The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
How to do (or not to do)… gender analysis in health systems research
Open accessAbstract
Gender—the socially constructed roles, behaviours, activities and attributes that a given society considers appropriate for males, females and other genders—affects how people live, work and relate to each other at all levels, including in relation to the health system. Health systems research (HSR) aims to inform more strategic, effective and equitable health systems interventions, programs and policies; and the inclusion of gender analysis into HSR is a core part of that endeavour. We outline what gender analysis is and how gender analysis can be incorporated into HSR content, process and outcomes. Starting with HSR content, i.e. the substantive focus of HSR, we recommend exploring whether and how gender power relations affect females and males in health systems through the use of sex disaggregated data, gender frameworks and questions. Sex disaggregation flags female–male differences or similarities that warrant further analysis; and further analysis is guided by gender frameworks and questions to understand how gender power relations are constituted and negotiated in health systems. Critical aspects of understanding gender power relations include examining who has what (access to resources); who does what (the division of labour and everyday practices); how values are defined (social norms) and who decides (rules and decision-making). Secondly, we examine gender in HSR process by reflecting on how the research process itself is imbued with power relations. We focus on data collection and analysis by reviewing who participates as respondents; when data is collected and where; who is present; who collects data and who analyses data. Thirdly, we consider gender and HSR outcomes by considering who is empowered and disempowered as a result of HSR, including the extent to which HSR outcomes progressively transform gender power relations in health systems, or at least do not further exacerbate them.
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Citations
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Cited by
Disrupting gender norms in health systems: making the case for change
Hay, K., McDougal, L., Percival, V., Henry, S., Klugman, J., Wurie, H., Raven, J., Shabalala, F., Fielding-Miller, R., Dey, A., et al. (2019) · The Lancet · doi:10.1016/s0140-6736(19)30648-8 · Cited by 442
Self-citationWhy sex and gender matter in implementation research
Tannenbaum, C., Greaves, L., & Graham, I. D. (2016) · BMC Medical Research Methodology · doi:10.1186/s12874-016-0247-7 · Cited by 386
Xiong, C., Biscardi, M., Astell, A., Nalder, E., Cameron, J. I., Mihailidis, A., & Colantonio, A. (2020) · PLOS ONE · doi:10.1371/journal.pone.0231848 · Cited by 290
Smith, J. (2019) · Gender & Development · doi:10.1080/13552074.2019.1615288 · Cited by 256
Feletto, M., & Sharkey, A. (2019) · BMJ Global Health · doi:10.1136/bmjgh-2019-001711 · Cited by 63
Metadata
- Authors
- Morgan, R., George, A., Ssali, S., Hawkins, K., Molyneux, S., & Theobald, S.
- Venue
- Health Policy and Planning
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-04-26
- Volume
- 31
- Issue
- 8
- Pages
- 1069-1078
- ISSN
- 0268-1080 (ISSN-L)
- 1460-2237
- OpenAlex
- W2343806465
- Cited by
- 286
- References
- 44
- FWCI
- 15.11
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.