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Record W4412488544 · doi:10.1111/hdi.70009

The Effect of Nursing Care Based on Kolcaba's Comfort Theory on Symptom Severity and Comfort of Hemodialysis Patients

2025· article· en· W4412488544 on OpenAlexvenueno aff
Gamze Göke Arslan, Şebnem Çınar Yücel

Bibliographic record

VenueHemodialysis International · 2025
Typearticle
Languageen
FieldNursing
TopicNursing Diagnosis and Documentation
Canadian institutionsnot available
Fundersnot available
KeywordsHemodialysisMedicineComfort careNursing carePhysical therapyDialysisNursingInternal medicinePalliative care

Abstract

fetched live from OpenAlex

AIM: The present study was conducted to investigate the effect of nursing care structured according to Kolcaba's comfort theory and given to hemodialysis patients on their symptom severity and comfort. DESIGN: This quasi-experimental study was conducted with 46 patients; 22 were in the intervention group and 24 were in the control group, who received treatment in the hemodialysis unit of a training and research hospital in Türkiye between November 2021 and May 2022. METHODS: The Patient Information Form (PIF), Dialysis Symptom Index (DSI) and Hemodialysis Comfort Scale-Version II (HDCS-II) were used to collect data. RESULTS: While the mean DSI scores decreased in the intervention group over time, they increased in the control group. The mean score obtained from the overall HDCS-II increased over time in three follow-ups performed at different times in the intervention group. The mean score obtained from the overall HDCS-II decreased over time in three follow-ups performed at different times in the control group. CONCLUSIONS: In the present study, nursing care structured according to Kolcaba's Comfort Theory given to hemodialysis patients reduced the severity of the symptoms in the participants and increased their comfort levels.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.005
GPT teacher head0.290
Teacher spread0.285 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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