Racial differences in social network experience and perceptions of benefit of arthritis treatments among New York City Medicare beneficiaries with self‐reported hip and knee pain
Bibliographic record
Abstract
OBJECTIVE: To determine whether social network experience and perceptions of benefit of arthritis treatments influence the decision to seek diagnosis and treatment. METHODS: A population-based telephone survey of 515 black and 455 white Medicare beneficiaries was conducted. Validated questionnaires adapted for use in a telephone interview were used to identify people with self-reported symptoms of hip or knee pain. Treatment history for arthritis-related pain and perceptions of benefit of treatment were also assessed. RESULTS: Forty-two percent of blacks and 31% of whites reported hip or knee pain. Forty-two percent of blacks and 65% of whites reported knowing someone who had surgery for hip or knee pain (P < 0.0001). Blacks were less likely than whites to report that surgery had helped someone they knew with hip or knee pain (not significant). CONCLUSION: Blacks know fewer people who have had surgical treatment of hip and knee pain than whites and appear to be less likely to perceive that such treatment is beneficial.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".