Scope of practice of midwifery within the nursing profession- Perception of Midwifery Trained Registered Nurses a qualitative study
Bibliographic record
Abstract
Objectives: Midwifery scope of practice within the nursing profession has been a contentious issue in South Asian settings. To address a knowledge gap in Sri Lanka, we explored Midwifery Trained Registered Nurses’ (MTRNs) perceptions of their role in intra-natal and post-natal units in Tertiary care hospitals in Western province of Sri Lanka. Methods: Three focus group discussions (FGDs) were conducted with 22 MTRNs from selected hospitals. FGDs were recorded, transcribed verbatim, and analyzed using qualitative content analysis. Results: Three emerging themes were identified: role of MTRN, role of other professionals and role disagreements. MTRNs described ‘my role’ in terms of individual tasks, placing themselves outside of the arena of the others in the team. Their role was characterized by observation of their own seniors and peers. ‘Others’ including midwives and medical officers, who were identified outside of the realm of their group, performed tasks and held responsibilities which constantly overlapped with their own. Disagreements with regards to their roles and responsibilities were common between MTRN and others, resulting in confusion, frustrations and conflicts. Labour room was the most contentious setting where lack of clear role identification created conditions for conflict. Conclusions: MTRN’s practice was circumstance driven and limited in scope. Different professional groups lacked clarity regarding their own roles and responsibilities and as a result, failed to develop a team identity. Clear job descriptions, written protocols and delegation of responsibilities should define MTRN’s scope of practice in order to improve the dynamics within maternity healthcare team.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".