95739 Chap.5 Co-design and Intersectionality in Epidemiology
Co-design and Intersectionality in Epidemiology
Sustainability inside the discipline
Week 3 argues that epidemiology and biostatistics must account for environmental change and integrate social determinants with ecological factors, which most benefits vulnerable populations.
Co-design
Co-design involves affected communities in every stage of research, as the oral health study with Aboriginal communities did through consultation, adapted surveys and yarning circles.
Whom and which epidemiologists count
Doan and colleagues show how fixed categories, additive interaction terms, imputation and weighting can hide people, and how a narrow workforce shapes what is studied.
Why it matters for practice
Research that counts people accurately, and is shaped by them, produces interventions that fit their lives; the Task B quiz tests exactly these arguments.
What this chapter covers
- 01
Sustainability as a framework in epidemiology
- 02
Co-design across the research process
- 03
The Aboriginal oral health study
- 04
Workforce diversity and sustainability
- 05
Predetermined categories and nonresponse
- 06
Intersectionality and the interaction term
- 07
Imputation, weighting and overgeneralisation
Worked example · free
Match co-design actions to the stages of a study
- 1Choosing the question belongs to planning.
- 1Testing the survey wording belongs to planning as well, and shapes data collection.
- 1Resident interviewers carry out data collection.
- 1Reviewing patterns belongs to analysis and interpretation, where local knowledge prevents misreadings.
- 1Writing the community report is translation, turning findings into action.
Key terms
- Imputation
- A statistical method that fills in missing data on assumptions that may be wrong.
- Yarning Circle
- A traditional conversational method used to collect data in a way that builds trust and open communication.
- Epidemiological Transition
- The idea of a shift in disease patterns over time, which the module notes is increasingly challenged.
Co-design and Intersectionality in Epidemiology FAQ
What is co-design in epidemiological research?
A collaborative approach in which stakeholders, especially the people affected, take an active part in designing and running the research rather than researchers making every decision. Week 3 stresses that it applies from planning and data collection through to interpretation and translation of the results.
Why do Doan and colleagues criticise interaction terms for intersectionality?
They call the usual approach theoretically vague because it treats identities as additive, combining category effects. Crenshaw argues that living at an intersection is more than racism and sexism added together, so the authors want people at those intersections involved in the research itself.
What are the risks of imputation and weighting?
Imputation can rest on inaccurate assumptions and never explains why people are missing. Weighting a small group up to match a population makes a few respondents stand for many, which risks overgeneralisation, much like asking a few people to explain the experience of a whole race.
How does workforce diversity support sustainability?
The module says a diverse workforce makes initiatives more relevant and trusted, increases participation in studies, encourages new methods and cross-disciplinary collaboration, and helps the professions adapt to emerging health challenges and social change.
Why did co-design matter in the oral health study?
Aboriginal leaders, Elders and health workers shaped the question, the survey wording, the use of yarning circles and the interpretation of results. The module says this produced more accurate, meaningful data, targeted interventions and a community that felt the research belonged to it and could be trusted.
What does the Task B quiz cover?
It is an in-class quiz of ten questions, worth 10%, held in Week 5 and based on the Week 3 case drawn from the Doan paper. The task page lists eight guiding questions, from intersectionality and diversity to bias, social categories, overgeneralisation and the effects of imputation and weighting.
Why might researchers misread results without community input?
The module imagines a rural study of social support and mental health in which family gatherings matter greatly. Researchers far from the community might misinterpret or miss that finding; involving community members in interpretation keeps results accurate, culturally relevant and useful to the people studied.
Assessment move
For Task B, answer each of the eight guiding questions in two sentences with your own example. Learn the three Doan arguments, whom epidemiologists count, what they count and which epidemiologists count, and the two methods they question. For co-design, be able to name one action at each research stage, and use the oral health study as your evidence that it works.
Read the Brough (2001) article before the tutorial and note one way epidemiological description carried social assumptions.
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