The acceptance of digital health applications by the older generation – a multi-perspective approach

The potential of digitizing the health system is broad, with benefits for all stakeholders in the healthcare system, particularly in terms of improved quality of care and cost savings. In Germany, a widespread use of the electronic patient records (elektronische Patientenakte, ePA) is considered to have the greatest potential benefits among health technologies (Hühne, 2022). From the beginning of 2021, every person with statutory health insurance in Germany has had the opportunity of using the ePA, which is a file in which a person’s medical findings and reports are stored digitally and can be accessed by all authorized medical providers, with the individual patient having the sovereign rights (Bundesministerium für Gesundheit, o.d.). The various functions of the ePA would bring many benefits, allowing medical history and medication schedules to be viewed by all physicians, which can lead to higher quality of health care. However, the adoption and use rates of the ePA are still very low, and so are the potential benefits. Therefore, the current idea is that the ePA will be automatically activated for all citizens and that it would be necessary to actively object to such activation, which is hoped will increase the number of users (gematik, n.d.). Due to the higher incidence of multimorbidity with increasing age, the use of ePA may be particularly beneficial for older people. However, factors such as a lack of digital literacy or digital tools, computer anxiety and resistance to change can be cited as barriers to the use of (health) technologies for the older generation (e.g. Chen & Shou 2014; Hoque 2017). Researchers have found that family members are often involved in specific technology decisions made by older people (Luijkx, 2015). However, little is known about where and how exactly the adoption of digital health technologies among older people is influenced by social contacts.

As an understanding of this could help to identify approaches to increase the effective and long-term use among this group, this research project will provide new insights into a relevant topic based on established research findings. In the past, various theories and models have been developed over time that seek to explain why people do or do not accept a particular technology, such as the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). Over the years, these models have been further developed, modified and extended, and applied in different contexts (e.g., M. K. Lee et al., 2005; Aggelidis & Chatzoglou, 2009). However, these models tend to focus on attitudes and intentions at a particular point in time and often ignore the whole adoption process of a technology, which consists of different attitudes and experiences before, during and after the adoption (Wang et al., 2018), and the differences between use and effective use (Burton-Jones & Grange, 2013).

Therefore, this research project aims to extend current technology acceptance research in the context of digital health technologies for older adults. To this end, the ePA will serve as the main research context.

Four preliminary research goals can be derived which will be addressed using different research methods according to the mixed-methods approach:

1. Review the literature to assess the current state of research on the influence of social contacts on technology acceptance of digital health among older adults
2. Assess qualitatively the dyadic health technology adoption process by older adults and social contacts
3. Derive and create different profiles of potential user groups with individual needs and preferences that should be targeted by different strategies.
4. Investigate the factors that lead to an effective use of the ePA by older adults (e.g., through a comparative cross-country study).

Aggelidis, V. P. & Chatzoglou, P. D. (2008). Using a modified technology acceptance model in hospitals. International Journal of Medical Informatics. 78, 115-126.

Bundesministerium für Gesundheit (n.d.). Die elektronische Patientenakte (ePA). https://www.bundesgesundheitsministerium.de/elektronische-patientenakte.html.

Burton-Jones, A. & Grange, C. (2013). From Use to Effective Use: A Representation Theory Perspective. Information Systems Research. 24-3. 632-658.

Chen, K. & Shou Chan, A. H. (2014). Gerontechnology acceptance by elderly Hong Kong Chinese: a senior technology acceptance model (STAM), Ergonomics, 57:5, 635-652

Gematik (n.d.) ePA. Accessed in: https://www.gematik.de/anwendungen/e-patientenakte.

Hoque, R. & Sorwar, G. (2017). Understanding factors influencing the adoption of mHealth by theelderly: An extension of the UTAUT model. International Journal of Medical Informatics 101 (2017) 75–84.

Hühne, P. (2022). Digitalisierung im Gesundheitswesen: die 42-Milliarden-Euro-Chance für Deutschland. McKinsey&Company. Accessed in: https://www.mckinsey.de/news/presse/2022-05-24-42-mrd-euro-chance.

Lee, M., Cheung, C. M.K., Chen, Z. (2005). Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation. Information & Management. 42, 1095-1104.

Luijkx, K., Peek, S., Wouters, E. (2015). Grandma, You Should Do It – It’s Cool” Older Adults and the Role of Family Members in Their Acceptance of Technology. International Journal of Environmental Research and Public Health. 12. 15470-15485.

Wang, K. H., Chen, G., Chen, H. (2018). Understanding technology adoption behavior by older adults. Social behavior and personality. 46-5, 801-814.