Social Acceptance toward a Childcare Support Robot System: webbased cultural differences investigation and a field study in Japan
Masahiro Shiomi and Norihiro Hagita
ATR-IRC, Kyoto, Japan
Masahiro Shiomi received M. Eng. and Ph.D. degrees in engineering from Osaka
University in 2004 and 2007. From 2004 to 2007, he was an intern researcher at theIntelligent Robotics and Communication Laboratories (IRC). He is currently a groupleader in the Agent Interaction Design department at IRC, Advanced
Telecommunications Research Institute International (ATR). His research interests
include human-robot interaction, robotics for childcare, networked robots, and fieldtrials.
Norihiro Hagita received B.S., M.S., and Ph.D. degrees in electrical engineering from
Keio University, Japan in 1976, 1978, and 1986. From 1978 to 2001, he was with the
Nippon Telegraph and Telephone Corporation (NTT). He joined the Advanced
Telecommunications Research Institute International (ATR) in 2001 and established the
ATR Media Information Science Laboratories and the ATR Intelligent Robotics andCommunication Laboratories in 2002. His current research interests include
communication robots, networked robot systems, interaction media, and patternrecognition. He is a fellow of the Institute of Electronics, Information, andCommunication Engineers, Japan as well as a member of the Robotics Society of Japan,
the Information Processing Society of Japan, and The Japanese Society for Artificial
Intelligence. He is also a co-chair for the IEEE Technical Committee on Networked
Robots.

Social Acceptance toward a Childcare Support Robot System: webbased cultural differences investigation and a field study in Japan
This paper investigates people’s social acceptance of a childcare support robot
system and compares it with existing childcare technologies (anesthesia duringlabor and baby food, i.e., processed food and formula milk) through web-basedquestionnaires between Japan and USA and a field study in Japan [1]1. We
investigated social acceptance through four scales: intention to use, safety andtrustworthiness, negative attitudes, and decreasing workload. For this paper, ourparticipants included 400 people (200 from each country) in Japan and USA
located through a web-based survey who answered questionnaires about the fourscales to investigate their social acceptance of childcare support technologies.
Our web-based survey results indicate that our system’s concept was evaluatedlower than current childcare support technologies in both Japan and USA. We
also conducted a field trial with 30 additional people in Japan and through theiractual experiences investigated their evaluations of the prototype of our childcare
support robot system.
Keywords: childcare support, social acceptance, robot for children

1. Introduction
Falling birth rates and aging populations are common problems in developed countries,
including Japan and Germany. Robotics research works continue to focus on thephysical and mental supports of elderly people. Many robotics researchers havedeveloped robotics systems and investigated their effectiveness because this research isessential to support such societies and to enhance the abilities of seniors or theircaregivers in various daily environments. For example, Yu et al. investigated the effects

1

This paper is an extended version of a previous work [1] and contains additional experimental
results and more detailed discussions.

of a social assistive pet robot with elderly people with dementia from the viewpoint of
improving their moods and stimulating interaction [2]. Shiomi et al. developed anautonomous wheelchair robot to support the movement of seniors and concluded that
their robot is preferred over human caregivers from the viewpoint of the simplicity ofmaking requests [3]. Iwamura et al. developed a shopping assistant robot and reported
that a human-like appearance and a chat function increased the social acceptance ofelderly people toward such robots [4].
Even though various robot systems have been developed to support seniors, relatively
scant attention has been focused on supporting childcare, which is another essential
problem caused by aging societies. Some research works have developed robot systems
that directly support childcare, for example, sensor networks or wearable sensors thatrecognize children’s behaviours in kindergarten environments and support the
paperwork of childcare workers [5] [6]. Fink et al. created and investigated theeffectiveness of a robotic toy box that motivates young children to pick up their things[7]. Abe et al. developed a telepresence robot for interaction between seniors andbabies/toddlers [8].
These research works developed robot systems that can also be used to support
childcare. However, they did not focus on the social acceptance of their systems. We
believe that the issue of such social acceptance is essential for their integration in thereal world, similar to elderly-care support robot systems. In this research work, wedeveloped scales to investigate the social acceptance of childcare support robot systems,
because it is difficult to apply the knowledge and measurements of social acceptancefrom elderly-care support robot systems to childcare support robot systems since they
have different characteristics and requirements. We must also investigate the culturaldifferences of the social acceptance of childcare support robot systems. Althoughseveral research works have already conducted cross-cultural surveys about attitudes
toward robots [9, 10], they mainly focused on adult participants. Culture is strongly
related to childcare attitudes [11]. For example, according to a survey by theInternational Labour Organization, USA is the only developed country that doesn’t
guarantee paid maternity leave. Taking paternity leave is also difficult in Japan [11].
The main contribution of this paper is its investigation of the social acceptance of two
countries (Japan and USA) by developing scales to measure the social acceptance of achildcare support robot system, which was designed based on childcare worker opinions(Fig. 1). An extra trial investigated how people who experienced the childcare robot
system evaluated it using our developed scales.

