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Record W2610526409 · doi:10.4314/thrb.v19i2.5

Prevalent use of herbs for reduction of labour duration in Mwanza, Tanzania: are obstetricians aware?

2017· article· en· W2610526409 on OpenAlexaboutno aff
Haruna Dika, Mauki Dismas, Shabani Iddi, Richard Rumanyika

Bibliographic record

VenueTanzania journal of health research/Tanzania Journal of Health Research · 2017
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsnot available
FundersUniversity of Health and Allied Sciences
KeywordsTanzaniaMedicineChildbirthHerbPregnancyTraditional medicineEnvironmental healthMarital statusQuarter (Canadian coin)DemographyMedicinal herbsPopulationGeography

Abstract

fetched live from OpenAlex

Background: The use of herbs during pregnancy and labour is rapidly increasing because the herbs are considered to be natural and therefore free of risks. Despite of this perception, a number of herbs have been reported to have negative effects to the new-borns and the mothers. Therefore, this study aimed to determine the prevalence and factors associated with the use of herbs during labour among women in Mwanza, Tanzania.Methods: The study involved women who delivered at Bugando Medical Centre and Sekou Toure Hospital in Mwanza, north-western Tanzania. Data were collected using questionnaires. Comparison of prevalence of herb use by various factors was done. Results: A total of 178 women were involved in the study. The mean age of participants was 26.6 ± 5.4 years. The prevalence of herb use was found to be 23.0%. The use of herbs was significantly associated with marital status (p = 0.011) and the use during previous deliveries (p = 0.000).Conclusion: The study findings signify that, about a quarter of women in Mwanza use herbs during childbirth and the use encourages recurrent use of these herbs in subsequent pregnancies. A large scale survey is recommended to determine the extent of use of traditional herbs during pregnancy and childbirth countrywide. Studies to determine the toxic profile of the herbs which are used are also needed so as to address the matter to the community.

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.

How this classification was reachedexpand

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)0.058
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0580.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.002
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.004
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 head0.502
GPT teacher head0.540
Teacher spread0.038 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2017
Admission routes1
Has abstractyes

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