Development of a decision aid to address racial disparities in utilization of knee replacement surgery
Bibliographic record
Abstract
OBJECTIVE: Previous studies suggest that poorer knowledge and expectations about surgical outcomes may be responsible for low rates of total knee replacement (TKR) among African American males. The goal of this study was to pilot test the scope, acceptability, and efficacy of an educational videotape and tailored TKR decision aid designed to reduce disparities in TKR knowledge and expectations. METHODS: African American and Caucasian male veteran volunteers ages 55-85 years with moderate to severe knee osteoarthritis (OA) were recruited. During group meetings, patients viewed a video about knee OA treatments and were provided a personalized arthritis report that presented predicted patient outcomes should they decide to undergo TKR. Patients completed baseline and postintervention questionnaires that included an adapted Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) instrument to measure post-TKR expectations (0-100 scale with higher scores reflecting poorer outcomes). RESULTS: A total of 102 patients (54 African American, 48 Caucasian) completed the baseline survey and 64 patients attended the intervention. There were no significant differences by race between patients completing and those dropping out of the study. At baseline (n = 102), African American patients expressed lower expectations about post-TKR outcomes than did Caucasian patients for both pain (WOMAC score 41 versus 34; P = 0.18) and physical function expectations (WOMAC score 38 versus 30; P = 0.13). Among African Americans who underwent the intervention, expected pain and physical function improved to 31 (P = 0.04 versus baseline) and 30 (P = 0.09 versus baseline), respectively. Caucasian patients' expectations changed little. CONCLUSION: Disparities in baseline knowledge and expectations about TKR may be improved with the combined educational video and tailored decision aid.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".