            geront      Gerontologistgeront      The Gerontologist      The Gerontologist      0016-9013      1758-5341              Oxford University Press                    33510.1093/geront/43.3.335                        USE OF TECHNOLOGY                            A Comparison of Assistive Technology and Personal Care in Alleviating Disability and Unmet Need                                          Agree            Emily M.                    PhD                      1                                                          Freedman            Vicki A.                    PhD                      2                                      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@jhsph.edu                    6        2003            43      3      335      344                        16          9          2002                          25          4          2002                            The Gerontological Society of America        2003                    Purpose:The authors examine differences in reports of residual disability and unmet need by type of long-term care arrangement (assistive technology or personal care).Design and Methods:This study compares three specific dimensions of residual difficulty (pain, fatigue, and time intensity) and reports of unmet need across care arrangements. Samples from the U. S. 1994–1995 National Health Interview Survey Phase 2 Disability Supplements include adults with limitations in bathing, transferring, walking, and getting outside.Results:Even when differences in underlying disability are accounted for, assistive technology (AT) confers no additional benefit in the three dimensions of residual difficulty analyzed here. AT users equally or more often report that tasks are tiring, time consuming, or painful, even when they use assistance. Though this would appear to indicate unmet needs for care, fewer AT users report a desire for hands-on personal care.Implications:Though disability alleviation by technology is no better on specific dimensions of difficulty, technology users report less unmet need for personal care. Designing appropriate and cost-effective home care for adults with disabilities requires a better understanding of the ways in which technology users may differ from others and the circumstances under which technology can be most effective.                    Long-term care        Effectiveness         Activities of daily living                              hwp-legacy-fpage          335                          hwp-legacy-dochead          RESEARCH ARTICLE                                      Designing appropriate and cost-effective home care for adults with disabilities is a priority in aging societies. The number of older adults with disabilities is large and continues to grow, despite reductions in disability rates over the past two decades (Schoeni, Freedman, & Wallace, 2001). Currently, approximately 15% of the adult U. S. population, or 40 million people, are limited in activities as a result of a chronic health condition (Kaye, LaPlante, Carlson, & Wenger, 1996). The vast majority of adults with disabilities live in the community, and facilitating their ability to live independently is an increasingly important public health concern.      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.        In this article we hypothesize that different approaches to bridging disability may alleviate difficulty in different ways. We expect that assistive devices may alleviate difficulty by minimizing the pain associated with a task, whereas personal care may lessen the time and energy necessary to accomplish a task. Because devices increase an individual's capacity for self-care, we expect devices to be more effective than personal care in reducing unmet need.                    Methods              Data        Data are from the 1994 and 1995 Phase 2 Disability Supplements to the U. S. National Health Interview Survey, hereafter referred to as the NHIS-D2 (National Center for Health Statistics, 1998a, 1998b). These data provide detailed information on the use of assistive devices and environmental modifications for limitations in ADLs.        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      Assistive device use is quite common among persons who have underlying difficulty with the four activities considered here. Between 16% (of persons with underlying difficulty transferring) and 39% (of those who have underlying difficulty walking) use assistive technology alone to accommodate their difficulty (see Table 1). An additional 13–33% use assistive technology in combination with personal care. Taken together, 29–64% use one or more devices, with devices dominating most clearly in basic mobility activities (walking and going outside).      Those with underlying difficulty bathing or getting outside are slightly older on average (67 vs. 63 years). However, the distributions by sex, minority status, and education are similar across the samples, with a majority of people being female; approximately 16–17% are non-White, approximately 7% are Hispanic, and the majority have at least completed high school (∼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).      Among those who do use some type of assistance, those who use assistive devices alone report more moderate levels of underlying difficulty compared with those who use hands-on help (alone or in combination with assistive technology). Only 13–21% of those who use technology by itself state that they would be unable to perform the task without assistance, compared with 26–43% of those depending on personal care alone. As already noted, those who rely on both personal care and assistive technology report the greatest amount of difficulty, with 51–59% reporting that they would be completely unable to perform the task without assistance.      