Abstracts Track 2021


Nr: 4

The 'Forgotten' Personas in the European Spectrum of Older Adults and (Their) Care-givers: Key Contributions from the Cases of Cyprus and Romania


Cosmina Paul, Vasilis Giannoglou, Evangelios Koulis and Idoia Munoz

Abstract: To meet the demand of the heterogeneous group of older persons in Europe and to support their ageing in place, researchers and developers need to precisely design products and services which would be successfully used by their end-users. Hence, the persona method is key in developing user centred approach technologies. This study introduces the development of 4 new European personas, which are often overlooked by the current studies while their presence is a reality and their frequency is increasing: the retirement migrant, the hyphenated identity of being both an older adult and unprofessional informal carer (often for a parent or a spouse), the ex-caremigrant and the undocumented migrant. Often the identities of an older adult range on a continuum from being a care-giver to becoming a care-receiver and we need to account for that. These findings aim to support researchers and developers in being more precise when constructing their target users of new technologies for aging in the place. The innovativeness of the study is emphasized in increasing the representativeness of the European older adults’ personas and (their) unprofessional care-givers. This work was performed in the frame of the EU project Senior-TV (AAL/Call2019/182), entitled iCan. ICTbased assistant for everyday life, funded by the AAL Programme, co-funded by the European Commission and the National Funding Authorities of Cyprus, Spain and Romania.


Nr: 10

Identification of Factors Influencing Development of an Engaging Type 2 Diabetes Mellitus Application for Self-management


Kuthethur Sneha Jagannath Das, Nic Moens and Felix Janszen

Abstract: Type 2 Diabetes Mellitus (T2DM) is a chronic condition affecting the geriatric population globally. Studies show that T2DM will affect approximately 642 million people worldwide by 2040. Maintaining optimal blood glucose levels (BGL) is the crux of T2DM care. T2DM care involves sufficient pursuit of physical activity, healthy diet, medication adherence, and periodic monitoring of BGL. Thus, self-management by adopting healthy lifestyle behavior choices from the patient's side is integral for T2DM care. Advancements in medical technology have enabled the implementation of mobile health (mHealth) for remote self-management of chronic conditions. Various features such as self-monitoring, feedback, and reminders can be included in a mHealth solution thus facilitating self-management behaviors in the patient. To adopt and sustain healthy behaviors, engagement of the user with the digital health intervention is crucial and studies have also shown that user engagement is a precondition for achieving health effectiveness. Engagement is defined as the quality of the user's experience with technology and focuses on understanding how the user interacts with the technology. In our project, we aim to develop a clinical and evidence-based mHealth smartphone application (app) that would support T2DM patients in maintaining their BGL levels within the target range through the adoption of healthy lifestyle behaviors through remote monitoring and coaching. The CeHReS roadmap is being adopted in the development of the proposed app. As the first step in this project, we aimed to understand the factors influencing user engagement with a T2DM management app. For this purpose, we conducted a stakeholder discussion consisting of a panel of experts. The expert panel consisted of 5 members with expertise in the areas of eHealth, behavior change, Artificial Intelligence, app development, and T2DM. This expert evaluation was conducted by showing the panel members some of the interfaces designed (The scope of these initial interface design processes is not the focus of this abstract) in the form of wireframes and gathering their views on the scope of user engagement through a questionnaire and panel discussion. Based on the insights gained from the expert evaluation, a decision to conduct a literature study was taken. For this purpose, 10 papers focusing on T2DM, mHealth,eHealth, telemedicine, and engagement were identified from JMIR (open source). The results from the expert stakeholder discussion and literature study identified 9 factors affecting patient engagement with a T2DM mHealth intervention. The factors can be grouped into the sociodemographic category. Health illiteracy, digital illiteracy, education level, income level, age, ethnicity, residence, cultural awareness, and clinician presence are the factors. It was also evident from the analysis of the results that the factors are interrelated to each other. As the next step in this project, the results obtained from this small study have been taken as input to further optimize the interface designs and are currently in the app development phase. With this developed functional prototype, we aim to conduct a longitudinal user evaluation study with T2DM patients belonging to different age groups, education levels, income levels, and ethnicity. This user evaluation will focus on the usability, user experience, and effectiveness of the app.

Nr: 11

Using Data Transparency to Understand Health Behavior during a Pandemic: Exploring Older Adult Utilization of Alternative COVID-19 Testing Options


Doria Weiss and Douglas Elwood

Abstract: The pandemic has presented an unprecedented challenge to the traditional healthcare system and altered individual health-seeking behaviors. Medical visits declined almost 40% in the beginning of the pandemic and continue to fluctuate. Lack of a national testing strategy coupled with shifting advice on maintaining distance from clinics limited access to testing in traditional venues. Older adults are more likely to have underlying conditions and experience severe symptoms, augmenting the importance of testing that cohort while limiting exposure in clinical settings. The purpose of this review is to explore health behavior among older adults who engaged in an expanded telehealth model, which provided access to nearly 18 million total COVID-19 tests nationally. To understand more who was accessing testing through this model , we created a dashboard to make the data transparent and capture the salient information. We analyzed the demographic characteristics of those who engaged in the model. We also assessed trends in positivity rates. Results show that 29.5% of over 18 million individuals were 31-45 years old and 20.3% were 46-65 years old, while 10% were 61-75 years old. The highest COVID-19 positivity rates in this timeframe were among those aged 46-60 years old (6.8%) followed by those aged 61-75 years old (6.7%) and 18-30 years old (6.4%). Middle aged and older adults represented the highest positivity rates, yet were not obtaining testing as frequently as younger adults. In order to curtail the pandemic, increased access to testing while limiting potential exposure is crucial, particularly for those who are most at risk. As traditional medicine has struggled to keep itself upright, viable options for testing outside of normal venues is critical, as is capturing data related to behavior and understanding effects of various programs. This expanded telehealth model and the corresponding dashboard provide a blueprint for exploring current response mechanisms to address future policy and public health measures.