8120
mm

B

A

B
A
C

C
5200 mmFig. 1 Prototype of intelligent playroom as a childcare support robot system

2. Design of Childcare Support System
2.1 Interviews with childcare workers at nursery schools
Before constructing our childcare support robot system, we interviewed 26 teachers at
three Japanese nursery schools to investigate what kinds of childcare support they

wanted. In the sessions at different nursery schools, one male interviewer, a qualified
childcare worker, interviewed three groups of seven, nine, and ten female teachers. We
conducted group interviews due to time constraints since conducting individualinterviews with each teacher was difficult.
Before the interviews, we explained the purpose of this research, and showed threevideos from our past research works: a humanoid robot interacts with younger children
at a train station such as a chat and free-play interaction [12], our people-tracking
system using environmental sensors which tracks pedestrians including younger
children at a shopping mall [13], and an integration system between an acceleration
sensor and the tracing system to identify people in a real environments [14]. The
duration of each of them was about 30 seconds. The reason of why we showed videos
before interviews is to focus conversation topics during limited time period as much as
possible.
In semi-structured interviews, we asked what kinds of support they wanted after theabove explanations that followed the same procedure to avoid any interviewer bias.
Even though sometimes conversation topics spread out because of discussions among
the teachers, the interviewer tried to maintain the semi-structured interview procedure.
At the end of discussion, the interviewer asked the teachers of each group to summarize
their discussions about the possibilities to use technologies to support their childcare.
Through interviews and discussion, all three groups identified two types of childcare
supports: helping with paperwork and entertaining children/keeping them occupied.
Even though the interviewer did not share the interview results of one group with theother groups, different groups discussed the same topics and summarized them at theend of discussions. Moreover, as an additional analysis, one coder analysed andclassified the transcribed interview results. In total the coder transcribed 52

conversation topics and categorized them due to their contents. As a result, there are
five categories: helping with paperwork through recoding children’s activities (24topics), entertaining children/keeping them occupied (16 topics), security (2 topics),
negative perspective (7 topics) and other themes (3 topics). We note that the topics insecurity category includes similar contents to the helping with paperwork category,because it is mainly talking about recording camera/audio information for security
purpose. Therefore, we though that these two needs are obviously critical for childcare
support.
The first need is helping with paperwork, including recording children’s activities atnursery schools. The childcare workers are interested in sensor data that could berecorded and provided by cameras or human-tracking systems. Such information would
be helpful when they record children’s activities. Even if they cannot directly monitor
the children when they are busy, they can confirm what the children are doing throughsensor data. Note that some nursery schools are already using cameras to record daily
activities for security purposes, but such systems have not been expanded to support
office functions.
The next need is entertaining children and keeping them occupied. Our participating
childcare workers reported that they would benefit during such hectic times as changing
diapers if a system entertained children for just a few minutes. They seemed to envision
robots as intelligent toys or smartphones.
As described above, we did receive several negative responses about recordingchildren activities and using robot systems from each group; one group reported thatsuch negative effects should be considered at the end of discussion. For example, somechildcare workers expressed concerns about potential long-term ramifications. A few
worried that reliance on such systems might reduce the quality of care and divert theattention of teachers away from childcare. Several expressed reservations about using
such sensors and robots to record children’s daily activities due to privacy concerns.
However, even if a few negative comments surfaced, the childcare workers basicallyappeared receptive to sensors and robots for childcare in the context of providing
support in nursery schools.

2.2 System overview
Based on the interview results at the nursery schools, we set two design policies for ourchildcare support robot system. The first supports office work, especially recording andindexing children’s daily activities at nursery schools. Even if complete autonomous
indexing of such daily activities is difficult because of the limitations of current
technologies, indexing part (and recording most) of the data will support such
paperwork responsibilities. The second supports the entertaining of children throughrobots. When childcare workers are busy, it would be helpful to attract children to therobot even for just a few minutes, e.g., when changing diapers.
Based on these considerations, we built a prototype of an intelligent playroom (Fig.
1) that is about 40 m2, which is big enough to accommodate over five adults and fivechildren. We attached environmental depth sensors to the ceiling and used a humantracking algorithm with them [13]. Our tracking system monitors the position of all thepeople in the area at 20 Hz with an accuracy of approx. 30 cm. This system has
robustness toward illumination changes and the colors of clothing because it uses depth
information, which is useful for real environments where the sun shines. Since depth
cameras see from top to down, they are also robust for crowded situations. For thissystem, we installed 16 depth sensors (1 Kinect V2 (Microsoft), 13 Xtions (ASUS), anda 2D-Imager (Panasonic)). We also installed two microphone arrays (16 microphones)

and two USB cameras to record the sounds/videos of the children and the parents in theroom (Fig. 2). Since our system remains under development, it only records the
positions, the videos, and the sounds; indexing children activities is future work.
We also installed a ball-type toy robot named Sphero (http://www.sphero.com/sphero)or a tank-type toy robot named Romo (http://www.romotive.com/) to investigate how
children interacted with them (Fig. 3). The robots were teleoperated in pre-defined
behaviours, i.e., the Wizard of Oz style [15]. We defined the behaviours to temptchildren to chase the robot, which eluded them. Thus the robot briefly distracted thechildren.

