Patients’ values and preferences of the expected efficacy of hip arthroscopy for osteoarthritis: a protocol for a multinational structured interview-based study combined with a randomised survey on the optimal amount of information to elicit preferences
Bibliographic record
Abstract
INTRODUCTION: Symptomatic hip osteoarthritis (OA) is a disabling condition with up to a 25% cumulative lifetime risk. Total hip arthroplasty (THA) is effective in relieving patients' symptoms and improving function. It is, however, associated with substantial risk of complications, pain and major functional limitation before patients can return to full function. In contrast, hip arthroscopy (HA) is less invasive and can postpone THA. However, there is no evidence regarding the delay in the need for THA that patients would find acceptable to undergoing HA. Knowing patients' values and preferences (VP) on this expected delay is critical when making recommendations regarding the advisability of HA. Furthermore, little is known on the optimal amount of information regarding interventions and outcomes needed to present in order to optimally elicit patients' VP. METHODS AND ANALYSIS: We will perform a multinational, structured interview-based survey of preference in delay time for THA among patients with non-advanced OA who failed to respond to conservative therapy. We will combine these interviews with a randomised trial addressing the optimal amount of information regarding the interventions and outcomes required to elicit preferences. Eligible patients will be randomly assigned (1 : 1) to either a short or a long format of health scenarios of THA and HA. We will determine each patient's VP using a trade-off and anticipated regret exercises. Our primary outcomes for the combined surveys will be: (1) the minimal delay time in the need for THA surgery that patients would find acceptable to undertaking HA, (2) patients' satisfaction with the amount of information provided in the health scenarios used to elicit their VPs. ETHICS AND DISSEMINATION: The protocol has been approved by the Hamilton Integrated Research Ethics Board (HIREB13-506). We will disseminate our study findings through peer-reviewed publications and conference presentations, and make them available to guideline makers issuing recommendations addressing HA and THA.
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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 | 0.079 | 0.066 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.036 | 0.006 |
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".