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Record W4385845717 · doi:10.2196/43985

Effects of Virtual Reality Exercises on Chronic Low Back Pain: Quasi-Experimental Study

2023· article· en· W4385845717 on OpenAlexvenueno aff
Waqar Afzal, Ashfaq Ahmad, Hafiz Muhammad Bilal Hanif, Nauman Chaudhary, Syed Amir Gilani

Bibliographic record

VenueJMIR Rehabilitation and Assistive Technologies · 2023
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical therapyLow back painMedicineLumbarAnalysis of varianceChronic painRehabilitationPhysical medicine and rehabilitationSurgeryAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Low back pain is a common health problem globally. Based on the duration of pain, it is classified as acute, subacute, or chronic low back pain. Different treatment strategies are available to reduce chronic low back pain. Virtual reality (VR) is a novel approach in back pain rehabilitation. OBJECTIVE: This study aimed to compare the effects of VR games on chronic low back pain. METHODS: This quasi-experimental study was conducted among 40 patients with chronic low back pain. The data were collected using a nonprobability, convenient sampling technique. Patients visiting the Department of Physiotherapy, Government Services Hospital, Lahore, Pakistan, were recruited and equally divided into 4 groups. Group A received the Reflex Ridge game; group B received the Body Ball game; group C combined the 2 games without back-strengthening exercises; and group D combined the 2 games with back-strengthening exercises. The participants received 8 treatment sessions, with 3 sessions/wk. The outcomes were pre- and posttest measurements of pain intensity, low back disability, and lumbar range of motion. The repeated measurement ANOVA was used for inter- and intragroup comparison, with significance at P≤.05. RESULTS: The study comprised a sample of 40 patients with low back pain; 12 (40%) were female and 28 (60%) were male, with a mean age of 37.85 (SD 12.15) years. The pre- and posttest mean pain scores were 7.60 (SD 1.84) and 4.20 (SD 1.62) in group A, 6.60 (SD 1.776) and 5.90 (SD 1.73) in group B, 6.90 (SD 1.73) and 5.40 (SD 1.07) in group C, and 7.10 (SD 1.53) and 3.60 (SD 0.97) in group D, respectively. The mean pain score differences of group D (combining the Reflex Ridge and Body Ball games with back-strengthening exercises) compared to groups A, B, and C were -.60 (P=.76), -2.30 (P<.001), and -1.80 (P=.03), respectively. Regarding the range of motion, the forward lumbar flexion mean differences of group D compared to groups A, B, and C were 3.80 (P=.21), 4.80 (P=.07), and 7.40 (P<.001), respectively. Similarly, the right lateral lumbar flexion mean differences of group D compared to groups A, B, and C were 2.80 (P=.04), 5.20 (P<.001), and 4.80 (P<.001), respectively. The left lateral lumbar flexion mean differences of group D compared to groups A, B, and C were 2.80 (P<.001), 4.80 (P=.02), and 2.20 (P<.001). respectively, showing significant pre- and posttreatment effects. CONCLUSIONS: VR exercises had statistically significant effects on improving pain, low back disability, and range of motion in all groups, but the combination of Reflex Ridge and Body Ball games with back-strengthening exercises had dominant effects compared to the other groups. TRIAL REGISTRATION: Iranian Registry of Clinical Trial IRCT20200330046895N1; https://en.irct.ir/trial/46916.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.013
GPT teacher head0.320
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

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