16 microphones

Depth sensor

Fig 2 Microphone array and a depth sensor on ceilingFig. 3 Sphero and Romo from our experiments

3. Experiment: Web-Based Evaluation
In this section, we describe an experiment with a web-based survey to understand theperceptions of people from two different countries of a robot system that provides
childcare support. We also evaluate the reliability of our developed scales that measure
the social acceptance.

3.1 Hypothesis and predictions
Even though social robots are spreading worldwide, childcare support robotics
technology is still being developed and remains relatively unknown for ordinary people.
Such new concepts or technologies basically suffer from much lower social acceptancethan such current technologies as processed baby food or baby formula, both of which
are now commonly used in developed countries. However, when these newtechnologies were first introduced, their social acceptance was much lower. Since mostpeople have little or no experience using such new technologies, they cannot imagine
whether they are safe and/or beneficial, and this “ignorance” restricts social acceptancefrom the beginning of their introduction. In childcare, using such technologies might beperceived as irresponsible.
Based on these considerations, we expect people to have low social acceptance ofchildcare support robot systems because they are relatively uncommon and have neverbeen used. Even though our hypothesis assumes negative results for current childcare
support robot systems, investigating such impressions is crucial to understanding theircurrent situations. Therefore, we made the following hypothesis:

Prediction 1: People will have lower social acceptance for a childcare support
robot system than current childcare support technologies.

We also speculated on culture differences, because attitudes toward childcare differ
among countries. For example, Japanese people are much less likely to leave theirchildren with babysitters, a custom that is ubiquitous in American [16] [17] [18]. Barratt
et al. reported that Japanese infants only receive about two hours per week ofnonmaternal care, but American infants receive about 23 hours [19]. Shwalb et al.
described Japanese nonmaternal child care by considering cross-cultural differences[20]. Caudill also reported different maternal attitudes about babies [21] [22]. Since a
typical American mother considers her baby a separate and autonomous being, her goal
is to help her baby learn how to actively express his needs and/or wishes. On the other
hand, a typical Japanese mother considers her baby an extension of herself and believes
that she knows what is best for him/her [21]. Caudill et al. and Otaki et al. also reported
that Japanese mothers spend more time with or in the presence of their babies than
American mothers, due to the differences of their life style such as working time ofJapanese fathers [22] [23]. Such differences toward babysitting might influence thesocial acceptance of childcare support robot systems or other childcare support
technologies.
Moreover, American people had more positive social acceptances toward bothinformation and communication technologies in education context [24] and a medical
technology in childbirth context [25], compared to Japanese people; we note that in bothstudies the participants included parent-generation. We thought these differences ofattitudes to technologies in childcare/education contexts probably reduce social

acceptance of Japanese toward childcare support technologies more than in Americans.
Therefore, we made the following hypothesis:
Prediction 2: Americans will have higher social acceptance for childcare support
technologies than Japanese people.

3.2 Participants
In this experiment, we contracted with an online survey company in Japan to collectresponses. Its participant pool (approximately 2 million people) was filtered andcategorized into four categories: licensed Japanese childcare workers and Japaneseparents with preschool children as well as their American counterparts. The inclusion
criteria for the licensed childcare workers stipulated that they were currently working asa childcare worker. The inclusion criteria for the parents stipulated that they werecurrently living with children up to six years old.
Our survey included 200 Japanese people (100 licensed female childcare workers fornursery schools and 50 female and 50 male parents with preschool children), and 200
Americans (100 licensed female childcare workers and 50 females and 50 males withpreschool children). The participants were recruited by e-mail to join a web survey. The
number of samples was controlled to include identical ratios of mothers and fathers, butsince the ratio of registered male childcare workers was too small, we only included
female childcare workers and paid them approximately 500 yen (about $5.00) for their
participation.

3.3 Procedure
In our survey, the participants answered questionnaires about three kinds of childcare
support technologies: anesthesia during labor, baby food, and childcare support robot
systems.
We chose anesthesia during labor as a candidate for two main reasons: during laborboth participants (parents and childcare specialists) in Japan and America are familiar
with it, and during labor it tangentially supports childcare, even though it is literally asupport for childbirth. Concerning the first reason, in America, 61.0% of mothers
received epidural or spinal anesthesia during labor at 2008 [26], suggesting that it is awell-known technology. Even though our participants did not have children, they are
obviously potential parents, and therefore we believe they have knowledge about acommon childbirth support. Also in Japan, qualified childcare workers work not only atkindergarten/nursery schools but also at midwifery homes that support childbirth.
Examinations of qualified childcare licenses include several childbirth topics, which are
not directly related to anesthesia during labor. Studying such information provides
knowledge about childbirth for childcare workers. In fact, all of the childcare workers in
the interviews were familiar with anesthesia during labor, even though they had notexperienced it.
For the second reason, decreasing pain during childbirth contributes to childcare by
maximizing maternal comfort and mobility after it. Moreover, acute pain duringchildbirth has been linked to postpartum depression [27]. Therefore, even thoughanesthesia during labor is for childbirth, we believe it is also related to childcare.
For each technology, we briefly explained the meaning of our three examples, e.g.,“baby food includes powdered milk and instant baby food.” For the childcare support
robot system, we prepared two illustrations and texts to explain our two concepts
because the participants are less familiar with our system than anesthesia during laborand baby food. The maximum answer time for all the questionnaire items was 20
minutes. We counterbalanced the order of the items to avoid order effects among theconditions.

