Personality Traits and Health Behaviors as Predictors of Fall Among Community-Dwelling Older Adults: Findings From the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
Objectives: To examine whether personality traits and health behaviors predict falls in community-dwelling older adults. Methods: Longitudinal data from the Canadian Longitudinal Study on Aging (CLSA) at baseline (2011–2015) and follow-up two (2018–2021) were analyzed using logistic regression for 5270 adults aged 65 and older, with an alpha level of 0.05. Results: At baseline, participants’ mean age was 72 years, with 51.1% female. Most identified as White (96.7%) and had education beyond secondary (81.5%). Increased physical activity (OR: 1.012, 95% CI: 1.01–1.014), decreased alcohol consumption (OR: 1.634, 95% CI: 1.419–1.883), and smoking cessation (OR: 2.8, 95% CI: 2.198–3.568) increased fall risk, while conscientiousness (OR: 0.832, 95% CI: 0.792–0.874) and openness (OR: 0.959, 95% CI: 0.922–0.998) were protective at follow-up two. Personality changes significantly influence falls. Discussion: Findings highlight the complex interplay between personality traits, health behaviors, and falls, suggesting a one-size-fits-all approach to fall prevention may be insufficient.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".