Effect of stepped care on health outcomes in patients with osteoarthritis: an observational study in Dutch general practice
Bibliographic record
Abstract
BACKGROUND: A stepped care strategy (SCS) to improve adequate healthcare use in patients with osteoarthritis was developed and implemented in a primary care region in the Netherlands. AIM: To assess the association between care that is in line with the SCS recommendations and health outcomes. DESIGN AND SETTING: Data were used from a 2-year observational study of 313 patients who had consulted their GP because of osteoarthritis. METHOD: Care was considered 'SCS-consistent' if all advised modalities of the previous steps of the SCS were offered before more advanced modalities of subsequent steps. Pain and physical function were measured with the Western Ontario and McMaster Universities Osteoarthritis Index (range 0-100); active pain coping with the Pain Coping Inventory (range 10-40); and self-efficacy with the Dutch General Self-Efficacy Scale (range 12-48). Crude and adjusted associations between SCS-consistent care and outcomes were estimated with generalised estimating equations. RESULTS: No statistically significant differences were found in changes over a 2-year period in pain and physical function between patients who received SCS-inconsistent care (n = 163) and patients who received SCS-consistent care (n = 117). This was also the case after adjusting for possible confounders, that is, -4.3 (95% confidence interval [CI] = -10.3 to 1.7) and -1.9 (95% CI = -7.0 to 3.1), respectively. Furthermore, no differences were found in changes over time between groups in self-efficacy and pain coping. CONCLUSION: The results raised several important issues that need to be considered regarding the value of the SCS, such as the reasons that GPs provide SCS-inconsistent care, the long-term effects of the SCS, and the effects on costs and side effects.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".