Effects of a DXA result letter on satisfaction, quality of life, and osteoporosis knowledge: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Undiagnosed, or diagnosed and untreated osteoporosis (OP) increases the likelihood that falls result in hip fractures, decreased quality of life (QOL), and significant medical expenditures among older adults. We tested whether a tailored dual energy x-ray absorptiometry (DXA) test result letter and an accompanying educational bone-health brochure affected patient satisfaction, QOL, or OP knowledge. METHODS: The Patient Activation after DXA Result Notification (PAADRN) study was a double-blinded, pragmatic, randomized trial which enrolled patients from 2012 to 2014. We randomized 7,749 patients presenting for DXA at three health care institutions in the United States who were ≥ 50 years old and able to understand English. Intervention patients received a tailored letter four weeks after DXA containing their results, 10-year fracture risk, and a bone-health educational brochure. Control patients received the results of their DXA per the usual practices of their providers and institutions. Satisfaction with bone health care, QOL, and OP knowledge were assessed at baseline and 12- and 52-weeks after DXA. Intention-to-treat analyses used multiple imputation for missing data and random effects regression models to adjust for clustering within providers and covariates. RESULTS: At 12-weeks 6,728 (86.8 %) and at 52-weeks 6,103 participants (78.8 %) completed their follow-up interviews. The intervention group was more satisfied with their bone health care compared to the usual care group at both their 12- and 52-week follow-ups (standardized effect size = 0.28 at 12-weeks and 0.17 at 52-weeks, p < 0.001). There were no differences between the intervention and usual care groups in QOL or OP knowledge at either time point. CONCLUSIONS: A tailored DXA result letter and bone-health educational brochure sent to patients improved patient satisfaction with bone-related health care. TRIAL REGISTRATION: Clinical Trials.gov Identifier: NCT01507662 First received: December 8, 2011.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".