Effectiveness of a lumbopelvic monitor and feedback device to change postural behaviour: the ELF cluster randomised controlled trial
Bibliographic record
Abstract
OBJECTIVES: The aim of this clustered, randomised controlled trial was to assess the effectiveness of a lumbopelvic postural feedback device for changing postural behaviour in a group of healthcare workers. We hypothesised that workers exposed to auditory postural feedback would reduce the number of times forward bending posture is adopted at work. METHODS: This was a participant and assessor blinded, randomised, sham-controlled trial with blocked cluster random allocation. We recruited healthcare workers from aged care institutions. Healthcare sites were randomly allocated to the feedback or sham group (SG). A postural monitoring and feedback device was used to monitor and record lumbopelvic forward bending posture, and provided audio feedback whenever the user sustained lumbopelvic forward bending posture that exceeded predefined thresholds. The primary outcome measure was postural behaviour (exceeding thresholds). We used a robust variant of repeated measures mixed-effect model for assessing within-group and between-group differences in postural behaviour. RESULTS: We recruited 19 sites, and 130 healthcare workers participated. There were no within-group changes on the number of times postural threshold was exceeded at 1-week follow-up (feedback group: -0.7, 95% CI -2.61 to 0.72; SG -0.3, -1.65 to 0.98), and no differences (0.05, 95% CI -1.83 to 1.94) between SG and feedback group. CONCLUSIONS: Findings from this trial indicate that audio feedback provided by a postural monitor device did not reduce the number of times healthcare workers exceeded the postural threshold. TRIAL REGISTRATION NUMBER: ACTRN12616000449437.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".