Human Factors and Employment Issues Related to the Use of ...
Human Factors and Employment Issues Related to the Use of Assistive Technologies
Brad Hedrick, Janet Reis, and Mark Newsom
University of Illinois at Urbana-Champaign
Allen W. Heinemann
Rehabilitation Institute of Chicago and Feinberg School of Medicine
Northwestern University
Theresa Louise-Bender Pape
Edward Hines Jr. VAH, The Rehabilitation Institute of Chicago and
Northwestern University’s Feinberg School of Medicine
July 2003
The work presented here was performed pursuant to a grant from the U.S. Social Security Administration (SSA) funded as part of the Disability Research Institute. The opinions and conclusions expressed are solely those of the author and should not be construed as representing the opinions or policy of SSA or any agency of the Federal Government.
Acknowledgement
The project investigators wish to thank Larry Manhiem, Marcia Scherer, and Mary Grace Kovar for their consultative assistance on the project’s methodology and instrumentation, and Bridget Smith and Scott Miskevics of Hines VA Medical Center for their assistance with data analysis. We also wish to thank Ron Flink and Frances Weaver of Edward Hines Jr. VA Hospital for their in-kind support of this project.
Table of Contents
Page
Abstract 4
Introduction 6
Methodology 9
Results 14
Discussion 37
References 42
Appendix: Survey Materials……………………………………………………………………… 45
Abstract
The purpose of this study was to examine the relationship between assistive technology (AT) cost, underwriting, ownership, employment history, and employer accommodations for individuals with spinal cord injury or disease (SCID). This study gathered information from two groups of working aged adults (18-64 years old) with SCID: one group of college educated adults, among whom 36% completed a Bachelor’s Degree and 64% completed at least some graduate school, and a second group of adults who had varied or mixed educational levels (35% had no college experience, 34% had completed some college, and 31% had completed at least a Bachelor’s Degree). Since there is currently no standardized method for gathering such information, the development of a survey instrument also became an important part of this project.
Overall, the present study suggests that assistive technologies are important for the employment success of individuals with SCID. The majority of the devices owned by the respondents were characterized as important to work, and devices identified as important to work were 3.5 times more expensive than other devices. The mean cost of AT devices was 68 to 124 percent greater for persons who were self-employed than for individuals in other areas of employment. Depending upon the individual’s underwriting resource options, this could be a substantial barrier to individuals for whom entrepreneurial work at home is the most viable employment option (i.e., individuals with more severe disabilities, individuals who have difficulty finding alternate transportation resources or routine medical appointments requiring time away from a “traditional” office setting, etc.). With regard to underwriting, individuals who were working for pay or who had worked for pay in the past five years were more likely to have purchased at least one assistive technology device for themselves as compared to individuals who had not worked in the past five years.
Education was found to be significantly related to employment status for both the college-educated group and the mixed-education level group. The college-educated adults were significantly more likely to be working at the time of interview or to have worked for pay in the past five years as compared to the mixed-education level adults (92% and 29%, respectively). In addition, the college-educated group reported owning significantly more assistive technology devices than the mixed-education group (5.19 devices and 4.19 devices, respectively).
Access to workplace accommodations appears to have been quite good for both groups, and AT satisfaction levels for all respondents were very high regardless of employment status and employment history. Further, most work place accommodations were reported to have already been at the work site or to have been implemented specifically for the respondent.
INTRODUCTION
Spinal cord injury or disease (SCID) constitutes a set of conditions that reflect a broad constellation of altered physiology, secondary medical complications and changed social roles, all of which influence activity participation (Weaver, Hammond, Guihan, & Hendricks, 2000). Estimates of national prevalence of SCID in the U.S. range from 250,000 to 400,000 individuals (National Spinal Cord Injury Statistical Center, 2001). Approximately 22% of these individuals are U.S. military veterans, of whom more than 40% were injured in military service (Berkowitz, Harvey, Green & Wilson, 1992; DeVivo, Black & Stover, 1993; DeVivo, Richards, & Go, 1991; Stover & Fine, 1987). Life expectancy of persons with SCID has improved dramatically, from 20-33 years in 1987 to 55-65 years in 1995 (when injury occurs at age 20) (DeVivo, et al., 1991; Frankel et al., 1998; Lasfargues, Custis, Morrone, Carswell, & Nguyen, 1995; Stover & Fine, 1987). Individuals most likely to incur SCID are young with many productive work force years ahead of them.
