Repeatability of Clinical, Biomechanical, and Motor Control Profiles in People with and without Standing-Induced Low Back Pain
Bibliographic record
Abstract
A major research focus is optimization of interventions for low back pain (LBP). Predisposing factors for LBP development have been previously identified. To differentiate changes in these factors with intervention, factor stability over time must be determined. Twenty-three volunteers without LBP participated in a LBP-inducing standing protocol on two separate days. Outcome measures included visual analog scale (VAS) for LBP and trunk/hip muscle coactivation patterns. Intraclass correlation coefficients (ICCs) were used to examine repeatability. Between-day repeatability of outcome measures was excellent (ICCs >0.80). Individuals were consistent in subjective LBP, with 83% reporting similar day-to-day VAS levels. Muscle co-activation patterns and LBP reports are stable measures over time for this LBP-inducing protocol. Changes in these measures following intervention can be considered to be treatment effects and are not due to natural variability. This provides support for use of this protocol in studying interventions for standing-induced LBP.
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 | 0.003 | 0.013 |
| 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) | 0.000 | 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 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".