The relationship between core endurance, physical activity level and balance in office workers
Bibliographic record
Abstract
Objectives. The aim of this study was to evaluate the relationship between core endurance tests and physical activity level, balance, ergonomics and pain in office workers. Methods. The study included 57 office workers who had been employed for at least 1 year. Core endurance was assessed using McGill core endurance tests. Physical activity, balance, pain and ergonomic risks were evaluated with the international physical activity questionnaire (IPAQ), timed up and go (TUG), visual analog scale (VAS) and rapid office strain assessment (ROSA), respectively. Results. A significant correlation was found between balance and static core endurance tests. However, no significant correlation was found between ergonomics and physical activity level and core endurance tests except for trunk extension and prone bridge tests. In addition, there was a significant difference in core endurance tests for patients with and without regular exercise habits. Waist circumference and hip circumference measurements were found to be significantly negatively associated with static core tests. Conclusion. Core endurance was found to be associated with exercise habits, balance, hip and waist circumference and ergonomics in office workers. Improving core endurance may be beneficial for preventing musculoskeletal risks in office workers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".