| HOME | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|---|
| ||||||||||||||||||||||||||||||||
Correspondence: Address correspondence to Emily M. Agree, PhD, Department of Population and Family Health Sciences, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Room E4014, Baltimore, MD 21205. E-mail: eagree{at}jhsph.edu
 |
Abstract |
|---|
 TOP Abstract MethodsResultsDiscussionReferences |
|---|
Key Words: Long-term care • Effectiveness • Activities of daily living
More than 75% of older adults with disabilities use some kind of assistive device, most often to assist with mobility (Russell, Hendershot, LeClere, Howie, & Adler, 1997), and the number has been growing over time (Manton, Corder, & Stallard, 1993; Russell et al., 1997). Devices are used both independently and in conjunction with personal caregiving services. However, the relative advantages of assistive technology and personal care are not well understood, in part because most studies evaluate one or the other, but rarely the two together.
Most research on assistive technology evaluates the efficacy and costs of specific devices (e.g., Chen, Mann, Tomita, & Burford, 1998; Gitlin & Levine, 1992; Kohn, LeBlanc, & Mortola, 1994; Mann, Hurren, Charvat, & Tomita, 1996; Sanford, Arch, & Megrew, 1995; Steinfeld & Shea, 1995), or it broadly examines the use of any assistive devices (Manton et al., 1993; Norburn et al., 1995; Zimmer & Chappell, 1994) or the number of devices used (Hartke, Prohaska, & Furner, 1998; Heide et al., 1993; Mann, Hurren, & Tomita, 1993). Studies of assistive technology emphasize the extent to which the acceptability and effectiveness of home-based technologies vary, depending on the training provided (Gitlin & Levine, 1992), the amount of stigma perceived by the user (Arras, 1995), and how much the introduction of assistive technologies transforms the home from a personal space to a health care delivery location (Tamm, 1999). Similarly, population-based efforts to understand the effectiveness of personal care arrangements often altogether exclude a consideration of self-care through assistive technology (Allen & Mor, 1997; Desai, Lentzner, & Weeks, 2001; Tennstedt, McKinlay, & Kasten, 1994). These studies instead focus on the trade-offs between formal and informal care or on the extent to which formal care can defer institutionalization (Soldo & Freedman, 1994).
Attempts to measure outcomes that reflect the effectiveness of interventions for disability are relatively new and differ depending on whether the goal is to evaluate rehabilitation services specifically or more general effects on the ability to live independently (Andresen, Lollar, & Meyers, 2000). A recent national study examined the effectiveness of assistive technology in terms of its impact on hours of personal care for older adults with disabilities, assuming that the decision to use devices is independent of the acquisition of caregivers (Allen, Foster, & Berg, 2001). This study found that those who use assistive technology also use fewer hours of personal care. Two additional small-scale experiments have evaluated the effectiveness of interventions to increase the use of assistive devices (Mann, Ottenbacher, Fraas, Tomita, & Granger, 1999) and environmental modifications for dementia (Gitlin, Corcoran, Winter, Boyce, & Hauck, 2001). Although sample sizes were small, both studies suggested that increased use of technology may slow functional declines, lower health care costs, and increase efficacy among some caregivers. However, none of these studies directly compare the effect of assistive technology and personal care on functional health. Two other nationally representative studies have evaluated the relative effectiveness of assistive technology and personal care in terms of reported reduction of disability (Agree, 1999; Verbrugge, Rennert, & Madans, 1997). Both studies found that the use of assistive technology was associated with greater reduction of overall levels of difficulty in either activities of daily living (ADLs) or mobility impairments when compared with personal care. Though each used distinct measures and different data sets, these studies both relied on broad judgments about levels of difficulty with tasks to determine effectiveness.
In sum, much of the prior research on this topic either has failed to directly compare outcomes related to assistive technology and personal care, begging the question as to when and whether each is most appropriately used (Allen et al., 2001; Gitlin et al., 2001; Mann et al., 1999), or has relied on global assessments of residual difficulty that do not offer insight into the mechanisms by which different care arrangements alleviate needs (Agree, 1999; Verbrugge et al., 1997).
