Women's Daily Life Experiences After Female Genital Mutilation – A Scoping Review
Bibliographic record
Abstract
Introduction: Female Genital Mutilation (FGM) affects over 200 million women worldwide, leading to profound physical, psychological, and societal challenges. This scoping review explores the impact of FGM on women’s daily lives from an occupational therapy and occupational science perspective. Aim: To synthesize existing knowledge about women’s daily life experiences after FGM and its implications for occupational participation.Method: A scoping review, guided by Arksey and O’Malley’s framework as refined by Levac et al., analysed 14 studies published between 2002 and 2023 across five electronic databases: Assia, Cinahl, PubMed, Medline, and Scopus. The studies originated from diverse geographical contexts, including four from Canada, three from Nigeria, two from Sweden, and one each from the UK, Norway, Belgium, France, and a global study.Results: Four themes emerged, focusing on contextual influences in daily life: (1) marital and sexual life, highlighting pain and strained relationships; (2) everyday occupations and responsibilities, disrupted by chronic pain; (3) healthcare access, marked by stigma and cultural misunderstandings; and (4) cultural identity, balancing traditional values with integration in new cultural settings.Conclusions: FGM significantly disrupts daily life, with chronic pain and cultural stigmas influencing occupational participation. OT offers potential for addressing these issues through culturally sensitive, client-centered care.Significance: This study underscores the need for OT interventions that integrate cultural humility and holistic approaches to enhance the well-being and autonomy of women affected by FGM.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".