CROSS-SECTIONAL ASSOCIATION OF FALLS AND POST-TRAUMATIC STRESS IN CANADIANS ACROSS LEVELS OF FRAILTY
Bibliographic record
Abstract
Abstract Frail older adults are vulnerable to stressors and are more likely to experience adverse outcomes. Post-traumatic stress is common in older adults, and can be related to common adverse outcomes, such as falls. We examined whether falls are associated with post-traumatic stress in middle-aged and older Canadians, by levels of frailty. We conducted cross-sectional analysis of the baseline assessment of the Canadian Longitudinal Study on Aging’s tracking cohort, comprising 21,241 individuals, aged 45 to 85 years. We constructed a 60-item frailty index (FI) and defined post-traumatic stress using the primary care post-traumatic stress disorder four-item tool (score 3 as the cut-point). Logistic regressions with post-traumatic stress as the dependent variable and at least one fall in the past year as the independent variable, were adjusted for socio-demographic variables and stratified according to FI 0.1 groups. Prevalence of post-traumatic stress and falls was of 6.5% and 5.0%, respectively for the whole sample. Among those who did not fall prevalence of post-traumatic stress ranged across frailty levels from 3.2% (FI<0.1) to 24.5% (FI≥0.3). Among those who fell, post-traumatic stress ranged from 3.4% (FI<0.1) to 36.9% (FI≥0.3). Falls were not significantly associated with post-traumatic stress among people who had an FI<0.3, but among those with an FI≥0.3 the odds ratio for having post-traumatic stress for those who fell was 2.25 (95% CI 1.2-4.23, p=0.011) compared to non-fallers. In conclusion, high levels of frailty can impact how a stressor, such as a fall, can be associated with an adverse psychological outcome.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".