The purpose of this study is to further investigate the relative effectiveness of assistive technology and personal care in alleviating disability among adults with difficulty in ADLs. Using nationally representative disability survey data, we compare three dimensions of disability for which both underlying and residual difficulty can be assessed—pain, fatigue, and time intensity—across different combinations of assistive technology and personal care use. We also examine reports of the need for hands-on assistance across care arrangements.
Framework
The conceptual framework of the disablement process (e.g., Pope & Tarlov, 1991; Verbrugge & Jette, 1994) gives us some foundation for understanding how different care arrangements may alleviate different dimensions of disability. In this framework, disability is socially defined, being the product of the individual's functional capacity, the demands of the physical and social environment, and his or her own expectations about daily life. Verbrugge and Jette (1994) make the additional important distinction between underlying difficulty—the level of difficulty without help or special equipment—and residual difficulty—that is, with whatever assistance is generally used.
Both underlying and residual disability encompass various levels of difficulty. At one extreme, an individual may be completely unable to carry out an activity without assistance; alternatively, an individual may be able to carry out an activity without assistance but with some or a lot of difficulty. The most commonly reported dimensions of difficulty in this context are pain and fatigue (Albrecht & Devlieger, 1999); tasks that are time consuming to carry out (or more time consuming than under usual or optimally functioning circumstances) may also be identified as being difficult. Closely related to residual difficulty is the concept of unmet need, that is, whether an individual thinks he or she requires more assistance.
The disabling effects of an impairment can be reduced or potentially eliminated in a number of ways (see Figure 1). Individuals may compensate for their disability by using personal care, they may alter their ability to carry out the task (through rehabilitation or device use), or they may alter the demands of the environment (through, e.g., a home modification). Each of these approaches may be adopted in isolation or may be combined into a more complex care arrangement. Compensation, because it involves the cooperation of one or more helpers, creates a state of dependency. In contrast, assistive technologies and related environmental modifications enhance independence either by expanding the capacity of the individual or reducing the demands of the environment.
|
|
Methods |
|---|
|
TOPAbstractMethodsResultsDiscussionReferences |
|---|
The U. S. NHIS is a nationally representative health survey of approximately 48,000 households (122,000 persons) conducted annually by the U. S. National Center for Health Statistics. The survey consists of a core questionnaire that collects health information and demographic background on every person in the household. Each year supplemental surveys on specific health topics are included. In 1994 and 1995, a supplement on disability was administered in two phases over approximately 3 years. Phase 1, administered at the same time as the NHIS core interview, collected basic measures of impairment and functional health from a designated individual about all household members.
Household members who were identified as disabled in Phase 1, using a broad definition of disability (the presence of any impairment, functional limitation, or disability), were interviewed in person 7–17 months later to obtain more detailed information (Phase 2). Separate questionnaires were administered to children (under 18) and adults (age 18 and older). Response rates were approximately 95% for the core and 87% for the supplements.
Sample Selection
To examine the effectiveness of care arrangements in alleviating disability, we focus on the adult population with underlying limitations in ADLs—those who report that they have difficulty carrying out an activity by themselves and without special equipment. This definition includes both persons currently using some form of care as well as a substantial number who report difficulty but make use of no personal care or assistive devices.
Because assistive devices tend to be task specific in response to disabling conditions (Agree & Freedman, 2000), analyses are conducted separately for samples reporting underlying difficulty with each of four daily activities: bathing or showering (n = 3,493), getting in or out of bed or chairs (n = 3,834), walking (n = 7,051), and getting outside (n = 3,542). Although respondents also were asked about difficulty with dressing, eating, and getting to or using the toilet, sample sizes were too small, and the use of assistive technology too rare in the case of dressing and eating, to analyze care arrangements for these activities. Respondents with multiple ADL difficulties may be in more than one sample.
Measures of Assistive Technology and Personal Care
Questions are asked about assistive technology in the ADL assessment section of the NHIS-D2 instrument. For each ADL, participants who answer that they use a special device or piece of equipment to perform a task are asked to name the type of technology that they use. Interviewers use a checklist to simplify the recording of answers. For the four activities we analyze here, the specific equipment includes hand bars or rails, and bath stools, seats, or chairs (bathing); canes, walkers, special cushions, lift chairs, a hospital bed, and a trapeze or sling (transferring); and canes, walkers, crutches, and wheelchairs (getting around indoors and going outside). An analysis of specific items was not possible because devices other than canes and walkers were not mentioned frequently enough to allow separate analyses. Grouping all assistive technologies for a given activity together also allowed us to include sample persons who reported using special equipment without providing a specific type.
