The study was approved by the Mayo Clinic Institutional Review Board. The study used a cross-sectional survey design.

We displayed posters and ads in select community locations in Rochester, MN, and on websites and conducted face-to-face outreach between March 5 and June 11, 2018. We recruited a convenience sample of adolescents from three community settings that serve racially and socioeconomically diverse youth and offer programs after school and on weekends. Study team members consulted with the staff at each community-based organization to determine appropriate times for recruitment and data collection. Recruitment took place four times at the Rochester Public Library and three times at the YMCA, each lasting about three hours; a local church also hosted one recruitment event.

Study staff screened adolescents in person to determine their potential to participate based on the study eligibility criteria: (1) aged 12-17 years old and (2) possessing a completed written informed consent and assent document, signed by the parent or guardian and participant. Exclusion criteria were being older than 17 years old and younger than 12 years old. We did not track the number of adolescents who received consent forms but did not complete them.

The robotic system-human interface technology was used as a robotic-assisted exercise coach. The interface was delivered in real time via an iPad tablet placed on a mobile robotic wheel base and controlled remotely by an iOS device or computer. Developed by Double Robotics, Inc, for telecommuting and school attendance, the device measures 5 feet 1 inch in length. The “robot” iPad interface (see Figure 1) and the mobile phone device used to control it both required installation of the Double app (Double Robotics) [20,21].

Wi-Fi access on both devices was necessary to ensure functionality, which was available in each of the three community settings where the robot was demonstrated. A study staff member was designated as the exercise coach; she logged into the Double app through her mobile phone device and remotely interfaced with the iPad robot for demonstration purposes.

Prior to recruitment events, possible participants were identified at each setting by community and study staff, who gave a brief overview of the study to assess interest in participating. Those interested were asked to return the assent and consent forms, signed by the participant and his or her parent or guardian, on the day of recruitment. For some participants, these procedures all occurred on the same day. Once consent was obtained by study staff, participants observed the demonstration in a group setting in a private room with 7-10 other adolescents. The demonstration consisted of a 3-5-minute session during which a study team member played the role of the exercise coach.

The coach followed a script, included in Textbox 1 below, adapted from a prior study that assessed the acceptability of a robotic human trainer among diverse adults [22]. The script and anticipated intervention is based on social cognitive theory, including a focus on social support, reinforcement, and enhancing self-efficacy by providing feedback from the coach, along with emphasizing benefits of, and reducing barriers to, exercise [23]. The trainer began with a brief introduction of herself, a discussion about the benefits of exercise, and an explanation about the potential role of a robotic trainer, followed by a demonstration of the robotic trainer in motion and performing maneuvers. The script did not focus on a specific type of exercise or physical activity.

Following the demonstration, participants were given the survey, which took about 5-10 minutes to complete. Study staff then briefly reviewed the survey for possible unanswered items and placed it in a collection box. Participants received a US $25 gift card as remuneration for their time.

The four-page survey included 28 items and did not collect any identifying personal information. Survey items assessed selected sociodemographic characteristics: zip code, age, biological sex, current grade level, and self-reported height and weight. We assessed cigarette smoking and depression history because of the inverse association shown with these variables and physical activity [24-26]. Our depression and lifetime smoking status questions were developed for this study but were similar to other validated single-item measures [27,28]. Participants were asked about their smoking history (ie, “Have you ever tried cigarette smoking, even one or two puffs?”) and depression history (ie, “Have you ever experienced depression now or in the past?”); each item had a yes or no response option. Exercise habits were assessed with the following question: “During the past seven days, on how many days were you physically active for at least 60 minutes per day? (Add up all the time you spent in any kind of physical activity that increased your heart rate and made you breathe hard some of the time),” to which they indicated 0-7 days [29].

Body mass index (BMI) was calculated for each participant using self-reported height and weight. Estimated household income was generated from the 2016 US American Community Survey by zip code (ie, postal code) [30,31]. Based on the sample distribution, household income was categorized into three categories: low, medium, or high.

The survey also included the eight-item, validated Technology Acceptance Scale (TAS). The TAS comes from the Davis Technology Acceptance Model [32-34]. Items assess (1) perceived usefulness and (2) perceived ease of use of new technologies. Each item was rated on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Two items on the scale were reverse scored. Total possible scores ranged from 8 to 40, with higher scores indicating greater potential acceptance of the robotic trainer technology. For the current sample, Cronbach alpha was .70, suggesting relatively high internal consistency reliability.

Four additional questions assessed general reactions to robots, likelihood for using this technology for health promotion purposes, and reasons for engaging in physical activity. Participants were asked the following: “Do you think you and your friends are likely to use the robot to help you exercise?” and “Do you think there is a need for a robotic human trainer to help kids exercise?”; response options to each item were yes or no. In addition, adolescents were asked the following: “Where would you be most likely to use the robotic trainer?”; response options were at school, local gym, and after-school program, as well as other, in which participants could write in their response. Furthermore, adolescents were provided a list of four reasons why they might engage in physical activity and were asked to rank order each reason from most to least important (1-4): to get or stay healthy, sports training, to have fun with friends, and to lose weight.

SPSS Statistics for Windows (IBM Corp) was used to analyze the data; the data were summarized using univariate and bivariate statistics. Acceptance ratings—TAS individual items and total score—were summarized for the overall sample using descriptive statistics. The association of TAS total score with sociodemographic characteristics was examined using t tests for dichotomous variables of age group (12-14 versus 15-17 years), sex (male or female), racial minority status (yes or no), meeting physical activity national recommendations (yes or no), and depression history (yes or no). One-way analysis of variance (ANOVA) was used to examine the association of total TAS score with BMI, categorized as underweight, normal, or overweight, and estimated household income status, categorized as low, medium, or high. P values of .05 or less were used to denote statistical significance.

Table 1 shows the sociodemographic characteristics of the 190 youth who participated in the study. Among them, 45.5% (86/189) were female (one person did not answer the question on sex), 56.8% (108/190) were white, and 36.8% (70/190) were African American or black. A total of 5.8% (11/190) of the sample reported Hispanic ethnicity. Approximately half of respondents (94/190, 49.5%) were between the ages of 12 and 14 years. Low-income household status was estimated for 28.4% (54/190) of the sample. Only about one-quarter (47/190, 24.7%) of participants met national recommendations for physical activity. The mean BMI was 21.8 kg/m² (SD 4.0), 19.5% (37/190) of respondents were classified as overweight, and 18.4% (35/190) had experienced depression now or in the past. Very few reported they had ever tried cigarette smoking.

Table 2 shows the mean and total TAS scores. The mean total score was a 32.8 (SD 4.2, range 12-40) out of a possible score of 40, indicating high technology acceptance. No statistically significant associations were found between TAS total score and participant sex, age group, racial minority status, participant-estimated neighborhood household income, meeting physical activity recommendations, BMI, or depression history (P>.05 for all).

We found that 67.8% (129/190) of participants agreed that they and their friends would be likely to use the robot to help them exercise; 77.8% (148/190) agreed that there is a need for a robotic human trainer to help kids exercise. When participants were asked where they think they would most likely use the robotic trainer, 71.1% (135/190) indicated a local gym such as the YMCA, 40.0% (76/190) reported in a school setting, and 46.8% (89/190) indicated at an after-school program; 71.1% (135/190) suggested other locations, all of whom wrote “at home.” When given a list of four reasons about why they engage in physical activity, 42.1% (80/190) of respondents reported that to get or stay healthy was the most important reason and 46.8% (89/190) indicated that to lose weight was the least important reason.