The Merits of Affinity Groups, Part Two: How Peer Learning Works

 

It’s essential to challenge and expand the ideas we take for granted when we engage in the work of data sharing. Peer learning is a great way to do that. It allows us to stretch the boundaries of our imagination and create space for those who hold different kinds of knowledge.

 

Where You Stand Matters

What we know and what we are permitted to know are often influenced by our gender, class, race, ethnicity, sexuality, and physical abilities. Put simply, knowledge is socially situated

It’s not hard to see how our position in society can affect what we know. Anyone, for instance, who’s ever had to experience homelessness knows more about the challenges and complexities of the situation than someone studying homelessness as a distant phenomenon. Those with lived experiences are often in a superior position to understand the problem and propose solutions.

How social positions dictate what we are permitted to know is a slightly different matter. Take the foundational assumption of modern economics that all human beings are by nature self-interested and calculating actors who always seek to get the greatest pleasure or profit out of any situation. Historically, the myth of the selfish, rational decision-maker (the ‘homo economicus’) has been put forward by a white, male political class. To this day, their psychological assumptions about human nature – disproved by experimental psychology time and again – continue to determine college curricula and policy decisions, thus shaping the world around us and what we know about it.

These things may sound philosophical, but they matter a great deal. After all, our socially defined and limited knowledge comes up in public health too.

In our previous post, we discussed how our notions of health ultimately define what health-related data we collect, and how our views of data and technology influence what health measures we implement. Given how knowledge is socially situated, the first step to getting data sharing right is to challenge and expand the very ideas we hold and take for granted.

We suggested that peer learning is a useful tool for stretching the boundaries of our imagination. Learning from others can help us combat our assumptions and biases while creating space for those who hold different kinds of knowledge. We supported this by examining the benefits of peer-learning within the All In network’s Affinity Groups.

In this post, we go into more detail about our findings.

 

Affinity Groups: Initial Findings

All In: Data for Community Health is a nationwide network of communities that share their successes and challenges from their data-sharing efforts with each other.² The Affinity Groups within the All In network are designed to foster peer learning around specific topics.

In 2021, All In launched eight Affinity Groups to explore topics such as health and housing, behavioral health, care coordination, and more. Discussions were led by the participants, while subject matter experts facilitated activities for each group. Peer-to-peer connections, consultancy, education, sharing toolkits, frameworks, resources, and in some cases technical assistance helped the participants better engage with the topics.

At the end of the nine-month program, DASH’s research and learnings team carried out a post-assessment of each group with the help of Ruchi Patel, a Northwestern University master’s student and Illinois Public Health Institute (IPHI) intern (2021-2022).³ Leading the process, the research team designed the evaluation tool for participants and subject matter expert leaders, while Patel assessed the program as a whole and designed the support staff survey tool.

The main findings from our assessment are summarized below:

  • 69% of total responses indicated that affinity group participation influenced the data-related practices of participants to some extent or to a great extent.
  • 61% of responses indicated that the participants integrated equity concepts into their work to some extent or to a great extent.
  • 89% of respondents reported that they would be somewhat or very likely to participate in a future affinity group.

 

Timely Discussions

Several participants shared that the Affinity Groups took place at an opportune time in their professional lives.

The Centering Racial Equity Throughout Data Integration group, for instance, was a six-part series that helped affinity group members consider positive and problematic practices in centering racial equity through the six stages of the data life cycle.⁴

One participant let us in on the relevance these discussions had to their work:

“[In my director-level role] it’s extremely important that I start to ground our data policies and practices in racial equity and in the utmost respect and deference to our communities. To that end, I’m thinking carefully about transparency around data collection, collecting only the minimum needed, and having very strict policies and transparency around data sharing and data use. I’m also thinking a lot about any algorithms we might build, and that we need to construct them in such a way that doesn’t perpetuate or exacerbate discrimination or racial/ethnic/gender/sexual orientation biases.”

 

 

Another example came from the Re-imagining Technology in Support of Cross-Sector Referral and Care Coordination group.

In the early stages of this group, participants let us know that they were interested in referral platforms and related technology. In response, we held informational sessions with potential subject matter expert leaders, including Greg Bloom with Open Referral (who led this group) and Yuri Cartier with SIREN (who shared in facilitation).

Following these sessions, we developed an approach that examined how communities can re-balance their relationship with technologies of resource referral and social care coordination. As a result, participants were able to dive deeper into the subject matter and consider themes they hadn’t originally considered before. Here’s how one participant put it:

“The Reimagining Technology Affinity Group was truly engaging and utilized very cool innovative approaches to tackling tough concepts in a virtual environment. The subject matter experts took their time to really dig deep into topics like governance, data standards, and trust. These are things that I often don’t learn about as the founder of a community-based organization. I have now been able to reinforce the importance of building community agency into the development of community plans through shared resources and data equity.”

