Gender Differences in Core Muscular Endurance and Trunk Muscle Balance Ratios Among Pakistani University Students: A Cross-Sectional Study Using McGill’s Torso Battery
Bibliographic record
Abstract
Background: Gender differences in core muscular endurance are well documented, but no study has examined all three of McGill’s clinically recommended trunk muscle balance ratios in a gender-balanced young adult population. Aim: To investigate gender differences in core endurance times and trunk muscle balance ratios among university students using the complete McGill torso battery. Methods: One hundred and twenty-eight university students (64 males, 64 females; aged 18–24 years) performed the trunk flexor, extensor, right and left side-bridge endurance tests in fixed order. Flexion:extension, side-bridge:extension (right and left), and right:left ratios were calculated and classified as “Good” or “Poor” using established clinical cut-offs. Non-parametric tests (Mann-Whitney U, χ²) were applied due to non-normal distribution. Results: Males exhibited significantly longer endurance in the extensor (p = .001, r = 0.28), right side-bridge (p < .001, r = 0.61), and left side-bridge tests (p < .001, r = 0.62). No significant difference was found in flexor endurance or flexion:extension ratio. Males showed significantly better (lower) side-bridge:extension ratios on both sides (p ≤ .015), whereas right-to-left asymmetry affected 89% of the total sample. Conclusion: University-aged males demonstrate superior lateral core endurance and more favourable clinical balance ratios than females. The high prevalence of poor ratios, especially among female students, underscores the need for early, gender-specific core conditioning programmes in higher education settings.
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 | 0.001 |
| 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) | 0.003 | 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".