Predictors of Assistive Technology Use: The Unimportance of Age

RESNA 28th Annual Conference - Atlanta, Georgia

Caren Sax, Ed.D., CRC & Marcia J. Scherer, Ph.D., MPH, CRC

ABSTRACT

Recent advances in outcomes assessment research verify the importance of an appropriate early assessment of consumer needs for assistive technology (AT). Within the context of a 2004 online graduate course addressing the applications of rehabilitation technology, vocational rehabilitation counselors in 25 states were introduced to the Matching Person and Technology (MPT) Model to assess the AT needs of consumers for a course project. Three months post-course, counselors were asked to rate the appropriateness of the match of AT with the consumer. Items from the Assistive Technology Device Predisposition Assessment (ATD PA) have been shown to differentiate consumer predispositions to AT use as well as AT and user match. In addition, there are no significant differences due to age within this sample of consumers served by these counselors.

KEY WORDS: Assistive technology, quality of life, evidence-based practice, outcomes research

BACKGROUND

The value of assistive technology to the consumer is only as good as the appropriateness of its use for that individual. Recent advances in rehabilitation and assistive technology outcomes research verify the importance of an appropriate early assessment of consumer needs for assistive technology (AT). 1,2,3,4 Additionally, recent survey results released by Clarkson University and Good Shepherd Rehabilitation Network list barriers that may further prevent individuals with disabilities from enjoying the benefits of AT products and these include: lack of funding; limited knowledge of the technology itself; shortage of trained experts; and inadequate collaboration among the researchers, AT providers, and AT users. 5 Survey responses from 355 rehabilitation professionals indicated that education, awareness and interest in assistive technology need to be improved and that improved education of consumers and providers would be among the best ways to enhance utilization of assistive technology.

As a way of improving awareness about AT, a course about rehabilitation technology is required to complete a graduate degree offered by a consortium of universities across the US. San Diego State University, University of North Texas, and Georgia State University provide a Council on Rehabilitation Education (CORE) accredited 6 Masters of Science in Rehabilitation Counseling through distance learning technology. Typical students are vocational rehabilitation counselors employed by state agencies who need to obtain a Master’s degree in rehabilitation counseling and/or pass the certification exam in order to maintain their employment. The 12-week course is interactive, using mediated technology (e.g., discussion boards, weblectures, video and audiostreaming). In addition to offering research, resources, and strategies for AT access, acquisition, and funding, the course includes a team project that requires students to identify an individual who is interested in and may benefit from the use of assistive technology, and to help the individual make informed decisions on the assistive technology devices that best fits his or her needs. 7,8 Students are introduced to the Matching Person and Technology (MPT) Model 9 in order to assess the following areas: determination of the milieu/ environment factors influencing use; identification of the consumer's personal and psychosocial characteristics, needs and preferences, and description of the functions and features of the most desirable and appropriate technology. The use of the MPT model is useful for rehabilitation counselors as it is both a personal and collaborative assessment, that is, the consumer and provider can complete the forms together by using the tools as interview guides. The MPT process is validated for use by persons with disabilities (ages 15 and up), applicable across a variety of users and settings, and the measures have been determined to have good reliability and validity . 10, 11

The purpose of this study was to quantify the value of a comprehensive assessment to determine the best match of consumer and assistive technology (AT) and to determine if consumer age significantly influences ratings of subjective capabilities; subjective quality of life, mood, support from others, motivation for AT use, program/therapist reliance, self-determination/self-esteem; and ratings of device match and the importance of particular device characteristics in 12 areas. Examples of these characteristics include, from the consumer’s perspective: how the device helps me to achieve my goals; how the device will benefit me and improve my quality of life; the level of confidence and security in using the device; how well the device can be integrated into my routine and environments; and the comfort level in using the device around friends, family, at school or work, and in the community.

METHODOLOGY

The participants included 64 vocational rehabilitation counselors in 25 US states who were enrolled in the Applications of Rehabilitation Technology distance education course in March to June 2004. Each counselor identified one consumer to work with during the course to determine the appropriate assistive technology device/equipment to meet an individualized employment or independent living goal. Counselor training in the Matching Person and Technology (MPT) Model and consumer completion of the MPT tool, Assistive Technology Device Predisposition Assessment (ATD PA) were used as the interventions, with the item responses on the ATD PA used as the measure.

