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Record W4405093449 · doi:10.1097/hnp.0000000000000713

The Effects of Su Jok Therapy on Pain, Fatigue, Insomnia, Nausea, and Vomiting Experienced by Patients With Gastrointestinal System Cancer

2024· article· en· W4405093449 on OpenAlexaboutno aff
Demet Güneş, Elanur Yılmaz Karabulutlu

Bibliographic record

VenueHolistic Nursing Practice · 2024
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNauseaVomitingMedicineVisual analogue scaleInsomniaCancer painRetchingGastrointestinal cancerCancerCancer-related fatigueRandomized controlled trialPhysical therapyAnesthesiaInternal medicineColorectal cancerPsychiatry

Abstract

fetched live from OpenAlex

Su Jok therapy is used as an energy-based complementary and alternative method in cancer patients. The study was conducted to determine the effects of Su Jok therapy on pain, fatigue, insomnia, nausea, and vomiting experienced by patients with gastrointestinal cancer. This randomized controlled trial was conducted with 48 patients. Data were collected by the researcher by using an introductory information form, the short form McGill pain questionnaire, the cancer fatigue scale, the insomnia severity index, the Rhodes index of nausea, vomiting, and retching, and the visual analog scale. It was found that, after the application of Su Jok seed treatment, there was a significant decrease in the mean scores of the intervention group on the McGill pain scale, the cancer fatigue scale, the insomnia severity index, and the Rhodes index of nausea, vomiting, Su Jok therapy was effective in reducing the pain, fatigue, insomnia, nausea, and vomiting scores of patients with gastrointestinal cancer.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.366
Teacher spread0.336 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations1
Published2024
Admission routes1
Has abstractyes

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