IS BALANCE CONFIDENCE AN IMPORTANT DETERMINANT OF PHYSICAL ACTIVITY LEVELS IN OLDER PERSONS WITH TYPE 2 DIABETES?
Bibliographic record
Abstract
Improving physical activity is crucial for management of type 2 diabetes (diabetes) particularly in older persons. Poor balance confidence is a common concern in older population that can lead to restriction of physical activities. We identified differences in physical activity levels between older persons with and without diabetes and examined low balance confidence as a potential determinant of reduced physical activity levels in those with diabetes. 60 persons aged ≥65 years were recruited; 46 with diabetes for ≥5 years and 14 without diabetes. Physical activity level was measured using the Human Activity Profile Adjusted Activity Score (HAP-AAS) that takes into consideration the activities that the person has stopped performing. Balance confidence was measured by the Activity Specific Balance Confidence (ABC) scale. Potential covariates to be included in the multiple regression analysis were selected using bivariate correlation analysis of demographics, knee extensor strength, ankle proprioception, fall history in the previous year, balance performance and depression with HAP-AAS scores at p<0.05. Age and BMI were significantly different between those with and without diabetes. ANCOVA adjusted for age and BMI demonstrated HAP-AAS scores were significantly lower in the elderly with diabetes (p<0.05). The fully adjusted multiple regression model explained 50% variance in HAP-AAS scores and demonstrated ABC scores as the only significant determinant of HAP-AAS scores (p<0.05). Balance confidence is a strong determinant of physical activity levels in older persons with diabetes. Monitoring of and intervention for balance confidence may be required to improve physical activity levels in older persons with diabetes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".