On Suggestibility and Placebo: A Follow-Up Study
Bibliographic record
Abstract
Identifying what makes some people respond well to placebos remains a major challenge. Here, we attempt to replicate an earlier study in which we found a relationship between hypnotic suggestibility and subjective ratings of relaxation following the ingestion of a placebo sedative (Sheiner, Lifshitz, & Raz, 2016). To assess the reliability of this effect, we tested 34 participants using a similar design. Participants ingested a placebo capsule in one of two conditions: (1) relaxation, wherein we described the capsule as a herbal sedative, or (2) control, wherein we described the capsule as inert. To index placebo response, we collected measures of blood pressure and heart rate, as well as self-report ratings of relaxation and drowsiness. Despite using a similar experimental design as in our earlier study, we were unable to replicate the correlation between hypnotic suggestibility and placebo response. Furthermore, whereas in our former experiment we observed a change in subjective ratings of relaxation but no change in physiological measures, here we found that heart rate dropped in the relaxation condition while subjective ratings remained unchanged. Even within a consistent context of relaxation, therefore, our present results indicate that placebos may induce effects that are fickle, tenuous, and unreliable. Although we had low statistical power, our findings tentatively accord with the notion that placebo response likely involves a complex, multifaceted interaction between traits, expectancies, and contexts.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".