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Assessment of knowledge, attitude and practice towards management of postpartum hemorrhage among third year nursing students at University of Namibia, main campus

2022· article· en· W4225003981 on OpenAlexaboutno aff
Victoria Shinyongo, Hilde Liisa Nashandi, Taimi Amakali-Nauiseb

Bibliographic record

VenueInternational Journal of Community Medicine and Public Health · 2022
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)MedicineNursingMaternal deathDescriptive researchPositive attitudeMaternal mortality rateFamily medicinePsychologyPopulationEnvironmental healthGeography

Abstract

fetched live from OpenAlex

Background: Postpartum hemorrhage (PPH) is commonly defined as blood loss of 500ml or more within 24 hours after birth. PPH is the leading cause of maternal mortality in the low-income countries and the primary cause of nearly one quarter of all maternal death globally. Namibia recorded the highest direct cause of maternal deaths for the period of April 2010 to March 2012 which was linked to bleeding after delivery. The purpose of the study was to assess the knowledge, attitude and practice towards management of PPH among third year nursing students at University of Namibia and to assess the maternal nursing care students rendered to woman with PPH.Methods: The researcher used descriptive research design and quantitative approach to collect the data. The researcher obtained primary data directly from 49 third-year nursing students of the University of Namibia (UNAM). Students filled in the Google form/online survey provided to them and all the responses were recorded on the researcher’s Google account.Results: From the study, 83.7% of the participants were females, while 14.3% were males and 2% prefer not to respond. The results indicate that majority of the participants are competent and have sufficient knowledge and positive attitude toward management of PPH.Conclusions: It is critical that student nurses at UNAM, Main campus are trained well with the necessary PPH knowledge to save maternal lives.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.066
GPT teacher head0.422
Teacher spread0.355 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2022
Admission routes1
Has abstractyes

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