Assistive technologies (AT) have been reported to improve the functional independence of persons with disabilities, and to afford them a greater opportunity for societal participation and integration (Heinemann & Pape, 2001; Pape, Kim & Weiner, 2002). These technologies are designed to circumvent environmental barriers, maximize independence and increase activity participation among persons with physical disabilities resulting from SCID (Dittuno, Stover, Freed, & Ahn, 1992). Logically, the improvements in functional independence, societal participation and integration attributed to AT use should also serve to enhance the employability of persons with disabilities. However, little is known about the extent of AT use in the workplace and the role AT may play in reducing employment-related barriers and enhancing employment outcomes of persons with disabilities. If AT use is successful in reducing or removing these barriers, the potential cost savings realized by the Social Security Administration through successful efforts to facilitate beneficiaries’ return to work through AT use may prove to be considerable over time.
The current literature on assistive technology use and ownership is mainly focused on elderly persons with disabilities. When available, the research relevant to younger, working age individuals does not fully discuss the relationship of AT to issues of employment, cost, or life productivity outcomes. Very little has been published on the details of AT use in the workplace, and reliable standardized methods for gathering this information is not yet fully developed. Specifics about the cost of AT for persons with SCID, underwriters for the purchase of the devices, device repair history, underwriters for repairs and/or replacement of the devices, and related cost issues are also not easily obtainable or accessible. The cost information that is available relates to the treatment of SCID. And, although it is not directly related to the cost of using AT, this information provides a glimpse into the financial burdens faced by these individuals after injury. Treatment costs for individuals with SCID have been defined in the literature as direct costs including variables such as in-patient hospitalizations, out-patient services, physician services, equipment, medications, attendant care, supplies, environmental modifications, nursing homes, household assistance and vocational rehabilitation. Average treatment costs for the first year after injury was reported in 1995 to be as high as $300,000/injury (DeVivo, 1997). Recurring treatment charges ranged from $17,275 to $33,439 annually with a lifetime treatment cost of $969,659. Total direct treatment costs for individuals with spinal cord injury nationwide were reported to exceed seven billion dollars in 1995 (Botel, Glaser, Niedeggen & Meindl, 1997; Burnett, Cifu, Kolakowsky-Hayner, & Kreutzer, 2001; Cifu, Seel, Kreutzer & McKinley, 1999; DeVivo, 1997; Fiedler, Prakash, Maiman & Apple, 1999; Harvey, Wilson, Greene, Berkowitz & Stripling, 1992; Johnson, Brooks & Whiteneck, 1996; Stover & Fine, 1987). To paint an accurate picture of the total costs incurred, the costs of AT utilized after injury should be added to these overall treatment costs. The current study aims to identify the costs of AT utilized after injury and to investigate how employment outcomes, salary histories, productivity successes and quality of life issues relate to assistive technology use and costs.
Objectives
The purpose of this study was to examine the relationship between AT ownership, employment history, employer accommodations, AT costs and other factors for two complementary groups of working-aged adults with SCID.
Since there is currently no standardized method for gathering such information, a method needed to be developed and tested. In direct response to this need, the development of a survey instrument became an important part of this project. It is hoped that the questionnaire developed will be used, edited, and improved upon as a tool for systematically investigating the role of AT and its impact upon employment outcomes at the local, state, regional, and national levels. Furthermore, by identifying the cost of AT devices that are reported to contribute to a reduction in employment-related barriers and/or enhancing employment outcomes of persons with disabilities, the results of this study may inform policy makers as they discuss issues related to AT for working-aged individuals with disabilities. Results may also inform vocational rehabilitation agencies about additional return to work support options for these individuals.
Research Questions
The specific research questions addressed in this study were:
1. What are the types of AT devices owned by individuals with spinal cord injury or disease?
2. How much do these devices cost?
3. For individuals recently employed, does the cost of devices vary by disability severity, employer category or importance of the device to work?
4. Who underwrites the purchase and maintenance costs of the devices owned?
5. What are the specific AT devices identified as important to work?
6. Are there any unmet AT needs in terms of workplace accommodations, AT repair histories, and overall satisfaction with the devices owned?
