Investigating the Significance Levels of Indicators that Increase the Risk of Falling in the Older Adults
Bibliographic record
Abstract
Objectives: Falls are very common in olders adults. The study's objective is to evaluate the importance of the levels of multiple indicators that raise the older population's risk of falling. Methods: The study examined 110 individuals over 65 years of age. Participants' cognitive abilities were examined using the Montreal Cognitive Assessment(MoCa) Scale. The Functional Reach Test (FRT) measured anterioposterior dynamic balance, while the Tandem Stance Test(TST) tested lateral stability. Fall risk and static and dynamic balance were assessed using the Berg Balance Test (BBT). Time Up and Go Test(TUGT) assessed functional mobility. A 1-minute sit-to-stand test measured lower extremity endurance and functional muscular strength. Cervical proprioception was assessed using a stabilizer. Results: Participants had a mean age of 71.26±6.20 years and experienced 0.41±1.02 falls in the past year. TST duration: 25.95±7.93 seconds, MoCa: 18.65±4.90, FRT: 21.83±8.38, BBT: 51.11±4.47, TUGT: 12.01±3.89, 1MSTS: 18.61±8.23, cervical proprioception error: 15.49±13.01 A statistically insignificant negative connection was seen between the number of falls and age(r=-0.081,p=0.399), height(r=-0.030,p=0.756), tandem standing (r=0.144,p=0.134), cognitive level(r=-0.015, p=0.878), Berg Blance test(r=-0.079, p=0.414) and cervical proprioception(r=-0.135, p=0.160). Men reported more falls than women, with an odds ratio of 3.14 (95% confidence interval: 1.21-8.14). Gender and falls are significantly associated (p = 0.018*), suggesting males may fall more. Conclusion: This study provides valuable insights into the factors associated with falls among older people. The findings reinforce the importance of gender as a key factor in falls, revealing the possible impact of body weight, balance, and age on the probability of experiencing 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".