PRESIDENTIAL SYMPOSIUM: THE IMPACT OF FALLS AND FEAR OF FALLING ON OLDER ADULTS’ MOBILITY: AN INTERNATIONAL PERSPECTIVE
Bibliographic record
Abstract
Falls and Fear of falling (FOF) are common in old age. Although the adverse consequences of falls and FOF were studied extensively, most studies were either cross-sectional, focused on one context, or varied widely in definitions and outcome measures used, which prevented researchers from conducting meaningful comparisons between different nations. The International Mobility in Aging Study (IMIAS) is a population-based, cohort study (2012–2016) on community-dwelling older adults in five sites: Canada (Kingston, Saint-Hyacinthe), Albania (Tirana), Colombia (Manizales) and Brazil (Natal). Drawing on longitudinal data from IMIAS and using validated and standardized tools in all study sites, presenters in this symposium will provide an overview of their recent research to improve our understanding of factors associated with falls and FOF at an old age in diverse locations, and investigate if FOF can independently lead to disability over time. Ms. Hwang, University of Hawaii, USA will share results from her study to test whether FOF is independently associated with average minutes walking per day among older adults. Dr. Auais from Queen’s University, Canada will discuss whether FOF could independently lead to functional disabilities after a 2-year period. Dr. Vafaei from the Queen’s University, Canada will explore potential mediators that could explain the longitudinal relationship between FOF and incident disability. Finally, Dr. Gomez, University of Caldas, Colombia will present his findings after testing a simple algorithm to predict falls over time and possible implications. This work has clinical and policy implications and could improve older adults’ mobility and, ultimately, their integration in local communities.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".