Efficacy of Mulligan Mobilisation, Maitland Mobilization, High Velocity Thrust, and Muscle Energy Technique on Disability, Pain and Displacement of Center of Gravity in Subjects with Sacroiliac Dysfunction –A Research Protocol (Preprint)
Bibliographic record
Abstract
Background: Sacroiliac joint (SIJ) dysfunction is associated with significant pain, disability, and altered postural control in adults. Manual therapies, including Mulligan mobilization, Maitland mobilization, high-velocity thrust (HVT), and muscle energy technique (MET), are routinely applied for the management of SIJ dysfunction. However, comparative evidence regarding their effects on pain, disability, and center-of-gravity (COG) displacement remains insufficient. Objective: This study aims to compare the efficacy of Mulligan mobilization, Maitland mobilization, HVT, and MET in improving pain, functional disability, and COG displacement in individuals with SIJ dysfunction. Methods: A randomized controlled, parallel-group trial will be conducted on participants diagnosed with unilateral SIJ dysfunction. Participants will be assigned in equal numbers to 4 groups, each receiving Mulligan mobilization, Maitland mobilization, HVT, or MET interventions administered 5 days per week for 3 weeks, in addition to a standardized exercise regimen. The primary outcomes will be pain (assessed using a visual analog scale [VAS]) and functional disability (assessed using the Modified Oswestry Disability Index [MODI]), and the secondary outcome will be COG displacement (measured by sway velocity, lift-up index on the left and right, COG alignment, movement time, and impact index). Results: We hypothesize that all interventions will lead to statistically significant reductions in pain and disability. Results will be analyzed after the completion of the study. Conclusions: This protocol is designed to provide robust comparative data on manual therapy approaches for SIJ dysfunction. Findings may guide physiotherapy practice by informing evidence-based recommendations for optimal management strategies.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".