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Record W2546006713

슬관절 치환술을 받은 환자의 WOMAC 지수와 생활만족도

2016· article· ko· W2546006713 on OpenAlexaboutno aff
박미애, 황선경, 이윤지

Bibliographic record

Venuenot available
Typearticle
Languageko
FieldNursing
TopicHealthcare Education and Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACMedicinePhysical therapyMoodArthroplastyOsteoarthritisDepression (economics)Life satisfactionSurgeryPsychologyPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Purpose: The aim of this study was to identify predictors of influencing on the physical function and life satisfaction in patients who underwent knee replacement arthroplasty. Methods: A convenience sampling of 70 patients who were hospitalized for knee replacement arthroplasty was taken from a university hospital. The instruments for the study were the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) Index, Life Satisfaction, Scale and the Geriatric Depression Scale. The exercise capacity was measured. Data were analyzed using t-test, one-way ANOVA, Pearson``s correlation coefficient, repeated measures ANOVA and multiple regression with PASW version 18.0. Results: The WOMAC index (F=48.28, p<.001) and the life satisfaction (F=12.45, p<.001) showed a significant change over time, with measurements before surgery, at 1 month and 3 months after surgery. The predictors of the WOMAC index at 3 months after surgery were leg muscle strength at discharge(β=.40) and life satisfaction at 1 month after surgery (β=.75). Life satisfaction at 3 months after surgery accurately predicted 44% of the WOMAC index at 3 months after surgery (β=-.48) and depression before surgery (β=-.35). Conclusion: The findings indicate that reducing depressive mood and strengthening leg muscles will improve patients`` physical function and life satisfaction after knee replacement arthroplasty.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0270.016

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 head0.035
GPT teacher head0.360
Teacher spread0.326 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2016
Admission routes1
Has abstractyes

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