The Role of Trunk Training for Physical Fitness and Sport-Specific Performance. Protocol for a Meta-Analysis
Bibliographic record
Abstract
The trunk (core) muscles are involved in daily functions (i. e., stabilizing the body in everyday tasks) and force generation of the limbs during athletic tasks such as kicking, throwing, or running. Even though trunk training is a popular means for improving physical fitness and athletic performance, the direct relationship of improved trunk function (i.e., stability, strength, or endurance), fitness and sport-specific performance is not conclusive. The aim of this proposed review is to evaluate the effects of trunk training on physical fitness and sport-specific performance, and to examine potential subject-related (e.g., age, sex) and trunk training-related moderator variables (e.g., training period, training frequency) for performance changes. We will conduct a systematic literature search in Web of Science, MEDLINE (via EBSCO) and SportDiscus. Relevant papers will be screened independently by two reviewers in two stages: (1) title and abstracts and (2) the full text of the remaining papers. A third reviewer will resolve possible disagreements. Data extraction and risk of bias of the included studies will be performed in addition to the PEDro scoring to judge the quality of the studies. A meta-analysis will be conducted to determine the efficacy of trunk training to increase physical fitness and sport-specific performance measures. In addition, subgroup univariate analyses were computed for subject-related (i.e., age, sex, performance level) and training-related moderator variables (i.e., training period, training frequency, training sessions, session duration). The results of this proposed systematic review and meta-analysis will assess the effects of trunk training on physical fitness and sport-specific and identify which subject-related and training-related moderate variables of trunk training modality might be beneficial for performance gains. This knowledge has potential importance for athletes and coaches in sports.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".