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The further implementation of robots in welfare
A co-created application for robot-assisted medication counselling
Malin Andtfolk
Corresponding author. Åbo Akademi University, Faculty of Education and Welfare studies, Department of Caring
Science, Vaasa, Finland, malin.andtfolk@abo.fi
Susanne Hägglund
Åbo Akademi University, Faculty of Education and Welfare studies, Experience Lab, Vaasa, Finland. Åbo Akademi
University, Faculty of Education and Welfare studies, Department of Caring Science, Vaasa, Finland,
susanne.hagglund@abo.fi
Sara Rosenberg
Åbo Akademi University, Pharmaceutical Sciences Laboratory, Faculty of Science and Engineering, Åbo Akademi
University, Turku, Finland. Åbo Akademi University, Faculty of Education and Welfare studies, Department of Caring
Science, Vaasa, Finland, sara.rosenberg@abo.fi
Mattias Wingren
Åbo Akademi University, Faculty of Education and Welfare studies, Experience Lab, Vaasa, Finland,
mattias.wingren@abo.fi
Sören Andersson
Åbo Akademi University, Faculty of Education and Welfare studies, Experience Lab, Vaasa, Finland,
soren.andersson@abo.fi
Prashani Jaysingha Arachchige
Åbo Akademi University, Faculty of Science and Engineering, Department of Information Technology, Turku, Finland,
Prashani.jaysingha.arachchige@abo.fi
Linda Nyholm
Åbo Akademi University, Faculty of Education and Welfare studies, Department of Caring Science, Vaasa, Finland,
linda.nyholm@abo.fi
Here we present the development of a new robot application. Using a user-centered approach, the aim is to enable human-robot
interaction and promote patient safety in medication counselling relevant to emergency contraceptive pill. Emergency contraceptive
pills seemed like a suitable choice because the primary pharmacy customers, being young, are comfortable with technology, no
prescription is needed to buy the pills in Finland, and the robot can provide non-judgmental interaction to the costumers. We suggest
the use of field study methods in future research in which both qualitative and quantitative data analyses are combined to expose the
challenges and/or opportunities inherent to the design of robot applications for use in human-robot interaction.
CCS CONCEPTS • Human-centered computing ~ Interaction design • Human-centered computing ~ Empirical studies in
collaborative and social computing
Additional Keywords and Phrases: Social robot, Real life scenarios, Medication counselling, Emergency contraceptive pill
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ACM Reference Format:
Malin Andtfolk, Susanne Hägglund, Sara Rosenberg, Mattias Wingren, Sören Andersson, Prashani Jaysingha Arachchige, and Linda
Nyholm, 2022. The further implementation of robots in welfare: A co-created application for robot-assisted medication counselling. In
Tampere ‘22: 25th Academic Mindtrek 2022 International Technology Conference (Academic Mindtrek), November 16-18, 2022,
Tampere, Finland, 4 pages.
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1 INTRODUCTION
Social robots can be defined as autonomous or semi-autonomous robots with an overall human-like appearance and
some movable parts [1] that interact with humans in a natural, efficient and a socially acceptable way [2]. Also known
as socially assistive robots, social robots can be considered the “intersection” of assistive robots and socially interactive
robots [3]. The goal underlying purposefully designing robots to look like humans is the furtherance of human-robot
interaction, whereby robots’ learning of relevant knowledge through the observation of and interaction with humans
might occur [4, 5]. As part of an ongoing research project, we are in the process of developing a new robot application
through which robot-assisted medication counselling can be facilitated; the process hitherto is presented below.
Overall healthcare and social welfare quality and safety can be facilitated through evidence-based effective care and
services. For example, ensuring patient safety involves safeguarding the safe and appropriate use of devices, resources,
facilities and medicines [6]. Medication counselling is an intervention whereby patients/customers are given information
about medication, with the aim to ensure safe use and prevent medication errors [7, 8]. High-quality medication
counselling can significantly improve the safety of medical treatment and help prevent medication-related problems
and/or resource inefficiency [9]. Shortcomings in the implementation of pharmacotherapy (e.g., professionals’ lack of
competence, time and/or language skills) can jeopardize patient safety [10]. Both the number of people needing
healthcare and the number of medications being offered have increased, thus pharmacists and others who provide
medication counselling can through their position and competence be said to play a crucial role in healthcare [11].
