Effects of Orange Oil Aromatherapy on Pain and Anxiety During Invasive Interventions in Patients With Hematopoietic Stem Cell Transplants
Bibliographic record
Abstract
Invasive interventions, such as peripheral intravenous cannula, port needle placement, and blood collection, are often required for both inpatient and outpatient follow-up patients with hematological malignancies and hematopoietic stem cell transplants. This prospective, randomized controlled experimental study assessed the effect of orange oil inhalation used in aromatherapy on pain and anxiety levels in invasive interventions with hematological malignancies and hematopoietic stem cell transplants. It was conducted prospectively with 80 patients with hematological malignancies who were treated in the adult bone marrow transplant unit and adult hematology service of a private hospital between May 2021 and April 2022. The orange oil inhalation used in aromatherapy was applied to patients in the intervention group. The Visual Analog Scale (VAS) and State-Trait Anxiety Inventory (STAI) were used for data collection. Regarding the personal characteristics of the patients, 42.5% were ≥61 years old, 60% were men, and 85% were married. VAS pain scores of the intervention group were statistically lower than those of the control group (P < .001). However, there was no statistically significant difference in the STAI scores of groups (P >.05). The study results show that orange oil inhalation has been determined to reduce pain during invasive interventions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".