Nonlinear Effects of Noxious Thermal Stimulation and Working Memory Demands on Subjective Pain Perception.

OBJECTIVE: A bidirectional relationship between working memory (WM) and acute pain has long been assumed, but equivocal evidence exists regarding this relationship. This study characterized the relationship between WM and acute pain processing in healthy individuals using an adapted Sternberg WM task. DESIGN: Participants completed a Sternberg task while receiving noxious thermal stimulation. Participants received a pseudorandom presentation of four different temperatures (baseline temperatures and individually determined low-, medium-, and high-temperature stimuli) and four levels of Sternberg task difficulty (0-, 3-, 6-, and 9-letter strings). SUBJECTS: Twenty-eight healthy participants were recruited from Stanford University and the surrounding community to complete this study. RESULTS: A nonlinear interaction between intensity of thermal stimulation and difficulty of the Sternberg task was noted. Increased cognitive load from the Sternberg task resulted in increased perception of pain in low-intensity thermal stimulation but suppressed pain perception in high-intensity thermal stimulation. Thermal stimulation had no significant effect on participants' response time or accuracy on the Sternberg task regardless of intensity level. CONCLUSIONS: Pain perception appears to decrease as a function of WM load only for sufficiently noxious stimuli. However, increasing noxious stimuli did not affect cognitive performance. These complex relationships may reflect a shared cognitive space that can become "overloaded" with input of multiple stimuli of sufficient intensity.

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

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.