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The TechSAge Minimum Battery: A multidimensional and holistic assessment of individuals aging with long-term disabilities
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Original Article
The TechSAge Minimum Battery: A multidimensional and holistic assessment of individuals aging with long-term disabilities Elena T. Remillard a, *, Patricia C. Griffiths a, Tracy L. Mitzner a, Jon A. Sanford a, Brian D. Jones b, Wendy A. Rogers c a b c
Center for Inclusive Design and Innovation, Georgia Institute of Technology, Atlanta, GA, USA Interactive Media Technology Center, Georgia Institute of Technology, Atlanta, GA, USA College of Applied Health Sciences, University of Illinois Urbana-Champaign, Champaign, IL, USA
a r t i c l e i n f o
a b s t r a c t
Article history: Received 20 May 2019 Received in revised form 16 December 2019 Accepted 17 December 2019
Background: People with disabilities acquired in early to mid-life are living longer, contributing to growing numbers of older adults who are aging with disability, an understudied population likely to be underserved. Objectives: This paper demonstrates the usefulness of the TechSAge Minimum Battery as a holistic assessment of health for people aging with disabilities. Methods: Survey data of socio-demographic and health characteristics were collected from 176 older adults with long-term vision, hearing, and/or mobility disabilities. A series of descriptive and bivariate analyses were conducted to illustrate the heterogeneity of the sample. An in-depth analysis of the subsample with vision difficulty was conducted to highlight the tool’s value in assessing detailed contextual information for a specific disability. Results: Prevalence of health conditions (M ¼ 4.1; SD ¼ 2.5), prescription medications (M ¼ 4.1; SD ¼ 3.9), and serious functional difficulties (M ¼ 1.6; SD ¼ 0.85) indicated a fair degree of comorbidity, but with considerable variation in number and type among individuals. Subjective health ratings were high overall, but lower scores were correlated with additional comorbidities (r ¼ 0.31-0.40, p ¼<.001). Analyses of the subsample with vision difficulty demonstrated heterogeneity in functional capacity, degree of impairment, duration, and use of supportive aids. Conclusions: Findings highlighted the heterogeneity among people aging with disability and demonstrated the importance of capturing multi-dimensional factors inclusive of an individual’s capacity, context, and personal factors, which the Minimum Battery provides in an integrated assessment. Potential healthcare applications of the tool are discussed with implications for bridging aging and disability services. © 2019 Elsevier Inc. All rights reserved.
Keywords: Aging Disability Aging with disability Assessments Comorbidity
Introduction The number of older adults with disabilities has increased dramatically and will continue to grow as the world population ages.1,2 In the U.S., growing numbers of older adults with disabilities can be attributed to people who are either aging into disability due to late-life functional declines associated with “normal aging” or aging with disability living with the long-term effects of disabilities
* Corresponding author. Center for Inclusive Design and Innovation, Georgia Institute of Technology, 512 Means Street NW, Suite 300, Atlanta, GA, 30318, USA. E-mail address: [email protected] (E.T. Remillard).
acquired in early to mid-life.3,4 The latter represents a relatively new phenomenon of increased longevity for people with long-term disabilities that corresponds to advances in medicine and rehabilitation. An estimated 12e15 million Americans have a disability acquired prior to the age of 405; this aging population is understudied and likely underserved.4 Long-term disability has profound implications for the health and healthcare of older adults. Aging with long-term disability has been linked to secondary health conditions, such as pain, depression, and falls.3,6 Additionally, people with long-term disabilities are subject to normative, age-related health conditions (e.g., arthritis, mild cognitive impairment) and declines (e.g., in vision and hearing), which can create complex challenges for activities of
https://doi.org/10.1016/j.dhjo.2019.100884 1936-6574/© 2019 Elsevier Inc. All rights reserved.
