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Record W4239108105 · doi:10.31234/osf.io/sh4f6

Super placebos: A feasibility study combining contextual factors to promote placebo effects

2020· preprint· en· W4239108105 on OpenAlexaff
Jay A. Olson, Michael Lifshitz, Amir Raz, Samuel P. L. Veissière

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsMcGill University
Fundersnot available
KeywordsPlaceboPsychological interventionIntervention (counseling)MedicinePopulationClinical psychologyPsychologyAdverse effectPsychiatryAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

Ample evidence demonstrates that placebo effects are modulated by contextual factors. Few interventions, however, attempt to combine a broad range of these factors. Here, we explore the therapeutic power of placebos by leveraging factors including social proof, positive suggestion, and social learning. This study aimed to test the feasibility of an elaborate "super placebo" intervention to reduce symptoms of various disorders in a pediatric population. In a single-arm qualitative study, participants entered an inactive MRI scanner which they were told could help their brain heal itself through the power of suggestion. The sample included 11 children (6-13 years old) diagnosed with disorders known to be receptive to placebos and suggestion (Attention Deficit Hyperactivity Disorder, Tourette Syndrome, chronic skin picking, and migraines). The children were given positive suggestions before entering the scanner for 2 to 4 sessions over the span of approximately one month. We assessed open-ended treatment outcomes via recorded interviews and home visits. The procedure was feasible and no adverse events occurred. Ten of the eleven parents reported improvements in their children after the intervention, ranging from minor transient changes to long-term reductions in subjective and objective symptoms (e.g., migraines and skin lesions). These preliminary findings demonstrate the feasibility and promise of combining a broad range of contextual factors in placebo studies. Future research is needed to assess the causal effects of such interventions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0020.004
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.098
GPT teacher head0.332
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2020
Admission routes1
Has abstractyes

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