The Effect of Aging on Physical Performance Among Elderly Manual Workers: Protocol of a Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: In 2012, the Danish Parliament decided to increase retirement age. Unfortunately, elderly people working in a physically demanding environment may be rendered unable to retain the ability to adequately perform the physical requirements of their jobs, due to age-related decreases in physical performance. Therefore, increasing the retirement age may not necessarily lead to the goal of keeping everybody in the labor market for a longer time. To date, our knowledge about the variations in physical performance of the elderly workforce is limited. OBJECTIVE: In this cross-sectional study we seek to investigate the effects of aging on physical performance among elderly manual workers. METHODS: Approximately 100 Danish manual workers between 50 and 70 years of age will be recruited. The main measurement outcomes include: (1) inflammatory status from blood samples; (2) body composition; (3) lung function; (4) static and dynamic balance; (5) reaction time, precision, and movement variability during a hammering task; (6) handgrip strength, rate of force development, and force tracking; (7) estimated maximal rate of oxygen consumption; and (8) back mobility. Additionally, information regarding working conditions, physical activity levels, and health status will be assessed with a questionnaire. RESULTS: Data collection is expected to take place between autumn 2017 and spring 2018. CONCLUSIONS: This study will increase the knowledge regarding variations in physical performance in the elderly workforce and may identify potential workplace hazards. Moreover, this study might shed light on the potentially problematic decision to increase retirement age for all Danish citizens.
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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 | 0.020 | 0.010 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".