Exploring participant attrition in a longitudinal follow-up of older adults: the Global Longitudinal Study of Osteoporosis in Women (GLOW) Hamilton cohort
Bibliographic record
Abstract
OBJECTIVE: We explored the magnitude of attrition, its pattern and risk factors for different forms of attrition in the cohort from the Global Longitudinal Study of Osteoporosis in Women. DESIGN: Prospective cohort study. SETTING: Participants were recruited from physician practices in Hamilton, Ontario. PARTICIPANTS: Postmenopausal women aged ≥55 years who had consulted their primary care physician within the last 2 years. OUTCOME MEASURES: Time to all-cause, non-death, death, preventable and non-preventable attrition. RESULTS: All 3985 women enrolled in the study were included in the analyses. The mean age of the cohort was 69.4 (SD: 8.9) years. At the end of the follow-up, 30.2% (1206/3985) of the study participants had either died or were lost to follow-up. The pattern of attrition was monotone with most participants failing to return after a missed survey. The different types of attrition examined shared common risk factors including age, smoking and being frail but differed on factors such as educational level, race, hospitalisation, quality of life and being prefrail. CONCLUSION: Attrition in this ageing cohort was selective to some participant characteristics. Minimising potential bias associated with such non-random attrition would require targeted measures to achieve maximum possible follow-rates among the high-risk groups identified and dealing with specific reasons for attrition in the study design and analysis.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".