Development of the Stanford Expectations of Treatment Scale (SETS): a tool for measuring patient outcome expectancy in clinical trials

Clin Trials. 2012 Dec;9(6):767-76. doi: 10.1177/1740774512465064. Epub 2012 Nov 20.


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.

Publication types

  • Evaluation Study

MeSH terms

  • Adult
  • Aged
  • Attitude to Health*
  • Clinical Trials as Topic / methods
  • Clinical Trials as Topic / psychology*
  • Data Interpretation, Statistical
  • Factor Analysis, Statistical
  • Female
  • Humans
  • Male
  • Middle Aged
  • Placebo Effect
  • Predictive Value of Tests
  • Psychometrics
  • Reproducibility of Results
  • Research Design
  • Research Subjects / psychology*
  • Surveys and Questionnaires*