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 also investigated (not shown) whether the proportion who reported underlying difficulty on each of the three specific dimensions varied across care arrangements. We found that those using both personal care and assistive technology were generally more likely than those using either one alone to report that a task is very tiring, takes a long time, or is very painful when carried out without assistance. When we stratified by the level of underlying difficulty, we found a much weaker relationship between care arrangement and specific dimensions of underlying difficulty.      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.      The same general pattern is evident when the investigation is restricted to those with more severe activity limitations (bottom panel of Table 3), although the differences are statistically significant only for bathing. For many activities and dimensions of difficulty, especially pain, care arrangements are not significantly related to residual difficulty. However, in those cases in which a significant association is found, it is opposite to the expected direction—assistive technology users more often report that a task is tiring or takes a long time even when they use assistance.      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).      However, those using assistive technology alone are consistently less likely to state that they need any hands-on help, at levels as low or lower than for those who use no care. For bathing, levels of unmet need are highest, but the differences across types of care are minimal and not significant (significance tests not shown). For the three mobility-related ADLs, the differences between those who use personal care (either alone or in combination with assistive technology) and those who do not (using either assistive devices alone or no care at all) are substantial and consistently significant across levels of disability.              Discussion      Facilitating the ability to live and work independently in the community is a central goal for gerontologists, policymakers, and public health practitioners. Although it is difficult to measure optimal care arrangements for adults with disabilities (Jette & Keysor, 2002), the results presented here further our understanding of the relative effectiveness of assistive technology and personal care in alleviating difficulty with daily activities. They also provide insights into the conceptualization and measurement of unmet need.      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.                                      Prior versions of this article were presented in Syracuse, NY, at the Center for Policy Research Seminar Series in Aging, Labor, and Public Finance in October 2000 and in Washington, DC, at the Annual Meetings of the Population Association of America in March 2001. We acknowledge the able assistance of Jonas Marainen and Hakan Aykan in preparing the data and the tables, and Mary Alice Ernish for bibliographic assistance. We also thank Donna Strobino, Douglas Wolf, and Timothy Smeeding for their helpful comments. This work was supported by Grant R01-AG15135 from The National Institute on Aging.                          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                          Figure 1.                      Alleviating underlying disability through personal care and assistive technology                                              Figure 2.                      Percentage of those with difficulty on each activity of daily living who report that a task is tiring, time consuming, or painful without assistance (those who are completely unable to perform an activity are not included)                                              Figure 3.                      Percentage of those reporting an unmet need for hands-on care by type of assistance and activity. AT = assistive technology.                                                           Table 1.                                              Care Arrangements and Sample Characteristics.                                                                           Characteristic                Bathing (n = 3,493)                Transferring (n = 3,834)                Walking (n = 7,051)                Getting Outside (n = 3,542)                                                                    Care arrangement (%)                                                                                                                No care                25.8                50.1                40.0                23.3                                                AT only                20.5                15.9                39.2                31.0                                                Personal care only                24.6                20.6                6.3                13.1                                                Personal care and AT                29.2                13.4                14.5                32.7                                                Total                100.0                100.0                100.0                100.0                                            Age (mean; years)                67.7                62.6                63.8                66.9                                                % Female                63.5                61.2                60.4                64.2                                                % Non-White                16.5                16.2                16.7                17.9                                                % Hispanic                6.7                7.1                6.7                6.8                                            Education (%)                                                                                                                Primary only (0–7)                17.5                14.5                14.7                17.1                                                Some HS (8–11)                27.6                27.4                28.6                28.6                                                HS graduate (12)                32.6                33.5                33.4                32.5                                                Some college (13+)                22.3                24.7                23.2                21.8                                                Total                100.0                100.0                100.0                100.0                                                                        Note: AT = assistive technology; HS = high school.                                                            