Respondents also were asked in the same section whether they received hands-on help from another person with that activity. For each ADL, information was obtained on the type and amount of personal care provided to the respondent. On the basis of this information, we classified respondents into four groups: no care, assistive technology only, hands-on personal care only, and both personal care and assistive technology.
Level of Underlying Difficulty
Comparing the effectiveness of care arrangements requires some ability to control for the differential selection of these arrangements based on the severity of underlying disability. For each activity, respondents were classified as having some difficulty, a lot of difficulty, or being completely unable to carry out the activity without assistance. We also present analyses for all respondents and for the subgroup reporting a lot of underlying difficulty with a given task.
Measures of Effectiveness
The NHIS-D2 provides task-specific measures of residual difficulty and unmet need. The survey included information on three explicit dimensions of residual difficulty. For each activity, respondents (with the exception of those who were completely unable to perform the task) were asked to assess whether the activity is "very tiring," "takes a long time," or is "very painful" under two circumstances: first, if it is performed without personal care or assistive technology, and second, when it is performed with the assistance of personal care or devices (if used). This information was used to classify whether respondents' difficulty with an activity was "eliminated" when using personal care or assistive technology or whether they report residual difficulty even when using assistance. In addition, all respondents who reported underlying difficulty with a given task were asked whether they needed (more) hands-on help with that activity, which was used to derive a measure of unmet need.
Limitations of the Data
Although the NHIS-D is a rich source of information on the health and care arrangements of persons with disabilities in the United States, there are some limitations of the data that merit attention here. First, as already noted, the NHIS-D2 excludes the most severely disabled (those who report that they are unable to perform a task without assistance) from the questions about specific dimensions of underlying and residual difficulty, thus limiting our conclusions to a more moderately disabled population for those particular analyses. Second, the sensitivity of a disability measure to clinically detectable differences in functional status is an important factor in comparing across types of care (Cohen & Marino, 2000). In this study, the dichotomous indicators for each specific dimension of difficulty made it possible to examine effectiveness only in terms of complete elimination of difficulty. We are therefore limited in our ability to examine more refined gradations of effectiveness in disability reduction as has been done in previous studies (Agree, 1999; Verbrugge et al., 1997). Finally, the cross-sectional nature of the data make it impossible to assess the role that the timing of acquisition of assistive technology and personal care plays in the effectiveness of such arrangements.
As already noted, prior research has indicated that assistive technologies may be more effective than personal care in alleviating disability. Consequently, we expect in the following analyses to find that, when we control for the level of underlying need, those who use assistive devices are less likely than those using personal care to report (a) residual difficulty on all dimensions of disability and (b) unmet need for personal care.
Methods
Because the NHIS-D2 is not a simple random sample but instead has a complex design with geographic clustering, statistical tests have been adjusted to take into account the complex survey design. All estimates are weighted with analytic weights normed to the appropriate sample size. Results discussed in the text are statistically significant at the p <.05 level unless otherwise noted.
|
Results |
|---|
|
TOPAbstractMethodsResultsDiscussionReferences |
|---|
|
55%). Table 2 shows the distribution of the severity of underlying disability stratified by the type of care used for each of the four ADLs. This table confirms that the combination of care adopted is clearly related to the overall amount of underlying difficulty with the task. Those who use no care of any kind are the least disabled, with between 66% and 79% reporting some underlying difficulty and 1–7% reporting they are completely unable to carry out the activity without assistance (11–20% report some difficulty and 48–60% report being completely unable to carry out the activity).
|
Figure 2 shows for those with underlying difficulty in each of the four activities the proportion who also report underlying difficulty on three specific dimensions: whether the activity is very tiring, very painful, or takes a long time. The top panel shows estimates for all levels of difficulty, and the bottom panel is limited to those reporting a lot of underlying difficulty. For example, 63% of those with difficulty bathing say that they find the activity to be tiring when they do not have help or equipment. We find that substantial proportions of persons who report underlying difficulty with a given task find the activity very tiring, time consuming, or very painful when they do not have hands-on help or use equipment (47–76%, depending on the specific task). Not surprisingly, the proportions reporting underlying difficulty on each of the specific dimensions are consistently higher among those who report a lot of underlying difficulty on the task, ranging 59–88% on average for all activities.
