The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.
Development of the Stanford Expectations of Treatment Scale (SETS): A tool for measuring patient outcome expectancy in clinical trials
Abstract
Background: A patient’s response to treatment may be influenced by the expectations that the patient has before initiating treatment. In the context of clinical trials, the influence of participant expectancy may blur the distinction between real and sham treatments, reducing statistical power to detect specific treatment effects. There is therefore a need for a tool that prospectively predicts expectancy effects on treatment outcomes across a wide range of treatment modalities. Purpose: To help assess expectancy effects, we created the Stanford Expectations of Treatment Scale (SETS): an instrument for measuring positive and negative treatment expectancies. Internal reliability of the instrument was tested in Study 1. Criterion validity of the instrument (convergent, discriminant, and predictive) was assessed in Studies 2 and 3. Methods: The instrument was developed using 200 participants in Study 1. Reliability and validity assessments were made with an additional 423 participants in Studies 2 and 3. Results: The final six-item SETS contains two subscales: positive expectancy (α = 0.81–0.88) and negative expectancy (α = 0.81–0.86). The subscales predict a significant amount of outcome variance (between 12% and 18%) in patients receiving surgical and pain interventions. The SETS is simple to administer, score, and interpret. Conclusion: The SETS may be used in clinical trials to improve statistical sensitivity for detecting treatment differences or in clinical settings to identify patients with poor treatment expectancies.
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“Participants’ expectancy will be assessed with the Stanford Expectations of Treatment Scale (SETS; [114]) at baseline”
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“Secondary outcomes showed promising signs, although the openlabel design and small sample size means that the results must be interpreted in the context of treatment expectancy at baseline, in which positive effects were higher than average and negative effects were lower than average [41].”
From Psilocybin‐assisted psychotherapy for methamphetamine use disorder: A pilot open‐label safety and feasibility study. (2025) · cites this paper as [41]
In the citing paper
“Valid measures of response expectancies include the Stanford Expectations of Treatment Scale (SETS), 87 and the credibility/expectancy questionnaire (CEQ). 88”
From Best Practice Recommendations for Conducting and Reporting Controlled Trials in Clinical Hypnosis Research (2024) · cites this paper as [87]
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“expectancy and negative expectancy), predicted a significant amount of outcome variance in patients receiving surgical and pain intervention [175].”
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Self-citation
Metadata
- Authors
- Younger, J., Gandhi, V., Hubbard, E., & Mackey, S.
- Affiliations
- Stanford Medicine (US)
- Venue
- Clinical Trials
- Publisher
- SAGE Publications
- Published
- 2012-11-20
- Volume
- 9
- Issue
- 6
- Pages
- 767-776
- ISSN
- 1740-7745 (ISSN-L)
- 1740-7753
- OpenAlex
- W2020646491
- Cited by
- 212
- References
- 69
- Citations by year
- 2026: 27 · 2025: 33 · 2024: 24 · 2023: 23 · 2022: 26 · 2021: 21 · 2020: 14 · 2019: 10 · 2018: 15 · 2017: 8 · 2016: 5 · 2015: 3 · 2014: 2 · 2013: 1
- FWCI
- 0.98
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Clinical Trials (publishedVersion)
- PubMed (publishedVersion)
- Funders
- School of Medicine, Stanford University
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Pain Management and Placebo Effect
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Social Sciences › Psychology › Clinical Psychology › Psychotherapy Techniques and Applications
- Keywords
- treatment expectancy, patient expectations, placebo effect, expectancy effects, scale development, psychometric validation, surgical treatment, pain interventions, statistical power
- MeSH terms
- Adult, Aged, Attitude to Health, Clinical Trials as Topic, Data Interpretation, Statistical, Factor Analysis, Statistical, Female, Humans, Male, Middle Aged, Predictive Value of Tests, Psychometrics, Surveys and Questionnaires, Research Design, Reproducibility of Results, Placebo Effect, Research Subjects
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