Spinal mobilization characteristics: a scoping literature review of biomechanical parameters
Bibliographic record
Abstract
Background Spinal mobilization (SMob) is often included in the conservative management of spinal pain conditions as a recommended and effective treatment. While some studies quantify the biomechanical (kinetic) parameters of SMob, interpretation of findings is difficult due to poor reporting of methodological details. The aim of this study was to synthesise the literature describing biomechanical parameters of manually applied SMob. Methods This study is reported in accordance with the Preferred Reporting Items for Scoping Reviews (PRISMA-ScR) statement. Databases were searched from inception to October 2022: MEDLINE (Ovid), Embase, CINAHL, ICL, PEDro and Cochrane Library. Data were extracted and reported descriptively for the following domains: general study characteristics, number of and characteristics of individuals who delivered/received SMob, region treated, equipment used and biomechanical parameters of SMob. Results Of 7,607 records identified, 36 (0.5%) were included in the analysis. Of these, SMob was delivered to the cervical spine in 13 (36.1%), the thoracic spine in 3 (8.3%) and the lumbopelvic spine in 18 (50.0%) studies. In 2 (5.6%) studies, spinal region was not specified. For SMob applied to all spinal regions, biomechanical parameters were: peak force (0-128N); duration (10-120s); frequency (0.1-4.5Hz); and force amplitude (1-102N). Conclusions This study reports considerable variability of the biomechanical parameters of SMob. In studies reporting biomechanical parameters, SMob was most frequently delivered to the lumbar and cervical spine of humans and most commonly peak force was reported. Future studies should focus on the detailed reporting of biomechanical parameters to facilitate the investigation of clinical dose-response effects.
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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 | 0.022 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.056 | 0.052 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".