3.4 Measurements
In our survey, based on our past research work, we prepared four scales to investigate
the social acceptance of childcare support technologies [1]: intention to use, safety andtrustworthiness, negative attitudes, and decreasing workload. We prepared different
kinds of childcare support technologies and added a short description to eachquestionnaire aspect, depending on the technologies: “if you or your partner have ababy” or “if you or your partner become parents.” Each item was rated on a 1 to 7 scale,where 7 is the most positive. The details of each scale are described as follows.

3.4.1 Intention to use
For this measurement, we adapted all three items from Heerink et al. [28] including,“I’m planning to use baby food in the next few days.” We measured intention to use
because this scale is modeled and indicates social acceptance, as shown in studies of theacceptance of new technologies [29] and social robots [30] [31]. Note that X changes
depending on the following conditions: anesthesia during labor, baby food, or achildcare support robot system.
-

I think that I’ll use X (or suggest that my partner use it) if I have a baby in the
future (anesthesia during labor) or if I’m going to raise a child in the near future(baby food, or a childcare support robot system).

-

If I have a baby (anesthesia during labor) or if I’m going to raise a child (babyfood, or a childcare support robot system), I’ll definitely use X.

-If I have a baby (anesthesia during labor) or if I raise a child (baby food or achildcare support robot system), I plan to use X.

3.4.2 Safety and trustworthinessA technology’s safety and trustworthiness are essential factors. For example, parents
believe baby food is healthy and safe; such feelings are crucial to disseminate atechnology throughout the world. Therefore, we constructed a scale to investigate thesafety and trustworthiness of our childcare support technologies by three distinct items:
trustworthiness, cleanness/safety, and anxiety.
-If I give birth or become a parent, I’ll trust X.

-

Using X will make childbirth (anesthesia during labor) or parenting (baby foodor a childcare support robot system) safer and more sanitary.

-

Using X will decrease my anxiety about childbirth or parenting.

3.4.3 Negative attitudes
Subjective self-images of childcare are another essential factor that people must address
to decide whether to use childcare support technologies. For example, if parents feelthat using them creates a gap with their personal self-images toward childcare or if they
are concerned how their friends or family could react, they might avoid suchtechnologies. Therefore, we measured their feelings about whether using newtechnology creates disparities from their own self-images about childcare by
constructing a scale of five distinct items. We avoided discussions about the merits ofspecific self-images because that debate depends on too many factors; we just want todetermine how people feel about childcare support technologies. Unlike other scales, ahigher value on this scale indicates negative attitudes about a technology because of thedifferences from self-images:-

If I am a parent, avoiding X is quite natural.

-

Using X negatively affects parents.

-

Since I believe that mothers should experience natural childbirth (anesthesia

during labor) or parenting (baby food or a childcare support robot system), X should not
be used.
- Since seriousness during childbirth or parenting increases affection for children, X
should not be used.
- Using X will create negative impressions in others.

3.4.4 Decreasing workload
Another reason for using childcare support technologies is to decrease the workload ofchildcare. Baby food decreases burdens and provides balanced nutrition. Since
anesthesia during labor also decreases the maternal physical load and pain in childbirth,
protecting the physical welfare of mothers after childbirth is critical. Therefore, weconstructed a scale of four distinct items to investigate the decreasing workload ofchildcare support technologies, the positive effects on children, and convenience:- Using X decreases the physical load in childbirth (anesthesia during labor) or
parenting (baby food or a childcare support robot system).
- Parents should use X to decrease the load of childbirth or parenting.
- Decreasing the load on parents who use X benefits children.
- Since X is convenient, it will decrease my childbirth or parenting load.

3.4.5 Reliability of measurements
Even though the reliability of each measurement has already been tested by our past
research [1], we re-tested the reliabilities through two web-based survey. Table 1 shows
the Cronbach’s alpha statistics of each measurement, all of which are within a solid
range in both surveys. Since such scales are generally considered reliable if Cronbach’s
alpha exceeds 0.70, we believe that our measurements are all reliable.