|
We next examine reports of residual difficulty, using the same three dimensions (whether the task is tiring, time consuming, or painful) and controlling again for the level of underlying difficulty. As shown in the top panel of Table 3, among persons with underlying difficulty, those who use assistive technology alone report residual difficulty more often than those using personal care (with or without devices). This relationship is significant, however, only for two dimensions (whether the task is tiring or time consuming) and three of the tasks (bathing, transferring, and going outside). For example, among those who report underlying difficulty with bathing, 75% of assistive technology users report that the task is very tiring when they use their equipment, compared with only 55% of those who use personal care alone (p <.05). Pain varies the least across care arrangements and is not significantly related to the type of care for any of the activities.
|
Figure 3 shows the proportion of people reporting a need for hands-on help by activity and level of underlying severity of disability. The proportions shown here are consistent with those of other studies (e.g., Desai et al., 2001) and generally low in comparison with the reports of residual difficulty shown in Table 3. The proportions reporting a need for (more) hands-on help are consistent across levels of underlying disability and types of care (the highest levels are 12–18% reported by those with a lot of underlying difficulty and who use personal care alone).
|
|
Discussion |
|---|
|
TOPAbstractMethodsResultsDiscussionReferences |
|---|
Consistent with previous studies (Agree & Freedman, 2000; Manton et al., 1993; Verbrugge et al., 1997), we find that assistive devices are the most common means of managing day-to-day tasks for older adults and that the extent to which assistive technology and personal care are used in combination is closely related to the amount of difficulty reported. Unlike previous researchers, however, we compare across care arrangements reports of residual disability on specific dimensions such as fatigue, duration, and pain. We find that although adults with disabilities using only assistive technology tend to be less disabled than users of personal care, they are more likely to report that a task is tiring or time consuming when they use their equipment. We also find that users of assistive technology are less likely to report a need for any hands-on help than those already using personal care.
Our analysis is limited in several ways. We were unable to compare the effectiveness of care arrangements on specific dimensions for the most severely disabled; thus we cannot draw any conclusions about the relative efficacy of care arrangements for those unable to perform a task without assistance. Moreover, we were able to explore only the complete elimination—rather than the reduction—of disability. There are many reasons that devices, which require some physical and cognitive effort to use, might reduce overall difficulty more easily than personal care, but not completely eliminate it. Future research should consider the relative effectiveness of personal care and assistive technology both on specific dimensions and in finer gradations. Finally, we were unable to explore with these cross-sectional data the more dynamic acquisition process underlying the disablement process. For example, a long-term user of assistive technology may become more proficient and consequently more satisfied than one who has newly acquired the device. Surely this is a fruitful area for further exploration.
Despite these limitations, our analyses provide several new insights into the relative effectiveness of personal care and technology. First, the present study suggests a need to probe more deeply into the salient dimensions of disability that assistive technology and personal care alleviate. Using global measures of difficulty, prior research found that assistive technology appeared to be more effective than personal care in reducing or eliminating disability (Agree, 1999; Verbrugge et al., 1997). We find instead that users of such technology report similar or greater amounts of residual difficulty on the three specific dimensions of residual difficulty with ADL tasks in these data. These findings do not contradict earlier work, but rather inform it, by expanding our definition of effectiveness. Qualitative research may help identify the most important dimensions related to the effectiveness of different care arrangements. In one of the few studies to address this question, Albrecht and Devlieger (1999) report that pain and fatigue are among the most common problems reported, but further work illuminating the nature and meaning of these dimensions is warranted.
Second, we find that persons with more severe disabilities are more likely to use personal care and less likely to use assistive technology exclusively. At the same time, like Agree (1999), we show the relative effectiveness of personal care and assistive technology on specific dimensions appears to diminish at higher levels of disability. These findings suggest that selection according to underlying disability is critical to take into account in any comparisons of effectiveness across care arrangements. In prior work this selection may have artificially increased the benefit attributed to assistive technology relative to personal care. In this study, we find the disadvantage of such technology on specific dimensions of disability does not appear to be explained by the underlying severity of disability, which is lower among assistive technology users.
