Online Disease Management Training for Older Adults With Osteoarthritis: A Randomized Controlled Trial
Bibliographic record
Abstract
INTRODUCTION: Using online methods in health education is an effective method that provides individual services to older adults with limited access to health services and allows for low-cost and continuous communication. METHODS: The study was completed with 52 older adults diagnosed with osteoarthritis, including 26 intervention and 26 control participants. For data collection, a Patient Information Form, Visual Analogue Scale, the Western Ontario and McMaster Universities Osteoarthritis Index, Self-Efficacy Scale in Arthritis, World Health Organization Quality of Life Instrument-Older Adults Module and a Telephone Counselling Follow-up Form were used. Individuals in the intervention group were provided with online training for the first 4 weeks and telephone counselling for the following 4 weeks. Scales were applied to both groups. RESULTS: The scales were applied to both groups at the first, second and last measurements. It was determined that there was a significant difference between the total pain and functional status scores of the individuals in the intervention and control groups at the second and last measurement (p < 0.05), while the average scores of the intervention group were lower control group. The total self-efficacy score and quality of life total score of the intervention group were statistically significantly higher than the total score of the control group (p < 0.05). CONCLUSIONS: As a result of the research, it was found that online education and telephone counselling given to elderly individuals with osteoarthritis were effective in reducing pain severity and improving functional status, self-efficacy and quality of life. TRIAL REGISTRATION: The trial was registered at ClinicalTrial.gov (NCT04816474/2021-08-10/https://register. CLINICALTRIALS: gov/).
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".