A survey of people with foot problems related to rheumatoid arthritis and their educational needs
Bibliographic record
Abstract
BACKGROUND: Up to 50% of people with rheumatoid arthritis (RA) have foot symptoms at diagnosis, hence early foot health intervention is recommended and this should include patient education. This study identifies, for the first time, the foot health education (FHE) needs of people with RA. METHODS: = 543) captured quantitative data in relation to the aims, methods of delivery, content, timing and accessibility of FHE. RESULTS: The majority concurred about the aims of FHE. Verbal delivery and websites were the most common methods. Written and verbal FHE were perceived to be the most effective methods. The point of diagnosis was the preferred time to receive it. Lack of access to FHE included minimal focus on foot health during consultations by both health practitioners and patients with RA. Participant gender, age, disease duration and living situation had a statistically significant influence on the results. CONCLUSION: Foot health education is rarely considered within the medical consultation. There is a lack of patient and/or health professional awareness of this need with a detrimental impact on foot health. Patients require health professionals to identify their foot education health needs. Tailored foot health education should begin at initial diagnosis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".