Placebo and nocebo response magnitude on temporomandibular disorder‐related pain: A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVES: The aim of this systematic review (SR) was to answer the following question: "In adult patients with temporomandibular disorder (TMD)-related pain, what is the placebo or nocebo effect of different therapies?" METHODS: A SR was performed with randomised clinical placebo-controlled trials on diagnosed painful TMD studies from five main databases and from three grey literature. Studies included must have sample older than 18 years, with painful TMD, which diagnosis was done by Research Diagnostic Criteria (RDC/TMD) or Diagnostic Criteria (DC/TMD). RESULTS: Out of 770 articles obtained, 42 met the inclusion criteria for qualitative and 26 for quantitative analysis. Meta-analysis indicated mean variation on pain intensity for placebo therapy was higher on laser acupuncture with 45.5 mm point reduction, followed by avocado soya bean extract with 36 mm and amitriptyline 25 mg with 25.2 mm. Laser showed a 29% of placebo effect, as well medicine with 19% and other therapies with 26%. Possible nocebo effect of 8% pain increase was found for intra-articular injection of Ultracain. CONCLUSIONS: Based on the available data, the placebo response could play a major effect on TMD pain management and may be responsible from 10% to 75% of pain relief. Laser acupuncture, avocado soya bean and amitriptyline promoted the higher placebo effect. Possible nocebo effect was found only for Ultracain injection with 8%. CLINICAL RELEVANCE: Clinicians could apply such evidence to optimise pain management and judgement about treatment efficacy, and researches may find it useful when designing their investigations.
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 | 0.023 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.038 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".