Go to previous article
Go to next article
Return to 2005 Table of Contents
Presenter(s)
Mark Harniss, Ph.D.
Center for Technology and Disability Studies
University of Washington
Box 357920
Seattle, WA 98195-7920
USA
Phone: 206-685-4181
Fax: 206-543-4779
Email: mharniss@u.washington.edu
Pat Brown, Ed.D.
Center for Technology and Disability Studies
University of Washington
Box 357920
Seattle, WA 98195-7920
USA
Phone: 206-685-0289
Fax: 206-543-5771
Email: pabrown@u.washington.edu
Kurt Johnson, Ph.D.
Center for Technology and Disability Studies
University of Washington
Box 357920
Seattle, WA 98195-7920
USA
Phone: 206-685-4181
Fax: 206-543-4779
Email: kjohnson@u.washington.edu
In their comprehensive review of the ATC field, LoPresti, Mihailidis, & Kirsch, 2004, recently described the growing body of research on ATC. They note that technologies have been developed to support individuals with a wide range of cognitive (e.g., prospective memory, executive functions, complex attention, self-monitoring) and information processing (e.g., visual, auditory) deficits. The devices used have included commercial devices such as microcomputers, personal digital assistants (PDAs), cell phones, and pagers as well as emerging devices that are still in research and development stages such as smart homes, robots, artificially intelligent memory and guidance aids, and virtual caregiving aids.
LoPresti et al. (2004), note several areas for continued work in the area of ATC. They argue that the primary focus for this field in the near future will be the continued development of new devices and the utilization of existing devices. Beyond that, they contend that the field needs to address the issues of usability over time (i.e., the human-technology-interface-customization, adaptability) and generalizability of device use across home and community settings. Finally, they wonder whether ATC devices will have rehabilitative potential and suggest that the field address this question.
In addition to these suggestions, we believe that the field must address the training protocols and supports needed by consumers and support professionals in order to learn to use technologies and maintain their use over time. Hart, O'Neil-Pirozzi, & Morita, (2003) make this point in their analysis of clinician expectations for using electronic devices with individuals with TBI. They found that although clinicians believed that the devices could be useful in supporting their clients, especially in the areas of learning, memory, planning and organization, two-thirds of the clinicians rated themselves as 'not at all' or 'somewhat' confident in their ability to teach clients how to use the devices. Not surprisingly, those clinicians who reported personal use of electronic devices (e.g., PDAs) expressed significantly more confidence in their ability to teach clients about the devices.
Implications for the Design of ATC. Because of the diversity found in the population of people with cognitive disabilities and the significant environmental demands they face, ATC will need to be broadly applicable to a wide range of individuals with different needs. When designing devices for individuals with cognitive disabilities one may need individualized interfaces and application models, devices will likely need to be easier and simpler to use, and one must consider visual and fine motor skill problems (Kim et al., 2000).
We conceptualize four design implications that must be considered when addressing the ATC needs of people with cognitive disabilities. These four implications help guide our decisions about the functionality needed by ATC.
First, as a result of the differing etiologies of cognitive disabilities and varying functional limitations, we assume individuals will possess different prerequisite skills and knowledge that might impact the use of assisted cognition devices. For example, individuals with multiple sclerosis (MS) may have been proficient technology users prior to the onset of their condition and may be able to learn to use new technology with more ease than individuals with mental retardation (MR) who might not have previous experience. Implication: Devices must provide intelligent support and user interfaces must be intuitive and appropriate. Second, we expect that individuals in these categories will differ in terms of the type of deficits with which they present. For example, individuals with acquired brain injury may have patterns of specific and global deficits based on their specific type of injury and very specific cognitive losses related to the location of trauma, whereas individuals with MR will commonly have more generalized deficits. It is also important to remember that many individuals will present with concurrent (non-cognitive) disabilities such as mobility or sensory impairments. Implication: Devices must be customizable and individualizable.
Third, we expect that there will be differences in the flexibility required of the assisted cognition devices based on an individual's condition. For example, individuals with MS and Alzheimer's disease will generally have decline of cognitive function, while individuals with acquired brain injury may show improvement and individuals with MR will likely be relatively stable in their cognitive function over time. Implication: Devices must be adaptable to change over time.
Finally, we expect that the need for cognitive support will differ based upon the cognitive demand of the task being attempted and that individuals who function quite well under some conditions will function less well when the demands of the task or environment change. Cognitive load theory (CLT) (e.g., Paas, Renkl, & Sweller, 2003) acknowledges that the 'cognitive architecture' of the brain (e.g., working and long-term memory, attention) has limits that can be overloaded. For example, working memory can handle only a small number of interactions at one time. When cognitive limits are reached, an individual becomes overloaded and unable to process more information. CLT theorists also postulate that there are intrinsic and extraneous cognitive loads. Intrinsic loads refer to the inherent demands of the task. For example, memorizing the capital of Washington State is inherently less demanding than explaining the cause and effect of the Civil War. The latter involves more background information and a more sophisticated understanding of events. Extraneous loads are cognitive loads that serve to increase the difficulty of the task, for example, completing a test with a time constraint. Intrinsic load serves as the base load of the task. Extraneous load on the other hand is modifiable. There are many variables that can be manipulated to modify extraneous load including novelty of the task, complexity, speed of completion, and stress. These concepts apply to individuals with disabilities using cognitive technologies. The interrelationship between their cognitive strengths and deficits and the intrinsic and extraneous load of the task help define what is doable for an individual. The addition of cognitive technologies provides a means for reducing some of the extraneous load. Implication: Devices must reduce cognitive load.Conclusion
Silverstein (2000) identified four goals of a disability policy framework. They include
1. Equality of Opportunity (i.e., individualization, meaningful opportunity, inclusion and integration)
2. Full Participation (i.e., involvement in decision making, informed choice, self-determination, self-advocacy)
3. Independent Living (as a legitimate outcome of public policy resulting from the provision of independent living skills development, long-term services and support including personal assistant services and assistive technology devices and services, and cash assistance)
4. Economic Self-sufficiency (as a legitimate outcome of public policy resulting from the provision of employment related support systems, cash assistance with work incentives, and tax policies to employers and employees) (p. 2).
Assistive technologies for cognition have the potential to support these goals by mediating the experience of disability for individuals with cognitive disabilities by enhancing systems of support. In particular, these devices may reduce barriers participation and may provide caregivers with cost-effective, safe strategies for providing assistance to the individuals they support.
Go to previous article
Go to next article
Return to 2005 Table of Contents