Comparison of two different nursing interventions for knee osteoarthritis patients in the community in northern Thailand
Bibliographic record
Abstract
Knee osteoarthritis (OA) is a common chronic disease that leads to knee pain, stiffness and limited physical function. A multi-faceted treatment composed of medication management, exercise, health education, and weight control is identified as effective for the reduction of knee pain and increased physical function. This quasi-experimental study undertaken in rural Thailand had an interrupted time-series design and examined whether a multi-faceted intervention delivered by nurse practitioners resulted in improved health status regarding knee OA symptom, quality of life and satisfaction with nursing care and reduced medication usage compared to standard treatment. There were 108 participants (58 experimental, 58 control) who completed the study. The multi-faceted intervention included education, group exercise, weight loss, and medication management delivered over aI2-week period. Four time points were used across the study (weeks 1 and 4 pre-intervention and 16 and 20 post-intervention) to collect data including the Western Ontario and McMaster Universities Arthritis Index (WOMAC), Self-Form 36 (SF-36), Leeds Satisfaction Questionnaires (LSQ) and medication usage diary. Analysis of variance and non-parametric analyses were used to examine differences across time and t-tests and mean change differences were used to examine the group differences pre- and post- intervention. The experimental group reported significant mean change increase in LSQ score and a mean change decrease in medication usage than the control group post-intervention. This supported the hypotheses that the multi-faceted intervention delivered by nurse practitioners would result in greater satisfaction with nursing care and a reduction in medication usage than standard treatment among patients with knee OA. There were no significant mean change differences in the WOMAC and SF-36 scores between the groups. However, both groups reported improvement in WOMAC and SF-36 scores so it is probable that both treatments helped to maintain health status and quality of life.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".