Chapter 7 200 however, is mostly based on cause and effect modeling.8 This positivistic and reductionist approach can hinder the identification of dynamic interactions and contextual gendered social practices that impact individual health. In complex systems, the question driving scientific inquiry should not be “what is the effect size and is it statistically significant once other variables have been controlled for?” but rather “does this intervention contribute, along with other factors, to the desirable outcome?”.9 This requires a methodology that includes in-depth, mixed-methods case studies that can act as concrete, context-dependent examples. It includes ethnographic narratives that focus on interconnectedness of multiple factors that come together as a whole from different perspectives.10 To avoid the reduction of gender sensitive research in clinical settings to the sole disaggregation of data based on gender identities, multimethod approaches in realworld social settings are needed. These approaches can enable the investigation of interrelationships between gender identities, contextual gender norms and roles and their impact on individual health, as well as their interaction with intersecting social factors such as age, sexual orientation, ethnicity, and socio-economic status. Rather than using gender identity as proxy for an intricate social process, a complexityinformed approach to gender will allow to focus on when, how and for whom gender becomes a relevant social factor that influences health outcomes. A complexity-led approach to gender in biomedicine should focus on how people are ‘doing gender’ and when and how this impacts individual care needs. It starts with close reading of patients’ narratives to understand how gendered aspects arise in individual experiences of illness (case studies) and through narrative reviews. It involves a deconstruction of gender into observable variables that become meaningful in a particular context; from individual mores, community customs, to institutional mechanisms where aspects of gender become conjunctively relevant as a determinant of health. It is based on emergent causality where multiple aspects of gender interact for a particular health outcome, but none can be argued to have a fixed ‘effect size’. Incorporating complexity theory into the study of gender and health will not only contribute to a more nuanced understanding of the construct of gender but can also help to overcome the reproduction of ingrained preconceptions and stereotypes that stand in the way of equitable and personalized care for all.
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