RESULTS

Table 1: Significant Pearson Product Moment Correlations Between Age and Subjective Capabilities
  1 2 3 4 5 6
1. Age
-
-.30*
-.26
-.35*
-.14
-.25
2. Hearing
-
-
-.51**
.20
-.32**
.04
3. Grasping
-
-
-
.33**
-.25*
.05
4. Health
-
-
-
-
.06
.12
5. Importance of freedom to go where desired  
-
-
-
-
-
.07
6. Many things to Accomplish  
-
-
-
-
-
-
* Correlation is significant at the .05 level (2-tailed)
** Correlation is significant at the .01 level (2-tailed)      

Of the 64 students in the course, 54 reported their consumer’s age. Consumer ages ranged from 17-77 with a mean age of 38.09 (S.D. = 15.4). Twenty-five percent of the sample was 23 or younger; 25% was 49 or older. Pearson correlations were done since age is a continuous variable, even though the remaining variables are all ordinal or nominal. The correlations showed that of the 66 items on the ATD PA , only two showed a significant age difference at the .05 level of significance (none at the .01 level of significance) and both had to do with subjective capabilities. The items are as follows (numbers correspond to location on ATD PA ):

2. Hearing (r =-.30)

12. Overall health (r= -.35)

Thus, as the respondents age increased, their ratings of their hearing and overall health decreased. These correlations are expected as age advances regardless of disability status and, thus, the fact that older participants rated lower capabilities in these areas can actually be interpreted to support the reliability of the ATD PA . When Spearman’s Rho correlations were done (due to the preponderance of ordinal and nominal variables) only three additional items were significant at the 05 level of significance (none at the .01 level of significance). The items are as follows (numbers correspond to location on ATD PA ):

7. Grasping and use of fingers

13. Freedom to go wherever desired [importance to the respondent, not satisfaction with current status in this area]

27. I have many things I want to accomplish

Again, decreases in each of these items are traditionally associated with advancing age for persons with or without disabilities.

DISCUSSION

Given the limited fiscal and personnel resources available to meet the AT needs of individuals with disabilities, it is important to use these resources efficiently and effectively. Rehabilitation professionals in collaboration with the consumer can use the MPT model to help make a better match of AT and user, regardless of age of the consumer. This study indicated that there were no significant correlations between age and any of the device match variables. The only items that were associated with age had to do with areas where advancing age is typically associated with decreases in ratings. The results suggest that a consumer-centered and comprehensive process for assessing and matching people with the most appropriate AT can overcome any barriers to AT use associated with age.

REFERENCES

  1. DeRuyter, F (1997).  The importance of outcome measures for assistive technology service delivery systems.  Technology and Disability .  6(1,2):89-104.
  2. Fuhrer, M. J. (2001). Assistive Technology outcomes research: Challenges met and yet unmet. American Journal of Physical Medicine and Rehabilitation , 80(7), 528-535.
  3. Jutai, J., Ladak, N., Schuller, R., Naumann, S., & Wright, V. (1996). Outcomes measurement of assistive technologies: An institutional case study. Assistive Technology , 8.2, 110-120.
  4. Wielandt, T. & Strong, J. (2000). Compliance with prescribed adaptive equipment: A literature review. British Journal of Occupational Therapy , 63(2), 65-75.
  5. Burt, R., Migliore, G., & Timm, B. (2004, Nov. 5). Rehabilitation professionals in nationwide survey cite significant barriers to assistive technology transfer . Retrieved January 13, 2005 from http://www.goodshepherdrehab.org/news-events/index.asp
  6. Council on Rehabilitation Education (CORE). (1997). Accreditation manual . Retreived October 2004 from http://www.core-rehab.org
  7. Sax, C. (2002). Assistive technology online instruction: Expanding the dimensions of learning communities. In M. J. Scherer (Ed.) Assistive technology: Matching device and consumer for successful rehabilitation , (pp. 213-227). Washington, DC: APA Books.
  8. Sax, C. (2002). Assistive technology education: An online model for rehabilitation professionals. Disability and Rehabilitation, 24 (1-3), 144-151.
  9. Scherer, M.J. (1998). The Matching Person & Technology (MPT) Model Manual, third edition . Webster, NY: The Institute for Matching Person & Technology, Inc.
  10. Scherer, M.J. & Cushman, L.A. (2001). Measuring subjective quality of life following spinal cord injury: A validation study of the Assistive Technology Device Predisposition Assessment. Disability & Rehabilitation , 23(9), 387-393.
  11. Scherer, M.J. & Cushman, L.A. (2000). Predicting satisfaction with assistive technology for a sample of adults with new spinal cord injuries. Psychological Reports , 87 , 981-987.

ACKNOWLEDGMENT

This research was funded by the National Institutes of Health, National Institute of Child Health and Human Development, National Center for Medical Rehabilitation Research, through grant number HD38220 to The Institute for Matching Person & Technology, Inc.

CONTACT:

Caren Sax, Ed.D., CRC
San Diego State University Interwork Institute
3590 Camino del Rio North
San Diego, CA 92108
619-594-7183
csax@mail.sdsu.edu