An Exploratory Survey of Older Women’s Post-Fall Decisions
Bibliographic record
Abstract
This research examined factors influencing older women's post-fall decision making. We surveyed 130 independent older women from continuing care retirement communities and non-institutional homes. We categorized women's post-fall decisions as medical, corrective, and social decisions, and examined the associations between post-fall decision categories, decisional conflict, number of post-fall changes, self-rated health, frequency of falls, severity of falls, health literacy, awareness and openness to long-term care institutional options, and demographics. Older women experienced greater decisional conflict when making medical decisions versus social ( p = .012) and corrective ( p = .047) decisions. Significant predictors of post-fall decisional conflict were awareness of institutional care options ( p = .001) and health literacy ( p = .001). Future educational interventions should address knowledge deficits and provide resources to enhance collaborative efforts to lower women's post-fall decisional conflict and increase satisfaction in the decisions they make after a fall.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".