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daily living.7e10 Adding to these challenges, a number of long-term health conditions (e.g., spinal cord injury, Multiple Sclerosis) are associated with “accelerated aging”, or the early onset of agerelated health conditions and impairments.11,12 Consequently, individuals with long-term disabilities are likely to experience increased disability for a longer period of time with greater unmet service needs than the general population.13 Aging vs. disability research There are substantial gaps in knowledge about the health needs of people aging with long-term disability, represented in Fig. 1 at the intersection of the aging and disability paradigms. Traditional research approaches to aging and disability have considered older adults and people with disabilities separately with distinct health-related needs defined by different constructs from the International Classification of Functioning, Disability and Health (ICF; 14); these differences have resulted in different intervention approaches, outcome goals, and scientific literatures. Age-specific research tends to focus on health conditions, with intervention approaches geared toward improving these conditions through medicine, surgery, or therapy. In contrast, rehabilitation and disability research primarily focuses on addressing impairments in body function and structure; common interventions, such as assistive technologies, aid individuals with a specific impairment in activity performance to facilitate participation. These differences have led to inconsistent definitions and measures that confound understanding and generalizability of health needs for people aging with disability. The great variation in how disability is defined and measured15 and the failure of population-based studies to assess disability duration or onset age provides limited opportunity to study subsamples of people aging with disability.16,17 There is a need for convergence in aging and disability measures to expand knowledge on the health needs of this understudied population.18 As a first step toward convergence, we developed the TechSAge Aging and Disability Model,9 which incorporates models of aging19,20 and disability14 to conceptualize differences in activity performance and participation between people who are aging or who have a disability and people who are aging and have a disability. The model depicts how people aging with disability are likely to have more environmental barriers and less access to effective facilitators, and ultimately experience
greater restrictions on activity and participation. TechSAge Minimum Battery Using the TechSAge Model as a conceptual framework, we developed the TechSAge Minimum Battery, the first self-report health questionnaire designed to provide a holistic understanding of the health and health needs of people aging with disability. The assessment was specifically designed for individuals aging with long-term vision, hearing, and mobility disabilities, coinciding with the 3 target populations of the RERC TechSAge project (Rehabilitation Engineering Research Center on Technologies to Support Agingin-Place for People with Long-Term Disabilities). Aging and disability measures of the Minimum Battery were strategically selected to map onto the basic ICF constructs,14 including health conditions, capacity (e.g., functional ability based on task performance in a range of daily activities), environmental context (e.g., use of supportive aids), and personal factors (e.g., demographics). The current paper presents a series of descriptive analyses that demonstrate the usefulness of the Minimum Battery in capturing the depth and complexity of health characteristics and support needs of people aging with disabilities. We provide aggregate and individual-level analyses of the overall sample to highlight the heterogeneity among people aging with disability. To illustrate the value of the Minimum Battery in gathering contextual information about a specific disability, we conducted an in-depth descriptive analysis of the subsample with vision difficulty as an example. Affecting nearly 7% of older Americans (ages 65þ), vision disability is associated with increased risk for a number of negative health outcomes (e.g., depression, hypertension, falls risk and injury, social isolation) that can compromise one’s ability to perform everyday activities and participate in society.22e24 As with other disabilities, the association between vision disability and health outcomes are numerous and complex, underscoring the importance of assessing broad aspects of health as in the Minimum Battery. Method Instrument The Minimum Battery is a self-report (168-item) questionnaire
Fig. 1. Conceptualization of the intersecting silos representing aging and disability research paradigms illustrating the knowledge gap for people aging with disability.
Please cite this article as: Remillard ET et al., The TechSAge Minimum Battery: A multidimensional and holistic assessment of individuals aging with long-term disabilities, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100884
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Table 1 Source materials included in the minimum battery. Components Personal Demographics
Subjective Health Health Condition
General Technology Experience Capacity Vision
Assessment
CREATE Demographic and Background Questionnaire27
Select questions; modified CREATE Demographic and Background Select 27 Questionnaire questions; modified Comorbidities and Age-Related Conditions among Select Persons with Spinal Cord Injury/Disease (SCI/D; 28) questions; Based on: Centers for Medicare and Medicaid modified Services29 30 Technology Experience Profile (TEP; ) Full; modified
U.S. Census Bureau American Community Survey (ACS) Disability Questions25 U.S. Health and Retirement Study (HRS) Vision Questions.31 Lighthouse International Functional Vision Screening Questionnaire32
Hearing
Speech, Spatial and Qualities of Hearing scale (SSQ12; 33)
Mobility
Late-Life Function and Disability Instrument: Function component34 Memory Issues Checklist35; modified from the Memory Functioning Questionnaire36
Cognition
Environment Vision
CATEA Consumer Network Registry Questionnaire37 National Health Interview Survey (NHIS) on Disability26
Hearing
CATEA Consumer Network Registry Questionnaire37 National Health Interview Survey (NHIS) on Disability26
Mobility
Version Used Description of Measures * denotes measure reported in current analysis
CATEA Consumer Network Registry Questionnaire37 National Health Interview Survey (NHIS) on Disability26
Full; modified Select questions; modified Select questions; modified Select questions; modified Full; modified Select questions; modified Select questions; modified Select questions; modified Select questions; modified Select questions; modified Select questions; modified Select questions; modified
*age, *education, occupational status, *income, *ethnicity, *housing type
*perceptions of health and health functioning (subjective health)