METHODOLOGY
This study gathered information from two groups of working aged adults (18-64 years old) who reported living with spinal cord injury or disease. One group was comprised of college-educated adults, among whom 36% completed a Bachelor’s Degree and 64% completed at least some graduate school. These individuals were selected from a database at the University of Illinois at Urbana-Champaign’s Division of Rehabilitation-Education Services (DRES). The other group was comprised of adults who had varied or mixed educational levels (35% had no college experience, 34% had completed some college, and 31% had completed at least a Bachelor’s Degree). All individuals in the mixed educational level group were also U.S. veterans. The inclusion of veterans accommodated two critical methodological objectives. The first was to assess the relationship between AT ownership and employment among individuals with SCID who have more diverse educational histories, and the second was to compare their self-reported AT ownership and cost information to that recorded in the Veterans Administration’s National Prosthetic Patient Database (NPPD). This comparison allowed assessment of the accuracy of self-reported information as compared to the national database records. Four hundred veterans with service and non-service-related SCID were randomly selected from the Allocation Resource Center (ARC) cumulative list. This random selection was filtered to exclude: 1) nursing home residents, 2) veterans who were hospitalized a total of 90 days within the past calendar year, 3) veterans 65 years of age and older, and 4) individuals positively cross-referenced with the Burroughs death file. This list was finally cross-linked with the National Prosthetic Patient Database, from which 200 veterans were randomly selected.
Of the 170 college-educated adults with SCID selected from the DRES Student Database, valid addresses and phone numbers were available for 140. These 140 adults were subsequently contacted for an interview. Of the 140 college-educated adults contacted, 94 participated in the study, resulting in a 67% response rate. Of the 200 mixed educational level adults who were contacted, 101 agreed to be interviewed, resulting in a 51% response rate. Therefore, the overall project response rate was 59%.
Individuals in both groups were mailed a letter informing them that they would be contacted by telephone and that their participation in a telephone survey would be requested at that time. The survey was described as a study aimed at determining the impact of assistive technology upon employment and productivity for persons with SCID. The letter included a description of the efforts taken to maintain confidentiality and research subjects’ rights. In case additional questions or further information was needed, contact information for project investigators was also included in the letter.
Questionnaire Design
The questionnaire used in this study was constructed from multiple reference sources and is called the Assistive Technology and Employment Interview (ATEI). Once constructed, the questionnaire and other survey materials were pilot-tested (with 5 college-educated adults and 5 mixed educational level adults). Materials were revised as needed and are included in the appendix.
The ATEI questionnaire included two parts. Part I contained items measuring: overall health, assistive technology history, employment history, functional limitations, co-morbidities, productivity, life satisfaction and various demographic variables. The assistive technology history section was developed from ABLEDATA (National Institute on Disability and Rehabilitation Research, n.d.) and T.W. King’s Assistive Tech: Essential Human Factors (1999). The AT categories included: manual mobility and independent living devices (MMIL), powered mobility and independent living devices (PMIL), prosthetic and orthotic devices (P&O), assistive computer technology (ACT), assistive listening devices (ALD), assistive seeing devices (ASD) and augmentative and alternative communication devices (AACD). Each category was operationally defined and examples of specific devices were referenced for clarification purposes. Examples used were drawn from ABLEDATA as well as from the National Health Interview Survey 1990: AT Supplement (National Center for Health Statistics, 1990), and the National Health Interview Survey on Disability 1995-96 (National Center for Health Statistics, 1995). The National Health Interview Survey 1990: AT Supplement (National Center for Health Statistics, 1990) was also the basis for items developed to identify the funding sources for device procurement, repair and replacement.
Part II of the ATEI was the Device-Specific Report Form, completed for each device reportedly owned by a respondent. This portion of the instrument included items measuring: the category of the device, the type of device, the manufacturer and model of the device, the year the device was acquired, whether the person had worked since obtaining the device, the importance of the device to an individual’s work, the frequency of device use within various settings, satisfaction with the device, and the frequency of device repair and problems encountered in the use of the device.
Items developed to measure functional limitations were adapted from the National Health Interview Survey Series Series 10 Disability Follow-back Survey Adult Questionnaire, Sections G - P (pages 348-397) (National Center for Health Statistics, 1995). Items addressing restricted activity and hospitalization days were adapted from the National Health Interview Survey Series 10 Core Questionnaire (pages 137-159) (National Center for Health Statistics, 1995). Measurements of the presence and chronicity of co-morbidities were identified from the literature (Weaver, et al., 2000), and life satisfaction measures were obtained via the Satisfaction With Life Scale (Diener, Emmons, Larsen, & Griffin, 1985).
Data Analysis
Descriptive and comparative analyses were conducted for each cohort and subgroups when possible (i.e., when cell sizes were large enough). In addition, logistic regression models were created using AT as a predictor of employment and SSA benefits history to adjust for the potentially confounding influence of factors such as disability severity, health status, hospitalization, physical activity level, functional status, and the presence of co-morbidities.
