Woman and girl-centred care for those affected by female genital mutilation: a scoping review of provider tools and guidelines
Bibliographic record
Abstract
BACKGROUND: A woman and girl centred, rights-based approach to health care is critical to achieving sexual and reproductive health. However, women with female genital mutilation in high-income countries have been found to receive sub-optimal care. This study examined documents guiding clinicians in health and community service settings in English-speaking high-income countries to identify approaches to ensure quality women and girl-centred care for those with or at risk of female genital mutilation. METHOD: We undertook a scoping review using the integrative model of patient-centredness to identify principles, enablers, and activities to facilitate woman and girl-centred care interactions. We developed an inclusion criterion to identify documents such as guidance statements and tools and technical guidelines, procedural documents and clinical practice guidelines. We searched the databases and websites of health professional associations, ministries of health, hospitals, national, state and local government and non-government organisations working in female genital mutilation in the United Kingdom, Ireland, Canada, The United States, New Zealand, and Australia. The Appraisal of Guidelines for Research and Evaluation tool was used to appraise screened documents. FINDINGS: One-hundred and twenty-four documents were included in this scoping review; 88 were developed in the United Kingdom, 20 in Australia, nine in the United States, three in Canada, two in New Zealand and two in Ireland. The focus of documents from the United Kingdom on multi-professional safeguarding (62), while those retrieved from Australia, Canada, Ireland, New Zealand and the US focused on clinical practice. Twelve percent of the included documents contained references to all principles of patient-centred care, and only one document spoke to all principles, enablers and activities. CONCLUSION: This study demonstrates the need to improve the female genital mutilation-related guidance provided to professionals to care for and protect women and girls. Professionals need to involve women and girls with or at risk of female genital mutilation in the co-design of guidelines and tools and evaluation of them and the co-production of health care.
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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 | 0.051 | 0.189 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.030 | 0.027 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".