Table 1 Cronbach’s alpha from web-based survey

Japan

USA

Anesthesia during labor
Baby food
Robot
Anesthesia during labor
Baby food
Robot

Average

Intention Safety and
Negative
Decreasing
to usetrustworthiness attitude
workload
0.956
0.82
0.909
0.832
0.935
0.799
0.923
0.907
0.971
0.844
0.917
0.894
0.976
0.852
0.837
0.854
0.971
0.75
0.8886
0.866
0.97
0.905
0.783
0.892
0.963
0.828
0.876
0.874

3.5 Results
3.5.1 Verification of hypothesis
We conducted a three-factor mixed ANOVA for each scale on the three technologies(anesthesia during labor, baby food, and robots), countries (USA/Japan), and participant
types (childcare workers, fathers, and mothers).
For intention to use (Table 2), the following main effects were significant:technologies, F(2, 788) = 139.286, p < .001, η2 = .261, countries, F(1, 394) = 35.114, p< .001, η2 = .082, and participant types, F(2, 788) = 11.290, p < .001, η2 = .054. The
two-way interaction effects were also significant among technologies, countries, andparticipant types, F(4, 1576) = 3,494, p = .008, η2 = .017. The simple interaction effects

were also significant between technologies and countries, F(2, 788) = 15.472, p <.001,
η2 = 0.038, and technologies and participant types, F(2, 788) = 5.137, p < .001, η2 =0.025.
The simple-simple main effect of countries was significant in anesthesia during laborand childcare workers (p = .001), baby food and childcare workers (p < .001), baby
food and fathers (p = .026), baby food and fathers (p < .001), and anesthesia duringlabor and mothers (p < .001).
The simple-simple main effect of participant types was significant in robots and USA(fathers > childcare workers: p < .001, mothers > childcare workers: p < .001) and baby
food and Japan (mothers > childcare workers: p = 0.23).
The simple-simple main effect of technologies was significant in childcare workers
and USA (baby food > anesthesia during labor: p < .001, baby food > robots: p < .001,
and anesthesia during labor > robots: p < .001), fathers and USA (baby food > robots: p< .001, and anesthesia during labor > robots: p < .001), mothers and USA (baby food >robots: p < .001, and anesthesia during labor > robots: p < .001), childcare workers andJapan (baby food > anesthesia during labor: p < .001, baby food > robots: p < .001, andanesthesia during labor > robots: p = .008), and mothers and Japan (baby food >anesthesia during labor: p < .001, and baby food > robots: p < .001),

Table 2 Average and standard deviation of intention to use
USA

Japan

Childcare
workers4(2.15)

Male
parents
4.55(1.75)

Femaleparents
4.75(1.97)

Childcare
workers
3.09(1.57)

Male
parents
3.73(1.64)

Femaleparents
3.09(1.74)

Baby food

5.16(1.55)

5.23(1.61)

5.21(1.69)

3.99(1.50)

3.98(1.40)

4.72(1.86)

Robot

2.16(1.52)

3.33(1.48)

3.17(1.67)

2.46(1.44)

3.61(1.13)

2.56(1.64)

Anesthesia
during labor

For safety and trustworthiness (Table 3), the following main effects were significant:technologies, F(2, 788) = 108.829, p < .001, η2 = .216, and participant types, F(2, 788)
= 11.298, p < .001, η2 = .054. The two-way interaction effects were significant among
technologies, countries, and participant types, F(4, 1576) = 2.609, p = .034, η2 = .013.
The simple interaction effects were also significant between technologies and countries,
F(2, 788) = 11.311, p < .001, η2 = 0.028, and technologies and participant types, F(2,788) = 3.257, p = .012, η2 = 0.016.
The simple-simple main effect of countries was significant in robots and childcare
workers (p = .004), anesthesia during labor and fathers (p = .020), baby food and fathers(p = .026), and anesthesia during labor and mothers (p = .005).
The simple-simple main effect of participant types was significant in anesthesia
during labor and USA (fathers > childcare workers: p = .018, mothers > childcare
workers: p = .017), baby food and USA (fathers > childcare workers: p = .016), robots
and USA (fathers > childcare workers: p < .001, mothers > childcare workers: p < .001),
robots and Japan (fathers > childcare workers: p = .002).
The simple-simple main effect of the technologies was significant in childcare
workers and USA (baby food > robots: p < .001, and anesthesia during labor > robots: p< .001), fathers and USA (baby food > robots: p < .001, and anesthesia during labor >robots: p <.001), mothers and USA (baby food > robots: p < .001, and anesthesia duringlabor > robots: p < .001), childcare workers and Japan (baby food > robots: p < .001,
and anesthesia during labor > robots: p = .008), and mothers and Japan (baby food >anesthesia during labor: p = .004, baby food > robots: p < .001, and anesthesia duringlabor > robots: p = .016).
Table 3 Average and standard deviation of safety and trustworthiness

USA

Japan

Childcare
workers
3.75(1.56)

Male
parents
4.39(1.25)

Femaleparents
4.39(1.45)

Childcare
workers
3.63(1.21)

Male
parents
3.76(1.13)

Femaleparents
3.63(1.24)

Baby food

3.88(1.10)

4.44(1.17)

4.07(1.38)

3.96(1.04)

3.93(0.82)

4.27(1.46)

Robot

2.32(1.31)

3.29(1.15)

3.19(1.46)

2.84(1.28)

3.60(0.92)

3.02(1.32)

Anesthesia
during labor

For negative attitudes (Table 4), the following main effects were significant:technologies, F(2, 788) = 81.289, p < .001, η2 = .171, countries, F(1, 394) = 18.655, p< .001, η2 = .045, and participant types, F(2, 788) = 7.117, p = .001, η2 = .035. The
simple interaction effect was also significant between technologies and participant types,
F(4, 1576) = 8.749, p <.001, η2 = 0.012).
The simple main effect of the participant types was significant in anesthesia duringlabor (childcare worker > mothers: p = .010, fathers > mothers: p = .002) and robots(childcare workers > fathers: p = .004, childcare workers > mothers: p < .001).
The simple main effect of the technologies was significant in childcare workers (babyfood > anesthesia during labor: p < .001, robots > anesthesia during labor: p < .001),
fathers (baby food > anesthesia during labor: p < .001, robots > anesthesia during labor:p = .018), and mothers (baby food > anesthesia during labor: p < .001, baby food >robots: p < .001, and robots > anesthesia during labor: p < .001).

