Validity of self-report for fractures among a multiethnic cohort of postmenopausal women: results from the Women's Health Initiative observational study and clinical trials
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study is to examine the validity of, and factors associated with, the accuracy of self-report (participant-report and proxy-report) for fractures. DESIGN: Study participants were from the Women's Health Initiative Clinical Trial and Observational Study cohorts. All women were postmenopausal; populations included American Indian, Asian/Pacific Islander, black, Hispanic, and non-Hispanic white. The average length of follow-up was 4.3 years. Self-reported fractures were adjudicated by reviewing medical records. The first adjudicated self-report of fractures for each participant was included in the analysis (n = 6,652). RESULTS: We found substantial variations in validity of self-report by the fracture site. Agreements between self-reports for single-site fractures and medical records were high for hip (78%) and forearm/wrist (81%) but relatively lower for clinical spine fractures (51%). The average confirmation rate for all single-site fractures was 71%. Misidentification of fracture sites by participants or proxy-reporters seemed to be a cause of unconfirmed self-reports. Higher confirmation rates were observed in participant-reports than in proxy-reports. Results of the multivariate analysis indicated that multiple factors, such as ethnicity, a history of osteoporosis or fractures, body mass index, years since menopause, smoking status, and number of falls in the past year were significantly (P < 0.05) related to the validity of self-report. CONCLUSION: The validity of self-reports for fracture varies by fracture sites and many other factors. The assessed validity in this study is likely conservative because some of the unconfirmed self-reports may be due to poor medical record systems. The validity of self-reports for hip and forearm/wrist fractures is high in this study, supporting their use in epidemiological studies among postmenopausal women.
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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 | 0.059 | 0.162 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".