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Record W4225263754 · doi:10.1186/s12978-021-01252-2

Addressing a silent and neglected scourge in sexual and reproductive health in Sub-Saharan Africa by development of training competencies to improve prevention, diagnosis, and treatment of female genital schistosomiasis (FGS) for health workers

2022· article· en· W4225263754 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueReproductive Health · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsBruyèreUniversity of Ottawa
FundersGrand Challenges CanadaWorld Health Organization
KeywordsReproductive healthMedicinePublic healthReproductive medicineSex organFamily medicineEnvironmental healthGynecologyNursingPopulationPregnancy

Abstract

fetched live from OpenAlex

BACKGROUND: Schistosomiasis is an acute and chronic disease caused by parasitic worms, that can take two main forms: intestinal or urogenital. If left untreated, the urogenital form can lead to female genital schistosomiasis (FGS) in women and girls; frequently resulting in severe reproductive health complications which are often misdiagnosed as sexually-transmitted infections (STIs) or can be confused with cervical cancer. Despite its impact on women's reproductive health, FGS is typically overlooked in medical training and remains poorly recognized with low awareness both in affected communities and in health professionals. FGS has been described as the one of the most neglected sexual and reproductive health issues in sub-Saharan Africa (Swai in BMC Infect Dis 6:134, 2006; Kukula in PLoS Negl Trop Dis 13:e0007207; Joint United Nations Programme on HIV/AIDS (UNAIDS) 2019). Increased knowledge and awareness of FGS is required to end this neglect, improve women's reproductive health, and decrease the burden of this preventable and treatable neglected tropical disease. METHODS: We conducted interactive virtual workshops, in collaboration with the World Health Organization (WHO), engaging 64 participants with medical and public health backgrounds from around the world to establish standardized skills (or competencies) for prevention, diagnosis, and treatment of FGS at all levels of the health system. The competencies were drafted in small groups, peer-reviewed, and finalized by participants. RESULTS: This participatory process led to identification of 27 skills needed for FGS prevention, diagnosis, and management for two categories of health workers; those working in a clinical setting, and those working in a community setting. Among them, ten relate to the diagnosis of FGS including three that involve a pelvic exam and seven that do not. Six constitute the appropriate behaviors required to treat FGS in a clinical setting. Eleven address the community setting, with six relating to the identification of women at risk and five relating to prevention. CONCLUSION: Defining the skills necessary for FGS management is a critical step to prepare for proper diagnosis and treatment of women and girls in sub-Saharan Africa by trained health professionals. The suggested competencies can now serve as the foundation to create educative tools and curricula to better train health care workers on the prevention, diagnosis, and management of FGS.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.765
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.090
GPT teacher head0.365
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it