Table 4 Average and standard deviation of negative attitude
USA

Anesthesia
during laborChildcare
workers
3.47(1.12)

Male
parents
3.46(1.27)

Japan
Femaleparents
3.22(1.22)

Childcare
workers
3.35(1.18)

Male
parents
3.64(1.17)

Femaleparents
2.73(1.24)

Baby food

4.54
(0.93)

4.60(1.08)

4.49(1.00)

4.00(0.96)

4.06(1.07)

4.50(1.29)

Robot

4.65(1.27)

4.17(1.05)

4.02(1.22)

4.28(1.34)

3.76(1.21)

3.36(1.34)For decreasing workload (Table 5), the following main effects were significant:technologies, F(2, 788) = 55.633, p < .001, η2 = .124, countries, F(1, 394) = 12.120, p= .001, η2 = .030, and participant types, F(2, 788) = 4.808, p = .009, η2 = .024. The
two-way interaction effects were also significant among technologies, countries, andparticipant types, F(4, 1576) = 2.511, p = .041, η2 =.013. The simple interaction effects
were significant between technologies and countries, F(2, 788) = 5.956, p =.003, η2 =0.015, and technologies and participant types, F(2, 788) = 2.923, p =.020, η2 = 0.015 .
The simple-simple main effect of countries was significant in anesthesia during laborand childcare workers (p = .043), baby food and childcare workers (p < .001), and baby
food and mothers (p =.001). The simple-simple main effect of the participant types was
significant in robots and USA (mothers > childcare workers: p = .038) baby food andJapan (mothers > fathers: p = .007), and robots and Japan (fathers > childcare workers:
p = .039).
The simple-simple main effect of the technologies was significant in childcare
workers and USA (baby food > robots: p < .001, and anesthesia during labor > robots: p< .001), fathers and USA (baby food > robots: p = .033, and anesthesia during labor >robots: p = .007), childcare workers and Japan (baby food > anesthesia during labor: p< .001, baby food > robots: p < .001, and anesthesia during labor > robots: p < .001),
and mothers and Japan (baby food > anesthesia during labor: p =.001, baby food >robots: p < .001, and anesthesia during labor > robots: p = .002).

Table 5 Average and standard deviation of decreasing workload
USA

Japan

Childcare
workers
3.85(1.09)

Male
parents
4.18(1.08)

Femaleparents
4.17(1.31)

Childcare
workers
4.16(0.94)

Male
parents
4.15(1.03)

Femaleparents
4.37(1.23)

Baby food

3.86(1.32)

4.08(1.33)

4.25(1.34)

4.71(1.08)

4.29(0.90)

5.04(1.35)

Robot

3.23(1.43)

3.56(1.13)

3.78(1.29)

3.47(1.24)

4.01(0.87)

3.67(1.32)

Anesthesia
during labor

Here, we summarize the results from our web-survey. For intention to use in thisstudy, American have more positive impressions than Japanese, except for anesthesia
during labor with fathers and childcare support robot system with all types. Scores ofchildcare support robot system are more negative than anesthesia during labor and baby
food, except for Japanese fathers.
For safety and trustworthiness in this study, American childcare workers havemore negative impressions about the childcare support robot system than Japanese.
American mothers and fathers have more positive impressions about anesthesia duringlabor than Japanese, and American fathers have more positive impressions about baby
food than Japanese. Childcare support robot system are more negative than anesthesia
during labor and baby food, except for Japanese fathers.
For negative attitude in this study, American have more negative impressions
than Japanese for childcare support technologies. Attitudes for childcare support robot
system are more negative than anesthesia during labor. Only Japanese mother is morenegative to baby food than childcare support robot.
For decreasing workload in this study, Japanese childcare workers have morepositive impressions about anesthesia during labor and baby food than American.

Japanese mothers have more positive impressions about baby food than American.
Scores of childcare support robot system are more negative than anesthesia during laborand baby food, except for American mothers and Japanese fathers.
These analysis results indicate that people have lower social acceptance for achildcare support robot system than the current childcare support technologies from theviewpoints of each scale, except for the part of scales in this study. Therefore,prediction 1 was partially supported. Moreover, American have higher scores forintention to use, but more negative scores for a part of scale which is opposite from ourassumptions. Therefore, prediction 2 was partially supported too.

4. Field Trial
In this section, we describe a field trial with ordinary people who experienced aprototype of our childcare robot system and investigate their perceptions andimpressions. Unlike like the above survey study that compared American and Japanesereactions, this field evaluation was only conducted with Japanese participants.

