Building a predictive model of U.S. patient willingness to undergo robotic surgery

Prior research regarding robotic surgery (RS) has largely focused on the engineering or medical aspects of these tools. A few studies have examined consumer opinions toward, or willingness to use, robotic surgeons; however, no study to date has examined what type of person would be willing to undergo RS. Across two studies, the current research fills this gap by building both a descriptive and predictive regression model used to predict what type of user would be willing to undergo RS. To build the descriptive model, 1324 potential patients were asked a series of questions about demographics, attitudes, opinions, and personalities. Results indicate that perceived value, familiarity, wariness of new technologies, fear of surgery, openness, anger, fear, and happiness are all significant predictors of willingness to undergo RS. A regression equation was developed and then used to predict scores in a second study with 1335 potential patients. The scores from both studies were compared for model fit. Several methods were used to validate the regression model, including correlational analyses, a t test, and calculation of the cross-validity coefficient. All three stringent tests showed strong model fit, explaining 62% of the variance in the model. These findings have both practical and theoretical values to the field and can be used to identify early adopters of this advanced medical technology.