Bibliographic record
Abstract
Diabetic peripheral neuropathy (DPN) is one of the most prevalent chronic complications of diabetes. One of its crucial therapy approaches is mind-body exercise. Recently, various exercise modalities, including stepping, resistance, aerobics, balance, and whole-body vibration, were investigated to construct the most suitable form of exercise for patients with DPN. The purpose of this study is to describe a standard protocol for mindfulness training combined with Tai Chi. The convenience sampling method was used to select 90 patients with DPN who met the inclusion and exclusion criteria from three communities. The three communities were randomly divided into the control group (CG), the Tai Chi group (TCG), and the mindfulness training combined with the Tai Chi group (MTCG). The CG was given routine health education guidance once a month, a total of three times. Based on the CG, the TCG practiced Tai Chi three times; the MTCG received mindfulness training combined with Tai Chi exercise a week for a total of 12 weeks. Before the intervention and 12 weeks after the intervention, the clinical symptoms, neurological function, attention awareness level, pain, and quality of life of the subjects were evaluated by Toronto Clinical Scoring System (TCSS), Mindful Attention Awareness Scale (MAAS), Visual analog scale (VAS), Diabetes Specificity Quality of life Scale (DSQL) and tumor necrosis factor-α. Overall, the addition of mindfulness training to Tai Chi effectively enhances the exercise effects of Tai Chi. Therefore, mindfulness training combined with Tai Chi is worthy of promotion and application.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.396 | 0.287 |
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".