Medication compliance systems and pill reminders: A constructed failure.

Author: Ms Vered Shay STSM Period: 2019-03-21 – 2019-04-02


Hosting institution: Department of Software Science Lab of Sociotechnical Systems Tallinn University of Technology. Tallinn, Estonia

From ITC: No



Medication compliance systems and pill reminders:
A constructed failure

Medications are the primary tools used to prevent and effectively manage chronic illnesses. However, despite their importance and benefits, appropriate medication use remains a challenge for both patients and providers. Patients frequently do not adhere to essential medications, resulting in poor clinical outcomes and increased the cost of care. The total cost estimate for non-adherence range from 100-300 billion $ each year in the USA alone, and include both direct and indirect costs. Non-adherence also increase the cost burden for informal family caregivers (Bosworth et al. 2014). Although prevalent in all age groups, when it comes to the elderly population, suffering from chronic diseases, the challenge encounters further complexity.

Different systems have the potential to assist with medicine compliance by organizing medications, reminding patients to take their medication and even by communicating compliance statuses to medical practitioners or caregivers. These systems range from simple pill organizing boxes to fancy systems based on sophisticated technology. While many solutions exist, medicine compliance remains a problem for many people. Adoption rates of said systems are low and initial enthusiasm is many times met with declining usage as time passes (Yap et al. 2016).

The goal of this STSM is to further the understanding of why people are reluctant to adopt pill reminder (PR) systems and why PR systems have not been the success that one would initially imagine them to be. Noncompliance is rooted in behavioural, cognitive and emotional aspects (Yap et al. 2016). Also more generally, emotions are considered increasingly important in patient experiences (Steine, et al., 2001). In order to address this challenge, our research is focused on the emotional constructs associated with the adoption and sustainable usage of PR systems. We propose first to analyze the emotional aspects of using PR systems and then based on these understandings, aim at designing and prototyping an example system that combines emotional requirements, along with functional and quality requirements. The method we propose to use for this purpose is motivational modelling.

The results of this STSM will be useful in designing future systems. We aim to publish our results as a paper in a suitable academic journal or as a paper in a suitable conference.

The goals of this STSM are aligned with the goals of the SHELD-ON COST Action by promoting health and well being in later life and allow older adults to live safely, comfortably, and healthily at home.

From this project, it is our intention to strengthen the collaboration between the research groups at Haifa University and Tallinn University of Technology by finding common ground for initiating projects together. This will instigate collaboration between the two groups that have yet to work together and that come from different scientific disciplines. In addition, we hope that the work carried out in this STSM will serve as the foundation for broader collaboration throughout the WG 4.4 (technology adoption), involving additional members in writing a grant for a larger research project.

We will analyze reasons for low usage of PR systems by using a co-design method of motivational modelling (Sterling & Taveter, 2009; Miller, et al., 2014; Miller, et al., 2015), which enables to elicit functional, quality and emotional aspects of PR systems. Based on the insight obtained this way, we will then try to design and prototype an example system that considers in a coherent way emotional requirements, along with functional and quality requirements.

Motivational modelling is a technique that allows ethnographers and requirements engineers to elicit and represent emotional requirements for technology engagement related to the goals to be achieved. In motivational modelling, three kinds of goals – do, be, and feel goals – are elicited from project stakeholders. Do goals or functional goals describe what the system to be designed should do, be goals or quality goals describe how the system should be, and feel goals or emotional goals describe how a user wants to feel when using the system. The results of the requirements elicitation sessions are converted into a motivational goal model (Sterling & Taveter, 2009; Miller, et al., 2014; Miller, et al., 2015). In a motivational goal model, hierarchically arranged parallelograms stand for functional goals representing what the system should do, whereby each sub-goal represents an aspect of achieving its parent goal. As is shown in Figure 1, corresponding quality goals representing how the system should be are associated with functional goals, and are represented by clouds. Corresponding emotional goals, represented by hearts, indicate how stakeholders should feel when interacting with the system. Stakeholders are abstracted into roles of the surrounding socio-technical system and are represented by person icons. The use of goal models has been refined in a variety of applications over recent years, including in designing personal emergency alarm systems for older adults (Mendoza, et al., 2013; Miller, et al., 2015; Pedell, et al., 2017). They contribute a practical way of communicating visually and verbally the functional, quality and emotional goals that need to be addressed in the design of new technology for adoption. Goal models can subsequently be used throughout the design process to steer exploration, experimentation and evaluation strategies.


(21/3 Half day) Day 1: – Literature review of psychological and particularly emotional aspects of medication compliance.
(22/3) Day 2: Solution review: reviewing existing solutions, categorizing them into groups, identifying companies active in this space. Seeking failures and successes of initiatives by companies that have tried to solve this problem in the past.
(23, 24/3) Days 3 + 4: Saturday, Sunday.
(25/3) Day 5: Continuing Solution review. Preparing a workshop on motivational modelling.
(26/3) Day 6: Conducting the workshop of motivational modelling in the Lab of Sociotechnical Systems. Participants of the workshop will include healthcare professionals and older adults.
(27,28, 29/3) Days 7-10: Designing and prototyping an example PR system based on the results of the workshop.
(30, 31/3) Days 11 – 12: Saturday, Sunday.
(01, 02/4) Days 13 – 14: Gathering feedback on the designed prototype from experts from Tallinn University of Technology and Tallinn University (social sciences and gerontology). Writing the final report.


Mendoza, Antonette, Tim Miller, Sonja Pedell, and Leon Sterling. (2013). The role of users’ emotions and associated quality goals on appropriation of systems: two case studies. In: Proceedings of the 24th Australasian Conference on Information Systems.

Miller, Tim, Bin Lu, Leon Sterling, Ghassan Beydoun, and Kuldar Taveter. (2014). Requirements elicitation and specification using the agent paradigm: the case study of an aircraft turnaround simulator. IEEE Transactions on Software Engineering 40(10), 1007-1024.

Miller, Tim, Sonja Pedell, Antonio A. Lopez-Lorca, Antonette Mendoza, Leon Sterling, and Alen Keirnan. (2015). Emotion-led modelling for people-oriented requirements engineering: The case study of emergency systems. Journal of Systems and Software 105, 54-71.

Pedell, S. Keirnan, A. Priday, G. Mendoza, A. Lopez-Lorca, A. Miller, T. Sterling L. (2017). Methods for Supporting Older Users in Communicating Their Emotions at Different Phases of a Living Lab Project. Technology Innovation Management Review 7(2), 7-19.

Steine, Siri, Arnstein Finset, and Even Laerum. (2001). A new, brief questionnaire (PEQ) developed in primary health care for measuring patients’ experience of interaction, emotion and consultation outcome. Family Practice 18(4), 410-418.

Sterling, L. and Taveter, K. (2009). The Art of Agent-Oriented Modelling. MIT Press.

Yap, A. F., Thirumoorthy, T., & Kwan, Y. H. (2016). Medication adherence in the elderly. Journal of Clinical Gerontology and Geriatrics 7(2), 64-67.

Zullig, L. L., Granger, B. B., & Bosworth, H. B. (2016). A renewed Medication Adherence Alliance call to action: harnessing momentum to address medication nonadherence in the United States. Patient preference and adherence, 10, 1189.

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