Determining Physiological and Psychological Predictors of Time to Task Failure on a Virtual Reality Sørensen Test in Participants With and Without Recurrent Low Back Pain: Exploratory Study
Bibliographic record
Abstract
BACKGROUND: Sørensen trunk extension endurance test performance predicts the development of low back pain and is a strong discriminator of those with and without low back pain. Performance may greatly depend on psychological factors, such as kinesiophobia, self-efficacy, and motivation. Virtual reality video games have been used in people with low back pain to encourage physical activity that would otherwise be avoided out of fear of pain or harm. Accordingly, we developed a virtual reality video game to assess the influence of immersive gaming on the Sørensen test performance. OBJECTIVE: The objective of our study was to determine the physiological and psychological predictors of time to task failure (TTF) on a virtual reality Sørensen test in participants with and without a history of recurrent low back pain. METHODS: We recruited 24 individuals with a history of recurrent low back pain and 24 sex-, age-, and body mass index-matched individuals without a history of low back pain. Participants completed a series of psychological measures, including the Center for Epidemiological Studies-Depression Scale, Pain Resilience Scale, Pain Catastrophizing Scale, Tampa Scale for Kinesiophobia, and a self-efficacy measure. The maximal isometric strength of trunk and hip extensors and TTF on a virtual reality Sørensen test were measured. Electromyography of the erector spinae, gluteus maximus, and biceps femoris was recorded during the strength and endurance trials. RESULTS: A two-way analysis of variance revealed no significant difference in TTF between groups (P=.99), but there was a trend for longer TTF in females on the virtual reality Sørensen test (P=.06). Linear regression analyses were performed to determine predictors of TTF in each group. In healthy participants, the normalized median power frequency slope of erector spinae (beta=.450, P=.01), biceps femoris (beta=.400, P=.01), and trunk mass (beta=-.32, P=.02) predicted TTF. In participants with recurrent low back pain, trunk mass (beta=-.67, P<.001), Tampa Scale for Kinesiophobia (beta=-.43, P=.01), and self-efficacy (beta=.35, P=.03) predicted TTF. CONCLUSIONS: Trunk mass appears to be a consistent predictor of performance. Kinesiophobia appears to negatively influence TTF for those with a history of recurrent low back pain, but does not influence healthy individuals. Self-efficacy is associated with better performance in individuals with a history of recurrent low back pain, whereas a less steep median power frequency slope of the trunk and hip extensors is associated with better performance in individuals without a history of low back pain.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 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".