Human-Computer Interaction, Clinical Trials, Type 2 diabetes, Clinical User-experience evaluation, Telemedicine

A worldwide demographic shift is in progress. The percentage of the population that is ageing (those over the age of 64 years) is projected to more than double in the next four decades. People aged over 64 has a higher burden of disease, so the demand for medical care will increase. Unfortunately, the present healthcare models will be inadequate to handle the demands of the ageing population.

One proposed remedy to provide in-home assisted healthcare with technology-intervened approaches. Telemedicine, telehealth and e-health are part of current technological approaches that provide clinical treatment through a technology intervention. In evidence-based medical science, these technology interventions are evaluated through clinical trials.

Clinical trials are targeted to measure only improvements in medical conditions and the treatment’s cost effectiveness. They do not investigate patients’ experiences with these technologies. However, the effectiveness of a technology also depends on the interaction pattern between the technology and its users, especially the patients. The discipline of Human-Computer Interaction (HCI) provides various user-centred evaluation methods to assess user interaction and satisfaction with a technology.

I developed a novel research methodology named the Clinical User-Experience Evaluation (CUE) for this qualitative research study. The CUE is an HCI user-evaluation technique that complements a wider medical clinical trial. This clinical trial investigated medical improvements and cost-effectiveness of telemedicine in-home monitoring technology for type 2 diabetes patients in the Townsville region in Australia. The clinical trial was governed by the Townsville-Mackay Medicare Locals (TMML). The CUE investigated how patients interacted with in-home monitoring technology that was being used as part of TMML’s clinical trial.

The CUE consisted of three stages (Figure 1). I defined the precise stages of CUE to separate it from the activities of the clinical trial (which were conducted by clinical researchers/nurses). The CUE uses an ethnographic approach. I carried out the CUE in the field with nine type 2 diabetes patients. In addition, I interviewed two nurses to complement the patients’ interviews.


Figure 1. The three stages of CUE methodology.

Stage 1 of CUE was a contextual inquiry that was performed in-situ at a patient’s home. Patients used the technology with the think-aloud method during this stage, during regularly scheduled times for using the technology.

Stage 2 of CUE was a semi-structured qualitative inquiry to understand patients’ experience and expectations. In addition, questions that arose during stage 1 and any topic mentioned by the patients were explored. The interview took place directly after stage 1, while perceptions were still fresh in the mind of the patients.

I observed certain patterns of behaviour among the patients in this clinical trial, during the first two stages. I developed a semi-anonymous survey to verify these observations by obtaining patients’ opinions. This survey in stage 3 was conducted online eight months after stage 2. The survey was semi-anonymous to encourage patients’ candour.

Prior to the implementation of the CUE, I conducted a meta-synthesis of past clinical trials of type 2 diabetes. The meta-synthesis demonstrated that past telemedicine technologies had positive behavioural outcomes on patients. Therefore, implementation of CUE held promises of new findings in a traditional clinical trial.

Data from CUE was analyzed and presented as the following topics in my thesis.

  1. Patients’ experience of using the device;
  2. A User-Centred Design (UCD) for type 2 diabetes patients;
  3. Domestication of the technology; and
  4. Hidden Hypotheses by patients and nurses-- this part presents my observations about the assumptions that the patients made about the trial and the assumptions that the nurses made about the patients and the technology. I call these assumptions “hidden hypotheses”.


Key analytical findings from the CUE depicted that patients value the benefits of in-home monitoring but the current device did not possess all functionalities that type 2 diabetes patients require. The UCD methodologically confirmed the functionalities the in-home monitoring device should contain, to meet the expectations of type 2 diabetes patients. Analysis on the domestication of the device showed that patients did not change the location of the device after the initial placement. The hidden hypotheses disclosed some causes of why patient feedback about technology may remain hidden in a medical clinical trial.


Parts of this research were published in the following papers.

  1. Jalil S (2013). Persuasion for in-home technology intervened healthcare of chronic disease: Case of diabetes type 2. Paper presented at the Adjunct Proceedings of 8th International Conference on Persuasive Technology (Persuasive-2013), Sydney, Australia, April 3-5
  2. Jalil S, Hardy D, Myers T, Atkinson I. But it doesn't go with the décor: domesticating a telemedicine diabetes intervention in the home. In: Proceedings of the 26th Australian Computer-Human Interaction Conference on Designing Futures: the Future of Design, 2014a. ACM, pp 280-289
  3. Jalil S, Myers T, Atkinson A Design Implications from the Preliminary Results of a Telemedicine Patient-Technology Interaction Study. In: The 7th International Symposium on Visual Information Communication and Interaction (VINCI' 2014), Sydney, Australia, 6-8 August 2014 2014b. ACM, pp 192-195
  4. Jalil S, Myers T, Atkinson I (2015) A Meta-Synthesis of Behavioural Outcomes from Telemedicine Clinical Trials for Type 2 Diabetes and the Clinical User-Experience Evaluation (CUE). Journal of medical systems 39 (3):1-21