The Effects of the Task Balance Training Program on the Glial Cell Line‐Derived Neurotrophic Factor Levels, Cognitive Function, and Postural Balance in Old People
Bibliographic record
Abstract
Exercise in the form of physical activity can provide neuroprotective benefits. The purpose of this study is to determine the effect of the task balance training program (TBT program) on the glial cell‐derived neurotrophic factor levels, cognitive function, and postural balance in old people. The population of this study was the old people members of the Batara Hati Mulia Gowa Foundation who were willing to participate in the study ( n = 66). The sample of this study was obtained through a random sampling technique to determine the treatment ( n = 32) and control ( n = 34) groups. Before and after implementing the TBT program, glial cell‐derived neurotrophic factor (GDNF) level measurement and cognitive function and postural balance assessment were performed. Cognitive function was measured by using Montreal cognitive assessment (MoCA). Postural balance was measured in two ways by using the timed up and go (TUG) test and Tinetti performance‐oriented mobility assessment (POMA). The treatment group showed significantly greater changes than the control group in GDNF levels (2.24 (±0.63) vs. 1.24 (±0.43), P = 0.001), cognitive function (24.66 (±3.42) vs. 19.18 (±2.67), P = 0.001), and postural balance (TUG [14.00 (±4.04) vs. 18.68 (±3.98)]; POMA [26.53 (±1.74) vs. 23.47 (±3.06)], P = 0.001) after training. The treatment group also showed a significant relationship between GDNF levels and cognitive function ( r = 0.840, P = 0.001) and postural balance (TUG [ r = 0.814, P = 0.001]; POMA [ r = 0.630, P = 0.001]). The TBT program affects the levels of GDNF in old people. The TBT program involves cognitive function improvement and affects postural balance changes in old people.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".