Creating technology that can be used by Older Adults — Key Considerations

Introduction

Facebook’s (now Meta’s) influence on the technology landscape is undeniable. When the company announced its vision for metaverse, it was evident that there would be a huge wave of innovation in the AR/VR/XR/MR space in the coming years — completely changing the way we interact and communicate.

As such, it is evident that older adults are going to get left behind, again.

So, I decided to put together a quick article outlining key considerations for anyone who considers older adults as a part of their user base.

Background

Over time I have helped numerous older adults set up, troubleshoot, and maintain their technology solutions both in India and in United States. During each interaction, my top priority was to listen, learn, and empathize with them about:

1. The needs that drove their initial adoption of technology
2. The pain points which discouraged their continued use of technology and/or limited their intention of extending adoption of technology

Interacting with people from different cultures, age groups, education levels, and varying experience with technology, I have acquired a unique perspective about the common pain points across this user group (older adults).

Impact of COVID-19

The increase in use of technology due to COVID-19 is undeniable — it is visible across cultures, geographies, and societies. While younger to middle-aged people have been quick to embrace a technology driven social experience, older adults have not been able to adapt (to a certain degree) either to the technology or to this new norm — resulting in increased feelings of isolation. Stemming from this mismatch in technology centric social experience/human connection, I hypothesize that older adults have become more resistant to technology adoption because of:

1. Workload Paralysis — The constant expectation of the younger members of the family that the older adults need to learn new technologies to stay connected can result in workload paralysis in the older adults.
2. Digital Nativity and Social Comparison — When older adults see how quickly younger members learn new technologies and compare that with their personal learning speed (which can be slower), they can feel discouraged to continue on the current learning trajectory.

Primary Drivers of Pain Points

As I have discussed causes of user pain points with older adults, some common themes regarding user behavior have surfaced:

1. Forgetfulness — Forgetfulness with carrying/keeping devices, putting on wearables, using keywords to activate voice assistants, and more generally forgetting how to use devices.
2. Willingness to learn — Lower willingness/resistance to learning new skills, technology, features, and methods of communication.
3. Frustration Threshold — Lower frustration tolerance resulting in quicker frustration with technology when it doesn’t work perfectly, reinforcing their resistance to learning (#2 above).

I hypothesize that the primary driver of user pain points is the mismatch between user behavior/expectations and technology design.

Design Considerations

Resulting from my hypotheses in the above sections, I suggest the below design considerations for creating technologies for older adults:

Don’ts

1. Learning curve — Don’t create something that requires/involves learning something new. This suggestion comes out of the following hypotheses — workload paralysis, digital nativity and social comparison, forgetfulness, and willingness to learn.
2. Wearables — Don’t create a wearable. This suggestion comes out of the following hypotheses — forgetfulness, willingness to learn, and frustration threshold.
3. Voice Assistants — Same as wearables (above)
4. Cyber hygiene — Assume they will not follow recommended cyber hygiene practices (multi factor authentication, strong password, etc.), so don’t create any technology that requires decision making on their part regarding privacy and security.
   For instance, don’t create a “free social media platform” that harvests their data and then obscurely introduce a way for them turn off this feature. Because they probably don’t even know that their data is being harvested, it is highly unlikely that they will understand the use of this feature.

Do’s

1. Leverage Prior knowledge — Understand what your user segment already knows (truly empathize with the user) and leverage that to create your product/service. This alleviates problems associated with learning curve (don’t #1 above).
   Let’s use a video calling app as an example: instead of expecting older adults to learn different ways (swipe, slide, click) to accept/decline call across all the different video calling apps, hand gestures can be leveraged to accept calls across all video calling apps. Absence of the programmed hand gesture can be interpreted as an implicit decline. This idea is rooted in the universal practice of using the “hello hand gesture” to acknowledge another person’s presence and no hand gesture implies that presence is not noticed/acknowledged/welcomed
2. Integration with everyday objects — If you are thinking about using wearables to deliver the benefit of your product, then try to re-imagine the product such that it can be integrated into everyday products that older adults are already accustomed to using.
   For instance, if your product is going to use a smartwatch to track activity/steps, consider creating hardware that can be embedded into footwear since this is something they are already accustomed to using.

Key takeaway

The main idea here is: deliver benefits and abstract complexity.