Last week my colleagues and I published a paper in
Implementation Science: “Exchanging and Using Research Evidence in Health Policy Networks: a statistical network analysis.” We set out
to understand which network factors might increase the likelihood that actors
exchange research evidence with each other. Here's why this is important:
- When people exchange evidence, they are more likely to use evidence,
- The use of research evidence can help improve the effectiveness and equity of health policies, and;
- Evidence exchange is a social process and thus should be studied using methods that enable the measurement and modeling of the social dimension.
Using exponential random graph models, we found that network structure, more than individual
attributes, explained why people provided or requested evidence in their
policy networks, and whether they used it to inform their own decision-making.
To help explain these findings, I provide some anecdotes
from my life in Burkina Faso.
Point 1: Leverage existing relationships
People in Burkina Faso are entrepreneurial. My good friend
Ai is young but has held any number of roles as research assistant, language
instructor, translator, guest house owner, CEO, etc. How does Ai succeed in these
roles? In addition to her intelligence, she understands the power of her networks and the importance of trustworthiness.
People's networks are large, and effective. It
would take 20 minutes to drive 100 meters with Mme Salimata Ki, my mentor in
the Ministry, as she knew everyone we drove past, and stopped to either have a
conversation with them or give them food or money if they needed it. My access
to respondents was thanks to her, and the woman could move mountains. I would
love to map her network. Actually, it reminds me of a study underway by JP
Onnela at Harvard where they hypothesize that the structure of participants at the Kumbh Mela replicates the global network
structure in India. Salimata is the Kumbh Mela of Burkina Faso.
The point is: Burkinabe’s are used to playing many roles in
their networks. We found that policy actors were more likely to exchange evidence with each other if they had other types
of relationships together. I called this ‘layering’ in the paper but it is
also called multiplexity in network terms.
What can we do? If
you have evidence to disseminate, encourage people to share it with their
friends, colleagues, officemates, family, tailor, butcher, etc. Journal
websites do this by allowing users to share on social media, but we know that
face-to-face ties – strong ties – are more likely to lead to useful knowledge
exchange because they help make information 'sticky.' So instead of the Facebook icon, let’s make a ‘talk’ icon and put it
on evidence outputs. Of course journal clubs are perfect for this. Point 2: Don’t eat too much street meat
There can be too much of a good thing, even in the world of
grilled meats and evidence exchange. On the meat front, I attended the annual
Festivale de grillades (grilled meat festival) in Ouagadougou with a close
friend from the U.S. There was an entry fee, so we were incentivized to eat as
much as possible. We egged each other on to eat and eat, to the point that we
began to perspire and felt dizzy, and this lasted for at least 24 hours. I believe clinicians refer to this as "meat sweats." I
doubt we would have succumbed to the meat if we had been with a more diverse
group of friends. Salimata would not have let me eat so much street meat!
In our study of evidence exchange networks, one policy issue
– community integrated management of childhood illness -- showed much higher frequency of exchange (and use) of
evidence than the other issues. This network also showed a propensity to
form cliques, aka triangles. Triangles represent a social process that we observe in networks at a greater frequency that can be explained by chance alone: people are more likely to form a relationship if they have a friend in common. When I see a network with lots of triangles, I think, "empirical signature of cohesive and congruent
policy communities!" (or, female adolescent friendship network). Indeed, analyses from my other chapters show that despite all
this exchange and ‘use’ in this network, evidence wasn’t used instrumentally to solve
tough problems about child health. It was used symbolically to justify pre-determined policy positions, mainly of development partners and donors. In other words, people came together to eat meat, it was tasty (i.e., the Lancet Child Survival series), they ate a lot, but
eventually it became difficult to discern whether the meat still tasted good or they continued to eat because everyone else was.
In other words, we need to support evidence exchange and
use, but we also need to make sure that people have the capacity to find and interpret the evidence and that network structure
does not encourage group-think over innovation.
What can we do?
Try to avoid attending meat festivals with your best friend. Instead, go with a diverse group. Invite some vegetarians! You will be more likely to try
new things, and your stomach will thank you. The National AIDS Council
(CNLS-IST) did this in the early 2000s by requiring representation of civil
society and PLHIV, ensuring the diversity of the Council and entrenching the
capacity and access of civil society organizations in the HIV policy domain. This
has had a lasting positive effect on the HIV policy network structure and its
effectiveness in Burkina Faso; we found the HIV actors were more likely to use
evidence when it was provided to them, and this network ultimately produced and used evidence to instrumentally achieve policy change.
Point 3: Use person-net, not Internet
If I had a nickel for every person (from North America and
Europe) who said, “Oh! You’re studying Facebook in Burkina Faso,” I’d have
about 85 cents (which is significant). Social media and online social networking is exciting, but not very
useful in Burkina Faso circa 2011.
Poor internet infrastructure poses one of the biggest challenges to the fidelity of many of the knowledge transfer, policy translation, and implementation science interventions that are shipped off to West Africa and elsewhere. When I arrived in Burkina in 2011 I was kindly given an office in
the Ministry of Health. I had no internet where I was living, there was really
no public internet (although I single-handedly supported the tonic water
industry in hotel lobbies), and the connection at the Ministry was really slow.
It was virtually impossible to read emails, much less download a research
article to inform policy with. So I looked around my office and realized that
if I bypassed the wifi router and plugged the Ethernet cord directly from the
wall into my computer, the internet performed much faster. Did it cross my mind
that this router might be used by other offices? Briefly, but no one said anything.
And then ONE MONTH LATER someone knocked on my door and asked whether they
could look at the router. I had turned off the internet to the entire Department.
Other common reasons for internet outages
included:
- Deep-sea underground digging in Guinea or Cote d’Ivoire had cut the internet cable. THE internet cable. For the continent.
- The popularity of copper jewelry meant that local internet cables were often dug up to make bracelets.
Needless to say, downloading research articles is not high
on your list of things to do when you have a brief window of connectivity. I
found that this meant that certain actors (i.e., development partners) had
better access to evidence than others, leading to the inequitable distribution of normative power. What can we do? We should be much more creative about the media we use to disseminate research evidence. Knowledge brokers, policy dialogues, printed policy briefs are all possible examples. Salimata puts research evidence on a CD to share with colleagues. Evidence at your fingertips.
Final point: My network made me do it!
I shook hands with a crocodile in Burkina Faso. My personal
attributes – risk preference, IQ, education, past experience – would not have predicted such a thing. But my husband encouraged me, and Salimata
facilitated it, and so I went to a village of sacred crocodiles and sat on one.
We know about social influence and heuristics in decision-making –
both came into play in my case -- but what is even more compelling, and also more
abstract, is the role of social structure on our decisions. That is, we are
influenced not only by what our friends are doing, but how are friends are connected to each other and to others. And this is
the main point of our paper. Controlling for individual attributes and shared
traits, whether or not two people
exchanged evidence was best explained by their network's structure.
What can we do?
As noted above, we can design networks that are more conducive to appropriate evidence exchange and use. I'm beginning to work towards this with NetworkRx, a very beta simulation tool to see the effect of network structure on policy outcomes. And stay away from crocodiles.
Hope you find the paper delicious.
