Effect Of High Resistance Weight Training On Reported Pain In Individuals With Type 2 Diabetes
Bibliographic record
Abstract
Chronic pain is common in the diabetic population and pain makes it difficult to sustain a physical activity program. There is evidence that strength training can significantly reduce pain, but this has not been explored in this population. PURPOSE: To examine the effect of a progressive, whole-body, high resistance weight training program on reported pain in adults with Type 2 diabetes. METHODS: Forty-three participants (age=60.9+10.7; BMI=33.5+7.6; waist:hip ratio=0.95+0.07; entering A1C=7.3+1.9) were assigned to a treatment group (n=19, 16 weeks of weight training) or a delayed treatment control group (n=24, 8 weeks of weight training). All subjects completed the McGill Pain Questionnaire at three intervals (0, 8, 16 weeks). The high intensity resistance training period (8 or 16 weeks) was three days a week on eleven different exercises with a progression up to loads representing 80% of one-repetition maximum. Pain was assessed using the McGill Pain Questionnaire that measured pain rating index total (PRIT), sensory (PRIS), affective (PRIA), evaluative (PRIE), miscellaneous (PRIM), number of words chosen (NWC), present pain intensity (PPI), and number of painful areas (NPA). A two-way ANOVA with one repeated factor was applied to determine group and test differences. RESULTS: Strength was significantly improved in both groups across all eleven exercises over the eight week time period with strength gains ranging from 30% to 74% (p=0.000). The treatment group continued to improve in strength over 16 weeks in the range of 51% to 134% (p=0.000). There were significant differences between the treatment and the delayed-treatment group for five of pain variables: PRIT (p=0.033), PRIS (p=0.029), PRIS (p=0.037), PRIM (p=0.017), and NWC (p=0.022). There were significant changes in pain perception in the treatment group for four pain variables (PRIT, PRIM, NWC, NPA) following training. In the delayed-treatment group, there were no significant changes in any pain variable between the pretest and the 8 week inactive period, but significant changes in four of the pain variables (PRIT, PRIS, PPI, NPA) after training in weeks 8-16. CONCLUSIONS: These results suggest that a progressive, whole-body weight training program has a positive impact on perception of pain in adults with Type 2 diabetes.
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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 | 0.001 |
| 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) | 0.001 | 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 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".