*presence of health conditions diagnosed by a health professional
frequency of use for 36 technologies in categories including: communication (e.g., phones), computers, everyday technology (e.g., microwaves), health care (e.g., pedometer), recreation (e.g., stereo) and transportation (e.g., GPS) functional capacity for *vision, *hearing, *ambulatory, self-care, *cognition, independent living) near and far distance visual ability
*functional vision problems (non-diagnostic screening questionnaire)
hearing abilities in various task-based situations
difficulty with various activities without assistance from other people or aids/ equipment frequency of different types of memory failures and perceptions of seriousness of forgetting
*use of vision assistive technology
*use of vision supportive aids
use of hearing assistive technology
use of hearing supportive aids
use of mobility assistive technology
use of lower and upper body supportive aids
Note. See technical report “TechSAge Minimum Battery: Overview of Measures”, for detailed information on source materials, modifications, and the complete set of questions.21
that is a compilation of measures including: demographics, health, vision/hearing/mobility functional abilities, technology use (general and assistive) and cognition (see Table 1). The questionnaire is available in paper and online versions and takes approximately 30e40 min to complete. A technical report with detailed information on source materials, modifications, and questions is available (link to ancillary material; 21). The Minimum Battery was not intended to produce a total score or to be validated as a whole. Wherever possible, sections of valid and reliable standardized population-based surveys were used to construct the Minimum Battery, such as disability questions from the U.S. Census Bureau’s American Community Survey and the National Health Interview Survey on (NHIS; 25, 26). In some cases, modifications were made to these measures to provide clarity, reduce redundancy, and standardize formatting. Where standardized instruments did not exist, we adapted instruments used in prior work, such as from the Center for Research and Education on
Aging and Technology Enhancement (CREATE) background questionnaire.27 To minimize participant burden, we selected the most pertinent items from source questionnaires. Original items were added to address knowledge gaps relevant to the TechSAge target populations, such as use of hearing assistive technologies (e.g., Video Relay Service, VideoPhone) for Deaf/hard of hearing participants. Measures reported in this paper Measures included in the current analysis are described here. For detailed information on all measures, see the technical report (link to ancillary material; 21). Demographics. Basic demographic information, including age, gender, race, education, and household income was derived from the CREATE Demographic and Background Questionnaire.27 Health. Three subjective health measures27 were used to rate
Please cite this article as: Remillard ET et al., The TechSAge Minimum Battery: A multidimensional and holistic assessment of individuals aging with long-term disabilities, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100884
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health in general (Global Subjective Health), “health in comparison to others their own age” on a five-point scale, ranging from “Poor” to “Excellent”, and “satisfaction with present health” on a 5-point scale where 0 is “Not at all” and 5 is “Extremely Satisfied”. This section included a 17-item checklist of health conditions from part one of the Comorbidities and Age-Related Conditions Questionnaire, developed to assess the presence of health conditions among people aging with spinal cord injury28; questions were originally based on the list developed by Medicare to assess chronic conditions among beneficiaries.29 Number of health conditions was used to develop a non-weighted, summary measure of comorbidity referred to as “Health Conditions” in the current analysis. Participants reported the total number of daily prescription medications they take (fill-the-blank question), creating a “Rx Medication” score that provides a comorbidity summary variable. Capacity. We assessed five domains of functional capacity, including four adapted from the U.S. Census Bureau’s American Community Survey (ACS; 25). These include having serious difficulty with the following: vision (seeing even when wearing glasses or contact lenses); hearing, mobility (walking or climbing stairs), and cognition (concentrating, remembering, or making decisions). Three questions were added as a measure of upper body capacity, including serious difficulty with: lifting ten pounds, reaching over one’s head, and using hands for writing, typing, or sign language. The domains were summed yielding a “serious difficulties” score ranging from 0 to 5, providing a non-weighted, summary subjective measure of comorbidity. Vision Functional Ability and Supportive Aids. Questions were adapted from the Lighthouse International Functional Vision Screening Questionnaire to assess level of difficulty (“0-none” to “5cannot do at all”) with 13 vision-related tasks.32 This section included a 10-item checklist of vision assistive technologies and supportive aids.26,37
Procedures The Minimum Battery was completed in 1 of 3 ways: 1) paper questionnaire mailed to participants with a self-addressed, prepaid return envelope; 2) screen-reader accessible online survey completed on a computer or tablet; 3) survey administered to a participant by a researcher or surrogate (i.e., family member). Data Analysis/Analytic Approach. To demonstrate the potential value of the Minimum Battery as a research tool, we report a systematically derived series of descriptive and bivariate analyses to highlight the heterogeneity of the TechSAge sample of people aging with disability and to illuminate the complexity and robustness of the data. Each successive analysis illustrates a different technique for using the dataset. 1. Sample Description. We conducted descriptive analyses of the socio-demographic characteristics and health measures of the sample, including means, standard deviations and percentages/ proportions of the aggregate data. 2. Visualization of Individual Health. Using individual-level health data, we developed a visual representation of the top and bottom deciles of the sample, in terms of the most and fewest numbers of serious difficulties, which demonstrates the multimorbidity and heterogeneity among sample. 3. Analysis of Global Health. We conducted descriptive and correlational analyses of overall subjective health based on global health and age-cohort comparisons to explore individual perceptions. 4. In-depth Analysis of Vision Subsample. We conducted in-depth analyses of the subsample of participants with vision difficulty as an example to illustrate how the Minimum Battery provides contextual information about a specific disability, including functional capacity, task-based performance difficulties, and use of supportive aids.
