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Record W3088723927 · doi:10.1177/0898010120961579

Peppermint Essential Oil for Nausea and Vomiting in Hospitalized Patients: Incorporating Holistic Patient Decision Making Into the Research Design

2020· article· en· W3088723927 on OpenAlexaboutno aff
Carla Mohr, Cassandra Jensen, Nicole Padden, Jamie M. Besel, Jeannine M. Brant

Bibliographic record

VenueJournal of Holistic Nursing · 2020
Typearticle
Languageen
FieldMedicine
TopicNausea and vomiting management
Canadian institutionsnot available
Fundersnot available
KeywordsNauseaVomitingHolistic nursingMedicineIntensive care medicinePsychologyNursingAnesthesia

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.117
GPT teacher head0.413
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2020
Admission routes1
Has abstractyes

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