Table 2.                                              Underlying Global Difficulty by Type of Assistance and Activity.                                                                                          Type of Assistance                                             Activity                 None                AT Only                PC Only                PC and AT                                                                    Bathing (n = 3,493)*                                                                                                                Some difficulty                71.1                46.9                34.3                17.0                                                A lot of difficulty                23.4                32.4                22.5                23.8                                                Completely unable                5.6                20.7                43.2                59.2                                                Total                100.0                100.0                100.0                100.0                                            Transferring (n = 3,834)*                                                                                                                Some difficulty                78.8                50.0                48.8                20.1                                                A lot of difficulty                19.9                37.1                24.4                29.2                                                Completely unable                1.3                13.0                26.8                50.7                                                Total                100.0                100.0                100.0                100.0                                            Walking (n = 7,051)*                                                                                                                Some difficulty                66.0                39.7                39.3                15.7                                                A lot of difficulty                29.7                41.3                34.7                36.7                                                Completely unable                4.2                19.1                26.0                47.6                                                Total                100.0                100.0                100.0                100.0                                            Getting outside (n = 3,542)*                                                                                                                Some difficulty                66.0                37.5                28.1                11.3                                                A lot of difficulty                27.1                37.1                30.7                30.8                                                Completely unable                6.9                25.4                41.3                58.0                                                Total                100.0                100.0                100.0                100.0                                                                        Notes: Denominators are in parentheses. AT = assistive technology; PC = personal care.                                      *χ2 test significant at p <.05.                                                            Table 3.                                              Residual Difficulty on Specific Dimensions by Global Level of Underlying Difficulty and Type of Assistance.                                                                                                          Type of Assistance                                            Activity                                  n                                AT Only                PC Only                PC and AT                                                                                                    All With Underlying Difficulty                                                                            Bathing                                                Very tiring*                    (695)                74.9                55.1                66.0                                                Long time*                (709)                83.0                49.4                62.8                                                Very painful, ns                (490)                70.2                62.5                67.0                                            Transferring                                                                                                                Very tiring*                (694)                70.1                56.0                59.3                                                Long time*                (785)                76.2                57.0                57.3                                                Very painful, ns                (801)                82.4                79.1                76.9                                            Walking                                                                                                                