Large-Scale Online stimulus Norming and Surveys about Perceptions in Healthcare

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Pain can be modulated by interpersonal processes that support the patient-provider relationship, and contextual factors related to the treatment environment. In this project, we investigate large-scale norms and beliefs about healthcare in America, and how perceptions of people and other visual cues in the treatment environment influence expectations about pain during treatment and about the pain other people feel. This project uses online survey methodologies to measure large scale normed beliefs and expectations from a geographically, ethnically, and socioeconomically diverse population of Americans. The purpose of this project is to investigate healthcare beliefs that may enhance or diminish pain in the clinic, which can be used to design studies in the laboratory to test if manipulating these beliefs can be advantageous for pain outcomes. Data collection for this project began in FY19. We began by asking how first impressions of medical providers influence expectations of pain during a medical procedure and expectations for post-surgical recovery. Past work has demonstrated that perceptions of medical providers competence influence the experience of pain in the clinic, and that perceptions of medical providers similarity to a patient influence the patients experience of pain in a simulated clinical interaction. In domains outside of healthcare, research has demonstrated that even first impressions of traits such as competence can influence expectations and behavior: for instance, more competent looking politicians are more likely to be elected. Therefore, we were interested in measuring whether peoples perceptions of medical providers influenced their expectations about pain they might experience if that medical provider were to conduct a procedure on them. We were also interested in whether their beliefs about medical providers and pain treatment options in general (i.e., medical providers in general are competent, I feel favorable about herbal medication for pain) would influence their expectations. In FY2019, we collected four samples on the online platform Mechanical Turk to test this question. Participants completed surveys in which they viewed images of peoples faces and were told that they should imagine that the faces were those of potential medical providers who could conduct a procedure on them. They first chose medical providers that they would prefer to conduct painful procedures on them, and then they rated how painful they expected those procedures to be and the types of treatment they would expect that they would need in post-surgical recovery. In two of our samples, we used computer generated faces; in two other samples, we used real human faces. In three of our samples, participants rated how similar the stimulus faces were to themselves. In some samples, participants also rated the faces on perceived competence (in other samples, we used stimuli from published stimulus sets on which these characteristics had already been rated). We observed that people preferred faces that looked more competent and more similar to them to be their medical providers. Furthermore, they expected to experience less pain and to have less need for prescription-strength pain medication following hypothetical procedures conducted by more competent looking medical providers and following procedures conducted by medical providers that were more similar to them. We are now exploring the role of their attitudes on their pain and treatment expectations, and are exploring the role of hypothetical provider demographic characteristics (e.g., race/sex) on participants expectations. We are also in the process of writing up a manuscript for publication explaining the effects of first impressions of provider competence and similarity on pain and treatment expectations.