Determining the Relationship Between Frailty and Fall Risk in Elderly People Living in Nursing Homes
Bibliographic record
Abstract
Objective: The study aimed to determine the relationship between the level of frailty and the risk of falls in the elderly living in nursing homes and to draw attention to this issue. Method: The cross-sectional and descriptive study was conducted in two state-owned nursing homes in Adana between January 2, 2023, and January 15, 2023. The study was conducted by face-to-face interviews with a total of 220 elderly people who met the research criteria and agreed to participate in the study. Data were collected using the Personal Information Form, Itaki Fall Risk Index, and Edmonton Frailty Scale. Results: 63,6% of the participants were women, and the average age was 76±8 (min=60, max=98). Female gender (58,3%), normal BMI (54,9%), lack of regular exercise (85,4%), presence of chronic disease (55,6%), use of assistive devices (85,6%), history of falling A statistically significant relationship was found between (63,9%) and hospitalization history (61,1%) and fall risk level (p<0.05). Normal BMI (60%), lack of regular exercise (70%), presence of chronic disease (70%), number of medications used 1-3 (55%), use of assistive devices (97,5%), history of falling (100%), a statistically significant relationship was found between the history of hospitalization (72,5%) and the risk level of severe frailty (p<0,05). A statistically significant relationship was found between frailty level and fall risk (p = 0,00). Conclusion: Elderly people with moderate and severe frailty were found to be at high risk of falls.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".