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Factors Predicting Patients’ Willingness to Use Robotic Dental Services

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Abstract

Prior research into automated dental procedures has largely focused on design and engineering issues; however, there is very little research that investigates the public’s perceptions of, or their willingness to undergo, robotic dentistry. Therefore, the purpose of the current study is to better understand the characteristics of a person who would be willing to undergo robotic dental cleanings by building a predictive model. Using a correlational research design with regression, two stages were utilized to complete the study. Through two stages of research, 475 participants were recruited via an online database. Stage one evaluated several statistical factors on user willingness to create a predictive regression model. Stage two employed a secondary sample to validate the predictive model created in stage one by testing the regression equation for model fit. This predictive model accounted for approximately 82% of the variance in willingness to use dental robots for cleanings. The significant predictors were feelings of fear, feelings of happiness, complexity, useful factor, fun factor, fear of dental visits, and age respectively. These results are useful for the design and marketing of dental robots.

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Authors and Affiliations

  1. College of Arts and Sciences, Embry-Riddle Aeronautical University, 600 South Clyde Morris Blvd., Daytona Beach, FL, 32114, USA

    Mattie Milner, Scott R. Winter, Stephen Rice, Emily Anania, Nadine Ragbir & Cynthia Smith

  2. Florida Institute of Technology, 150 W University Blvd., Melbourne, FL, 32901, USA

    Rian Mehta

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  1. Mattie Milner
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Appendices

Appendix 1

Value Scale. This Likert-scale consisted of five statements about participants’ perceived value of robotic dentistry, which ranged from Strongly Disagree (− 2) to Strongly Agree (2). The statements were as follows: (1) I think dental robot technology is useful, (2) Dental robots would be something valuable for me to won, (3) If dental robots were available, I think it would be beneficial to use one, (4) There would be value in using a dental robot, and (5) A dental robot is something that would be beneficial to me.

For validation, researchers conducted a factor analysis using the principle components and varimax rotation, demonstrating that all items loaded onto one factor. A Cronbach’s Alpha was performed to examine for internal consistency and resulted in a value of .91, indicating high internal consistency and a Guttman’s split-half test resulted in a coffecient of .85, indicating high reliability [18].

Complexity Perception Scale. This Likert-scale consisted of five statements about participants’ perceived value of robotic dentistry, which ranged from Strongly Disagree (− 2) to Strongly Agree (2). The statements were as follows: (1) The automation that controls dental robots is very complex, (2) It is a mystery to me how the automation that controls dental robots operates, (3) I have no idea what the automation that controls dental robots is doing, (4) It is difficult to know how the automation that controls dental robots works, and (5) I do not understand the automation that controls dental robots.

For validation, researchers conducted a factor analysis using the principle components and varimax rotation, demonstrating that all items loaded onto one factor. A Cronbach’s Alpha was performed to examine for internal consistency and resulted in a value of .86, indicating high internal consistency and a Guttman’s split-half test resulted in a coefficient of .85, indicating high reliability [18].

Familiarity Scale. This Likert-scale consisted of five statements about participants’ perceived value of robotic dentistry, which ranged from Strongly Disagree (− 2) to Strongly Agree (2). The statements were as follows: (1) I have a lot of knowledge about dental robots, (2) Dental robots have been of interest to me for awhile, (3) I have read a lot about dental robots, (4) I know more about dental robots than the average person, and (5) I am familiar with dental robots.

For validation, researchers conducted a factor analysis using the principle components and varimax rotation, demonstrating that all items loaded onto one factor. A Cronbach’s Alpha was performed to examine for internal consistency and resulted in a value of .91, indicating high internal consistency and a Guttman’s split-half test resulted in a coefficient of .84, indicating high reliability [18].

Wariness of New Technology Scale. This Likert-scale consisted of five statements about participants’ perceived value of robotic dentistry, which ranged from Strongly Disagree (− 2) to Strongly Agree (2). The statements were as follows: (1) New technology is not as safe as it should be, (2) In general, I am wary of new technology, (3) New technology is likely to be dangerous, (4) New technology scare me, and (5) I tend to fear new technology until it is proven to be safe.

For validation, researchers conducted a factor analysis using the principle components and varimax rotation, demonstrating that all items loaded onto one factor. A Cronbach’s Alpha was performed to examine for internal consistency and resulted in a value of .88, indicating high internal consistency and a Guttman’s split-half test resulted in a coefficient of .72, indicating high reliability [18].

Fun Scale. This Likert-scale consisted of five statements about participants’ perceived value of robotic dentistry, which ranged from Strongly Disagree (− 2) to Strongly Agree (2). The statements were as follows: (1) I am interested in trying out a dental robot, (2) I like the idea of dental robots, (3) I think it would be cool to have a dental robot work on me, (4) I think it would be fun to use a dental robot, and (5) I’ve always wanted to use a dental robot.

For validation, researchers conducted a factor analysis using the principle components and varimax rotation, demonstrating that all items loaded onto one factor. A Cronbach’s Alpha was performed to examine for internal consistency and resulted in a value of .93, indicating high internal consistency and a Guttman’s split-half test resulted in a coefficient of .90, indicating high reliability [18].

Appendix 2

Consumer willingness to undergo robotic dentistry. This scale was adapted from a previously validated willingness to fly scale [60].

Please respond how strongly you agree or disagree with the following statements.

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Appendix 3

Survey Instrument.

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Milner, M., Mehta, R., Winter, S.R. et al. Factors Predicting Patients’ Willingness to Use Robotic Dental Services. Int J of Soc Robotics 13, 1803–1821 (2021). https://doi.org/10.1007/s12369-020-00737-7

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