Abstract
Background: The traditional presentation of results of cognitive test and surveys using simple percentages or average score obscures topics failed or mastered by test takers. However, the Rasch technique revolutionises the presentation of a test result by connecting respondent latent knowledge (or ability) with the test items using Wright maps. Aim: To assess nurses and midwives’ knowledge of managing primary postpartum haemorrhage using a Wright map Methods: A twelve-item dichotomous (YES/NO) computer-based test developed from the recently updated WHO’s treatment bundle was presented to the respondents for fifteen minutes. A nine-member panel reviewed the test to ensure clarity and relevance to Nigeria’s public maternity setting. All the respondents were nurses and midwives with previous experience of responding to primary postpartum haemorrhage. Ethical approval was provided by the University of Huddersfield and the nurses’ association. After eight weeks of data collection, both descriptive and inferential analyses were conducted using a Wright map. Results: The 180 responses analysed on a Wright map showed that the lowest, average and highest measures to be 476.3 logits, 495.9 logits and 521.7 logits respectively. Also, 178 (98%) respondents incorrectly answered the question on the source of treatment evidence but correctly answered that uterine atony is the main cause of postpartum haemorrhage. However, all the respondents who scored below average (495.6 logits) incorrectly answered the question on oxytocin as the best uterotonic. Conclusions: Wright map analysis confirms the problem of the inadequate knowledge of maternity staff as a major barrier to the effective treatment of maternal bleeding. A significant difference was found in the knowledge of the treatment among the three levels of maternity settings, implying the need for effective educational intervention strategies.
| Original language | English |
|---|---|
| Article number | 6 |
| Number of pages | 13 |
| Journal | International Medical Education |
| Volume | 4 |
| Issue number | 2 |
| Early online date | 26 Mar 2025 |
| DOIs | |
| Publication status | Published - 1 Jun 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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