Feedback on Trunk Movements From an Electronic Game to Improve Postural Balance in People With Nonspecific Low Back Pain: Pilot Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Postural balance is compromised in people with low back pain, possibly by changes in motor control of the trunk. Augmenting exercising interventions with sensor-based feedback on trunk posture and movements might improve postural balance in people with low back pain. OBJECTIVE: We hypothesized that exercising with feedback on trunk movements reduces sway in anterior-posterior direction during quiet standing in people with low back pain. Secondary outcomes were lumbar spine and hip movement assessed during box lift and waiter bow tasks, as well as participant-reported outcomes. Adherence to the exercising intervention was also examined. METHODS: A randomized controlled trial was conducted with the intervention group receiving unsupervised home exercises with visual feedback using the Valedo Home, an exergame based on 2 inertial measurement units. The control group received no intervention. Outcomes were recorded by blinded staff during 4 visits (T1-T4) at University Hospital Zurich. The intervention group performed 9 sessions of 20 minutes in the 3 weeks between T2 and T3 and were instructed to exercise at their own convenience between T3 and T4. Postural balance was assessed on a force platform. Lumbar spine and hip angles were obtained from 3 inertial measurement units. The assessments included pain intensity, disability, quality of life, and fear of movement questionnaires. RESULTS: A total of 32 participants with nonspecific low back pain completed the first assessment T1, and 27 (84%) participants were randomized at T2 (n=14, 52% control and n=13, 48% intervention). Intention-to-treat analysis revealed no significant difference in change in anterior-posterior sway direction during the intervention period with a specified schedule (T2-T3) between the groups (W=99; P=.36; r=0.07). None of the outcomes showed significant change in accordance with our hypotheses. The intervention group completed a median of 61% (55/90; range 2%-99%) of the exercises in the predefined training program. Adherence was higher in the first intervention period with a specified schedule. CONCLUSIONS: The intervention had no significant effect on postural balance or other outcomes, but the wide range of adherence and a limited sample size challenged the robustness of these conclusions. Future work should increase focus on improving adherence to digital interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT04364243; https://clinicaltrials.gov/ct2/show/NCT04364243. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/26982.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.001 | 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".