To meet growing healthcare needs, the introduction of new digital solutions and welfare technology, e.g., social
robots, has been proposed [12]. The overall aim of our research is to promote patient safety through the development of
a new robot application through which robot-assisted medication counselling can be facilitated. Below we describe the
processes underlying the design, development, and evaluation of a bespoke robot application through which human-
robot interaction in medical counselling is enabled, with the goal to promote patient safety relevant to emergency
contraceptive pills. Emergency contraceptive pills are defined as a medication that can be used to prevent pregnancy
after sexual intercourse [13]. Such a parameter was chosen because we believe it will yield a suitable target group; those
who use such medication are often relatively young and (assumed to be) comfortable with new technology. This is also
consistent with prior research [14], that those who use emergency contraceptive pills are mostly women in ages between
21-24 years. In addition, the use of robots allows for what can be considered non-judgmental interaction [15], which is
appropriate for medication counselling. Another influencing parameter and as per legislation in Finland, a prescription
is not required for emergency contraceptive pills. However, although considered a non-prescription medication, such
medication is kept behind the counter and information about medication adherence and contraindications must be
provided. A user-centered approach is used [16] to strengthen the design of the application being developed [17].
Below, we first describe the research background, including the use of social robots in welfare contexts and
medication processes (Section 2). This is followed by an overview of the research process and discussion (Section 3). We
thereafter present our conclusions and provide suggestions for future research (Section 4).
2 RELATED WORK
2.1 Social robots in welfare contexts
The concept of applied social robotic technology and the use of social robots in welfare emerged a few decades ago,
where such technology was primarily used for assistance or to enable measurable progress, e.g., within rehabilitation or
convalescence [2]. In one earlier study, the use of a social robot for feeding assistance (e.g., retrieval, scooping, delivering
of food) was tested in a laboratory setting with several participants with various motor impairments. The overall
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experience was positive, and the study participants considered the system to be easy to use, safe and effective. However,
some participants were initially overwhelmed or intimidated by the large size of the robot used, with suggestions being
made that a smaller and user-friendlier assistance robot should be developed [18]. In another study encompassing young
children with cerebral palsy, researchers, therapists and the included children’s parents designed, developed and
evaluated the use of a social robot as a therapeutic aid during rehabilitation, with participants perceiving the robot to be
a great companion for children [19]. Social robots have even been tested in studies focusing on cardiac rehabilitation for
adult patients [20] and gait rehabilitation for neurological patients [21]. In the cardiac rehabilitation study, participants
(patients and clinicians) were positive regarding, e.g., the robot’s usefulness, safety, trust and utility [20]. In the gait
rehabilitation study, evaluated parameters were seen to improve for the participants interacting with the robot [21].
2.2 Social robots and medication processes
There have recently been studies in new fields of social robotics in which user attitudes and/or experiences have been
investigated, among others the use of social robots in medication processes. For example, social robots have been
developed to remind users about medication schedules [22] or to monitor medication adherence [I23], with several
benefits being shown. However, issues related to users’ adoption of new technologies [22] or a fading learning effect
have also been seen, which might occur if a robot is not developed in line with individual needs [23]. In one laboratory
investigation of the use of humanoid robots for medication management (drug administration, compliance and assistance
during the medication process) [24], the robot was considered viable but suggestions for longer-term interventions to
examine its practical use in applied settings were made.
Especially in comparison to other industries, social robotic technology is still not fully utilized within the welfare
sector [25]. In previous welfare sector research, a focus on the evaluation of several robot functions simultaneously has
mainly been employed [26]. Consequently, the investigation of individual functions, e.g., the use of social robots in
medication counselling, is lacking. Further research needs to be done that enables human-robot interaction in medication
counselling.
3 OVERVIEW OF THE RESEARCH PROCESS AND DISCUSSION
Following is an overview of the processes underlying the design, development and evaluation of a bespoke robot
application designed with the aim to enable human-robot interaction in medication counselling for emergency
contraceptive pills and with the goal to promote patient safety. As part of the FarmAInteraktion project at Åbo Akademi
University (May 2022 - December 2022), the ongoing research includes the interdisciplinary co-created design of a robot-
assisted application for medication counselling, including design of a prototype and iterative testing through real-life
simulations in a laboratory setting. To broaden the research perspective, research group members with experience of
welfare, pharmaceutics and technological development, user experience from the fields of Health Sciences,
Pharmaceutics, Information Technology, Psychology, and researchers from Experience Lab have been included. During
various phases of the research process, other users, e.g., pharmacists, pharmacy customers, and/or others involved in
the included iterative testing, will be invited to participate as co-creators.
