Is female genital mutilation/cutting associated with adverse mental health consequences? A systematic review of the evidence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: The adverse physical consequences of female genital mutilation/cutting (FGM/C) have been thoroughly investigated and documented. Yet, we know little about the adverse mental health consequences of the practice. To fill this research gap, we systematically reviewed studies that assessed any adverse mental health consequences related to FGM/C. METHODS: We searched four databases from inception to 21 December 2018. We then reviewed all titles and abstracts for relevant studies. We used the National Institutes of Health quality assessment tool to appraise the quality of each study and the Newcastle-Ottawa Scale to rate the risk of bias within studies. RESULTS: We included 16 studies in this review; only six studies examined the association between FGM/C and adverse mental health outcomes as the sole research question. Among the included studies, 10 were conducted at the participants' country of origin. The sample size of the populations studied ranged from 3 to 4800 participants. Only one study received a rating of 'good' methodological quality.Fourteen of the 16 studies reported an association between FGM/C and at least adverse mental health outcome. These included eight studies that reported a higher burden of adverse mental health outcomes among women who underwent FGM compared with women who did not undergo FGM/C. Four studies reported a correlation between the severity of FGM/C and the severity of adverse mental health outcomes. CONCLUSION: This systematic review documents an association between FGM/C and adverse mental health outcomes. Importantly, our review demonstrates the need for more rigorous research on the topic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it