Patterns and influences of interprofessional communication between midwives and CAM practitioners: a preliminary examination of the perceptions of midwives
Bibliographic record
Abstract
Women are increasingly using complementary and alternative medicine (CAM) such as naturopathy and Western herbal medicine during their pregnancy and midwives have described an affinity for CAM. However, the reality of the midwife-CAM practitioner interface remains largely unexplored. This study reports findings from a pilot survey of midwives (n=53), examining their behavioural patterns and attitudes towards communication with CAM practitioners. The results indicate that less than one quarter (22%) of midwives initiated formal CAM practitioner communications, despite 83% of respondents believing formal communication should exist. Nearly half (43%) of midwives lacked a clear understanding of the legal implications of recommending CAM (either products or practitioners) within their practice, whilst 67% reported understanding their workplace policies regarding CAM referral and use as part of their practice scope. Interprofessional behaviour and attitudes towards communication with CAM practitioners was found to be associated with professional experience, age and midwife involvement with research and education. More focus is needed on education and legislative support for safe CAM use in maternity care to develop procedures, guidelines and protocols for clinicians from discrete professional groups providing concurrent care to pregnant women. Achieving safe and collaborative interprofessional maternity care within the CAM field requires close attention from researchers, clinicians, hospital administrators and policy makers. © National Herbalists Association of Australia 2013.
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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 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".