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Author: William B. Rouse and Dennis McBride
This article focuses on cognitive assistive technologies that help people with disabilities in the workplace or older adults doing the “work” of daily life. The types of work and other activities needing assistance are outlined and likely technologies summarized. We briefly discuss the ecosystem that provides access to, regulates, and pays for such assistance and how best to navigate in it. We consider the economic impacts of assistive technologies in terms of employment and the ability of older adults to remain in their own home.
According to the Pew Research Center (2017), there were 40 million Americans with a disability in 2015, representing almost 13 percent of the civilian noninstitutionalized population. Older Americans are more likely to have a disability—25 percent of those ages 65–74 and 50 percent of those 75 or older. The study also reported that disabled Americans are less likely to have home broadband and digital devices.
Furthermore, the number of Americans 65 and older is projected to increase from roughly 50 million today to over 100 million by 2060, and their share of the total population will rise from 15 percent to nearly 24 percent (PRB 2018). Thus, the number of disabled and -older adults will grow dramatically in the coming decades.
Many people with cognitive and intellectual disabilities are capable of performing well on a number of work tasks, but lack the executive function to independently complete a workday. Smartphones and tablets can be used as assistive technologies to mitigate many of the barriers that limit both productivity and independence; smartphone prompts, for example, are helpful for people with memory issues and learning disabilities, and proper prompting is an affordable supplement to training.
The Assistive Technology Industry Association defines assistive technology (AT) as “any item, piece of equipment, software program, or product system that is used to increase, maintain, or improve the functional capabilities of persons with disabilities. Assistive technology helps people who have difficulty speaking, -typing, writing, remembering, pointing, seeing, hearing, learning, walking, and many other things. Different disabilities require different assistive technologies.”
Market projections for assistive technologies vary, but predict very substantial growth. McCue (2017) reports that “The global elderly and disabled assistive devices market was valued at $14 billion in 2015 and is expected to surpass $26 billion by 2024, according to Coherent Market Insights.” PRNewswire (2016) reports that “The US market for assistive technologies is projected to grow from $40.6 billion (including eyeglasses and contact lenses) in 2014 to…$58.3 billion in 2020, with a compound annual growth rate of 6.2 percent.”
It seems safe to conclude that assistive technologies represent both an enormous societal need and an impressive market opportunity.
Cognitive Assistive Tools
There is a wide range of ways that disabled and older adults can be assisted in their activities, be it in the workplace or their daily life (e.g., Bartleby 2018). This section briefly reviews selected efforts in this arena, with a focus on cognitive aids.
The National Academies of Sciences, Engineering, and Medicine (NASEM 2017) recently explored the promise of technologies for physical assistance such as wheeled and seated mobility devices, upper- and lower-extremity prostheses, hearing aids, and speaking aids. The report considered cognitive abilities to use these technologies, but not aids to augment cognitive disabilities.
A calculator is a well-known aid for those who cannot do arithmetic in their heads. We focus on devices for those with clinical diagnoses of intellectual and developmental disabilities (IDD). These “include autism, Down syndrome, traumatic brain injury (TBI), and dementia. Less severe cognitive conditions include attention deficit disorder (ADD), dyslexia (difficulty reading), dyscalculia (difficulty with math), and learning disabilities in general” (Mada 2018).
One study of adaptive tools to cope with age-induced cognitive disabilities concluded that social assistants and other intelligent devices should be able to non-intrusively monitor people, support daily routines, and enhance interpersonal communication (Jorge 2001). Such devices depend on machine learning, human-computer interaction, and mobile computing.
Several studies have reported the training benefits of assistive technologies, whereby the interventions result in improved human abilities. A recent study reports on the effects of technology-assisted therapy for intellectually and visually impaired adults suffering from separation anxiety (Hoffman et al. 2017). The intervention was via iPhone with face-to-face communication through which subjects shared their moods. Results showed significant decreases in separation anxiety and increases in quality of life.
