Combining transcutaneous electrical nerve stimulation with therapeutic exercise to reduce pain in an elderly population: a pilot study
Bibliographic record
Abstract
PURPOSE: Chronic pain is a highly prevalent and debilitating condition, and there is a pressing need to find safe, effective and affordable treatments to tackle this public health issue. This pilot study aimed to assess whether therapeutic exercises supplemented by transcutaneous electrical nerve stimulation induces a greater hypoalgesic effect than therapeutic exercises supplemented by sham transcutaneous electrical nerve stimulation, in an elderly population suffering from chronic pain. MATERIALS AND METHODS: Eighteen elderly participants suffering from chronic pain completed a therapeutic exercise program consisting of 45-min group sessions administered twice a week for 4 weeks. Half of the participants received real transcutaneous electrical nerve stimulation during the exercise sessions, while the others received sham transcutaneous electrical nerve stimulation. Participants completed pain questionnaires (McGill Pain Questionnaire, Brief Pain Inventory, Beck Depression Index) before and after the intervention, and recorded their pain levels on an 11-point numerical rating scale before and after each session (Clinical Trial.Gov ID: NCT02445677). RESULTS AND CONCLUSION: Our results suggest that supplementing exercise sessions with transcutaneous electrical nerve stimulation does not improve the long-term outcomes of elderly patients suffering from chronic pain, but does induce short-term hypoalgesia during exercise sessions. Our study also offers valuable guidelines for the implementation of a future and adequately powered study looking at this research question.Implications for rehabilitationThe application of transcutaneous electrical nerve stimulation during exercises is well tolerated by elderly individuals suffering from chronic pain.Supplementing exercises with transcutaneous electrical nerve stimulation does not seem to improve general outcome in elderly suffering from chronic pain.Notwithstanding, the addition of transcutaneous electrical nerve stimulation tends to produce a marked hypoalgesic effect during the exercise sessions, an effect that could prompt indirect benefits for pain patients.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".