The application is designed for use with the Furhat social robot platform, developed by Furhat Robotics [27]. This
particular social robot was selected for inclusion because its size, appearance and capacity for conversation were
considered to align with the research aim, the enablement of human-robot interaction in medication counseling. For a
visual overview of the robot see Figure 1. Fashioned as an animated face sitting atop a base, the Furhat robot can be
integrated with various information channels, includes a 3D animated projector with the capacity for 22 animated faces
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(additional customized faces created on-demand) and can interact in 40 different languages and in an unlimited number
of characters. The Furhat robot has many realistic and natural capabilities when interacting with its surroundings.
Moreover, the Furhat robot includes a voice user interface (all interaction is voice-based), thus the risk of spreading
pathogens is minimized because users do not need to touch the robot.
Figure 1: Visual overview of the Furhat social robot. Photographed by Furhat Robotics. (https://furhatrobotics.com/).
4 DESIGN APPROACH AND RESEARCH PHASES
The design and research phases will comprise two main phases, presented below.
4.1 Phase 1: Understanding the pharmacy context
The first phase of the project included mapping of previous research regarding use of social robots in medication
processes and investigating access to medication databases. It also included simulating a pharmacy at Experience Lab,
enabling us to scale down the complexity inherent in the pharmacy context. To deepen contextual understanding,
simulations between pharmacists and participants was underway in the form of real-life scenarios in the simulated
laboratory setting. During these simulations pharmacists provided participants with medication counselling relevant to
emergency contraceptive pills (e.g., giving information and advice about possible medication interactions, possible side
effects and/or contraindications). Data was collected from multiple sources, including video recordings, interviews and
discussions.
4.2 Phase 2: Designing and developing the interaction
The second phase of the project is currently ongoing. The data derived during Phase 1 will be used to design, develop
and evaluate the bespoke robot application. The design process will proceed in an iterative manner. The goal is to create
a robot application with the capacity to enable the Furhat robot to act as a pharmacist and provide counselling to
participants through which patient safety can be increased relevant to emergency contraceptive pills in the simulated
pharmacy setting. To assess the results of this phase of the research project, data will be collected from multiple sources,
including video recordings, interviews, discussions and robot software and hardware data.
5 CONCLUSION AND SUGGESTIONS FOR FURTHER RESEARCH
Despite initial implementation in the welfare sector, in-depth understanding of social robots’ utility in the provision of
medication counselling is lacking. The purpose of this ongoing research project is to design, develop and evaluate a new
robot application based on users’ needs through which robot-assisted medication counselling can be facilitated in
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pharmacy settings. The completion of this research project will result in a robot application that has been co-created
with relevant stakeholders. As such, this research will contribute to the deepening of knowledge on users’ needs and
the potential of social robots in medication counselling processes.
The initial findings from our mapping of previous research show that social robots can be suitable robot
technology in medication processes [28, 29], but a better approach to integrating existing pharmacy systems with robot
software solutions is needed [30]. Early findings from the lab studies elicited values when buying emergency
contraceptive pills. The participants corresponded to the four stages of care according to Tronto [31], attentiveness,
responsibility, competence, and reciprocity. The early findings also include a task analysis of the pharmacists providing
medication counselling. These initial findings from this ongoing research project provide a better understanding of the
individual needs and evaluations of the end users towards the use of a social robot in medication counselling of
emergency contraceptive pills. However, we are cognizant of the ethical challenges inherent to the development and
implementation of robot-assisted medication counselling (social and technical aspects), e.g., perceptions that robots
might cause harm to humans [32, 33].
In line with earlier research [34] and in accordance with initial findings from this ongoing research project, we argue
that suitable and easy-to-use robot applications cannot be developed from the use of individual measurement alone. We
instead advocate the inclusion of an interdisciplinary Research and Development (R&D) team, the perspectives of
multiple stakeholders in a co-creative process and the use of real-life scenarios and simulations to address usability
challenges and provide greater insight into how human-robot interaction can be used to strengthen patient safety. We
furthermore advocate the inclusion of a user-experience perspective and relevant decision-makers in a co-creative
process whereby relevant stakeholders’ attitudes can be aligned. We suggest the use of field study methods in future
research in which both qualitative and quantitative data analyses are combined to expose the challenges and/or
opportunities inherent to the design of robot applications for use in human-robot interaction.
ACKNOWLEDGEMENTS
We thank everyone who participated in this research project for valuable contributions. This work is funded by the
strategic research profiling area Solutions for Health at Åbo Akademi University [Academy of Finland, project# 336355].
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