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Record W4392748100 · doi:10.18502/ijph.v53i3.15135

Effect of Lavender Aromatherapy on Anxiety and Fatigue in Hemodialysis Patients: A Systematic Review and Meta-Analysis

2024· review· en· W4392748100 on OpenAlexaff
Mahbobeh Firooz, Gholam Reza Mahmoodi Shan, Leila Jouybari, Khadijeh Yazdi, Joseph Osuji

Bibliographic record

VenueIranian Journal of Public Health · 2024
Typereview
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsMount Royal University
FundersGolestan University of Medical Sciences
KeywordsAromatherapyLavenderMedicineHemodialysisAnxietyMeta-analysisTraditional medicineAlternative medicinePhysical therapyInternal medicinePsychiatryEssential oilBiologyFood sciencePathology

Abstract

fetched live from OpenAlex

Background: Several studies have evaluated the effects of lavender essential oil on the anxiety of hemodialysis (HD) patients, but most of them did not estimate the pooled effect size. The current systematic review and meta-analysis was conducted to evaluate the effects of lavender on anxiety and fatigue among HD patients. Methods: Eligible studies were selected based on the PRISMA steps and protocol. Literature was retrieved from PubMed, Web of Science, Scopus databases, Cochrane, ClinicalTrials.gov, and Google Scholar Search Engines until Sep 2022. The risk of bias and analysis were evaluated using version 2 of the Cochrane risk-of-bias tool and STATA v.14 software, respectively. Effect sizes were pooled using random effect models. Results: Nine studies were included. Lavender oil significantly reduced the average anxiety of HD patients compared to the control group (SMD: -2.51, 95% CI: [-3.56, -1.45], Z=4.67, P<0.001, I2 :89.9%). Also, it significantly reduced the average fatigue compared to the control group (SMD: -1.56, 95% CI: [-2.49, -0.63], Z=3.29, P=0.001, I2:92.2%). Subgroup analysis indicated controversial results regarding session frequency and drop number of lavender oil. Conclusion: Using Lavender oil significantly reduced fatigue and anxiety in HD patients.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.887
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0100.002
Bibliometrics0.0010.002
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 head0.386
GPT teacher head0.414
Teacher spread0.028 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations2
Published2024
Admission routes1
Has abstractyes

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