Bibliographic record
Abstract
OBJECTIVE: To familiarize family physicians with new and emerging evidence regarding the underlying central nervous system (nociplastic) pathogenesis of many chronic pain conditions and review modalities of psychotherapy that can specifically target nociplastic pain and other symptoms. QUALITY OF EVIDENCE: Psychotherapy modalities for the treatment of patients with nociplastic chronic pain (eg, pain reprocessing therapy, emotional awareness and expression therapy, intensive short-term dynamic psychotherapy) have level I evidence to support their efficacy in treating patients with various pain conditions as well as those with other chronic symptoms lacking clear structural causes. MAIN MESSAGE: Family physicians should be aware that many patients with chronic pain and other persistent symptoms may benefit from therapeutic approaches that target the central nervous system rather than the site where symptoms are felt. Meta-analyses have shown that older nonspecific modalities of psychotherapy (eg, cognitive behavioural therapy, acceptance and commitment therapy) have limited efficacy in treating patients with these conditions. Recent trial evidence and systematic reviews have shown that pain reprocessing therapy, emotional awareness and expression therapy, and intensive short-term dynamic psychotherapy can be helpful for many patients with nociplastic symptoms and may also help improve comorbid mood and anxiety symptoms. CONCLUSION: Psychotherapy is a safe and effective way to treat patients with chronic pain conditions that have nociplastic components. Access to effective therapy modalities may be a limiting factor, but self-treatment using online or virtual resources can be helpful for many patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".