Nocebo effect in Dermatology
Bibliographic record
Abstract
Nocebo effect, originally denoting the negative counterpart of the placebo phenomenon, is now better defined as the occurrence of adverse effects to a therapeutic intervention because the patient expects them to develop. More commonly encountered in patients with a past negative experience, this effect stems from highly active processes in the central nervous system, mediated by specific neurotransmitters and modulated by psychological mechanisms such as expectation and conditioning. The magnitude of nocebo effect in clinical medicine is being increasingly appreciated and its relevance encompasses clinical trials as well as clinical practice. Although there is hardly any reference to the term nocebo in dermatology articles, the phenomenon is encountered routinely by dermatologists. Dermatology patients are more susceptible to nocebo responses owing to the psychological concern from visibility of skin lesions and the chronicity, unpredictable course, lack of 'permanent cure' and frequent relapses of skin disorders. While finasteride remains the prototypical drug that displays a prominent nocebo effect in dermatologic therapeutics, other drugs such as isotretinoin are also likely inducers. This peculiar phenomenon has recently been appreciated in the modulation of itch perception and in controlled drug provocation tests in patients with a history of adverse drug reactions. Considering the conflict between patients' right to information about treatment related adverse effects and the likelihood of nocebo effect stemming from information disclosure, the prospect of ethically minimizing nocebo effect remains daunting. In this article, we review the concept of nocebo effect, its postulated mechanism, relevance in clinical dermatology and techniques to prevent it from becoming a barrier to effective patient management.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".