4.1 Participants
To gather participants, we put leaflets in a local childcare magazine that is distributed toa small city’s childcare centres. 64 people (30 parents and 34 preschool children)
participated in the field trial. The participants’ children were in preschool (i.e., under six
years old, average: 2.13, S.D: 1.16). Note that participating parents were required tohave at least one child younger than three years of age; nine participants (with toddlers)participated with older siblings who are younger than six years old. Parents were paid

4,000 yen (about $34, including transportation expenses) for two hours of participation.
30 parents (23 women and 7 men) answered questionnaires.

4.2 Procedure
In the field trial, the participants acted freely in the environment for two hours. The firsthour was used to acclimatize the children to the environment, to explain the concept ofour research, and to introduce the human-tracking and recording systems. Next theparticipants filled out informed consent forms. In the second hour, we randomly showedeither robot (Sphero or Romo) and started teleoperation to investigate the interactions
between children and parents. After two-hour sessions, the parents answeredquestionnaires, which included the developed scales. We asked them to fill out
questionnaires by considering childcare for their youngest child (ignoring or
downplaying the participation of older children, if applicable) because children’s ages
are related to attitudes toward childcare robot systems.

4.3 Measurements
In this field trial, we measured the same four scales of our experiment about a childcare
support robot: intention to use, safety and trustworthiness, negative attitudes, anddecreasing workload. We also interviewed the parents to identify what kinds ofchildcare support they wanted.
We again tested the reliability levels of each measurement in the field evaluation. The
results for each fell within a good range (Table 6). Since Cronbach’s alpha exceeded
0.70, we believe that our measurements are all reliable on average.

Table 6 Cronbach’s alpha from field evaluation

Robot

Intention Safety and
Negative
Decreasing
to usetrustworthiness attitude
workload
0.875
0.701
0.890
0.866

4.4 Results

4.4.1 Observed behaviours and interview results
Both the children and parents spent the first hour in the environment, which resembled
usual playrooms. The children freely played with other children and their parents oralone with toys. Parents were basically playing with their children or talking with otherparents.
In the second hour, the experimenter controlled the installed robots, which
entertained most of the children. For example, after a parent suggested that her daughter
chase Sphero (Fig. 4-a), the girl started to chase it (Fig. 4-b). She continued herinteraction with Sphero for more than 30 minutes (Fig. 4-c). Some crawling babies also
tried to look at the robot or capture it (Fig. 4-d). Romo also entertained children. Somechildren repeatedly asked their parents questions like, “where’s the robot?” when theyfailed to catch Romo. At the end of the trial, a few children wanted to remain in theenvironment, suggesting the potential success of an intelligent playroom.

(a)

(b)

(c)

(d)

Fig. 4 Children interacting with SpheroOn the other hand, some children did not want to interact with either robot. Theirparents thought their children might have been scared by an object darting around thefloor. Even if their parents interacted with the robot, the children refused to interact with
it during the trial.
After observing enough of each child’s behaviors, we interviewed parents to
scrutinize their attitudes about our childcare support robotics system. All of the parents
positively evaluated our sensing system. They believe that such sensor data will lead togreater understanding of children activities, even though they expressed concern about
the privacy risks of the recorded data.
For using a robot to train their children, they also positively evaluated the robot after
observing its interactions with their children. Even if it interacted with or entertained
their children for just a few minutes or more by moving around, parents could imagine
scenes where they might be too busy to play with their children or to distract them.
They believed that such robots could be considered intelligent toys like smartphones
and have advantages over them because the robot can move around with its sensor
information.

4.4.2 Questionnaire results
In our field study, we gathered questionnaire items using the same items of the firstexperiment. For reference, we conducted t-tests for each measurement about childcare
support robots between a web-based survey (Japanese participants) and a field study(Fig. 5); even though these comparisons were not well controlled, showing differences
is useful to understand how participants evaluated the system after their experiences.
For intention to use, the averages were 2.78 (S.D., 1.50) and 4.50 (S.D., 1.25). We
found a significant difference among the conditions (t(228) = -5.993, p < .001, d=1.17 ).
For safety and trustworthiness, the averages were 3.08 (S.D., 1.25) and 4.65 (S.D., 1.13).
We found a significant difference among the conditions (t(228) = -6.58, p < .001
d=1.27). For the negative attitudes, the averages were 3.92 (S.D., 1.35) and 2.32 (S.D.,
1.02). We found a significant difference among the conditions (t(228)=6.20, p < .001
d=1.22). For decreasing workload, the averages were 3.66 (S.D., 1.120) and 4.91 (S.D.,
1.01). We found a significant difference among the conditions (t(228) = -5.473, p < .001
d=1.13).

