledge' that is a dangerous thing in this instance. A clean mindset sparked by genuine curiosity about the subject is helpful - in so many instances, if we can just let go of the need to know, we can learn so much more.

First, use census data to define the community both in terms of race/ethnicity/primary language and also in terms of household size/income gradients. Second, develop strategies to reach out to each sector of significant size (define significant - 10%?), whether through existing community/neighborhood-based organizations, getting invited to neighborhood or church meetings, reaching out to recognized community liaisons/leaders, Back-to-School night events, and pop-up events at intentionally-located venues based on census block data, perhaps in combination with transit stop data from on-board surveys or electronic passenger count data. Third, observe who attended each event and compare the distribution of attendees with the community makeup.

The goal of an assessment is a critical factor in avoiding bias and clearly focusing on the outcomes the assessment is designed to support. A resource allocation goal is one goal that might lend itself to a more data-driven approach, but an alternative goal is the mobilization of people to create community solutions. This approach lends itself to a qualitative approach.

Mitigating biases in a community needs assessment can be done with a multifaceted approach. Avoid sampling bias through diverse and representative samples. Reduce measurement bias with standardized tools and clear metrics. Overcome confirmation bias by fostering open-mindedness. Address cultural bias by involving diverse community perspectives. Prevent reporting bias by maintaining transparency in reporting both positive and negative findings. Consider contextual and historical factors, involve the community, seek continuous feedback, and engage external experts. This multi-faceted approach ensures a more reliable and credible assessment, enhancing the effectiveness of community outreach initiatives.

In my former role as a Dance Department Chair, faculty colleagues and I accepted the first legally blind dance major. Having never taken a legally blind student through a four-year performing arts program, we needed to admit that we knew nothing, and that allowing her to dictate to us how to teach her would be the most effective way forward. It was a level playing field that required us to remain open, curious, and growing during her entire four years. We learned so much! And she graduated with honors. If we had allowed our biases to drive us, assuming we, as a faculty, knew what she needed, the experience would have been way more challenging for everyone.