Midwives’ Perceptions Regarding the Use of the Cardiotocograph Machine as an Intrapartum Monitoring Tool in Namibia: A Qualitative Research Study
Bibliographic record
Abstract
Although, at the time of this study, the cardiotocograph machine was the acceptable monitoring tool to be used intrapartum, its appropriate use was a matter of concern for midwives globally. This article reports the findings of a qualitative study which investigated the perceptions of midwives, who were working in a labor ward in a public referral hospital in Namibia, regarding the use of the cardiotocograph machine. The objectives of the study included: to explore and describe the perceptions of midwives working in a labor ward in Namibia regarding the use of the cardiotocograph machine as a labor monitoring tool; and to explore and describe how midwives working in a labor ward in Namibia perceived informing women who were in labor about the use of the cardiotocograph machine as a labor monitoring tool. The study site was a public referral hospital which offered services to the five northern regions of Namibia. The requisite data was collected using semi-structured, one-on-one interviews which were conducted with seventeen (17) purposively selected participants. The interviews were recorded on an audio device. The spiral method of data analysis was adopted. The study findings revealed that the participants had varying perceptions on the use of the cardiotocograph machine intrapartum and, as such, perceived its use as a challenge. It was concluded that midwives need to be empowered via refresher courses with regard to the use of cardiotocograph machine to ensure optimum results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".