Very tiring, ns                (1877)                80.1                77.0                76.6                                                Long time, ns                (1892)                83.0                78.9                78.5                                                Very painful, ns                (1531)                82.1                79.7                83.0                                            Getting outside                                                                                                                Very tiring*                (760)                86.7                78.2                77.2                                                Long time*                (766)                88.9                76.0                79.3                                                Very painful, ns                (617)                86.9                85.7                79.7                                                                            Those With a Lot of Underlying Difficulty                                                                                            Bathing                                                Very tiring*                (317)                76.3                60.2                70.3                                                Long time*                (332)                85.7                60.9                64.0                                                Very painful, ns                (222)                70.7                71.7                68.8                                            Transferring                                                                                                                Very tiring, ns                (326)                75.1                68.6                66.5                                                Long time, ns                (350)                78.7                72.1                63.7                                                Very painful, ns                (336)                87.6                88.4                84.9                                            Walking                                                                                                                Very tiring, ns                (1009)                85.4                87.1                82.7                                                Long time, ns                (1029)                87.2                86.6                85.8                                                Very painful, ns                (870)                85.1                87.0                86.1                                            Getting outside                                                                                                                Very tiring, ns                (410)                90.7                87.2                84.3                                                Long time, ns                (419)                87.5                85.3                85.1                                                Very painful, ns                (346)                86.3                85.6                83.5                                                                        Notes: Reported information is for those who use some type of assistance. Respondents who report they are completely unable to perform an activity are not included. AT = assistive technology; PC = personal care; ns = χ2 test not significant (p >.10).                                      *χ2 test significant at p <.05.                                                      References              Agree, E. M., 1999;. The influence of personal care and assistive technology on the measurement of disability. Social Science & Medicine,. 48:427-443.                    Agree, E. M., Freedman, V. A., 2000;. Incorporating assistive devices into community-based long-term care: An analysis of the potential for substitution and supplementation. Journal of Aging and Health,. 12:426-450.                    Albrecht, G. L., Devlieger, P. J., 1999;. The disability paradox: High quality of life against all odds. Social Science & Medicine,. 48:977-988.                    Allen, S. M., Foster, A., Berg, K., 2001;. Receiving help at home: The interplay of human and technological assistance. Journal of Gerontology: Social Sciences,. 56B:S374-S382.                    Allen, S., Mor, V., 1997;. The prevalence and consequences of unmet need—Contrasts between older and younger adults with disability. Medical Care,. 35:1132-1148.                    Andresen, E. M., Lollar, D. J., Meyers, A. R., 2000;. Disability outcomes research: Why this supplement, on this topic, at this time? Archives of Physical Medicine and Rehabilitation,. 81:(Suppl. 2), S1-S4.                    Arnstein, P., 2000;. The mediation of disability by self-efficacy in different samples of chronic pain patients. Disability and Rehabilitation,. 22:794-801.                    Arras, J., 1995;. Bringing the hospital home: Ethical and social implications of high tech home care. Baltimore: Johns Hopkins University Press.                    Chen, L. K., Mann, W. C., Tomita, M. R., Burford, T. E., 1998;. An evaluation of reachers for use by older persons with disabilities. Assistive Technology,. 10:(2), 113-125.                    Cohen, M. E., Marino, R. J., 2000;. The tools of disability outcomes research: Functional status measures. Archives of Physical Medicine and Rehabilitation,. 81:(Suppl. 2), S21-S29.                    Desai, M. M., Lentzner, H. R., Weeks, J. D., 2001;. Unmet need for personal assistance with activities of daily living among older adults. The Gerontologist,. 41:82-88.                    Eldar, R., 2000;. A conceptual proposal for the study of the quality of rehabilitation care. Disability and Rehabilitation,. 