Subtopic Deep Dive
FGM Prevalence and Social Norms
Research Guide
What is FGM Prevalence and Social Norms?
FGM Prevalence and Social Norms examines the geographic distribution, social drivers, and persistence of female genital mutilation/cutting practices using DHS survey data and social norm theory.
This subtopic analyzes prevalence rates across sub-Saharan Africa and beyond via Demographic and Health Surveys (DHS). Studies reveal social norms, gender power relations, and community influences as key persistence factors (Shell-Duncan et al., 2016; 79 citations). Over 20 papers from 2007-2020 map these dynamics, with Ahinkorah et al. (2020; 60 citations) identifying socio-economic determinants.
Why It Matters
Prevalence data from Modrek and Liu (2013; 46 citations) tracks declines in Egypt, guiding targeted interventions in high-prevalence zones like Sudan (Eldin et al., 2018; 59 citations). Yount et al. (2020; 35 citations) link community gender systems to daughters' FGM risk, informing norm-change programs. Gibson et al. (2018; 38 citations) expose hidden support via indirect questioning, enabling precise attitude-shift strategies that reduced FGM in Ethiopia communities.
Key Research Challenges
Measuring Hidden Support
Social desirability bias underreports FGM approval in surveys. Gibson et al. (2018; 38 citations) used indirect questioning in Ethiopia to reveal true prevalence. Standard DHS methods miss this, complicating intervention targeting.
Modeling Community Norms
Multilevel factors like gender systems drive persistence, requiring complex analyses. Yount et al. (2020; 35 citations) applied multilevel modeling in Egypt to link community influences to individual risk. Capturing these interactions demands large DHS datasets.
Tracking Prevalence Shifts
Declines vary by socio-economic status and region, needing longitudinal DHS tracking. Ahinkorah et al. (2020; 60 citations) analyzed sub-Saharan data to identify determinants. Serial surveys are resource-intensive across countries.
Essential Papers
A state-of-the-art synthesis on female genital mutilation/cutting: What do we know now?
Bettina Shell‐Duncan, Reshma Naik, C Feldman-Jacobs · 2016 · 79 citations
Efforts to end female genital mutilation/cutting (FGM/C) are a rising priority on many national and global agendas. Thus it is imperative to have a clear understanding of the scale and scope of the...
Debating medicalization of Female Genital Mutilation/Cutting (FGM/C): learning from (policy) experiences across countries
Els Leye, Nina Van Eekert, Simukai Shamu et al. · 2019 · Reproductive Health · 74 citations
Male circumcision and HIV prevention: ethical, medical and public health tradeoffs in low-income countries: Table 1
Stuart Rennie, Adamson S. Muula, Daniel Westreich · 2007 · Journal of Medical Ethics · 69 citations
Ethical challenges surrounding the implementation of male circumcision as an HIV prevention strategy
Socio-economic and demographic determinants of female genital mutilation in sub-Saharan Africa: analysis of data from demographic and health surveys
Bright Opoku Ahinkorah, John Elvis Hagan, Edward Kwabena Ameyaw et al. · 2020 · Reproductive Health · 60 citations
FGM/C decision-making process and the role of gender power relations in Sudan
Ahmed Eldin, Suad Babiker, Majdi M. Sabahelzain et al. · 2018 · 59 citations
This study by the Population Council, Nairobi and partners aimed to contribute to a better understanding of female genital mutilation/cutting (FGM/C) in Sudan and the way different families perceiv...
The ongoing violence against women: Female Genital Mutilation/Cutting
Jacinta Khasiala Muteshi, Suellen Miller, José M. Belizán · 2016 · Reproductive Health · 55 citations
Female Genital Mutilation/Cutting (FGM/C) comprises different practices involving cutting, pricking, removing and sometimes sewing up external female genitalia for non-medical reasons. The practice...
Exploration of pathways related to the decline in female circumcision in Egypt
Sepideh Modrek, Jenny Liu · 2013 · BMC Public Health · 46 citations
Reading Guide
Foundational Papers
Start with Modrek and Liu (2013; 46 citations) for Egypt decline pathways via DHS; Brown et al. (2013; 45 citations) for EU behavior change integrating social cognitive approaches.
Recent Advances
Prioritize Shell-Duncan et al. (2016; 79 citations) synthesis; Ahinkorah et al. (2020; 60 citations) on sub-Saharan determinants; Yount et al. (2020) multilevel Egypt analysis.
Core Methods
DHS survey multilevel modeling (Yount et al., 2020); indirect questioning (Gibson et al., 2018); socio-economic regressions (Ahinkorah et al., 2020).
How PapersFlow Helps You Research FGM Prevalence and Social Norms
Discover & Search
Research Agent uses searchPapers and exaSearch to query 'FGM prevalence DHS social norms sub-Saharan Africa,' surfacing Shell-Duncan et al. (2016; 79 citations) as top hit. citationGraph reveals clusters around Ahinkorah et al. (2020), while findSimilarPapers expands to Yount et al. (2020) for Egypt-specific norms.
Analyze & Verify
Analysis Agent runs readPaperContent on Gibson et al. (2018) to extract indirect questioning methods, then verifyResponse with CoVe checks hidden support claims against DHS data. runPythonAnalysis loads prevalence stats from Ahinkorah et al. (2020) via pandas for GRADE evidence grading, verifying socio-economic correlations statistically.
Synthesize & Write
Synthesis Agent detects gaps in norm-change interventions post-Modrek and Liu (2013), flagging underexplored EU migration effects (Brown et al., 2013). Writing Agent applies latexEditText and latexSyncCitations to draft reports, with latexCompile generating polished PDFs and exportMermaid visualizing DHS trend diagrams.
Use Cases
"Analyze DHS data trends in FGM prevalence across sub-Saharan countries"
Research Agent → searchPapers('DHS FGM prevalence') → Analysis Agent → runPythonAnalysis(pandas on Ahinkorah et al. 2020 data) → matplotlib plots of socio-economic determinants output.
"Write LaTeX review on social norms driving FGM persistence"
Synthesis Agent → gap detection (Eldin et al. 2018) → Writing Agent → latexEditText(draft) → latexSyncCitations(Shell-Duncan 2016) → latexCompile → PDF with norm diagrams via exportMermaid.
"Find code for analyzing FGM survey data from papers"
Research Agent → paperExtractUrls(Yount et al. 2020) → Code Discovery → paperFindGithubRepo → githubRepoInspect → Python scripts for multilevel modeling output.
Automated Workflows
Deep Research workflow conducts systematic review of 50+ DHS-based FGM papers: searchPapers → citationGraph → GRADE grading → structured prevalence report. DeepScan applies 7-step analysis to Gibson et al. (2018): readPaperContent → runPythonAnalysis(indirect methods) → CoVe verification → norm bias checkpoint. Theorizer generates hypotheses on norm shifts from Modrek and Liu (2013) trends.
Frequently Asked Questions
What defines FGM Prevalence and Social Norms?
It maps geographic FGM distribution and social drivers like community gender systems using DHS data and norm theory (Shell-Duncan et al., 2016).
What methods measure hidden FGM support?
Indirect questioning reveals underreported approval, as in Gibson et al. (2018; PLoS ONE; 38 citations) from Ethiopia surveys.
What are key papers on prevalence drivers?
Ahinkorah et al. (2020; 60 citations) analyze DHS socio-economic determinants; Yount et al. (2020; 35 citations) model Egypt community risks.
What open problems persist?
Longitudinal tracking of norm shifts amid migration and medicalization debates; underexplored hidden support in non-African contexts (Brown et al., 2013).
Research Female Genital Mutilation/Cutting Issues with AI
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