Computer-assisted cognitive rehabilitation intervention in relapsing-remitting multiple sclerosis patients emphasized episodic memory, information processing speed/attention, and executive functions (Messinis et al. 2017). Over a 10-week period, 20 one-hour training sessions improved patient confidence in their cognitive function and yielded superior results compared to standard clinical care.
In a separate study, an assessment of a short cognitive training program for people with multiple sclerosis found that 12 weekly training sessions of 60–75 minutes significantly improved measures of verbal memory, working memory, and phonetic fluency; reduced anxiety; and enhanced quality of life (Pérez-Martin et al. 2017).
The opportunity is compelling, and technology trends suggest that the needed capabilities are feasible. Never-theless, there are myriad challenges to the adoption of assistive technologies for older and disabled adults, from the need for better-informed healthcare personnel to a lack of evaluation, limited access, and stereotypes.
An overview of the World Health Organization’s program on Global Cooperation on Assistive Technology (GATE) cites the following challenges (Boot et al. 2017):
One important question is “whether IDD are a disability or a health condition” (Salvador-Carulla et al. 2013). Depending on which position an organization takes, the patient may be seen by very different clinicians. Similarly, older adults may experience difficulties with activities of daily life that do not warrant clinical diagnosis but could greatly benefit from assistance. Unfortunately, the payment system usually requires a clinical diagnosis.
Another type of challenge is evaluation of assistive technologies. A comprehensive review of mental health smartphone apps reports that they are rarely subject to evidence-based evaluations (Bakker et al. 2016).
Although assistive technologies can contribute to social inclusion and interaction, only about 10 percent of people with IDD have access to such technologies (Owuor et al. 2018). Among older adults, numerous assessments of use of assistive technologies by older adults have indicated that as much as 30 percent use such assistance, particularly if they have physical disabilities.
Finally, stereotypes can affect the performance and function of older adults (NASEM 2018). A perception of the elderly as “older and wiser” can be beneficial, but negative images (e.g., that they are “weak,” “dependent,” “incompetent”) can undermine the performance and function of both older adults and individuals with disabilities and thus affect employment opportunities, self-image, and health.
A variety of services are needed to support disabled and older adults in employment and daily life. As shown in figure 1, organizations at local, state, and federal levels provide these services. Stakeholders include providers, suppliers, and payers; legislators and regulators; and local professionals, patients, and families (Rouse et al. 2019).
In addition, five federal laws protect individuals with disabilities from discrimination in employment (US DOL 2018):
And states have their own laws (NCSL 2018). Thus, there is an abundance of rules, regulations, and bureaucratic oversight functions, many of which conflict with one another.
Navigating in the ecosystem of figure 1 is quite complicated for those seeking services. People need to know what services are provided, how to access them, and how to pay for them.
An organizational entity is needed to help match resources to people in ways that greatly simplify this complex navigation. (This might itself benefit from an assistive technology, but detailed discussion of such a concept is beyond the scope of this paper.)
Integration of Assistive Technologies
Assistive technologies can be used to support disabled and older adults by
Figure 2 suggests how such technologies can be integrated to augment people’s knowledge and skills for successful -performance—whether the “work” is lawn maintenance, restocking grocery shelves, clearing cafe-teria tables, or performing the activities of daily life.
The feedback loops in figure 2 represent learning by humans and technologies. Ideally, the latter will “understand” not only the work domain of interest but also the particular individual in terms of workflow, behavioral tendencies, and preferences (Rouse and Spohrer 2019).
As mentioned, there is an enormous range of cognitive assistive technologies available, although most have received limited evaluation.
Jobs, Tasks, Skills, and Resources
Designers of assistive technologies need in-depth understanding of the knowledge and skills required for an individual’s successful performance of the jobs and tasks of interest. Cognitive task analysis (CTA) shows how cognitive deficiencies are likely to affect indi-viduals’ abilities to perform and can help designers understand how cognitive resources, skills, and strategies enable people to accomplish their work and other tasks (-Crandall et al. 2006).
Figure 3 provides a framework for mapping jobs to tasks, skills, and resources in order to identify challenges that an older adult or disabled worker is likely to encounter. Such mapping is complicated by the variety of ways in which disabilities are manifested; there can be significant individual differences in deficiencies of cognitive resources and skills.
