The Use of Poke Root in the Treatment of Lactational Mastitis: Practice Patterns among Midwives in British Columbia
Bibliographic record
Abstract
Introduction: The prevalence of mastitis has been reported as high as 33%. Effective milk removal, pain medication, and antibiotics are the mainstays of treatment. Midwives support the use of complementary and alternative medicines, but few studies have examined their use. This paper explores practice patterns of midwives in British Columbia with respect to the use of poke root, Phytolacca decandra, in the treatment of mastitis. Methodology: A questionnaire was distributed to all registered midwives in British Columbia asking about their familiarity with poke root, whether they recommend it for treatment of mastitis, how they recommend that it be used, and whether they perceive it as effective in treating mastitis. Results: A total of 106 questionnaires were returned. Fifty midwives (47.2%) reported using poke root. Over sixty-nine percent of respondents used it as a tincture, 22.4% used it as a homeopathic, and 8.2% used it topically. The dose, route, timing, and duration of use varied; however, there were few perceived side effects, and the satisfaction among midwives was high. Conclusion: The questionnaire responses demonstrate that a large number of midwives in British Columbia perceive poke root to be effective in treating lactational mastitis. Reported rates of satisfaction with the therapy among midwives were high. The tremendous variability in administration and the lack of known side effects highlight the need for a future study that will examine the effectiveness of poke root to facilitate informed choice discussion. This article has been peer reviewed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".