Secondary data analyses were conducted on the Veterans Administration’s National Prosthetic Patient Database (NPPD) (Downs, 2000) and the Division of Rehabilitation-Education Services Student Database. As noted earlier, the NPPD analyses were included for methodological purposes in order to identify all AT devices purchased for the mixed educational level group by the Veterans Administration between 1997 and 2002, as well as repair and replacement histories of these devices over that same time period. Comparisons were made between these two information sources in order to assess the reliability and accuracy of self-reports. A similar methodological comparison was not possible for the college-educated group since there is no such national database available for these individuals.
Due to questions surrounding the accuracy of self-reported cost recall, the cost of the AT devices reported by all respondents was averaged across manufacturers of the product. If the respondent named the specific device, manufacturer and model number, the manufacturer was contacted to obtain a direct sale price. If the manufacturer did not sell directly to consumers, the average retail price of the device from five retailers was used as an estimate. In addition, for the mixed educational level group, the NPPD was used to identify the recorded Veterans Administration cost for the original device, all repairs, and replacement of each device reported as owned by the respondents. Since original cost data in the NPPD are only available from 1998 forward, comparative analyses excluded the 1997 data.
Human Subjects Involvement
Since it was necessary to initially include identifying information for respondents (i.e., names, addresses, telephone numbers), human subject’s institutional review board approval was obtained from the University of Illinois at Urbana-Champaign, the Veterans Administration, Rehabilitation Institute of Chicago and Northwestern University. Interviews began in April 2002 and were completed in August 2002. Secondary data were extracted from the NPPD in September 2002 after mixed educational level group interviews were completed and data files could be matched. There was no need to retain the identifying information once the databases were linked. Therefore, this information was purged from the final data files.
Definition of Assistive Technology
The definitions of assistive technology devices and services used in this study are the same as those first set forth in the 1988 Technology Related Assistance for Individuals with Disabilities Act.[1] This Act defined an assistive technology device as: [2]
“…any item, piece of equipment, or product system, whether acquired commercially off the shelf, modified, or customized, that is used to increase, maintain, or improve functional capabilities of individuals with disabilities.”
The Assistive Technology Act definition of an assistive technology service is:
Any service that directly assists an individual with a disability in the selection, acquisition, or use of an assistive technology device, including... evaluation of the needs of an individual... Purchasing, leasing, or otherwise providing for the acquisition by an individual with a disability of an assistive technology device. Selecting, designing, fitting, customizing, adapting, applying, maintaining, repairing, or replacing assistive technology devices; ...Training and technical assistance...
This AT definition has been widely used and adopted in each piece of legislation subsequent to the Assistive Technology Act and as related to persons with disabilities (e.g., IDEA, ADA).
RESULTS
Subject Characteristics
Demographics. A variety of demographic characteristics for each group are presented in Table 1. The mixed-education level adults were significantly older than the college-educated group (49 years old and 40 years old, respectively), were more likely to be male (96% and 71%, respectively), non-White (33% and 5%, respectively) and single (51% versus 45%, respectively). The two respondent groups were similar in regard to disability severity. Fifty-seven percent (n=53) of the college-educated group reported having paraplegia, or loss of function in the lower body and extremities resulting from an injury or dysfunction to a part of the spinal cord below the cervical section of the spine, and forty-three percent had tetraplegia or paralysis to the cervical region of the spine resulting in a loss of function in both the upper and lower extremities. The mixed-education level group was evenly split with regard to disability severity.
Overall, 75 percent of the mixed-education level adults (n=76) reported having less than $10,000 in annual personal income, compared to only 7 percent of the college-educated adults (n=7). Conversely, 51 percent of the college-educated adults (n=48) had personal salaries of $35,000 to $75,000, in contrast to 7 percent of the mixed-education level adults (n=7). A similar difference was observed for household income with 43 percent of the college-educated group (n=40) reporting household incomes in excess of $75,000, compared to only 16 percent of mixed-education level group (n=16).
Table 1
Demographic Variables for College-educated and Mixed-education Level
Respondents
|Demographic |College-educated |Mixed-Education |p value |
|Categories |(N=94) |(N=101) | |
|Mean Age |40.4 years |48.7 years |0.0001* |
| | | | |
| |College-educated |Mixed-education | |
| |% (n) |% (n) | |
|Education level |(N=94) |(N=100) |----- |
| ................
................
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