7
6

***

***

***

***

5
4
3
2
1
Intention to use

Safety and and Negative attitude
trustworthiness

WEB

Field

Decreasing
workload*** : p < .001

Fig. 5 Average and S.E of each scale between a web-based survey and a field study

5. Discussion
5.1 Design implication
One important contribution of this study is that we made scales to investigate the social
acceptance of childcare support technologies and experimentally tested their reliability
through a web-based survey with two different countries. These scales can be used toinvestigate cultural differences about different kinds of childcare support robots fromvarious viewpoints, such as a telepresence robot for little children [8].
Another contribution is that we confirmed that experiencing a prototype systemincreases its social acceptance. Deploying an actual system in the real world is one
essential approach for the social implementation of robot services. In particular, to growthe research field of childcare support robotics, the social acceptance of systems must
be increased. Future work must develop more long-term field trials with our system toinvestigate its effectiveness.
In this research work, we used two kinds of moving robots: Sphero and Romo. Theirmain difference is their faces; Romo has an animated face on its display, unlike Sphero,
which doesn’t have one. We assumed that Romo would be more accepted by children
because of its anthropomorphic appearance, but our field study suggests that both robots
are equally attractive to children in experimental environments. For just playing with arobot in the short term, a robot’s physical movement (in this research, the robot wascontrolled by the operator) might be more effective than its anthropomorphic

appearance. Interesting future work will investigate the relationships among a robot’s
appearance, its movements, and the levels of boredom experienced by children.

5.2 Attitudes to anesthesia during labor and baby food between USA and Japan
In this research work, we focused on the differences between a childcare support robot
system and existing childcare support technologies, i.e., anesthesia during labor andbaby food. We did not deeply analyze them in the result section. In this section, we
describe an interesting phenomenon of cultural differences between USA and Japan
about existing childcare support technologies.
Our experimental results showed that Japan participants showed a lower intention touse baby food and anesthesia during labor than American participants; in fact, thediffusion ratios in these countries are also different [25]. On the other hand, Japan
participants showed lower negative attitude about baby food and anesthesia during laborthan American participants, who indicated higher negative attitudes to them than Japan
participants, even though Americans are more accustomed to them. This opposite
phenomenon between their higher intention to use (or the diffusion ratio) and negative
attitudes has also been reported in past research [25] conducted over 20 years ago.

5.3 Limitations
This research work has several limitations. In our web-based survey, we only compared
USA and Japan without involving European countries, which guarantee relatively large
paid leave from work to parents [11]. Therefore, the social acceptance of childcare
support robot systems by Europeans remains unknown. Since we only investigated threecandidates in our web-based survey, it is also unknown how participants evaluated othertopics such as babysitters, nannies, or baby-monitoring tools. Also, the United States
mixed with various value and culture systems from different races or countries,
therefore it was difficult to gather questionnaires uniformly by considering people’svarious characteristics. These limitations should be considered at interpretations of ourresults.
We only conducted interviews in Japan to design a childcare support system becauseof the difficulty of interviewing enough American teachers in Japan. Instead ofinterviews with American teachers, we investigated the workload of American childcare
workers. A survey reported that they spend much time on both communication withchildren and office work (such as documentation) [32]. This suggests that supports forboth tasks will also help American teachers, as in the Japanese case. In other words,
even though we did not interview American childcare teachers for designing ourchildcare support robot system, the psychological impact of the supports would
probably be similar for both countries because both childcare workers felt similar
workloads. Also, since other childcare support technologies (anesthesia during laborand baby food) are common between U.S and Japan, their psychological impact would
probably be similar, too.
In our field study, we failed to adequately control the ages of the participants and theexistence of siblings. Even an age difference of just a few months or the presence ofsiblings might hugely affect their interaction with a teleoperated robot. For instance, if achild is scared/intimidated by robots, her parents will probably have negative
impressions of the robots that caused low social acceptance. Our robots were controlled
by an operator during the field study; a completely autonomous robot might changeparental feelings. Moreover, the field study was conducted at one location, but people’s
attitudes could change depending on experimental locations.

In the comparison of a web-based survey and a field study, we didn’t control thenumber of participants and their background knowledge very well. We also only
conducted our field study in Japan, and these differences limit the interpretations of ourexperimental results. For example, for a web-based survey, video stimuli would provide
knowledge about childcare support robotics. Positive bias in the field study might also
exist because people without positive feelings for childcare support robotics might have
low motivation to participate in our experiment.

6. Conclusion
This paper investigated the social acceptance of people toward a childcare support robot
system from various viewpoints by comparing current childcare support technologies
through a web-based survey and a field study. We developed scales to investigate theessential factors related to using childcare support technologies from three perspectives:
safety and trustworthiness, negative attitudes, and decreasing workload. We first
conducted a web-based survey to investigate the social acceptance of both Americanand Japan people toward childcare support technologies. Our experimental results
indicate that the people of both countries showed lower social acceptance toward
childcare support robotics than current childcare support technologies (baby food andanesthesia during labor), except for a part of combination with participant types. In ourstudy, Americans might have higher intention to use toward childcare support
technologies than Japan people, but other scales were lower rated than Japan people.
Additionally, we conducted a field study to investigate whether the experiences of achildcare support robot system provide positive impressions to users.

Acknowledgements
This work was supported by JSPS KAKENHI Grant Numbers JP15H05322 andJP16K12505. We also thank the children, parents, and playroom staff members for theirhelpful participation.

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