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Record W4410141532 · doi:10.2196/67557

Effects of Traditional Chinese Exercise Yijinjing on Disability and Muscle Strength Among Patients With Chronic Low Back Pain: Protocol for a Randomized Controlled Trial

2025· article· en· W4410141532 on OpenAlexaffvenue
Cheng Wang, Xue Bai, Yukui Tian, Mengni Shi, Min Fang, Jing Xian Li, Qingguang Zhu, Junchang Liu

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPhysical therapyMedicineRandomized controlled trialLow back painOswestry Disability IndexMoodBack painQuality of life (healthcare)Physical medicine and rehabilitationChronic painPsychological interventionPain catastrophizingAlternative medicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Chronic low back pain (CLBP) is a common public health problem. Progressive loss of muscle strength leads to long-term chronic pain and disability. Yijinjing exercises, an ancient therapy dating back thousands of years, are widely used in China to treat low back pain. However, little is known about its benefits and scientific evidence for back extensor strength. This trial aimed to assess the efficacy of Yijinjing on disability and dorsal extensor strength in patients with CLBP. OBJECTIVE: We present a randomized controlled study to evaluate the efficacy of the traditional Chinese exercise Yijinjing on disability and back extensor strength in patients with CLBP. METHODS: This is a 2-arm, parallel-design, assessor-blinded, and analyst-blinded randomized controlled trial. The 106 participants with CLBP who were recruited will first receive basic traditional Chinese manual therapy to help relieve their physical discomfort. Second, they will be randomly divided into a Yijinjing group (n=53) and a control group with functional exercises (n=53) at a ratio of 1:1. The interventions for both groups will be carried out twice a week for 4 weeks. Patients in both groups will be followed up at 1 and 3 months after the intervention. The primary outcome is disability (measured by the Oswestry Disability Index). The secondary outcomes included pain intensity (assessed by the Numerical Rating Scale), data from isokinetic dynamometry, flexibility (assessed by the fingertip-to-floor test), mood (evaluated by the Pain Catastrophizing Scale and Fear Avoidance Beliefs Questionnaire), and quality of life (measured by the EQ-5D-5L). All adverse effects will be assessed using the Treatment Emerging Symptoms Scale, and data will be analyzed using an intention-to-treat analysis. RESULTS: The trial was funded in December 2023. The Institutional Ethics Committee of Yueyang Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, approved this study. The first patient was enrolled in February 2024, and as of August 2024, a total of 106 participants have been recruited. Data analysis has not yet begun and is expected to be published in January 2025. The protocol has been registered with the Chinese Clinical Trial Registry (ChiCTR2400081105). CONCLUSIONS: If this trial proves effective, it will guide the setup of a randomized controlled trial to demonstrate whether traditional Chinese exercise Yijinjing improves disability in patients with CLBP and is more effective than usual stretching exercises. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2400081105; https://www.chictr.org.cn/showprojEN.html?proj=214425. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/67557.

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)0.032
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.056
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.028
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0170.008
Bibliometrics0.0030.004
Science and technology studies0.0040.004
Scholarly communication0.0040.004
Open science0.0040.002
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0560.008

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 head0.030
GPT teacher head0.425
Teacher spread0.395 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations0
Published2025
Admission routes2
Has abstractyes

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