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Record W4295714576 · doi:10.53730/ijhs.v6ns8.12641

effect of an integrative nursing program on pain of school-age children with leukemia undergoing lumbar punctures

2022· article· en· W4295714576 on OpenAlexaff
Thapach Kansorn, Nataporn Wisoram, Suwarat Theerasut

Bibliographic record

VenueInternational Journal of Health Sciences · 2022
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineLumbarNursingPhysical therapyStatistical significanceNursing careRepeated measures designRandomized controlled trialPain assessmentClinical trialTest (biology)SurgeryPain managementInternal medicine

Abstract

fetched live from OpenAlex

The purpose of this quasi-experimental research was to examine the effect of an integrative nursing program on pain of school-age children with leukemia undergoing lumbar punctures. The Gate Control Theory provided the conceptual framework for this study. The subjects were 30 leukemia children aged between 8-12 years old undergoing lumbar punctures with the pain scores of two or over and being treated with chemotherapy at Khon Kaen Hospital. The first 15 children were allocated based on a simple random sampling of the control group and the last 15 children in the experimental group. The research instruments of this study were a pain assessment form and an Integrative Nursing Program. Children in the treatment group received integrative nursing care. The experiment was divided into three periods, namely pre-trial, post-trial, and follow-up periods. The data were analyzed using frequency, percentage, mean, standard deviation, and t-test. The findings of this research revealed that children undergoing the Integrative Nursing Program had significantly less pain than children receiving conventional nursing care at the statistical level of .05. The children received integrative nursing care had significantly less pain in post-trial and follow-up periods than the pre-trial period at the statistical level of .05.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.396
Teacher spread0.380 · 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 designObservational
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

Citations0
Published2022
Admission routes1
Has abstractyes

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