Third, the finding that assistive technology users less often report a need for hands-on help despite greater residual difficulty illustrates the likelihood that factors other than the severity of underlying disability influence the choice of care arrangements and must be attended to in both research and clinical practice. In particular, the use of assistive technology may be related to psychological factors such as receptivity, self-efficacy, and motivation, all of which have been shown to be related to the success of rehabilitative efforts (Arnstein, 2000; Grahn, Ekdahl, & Borquist, 2000; Zimmer & Chappell, 1999). Values related to autonomy and privacy also are important aspects of the acceptance and use of technology in rehabilitation and home care (Tamm, 1999).
Our findings also have implications for the conceptualization and measurement of unmet needs for care. Studies of unmet need have traditionally focused on personal care (Allen et al., 2001; Gitlin et al., 2001; Mann et al., 1999), finding, as we did here, quite low reported levels of unmet need, even among adults with severe disabilities. Such research may be missing a substantial amount of unmet need for assistance, were the concept more broadly defined to include needs for and use of assistive technology. Not only may there be unmet needs that can be better fulfilled by technology rather than personal care, but the findings from this study suggest that some proportion of the disabled population may have unmet needs but would not report a desire for personal care. Mann, Hurren, and Tomita (1995) reported that persons with arthritis expressed a need for additional devices, even describing new technologies to be invented. Including specific questions about the need for additional devices to patient assessments and survey instruments would contribute a great deal to our understanding of and interventions to reduce unmet needs.
In sum, indicators such as residual disability and unmet need do not in and of themselves allow us to identify the reasons that a particular care arrangement is more or less satisfactory. They do, however, make it possible to uncover circumstances in which types of care are less than optimal (Eldar, 2000). To meet the goal of facilitating the ability of adults to live and work independently in the community, it is essential for future research to explore the role of self-care more thoroughly. In particular, greater attention should be paid to identification of the different dimensions by which assistive technology and personal care alleviate difficulty and enhance independence.
|
Footnotes |
|---|
1 Department of Population and Family Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
2 Polisher Research Institute, Madlyn and Leonard Abramson Center for Jewish Life (formerly Philadelphia Geriatric Center), North Wales, PA.
Decision Editor: Laurence G. Branch, PhD
Received for publication April 25, 2002. Accepted for publication September 16, 2002.
|
References |
|---|
|
TOPAbstractMethodsResultsDiscussionReferences |
|---|
This article has been cited by other articles:
 |
|
 |
|
  M. Kitchener, T. Ng, H. Y. Lee, and C. Harrington Assistive Technology in Medicaid Home- and Community-Based Waiver Programs Gerontologist, April 1, 2008; 48(2): 181 - 189. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 N. E. Schoenberg, D. Shenk, and C. S. Kart Food for Thought: Nourishing the Publication of Qualitative Research Journal of Applied Gerontology, February 1, 2007; 26(1): 4 - 16. [Abstract] [PDF]
|
|
|
|
|
|
H. Meng, B. Friedman, A. W. Dick, B. R. Wamsley, G. M. Eggert, and D. Mukamel Effect of a Voucher Benefit on the Demand for Paid Personal Assistance Gerontologist, April 1, 2006; 46(2): 183 - 192. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Allen, L. Resnik, and J. Roy Promoting Independence for Wheelchair Users: The Role of Home Accommodations Gerontologist, February 1, 2006; 46(1): 115 - 123. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
V. A. Freedman, E. M. Agree, L. G. Martin, and J. C. Cornman Trends in the Use of Assistive Technology and Personal Care for Late-Life Disability, 1992-2001 Gerontologist, February 1, 2006; 46(1): 124 - 127. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. M. Kinney, C. S. Kart, L. D. Murdoch, and C. J. Conley Striving to Provide Safety Assistance for Families of Elders: The SAFE House Project Dementia, October 1, 2004; 3(3): 351 - 370. [Abstract] [PDF]
|
|
| ||||||||||||||||||||||||||||||||
| HOME | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|---|
