Peppermint Essential Oil for Nausea and Vomiting in Hospitalized Patients: Incorporating Holistic Patient Decision Making Into the Research Design
Bibliographic record
Abstract
Aims This study examined nausea and vomiting (N/V) in hospitalized patients following the use of inhaled peppermint essential oil (aromatherapy) compared to combined aromatherapy/antiemetics or antiemetics alone. Method and Materials A total of 103 hospitalized patients were offered one of three options to control N/V. Patient choice was considered in the holistic trial design so that patients were not denied either the essential oil or antiemetics. Patients rated nausea 0 to 10 on the Edmonton Symptom Assessment Scale at symptom onset and within 60 minutes of the intervention. Results Only three subjects enrolled in the antiemetic arm; thus this arm was eliminated from analysis, resulting in 100 evaluable patients. Mean nausea score improved significantly for the entire sample following the aromatherapy or aromatherapy/antiemetic intervention ( p < .0001). Patients in the aromatherapy arm had significant improvement in nausea compared to the combined aromatherapy/antiemetic arm ( p < .0001). Patient perception that peppermint oil relieves N/V significantly improved for the entire sample. Notable is that 65% of patients used peppermint essential oil alone. Conclusions Peppermint essential oil is an effective independent or complementary modality for relief of N/V in hospitalized patients. Research designs that incorporate patient decision making should be considered for studies in which placebos do not contribute to holistic care.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".