Effect of two physical exercise protocols on cognition and depressive symptoms in oldest‐old people: A randomized controlled trial
Bibliographic record
Abstract
AIM: To compare the effect of multicomponent and resistance training and detraining on cognition and depressive symptoms in oldest-old community-dwelling people. METHODS: A total of 69 sedentary older adults aged older than 80 years were assessed and randomized into three groups (control, multicomponent and resistance training). The multicomponent group performed protocol consisting of aerobic, strength and balance exercises. The resistance group participated in strength exercises using six machines. The control group did not perform any intervention. The training sessions had progressive intensity, lasted 16 weeks and included three sessions per week. The volunteers were assessed at baseline, at the end of the 16-week training sessions and after the 6-week detraining period. The assessment consisted of anamneses, Geriatric Depression Scale and cognition (Montreal Cognitive Assessment, Clock Drawing Test, verbal fluency and dual task). RESULTS: There were no significant differences between groups and times in any of variables; however, the adherence to training was low, mainly in the multicomponent group. CONCLUSIONS: Randomized controlled trials using adherence strategies and longer times comparing training variations are required to verify which training protocols are more effective and consistent on cognition and depression in oldest-old people.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".