 

Impact On Data-Related Practices

Over two-thirds of survey responses (69%) indicated that attending Affinity Group discussions influenced the data-related practices of the participants to some extent or to a great extent, suggesting that peer learning does indeed influence what kinds of data various collaborations collect.

Three themes emerged after participants shared anecdotes about what steps they had taken as a result of their participation:

  1. Early and authentic community engagement
  2. Harm reduction
  3. Data governance

 

One participant in the United Ways & 2-1-1 Partners Affinity Group, for instance, shared the following:

“The Affinity Groups have been extremely impactful for me because it allowed an opportunity to connect with like-minded leaders across the US. It also provided a safe space to share issues, successes and gain insight from others who are doing the work within 211’s, UW’s and other community agencies. I appreciated the ability to learn and connect with others because my previous experience was not coming from another 211 when I took the leadership role in MD. I was able to learn from those on the ground and with many years of experience to pull on with all my crazy ideas!”

 

 

Equity Related Practices

All In encouraged groups to incorporate health equity and racial injustice concepts, share lessons about shifting power to community members and related practices in multi-sector collaboration and data sharing, as well as share space with community members to draw on lived and learned experiences.

61% of responses indicated that equity concepts were integrated to some extent or to a great extent in their groups. Some key responses included the need for more resources from BIPOC authors, incorporation of more specific examples that illustrate equity concepts and principles, and more engagement directly with persons with lived experience of inequity in the development of materials. Two groups, in particular, focused on this issue: the Centering Racial Equity Throughout Data Integration and the Developing Meaningful Measures by Centering Community Voice groups.

One participant from the latter group shared:

“We are adopting a Cultural Humility statement to guide our work and will work on a Cultural Humility policy to recommend to the state for adoption. Making language understandable by eliminating or explaining acronyms and technical vocabulary along with providing bilingual materials or interpreters helps communication. Engaging those we hope to serve in the design of materials and activities is the most effective approach.”

 

Ebbs and Flows in Participation & Attendance

We saw overwhelming interest at the launch of our Affinity Groups. Meetings started strong and some of the discussions saw a surprisingly high number of participants.

But as the year progressed, some groups saw dwindling participation. Summer vacations, COVID virtual fatigue, along with conflicting schedules certainly could have been a factor.

 

 

Nevertheless, in our interpretation of the data, we concluded that participants found value in attending. They made valuable connections and found that their participation had an impact on their practices.

 

What’s Next?

In her research paper examining Affinity Groups,³ Ruchi Patel recommends four ways to improve the utility of these peer learning environments.

First, Patel suggests allocating more time to certain discussions while having those discussions take place less frequently. This recommendation comes with the added observation that smaller group sizes often lead to more engaged discussions. Naturally, length, frequency and group size should be evaluated on a case-by-case basis.

Second, the evaluation of Affinity Groups showed that participants were not very likely to engage in activities outside the group discussions. Patel’s recommendations include ensuring that participants are made aware of other relevant activities in advance, as well as making attendance of those events as easy as possible (e.g., free registration).

 

 

Third, Patel recommends creating a central email repository (so-called ‘listserv’) of all participants to ensure that sending out announcements can happen quickly and in a streamlined fashion. For those who aren’t involved in the administrative side of things, this may sound like a suggestion belaboring the obvious. However, contact management is a notorious thorn in the side of organizations. Those who engage in the grunt work of keeping contacts up to date know just how big the benefits are.

The final recommendation focuses on setting expectations from the get-go. Holding a kick-off meeting before Affinity Group discussions take place can help the facilitators and the participants arrive at a shared view of what everyone can expect to get out of the discussions. This also allows participants to share important resources with one another ahead of time. Ultimately, a kick-off meeting provides a much-needed opportunity to network, given how chances for participants to get to know each other during actual Affinity Group discussions are often limited.

If you’d like to start your own Affinity Group, make sure to keep an eye out for Part 3 of our Affinity Group blog series. If you haven’t already done so, read Part 1 here.

 


Footnotes:

¹ For more, see feminist standpoint theory.

² DASH manages the All In network in collaboration with their partners.

³ Patel, R., 2022. How Peer Learning Advances Multi-Sector Collaborations: An Evaluation of the All In: Data for Community Health Affinity Group Program. Northwestern University.

⁴ The six stages of the data cycle are outlined in the Centering Racial Equity Throughout Data Integration Toolkit.