Designing Pervasive Technologies for Older Adults
Designing Pervasive Technologies for Older Adults

Designing Pervasive Technologies for Older Adults

Many countries in the world are battling the ageing pandemic. In 2019, there were 703 million older adults (65 and over), which is projected to double to 1.5 billion in 2050 (United Nations, 2019). While population ageing should be celebrated as a success story, it quite often a source of grave concern. In fact, it places a strain on health and social care systems. As such, policy makers, the private sector, not for profit organizations, institutions for higher learning, engineers, and   designers are scrambling for solutions to solve the ageing problem.

Pervasive computing offers endless possibilities to mitigate the negative consequences of ageing. In addition, it promises to promote ageing in place by offering holistic solutions e.g., through the provision of social and psychological support, activity and fall detection, and the monitoring of dietary intake. These services are envisioned to improve the well-being and overall quality of life of older adults.

Although pervasive technologies have demonstrated a plethora of benefits, their adoption rate is significantly lower compared to their younger counterparts (Pew Research, 2014). Arguably, this can be attributed to the mismatch between the perceptions of the needs of older adults and that of designers and engineers. Oftentimes, the elderly are stereotyped as frail, dependent, and technology illiterate. While, despite their own ageing challenges they perceive themselves as strong and independent.  Also, the elderly population is often overlooked as a heterogeneous group, with each one having their unique diverse needs.   

Another issue, that affects adoption is the ethical implications of monitoring interventions. For instance, I worked with a group of elderly people in Western Europe to monitor their physical activities using smartphone sensors.  While some elderly participants  were pro adoption, others were against monitoring technologies for fear of losing their autonomy and privacy violations. In retrospect, a number of participants echoed fears of big brother is watching me and felt they were trading their privacy in exchange for the use of monitoring technologies.  Some were also concerned about the implications of data use and storage. In addition, the notion of relevance was quite prominent among the participant majority as they felt that assisted technologies were more appropriate for the frail elderly. For instance,  one elderly person (over eighty years old) felt that monitoring interventions would be more appropriate when she is older. In the same breath, others felt like they have lived and enjoyed life so if they are frail and dependent then death should be accepted as normal in one's lifecycle. Thus, privacy should be respected and  the elderly left unobserved.

Added to privacy infringements, a few participants in my previous work suggested that some design technologies require too much attentional resources and do not easily fit in their everyday routines. This often leads to disinterest and ultimately non-adoption.

Considering the above mentioned barriers to adoption, a number of design guidelines are outlined below.

  • Designers should avoid a one size fits all approach when designing interventions for the elderly. Thus, design interventions should be relevant to the specific target group within the heterogeneous elderly population.
  • While providing the needed support, design interventions should respect privacy, and  maintain the dignity and autonomy of the elderly population. In so doing, it is important that designers, engineers, and researchers employ strategies that promote trust in the elderly population.  In addition, it is crucial to provide transparent and thoroughly explained terms of use of technology solutions. This is anticipated to provide assurance with respect to the use and storage of their personal data.
  • Technology interventions should be intuitive and easily adaptable to fit in the daily routines of the elderly population.
  • Design interventions should be efficient, easy to learn, and demand less attentional resources, which ultimately reduces the cognitive load for the elderly population.

    Overall, these guidelines can be used to inform the design of pervasive technologies that are relevant to the elderly population and provide holistic support to facilitate healthy and active ageing.
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