22:(4): 163-169.                    Gitlin, L. N., Corcoran, M., Winter, L., Boyce, A., Hauck, W. W., 2001;. A randomized, controlled trial of a home environmental intervention: Effect on efficacy and upset in caregivers and on daily function of persons with dementia. The Gerontologist,. 41:4-14.                    Gitlin, L. N., Levine, R., 1992;. Prescribing adaptive devices to the elderly: Principles for treatment in the home. International Journal of Technology and Aging,. 5:(1), 107-118.                    Grahn, B., Ekdahl, C., Borquist, L., 2000;. Motivation as a predictor of changes in quality of life and working ability in multidisciplinary rehabilitation. Disability and Rehabilitation,. 22:(15), 639-654.                    Hartke, R. J., Prohaska, T. R., Furner, S., 1998;. Older adults and assistive devices: Use, multiple device use, and need. Journal of Aging and Health,. 10:99-116.                    Heide, A. van der, Jacobs, J. W. G., Albada-Kuipers, G. A., van, Kraaimat, F. W., Geenen, R., Bijlsma, J. W. J., 1993;. Self-report functional disability scores and the use of devices: Two distinct aspects of physical function in rheumatoid arthritis. Annals of Rheumatic Diseases,. 52:497-502.                    Jette, A. M., Keysor, J. J., 2002;. Uses of evidence in disability outcomes and effectiveness research. The Milbank Quarterly,. 80:325-345.                    Kaye, S., LaPlante, M. P., Carlson, D., Wenger, B. L., 1996;. Trends in disability rates in the United States, 1970–1994 (National Institute on Disability and Rehabilitation Research Report). Washington, DC: U. S. Department of Health and Human Services.                    Kohn, J. G., LeBlanc, M., Mortola, P., 1994;. Measuring quality and performance of assistive technology. Assistive Technology,. 6:(2), 120-125.                    Mann, W. C., Hurren, D., Charvat, B., Tomita, M., 1996;. The use of phones by elders with disabilities: Problems, interventions, costs. Assistive Technology,. 8:23-33.                    Mann, W. C., Hurren, D., Tomita, M., 1993;. Comparison of assistive device use and needs of home-based older persons with different impairments. American Journal of Occupational Therapy,. 47:980-987.                    Mann, W. C., Hurren, D., Tomita, M., 1995;. Assistive devices used by home-based elderly persons with arthritis. American Journal of Occupational Therapy,. 49:810-820.                    Mann, W. C., Ottenbacher, K. J., Fraas, L., Tomita, M., Granger, C. V., 1999;. Effectiveness of assistive technology and environmental interventions in maintaining independence and reducing home care costs for frail elderly: A randomized controlled trial. Archives of Family Medicine,. 8:210-217.                    Manton, K., Corder, L., Stallard, E., 1993;. Changes in the use of personal assistance and special equipment from 1982 to 1989: Results from the 1982 and 1989 NLTCS. The Gerontologist,. 33:168-176.                    National Center for Health Statistics., 1998;. 1994 National Health Interview Survey on Disability, Phase I and II [CD-ROM Series 10, No. 8A]. Hyattsville, MD: U. S. Department of Health and Human Services.                    National Center for Health Statistics., 1998;. 1995 National Health Interview Survey on Disability, Phase I and II [CD-ROM Series 10, No. 10A]. Hyattsville, MD: U. S. Department of Health and Human Services.                    Norburn, J. E. K., Bernard, S., Konrad, T., Woomert, A., DeFriese, G., Kalsbeek, W., et al 1995;. Self-care and assistance from others in coping with functional status limitations among a national sample of older adults. Journal of Gerontology: Social Sciences,. 50B:S101-S109.                    Pope, A. M., Tarlov, A., (Eds.) 1991;. Disability in America: Toward a national agenda for prevention. Washington, DC: National Academy Press.                    Russell, J. N., Hendershot, G. E., LeClere, F., Howie, L. J., Adler, M., 1997;. Trends and differential use of assistive technology devices: United States, 1994 (Advance Data No. 292). Washington, DC: National Center for Health Statistics.                    Sanford, J. A., Arch, M., Megrew, M. B., 1995;. An evaluation of grab bars to meet the needs of elderly people. Assistive Technology,. 7:36-47.                    Schoeni, R., Freedman, V. A., Wallace, R., 2001;. Persistent, consistent, widespread, and robust? Another look at recent trends in old-age disability. Journal of Gerontology: Social Sciences,. 56B:S206-S218.                    Soldo, B. J., Freedman, V. A., 1994;. Care of the elderly: Division of labor among the family, the market, and the state. In S. Preston & L. G. Martin (Eds.), The demography of aging. Washington, DC: National Academy Press.                    Steinfeld, E., Shea, S. M., 1995;. Enabling home environments: Strategies for aging in place. Paper presented at the 48th Annual Scientific Meeting of The Gerontological Society of America, Los Angeles, CA.                    Tamm, M., 1999;. What does a home mean and when does it cease to be a home? Home as a setting for rehabilitation and care. Disability and Rehabilitation,. 21:49-55.                    Tennstedt, S., McKinlay, J., Kasten, L., 1994;. Unmet need among disabled elders: A problem in access to community long term care? Social Science and Medicine,. 38:915-924.                    Verbrugge, L. M., Jette, A. M., 1994;. The disablement process. Social Science and Medicine,. 38:1-14.                    Verbrugge, L., Rennert, C., Madans, J., 1997;. The great efficacy of personal and equipment assistance in reducing disability. American Journal of Public Health,. 87:384-392.                    Zimmer, Z., Chappell, N., 1994;. Mobility restriction and the use of devices among seniors. Journal of Aging and Health,. 6:(2), 185-208.                    Zimmer, Z., Chappell, N., 1999;. Receptivity to new technology among older adults. Disability and Rehabilitation,. 21:(5/6), 222-230.            