Thread by @georgeinstitute

(1/10) ❗️Disclaimer❗️: Not an #intersectionality expert but care about #intersectionality & #healthequity. I want my research to reflect personal values. Below are just some of my musings on this ⬇️

(2/10) In my #epidemiology research, often constrained by what data is available to me...

e.g. forced to conflate #sex & #gender, treat gender as binary construct, collapse #ethnicity into meaningless categories etc. This is not good research! ☠️

(3/10) Most importantly, not doing justice to the people my research is aimed to serve. Want to change that.

(4/10) So what is #intersectionality? Fave definition from @AKapilashrami #ProfHankivsky here:

(bit.ly/3hR05V0)

(5/10) And how can we implement it better in #healthresearch and #healthpolicy ⁉️

(6/10) 1⃣ Break down silos – we NEED multi-disciplinary research. I can tell you about #studydesign, less verse in #powerstructures, #gendertheory or #structuralinequities. We can’t all be the triple whammy that is @feminineupheave - doctor, sociologist & epidemiologist🤯🤕

(7/10) 2⃣ Accept that a single research project won’t provide all the answers. We need #culturalshift in how we prioritise & conduct research to make sure the totality of evidence captures intersectional complexities.

(8/10) 3⃣ Mixed methods research is key. Epidemiology looks at health in a population but why can’t we include individuals’ voices during data interpretation? What would this look like? 🤔

(9/10) 4⃣ Better representation and more diversity in research – both research participants and the researchers. Projects like #NIHRInclude (bit.ly/3MvcsnZ) are important for this. But we also need to build #publictrust.

(10/10) 🖐️ Data data data = visibility visibility visibility. Without applying an intersectional lens to the collection of data, we're blinkered from the very beginning🙈