Inclusion of authorized deception in the informed consent process does not affect the magnitude of the placebo effect for experimentally induced pain
Bibliographic record
Abstract
The ethics of placebo research have been of paramount concern since the discovery of the phenomenon. To address these ethical concerns, Miller and colleagues (PLoS Med 2005 Sep;2(9):e262, 0853-0859) propose an alternate approach to placebo research, called "authorized deception", in which participants are alerted of the use of deception in the research prior to study enrollment and thus knowingly permit its use if they decide to participate. The present study sought to investigate the authorized deception methodology in experimentally induced placebo analgesia. The participants were randomly assigned to an authorized deception or non-authorized deception group. A commonly used protocol was employed wherein heat pain stimulation was surreptitiously lowered following the application of a placebo cream during a series of conditioning trials and the magnitude of the placebo effect was subsequently assessed in test trials for which the stimulus intensity was the same for both the placebo and control creams. Authorized deception did not have any negative impact on the magnitude of the placebo effect, recruitment and retention of participants, nor did it result in any significant psychological harm. The majority of participants who received this form of consent preferred it to the traditional approach in which the participants are not alerted to the presence of deception. These findings suggest that the use of authorized deception is a viable and ethically preferable alternative consent process for laboratory-based studies on placebo analgesia. Further studies are needed to examine the effect of authorized deception in clinical trials and other placebo research within a clinical setting.
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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 | 0.161 | 0.287 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".