The ways in which these capabilities are developed and deployed very much depend on the jobs, tasks, and individuals. The resources, skills, and actions listed in figure 3 can serve as a checklist for beginning the cognitive task analysis. This is best illustrated in the context of an example.
Case Study: Wearable Coach™
SourceAmerica has developed an approach to assistive technologies to support its 50,000 disabled -employees; deployment for older adults is a work in progress. -Figure 4 illustrates the overall functioning of a -Wearable Coach (-Nishman 2018). A beta version of the Job Coach functionality (for guidance on what tasks to perform, where and how to perform them) has been completed and evaluated; the Counseling Coach functionality (for managing anxiety, anger; overcoming frustration, fear) is in development.
The Wearable Coach is designed to be worn and (for the most part) used without looking at the screen, for un-obtrusive coaching with appropriate prompts and -reminders throughout the day. Users typically provide input to their device via gestures or voice. The device “-branches” through varying sequences based on information in each sequence combined with user input, time elapsed, time of day, location, downloaded information about what others may have accomplished, and anything else the phone may be able to sense (Nield 2017). Information is stored in the cloud, with a copy of relevant information on the user’s device. Real-time updates about completed work and productivity, worker whereabouts, or schedule changes are uploaded or downloaded, making them accessible to both the worker and management most of the time.
Typical work -sequences and prompts can be maintained in standard libraries, and companies or caretakers can use them to generate custom procedures and prompts. Simplified creation of work or activity sequences makes the system easy and inexpensive to maintain.
A simplified interface allows one to compile and nest sequences for a worker’s day along with the conditional branching needed to keep the person on track. Schedules can be rearranged in real time during the day to respond to changing needs, with such changes pushed to user devices.
The Commissary Helper is a version of the Wearable Coach that has been deployed in beta test mode at some 30 military commissaries worldwide (-SourceAmerica 2018) to help employees with disabilities manage grocery store shelves, for example, in terms of scanning expirations, restocking inventory, and retrieving stock from warehouse locations. It is easy to imagine a version of this coach, perhaps called Grocery Shopping Assistant, being deployed to help older adults navigate in grocery stores, find their desired purchases, and take advantage of specials and discounts.
Economics of Assistive Technologies
It is important to understand the economic value of assistive technologies. Ideally, their value will far exceed their costs. We consider two economic contexts: employment of people with disabilities (and possibly their caregivers), and independent living for people in their own homes rather than assistive facilities. For both scenarios assistive technologies yield sustained economic contributions via consumption of goods and services and reduced costs of care (relative to the baselines without assistance); for those employed, there is increased payment of taxes, for example. Thus, there are three enhanced cash flows, one due to savings and two to economic contributions.
These three cash flows can be projected, with inflation, and multiplied by the numbers of people in each class of the population of disabled and older adults to estimate overall cash flows, which can then be discounted to estimate net present values. Rather impressive value estimates tend to result, suggesting that significant investments in assistive technologies are warranted (Rouse 2010).
One difficulty with the fragmented AT delivery ecosystem is that these three cash flows do not appear on integrated financial statements. They accrue to different organizational entities. Thus, for instance, payers may see savings but not economic contributions and are therefore likely to undervalue expenditures for assistive technologies because their organizational accounting assigns no value to healthy, employed people. Clearly, design and operation of the AT delivery ecosystem needs to be approached with a view of the whole system.
Enormous human and economic benefits are possible from assistive technologies for disabled and older adults. Quality of life can be substantially enhanced and economic returns can easily justify such investments. Feasibility, however, depends on adopting a systems approach to understanding the extent of the opportunity in the context of the overall delivery ecosystem. Navigating this ecosystem is worthy of assistive technology in itself.
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 The Pew survey reported on “serious difficulty with hearing, vision, cognitive and ambulatory abilities, [and] difficulty with self-care and independent living.”
 The GATE challenges concern applications for IDD, but they extend to uses for older adults and have been modified here accordingly.