Living with osteoarthritis: patient expenditures, health status, and social impact
Bibliographic record
Abstract
OBJECTIVE: To determine "out-of-pocket" expenditures related to osteoarthritis (OA) and to explore whether demographic details, health status scores (Medical Outcomes Study 36-item Short Form [SF-36] and Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC]), or perception of social effect were expenditure determinants. METHODS: A prospective cohort study of community-dwelling subjects with OA completed 4 consecutive 3-month cost diaries. In addition, subjects completed the SF-36 and WOMAC at baseline and at 12 months. Social impact at baseline was collected. Four groups categorized by age and sex were compared. Patients undergoing joint replacement were excluded. RESULTS: Differences in health status were defined more by age than by sex, especially for physical function. The costs to the patients were high, particularly for women, who spent more on medications and special equipment. Women also reported receiving more assistance from family and friends. Higher disease-related expenditures were associated with greater pain levels, poorer social function and mental health, and longer duration of disease. Significant independent predictors of total patient expenditures related to OA were being female and having joint stiffness. CONCLUSION: Despite having heavily subsidized health care and access to the Pharmaceutical Benefits Scheme, out-of-pocket costs for patients with OA in Australia are considerable. Higher expenditures for patients with OA are related to more advanced disease, especially for women.
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 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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".