Participants A total of 176 TechSAge participants 50 years or older with motor, vision, and/or hearing disabilities completed the Minimum Battery. The convenience sample includes individuals who completed this assessment as a part of a TechSAge research study, focusing on three target populations (i.e., older adults with longterm vision, hearing, or mobility disabilities). The characteristics of the current sample reflected multiple studies with distinct designs and enrollment goals. Some studies focused solely on people aging with mobility disabilities, whereas others included participants multiple disability groups. Across studies, participants were at least 50 years old and had a self-identified vision, hearing, or mobility disability for at least 10 years. Vision participants self-identified as Blind or Low Vision, operationally defined as “unable to see” or “having serious difficulty seeing even when wearing glasses or contact lenses.” Hearing participants self-identified as Deaf or hard of hearing, “having serious difficulty hearing even when wearing a hearing aid or other hearing device” and using American Sign Language (ASL) as their primary language for communication. Mobility participants selfidentified as having a mobility disability, either “having serious difficulty walking or climbing stairs” or requiring use of a mobility aid. TechSAge studies collecting Minimum Battery data received approval from the Institutional Review Board (IRB) and all participants provided informed consent. IRB protocols and consent forms outlined how data are de-identified and made accessible to other TechSAge researchers. Participants were recruited through outreach to local and national disability resource organizations, as well as conferences, and word of mouth.
Results Sample Description Of the 176 individuals included in the analysis, 65% completed the Minimum Battery themselves and 35% had another person record their answers. On average, participants were 67 years old, ranging from age 51 to 83 (SD ¼ 6.2). The sample was predominately female (62.5%). Race distribution was 77.7% White/Caucasian, 16% African American, 2.3% multi-racial, and 3% as other. Almost 60% reported having a college degree or higher and 99% having at least a high school education. Nearly 95% lived in residential housing, including 67.7% in single-family homes. 45% of the sample was married. There was a mixed distribution across annual income brackets, with 27% reporting household earnings of less than $25,000 and 20% reporting $75,000 or higher. Total number of health conditions ranged from 0 to 12 with an average of 4.1 conditions (SD ¼ 2.5). Participants report taking between 0 and 22 daily prescription medications (M ¼ 4.1; SD ¼ 3.9) and an average of 1.6 serious functional difficulties (SD ¼ 0.85; Range 0e5). Distribution of reported serious difficulties were mobility (53%); upper body (40%); vision (40%); hearing (28.7%); and cognitive (6.5%). The prevalence of health conditions and serious functional difficulties among the sample indicated a fair degree of comorbidity and could suggest moderately poor health or function. Despite these health issues, most (84%) rated their health as good (52%) very good (7%) or excellent (25%) and claimed to be somewhat or extremely satisfied with their present health (70%).
Please cite this article as: Remillard ET et al., The TechSAge Minimum Battery: A multidimensional and holistic assessment of individuals aging with long-term disabilities, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100884
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Visualization of Individual Health
In-depth assessment of individuals with vision difficulty
Fig. 2 depicts data for participants reporting the greatest (top 10%) and least (bottom 10%) number of serious difficulties in the top and bottom sections of the figure, respectively. Data are sorted in descending order from most5 to least (0) number of serious difficulties. Each row represents a participant. For the 5 difficulty columns, a solid circle indicates serious difficulty (Yes), an open circle signifies “No”, and a blank cell indicates no response. The bars in the three left columns represent the magnitude of the comorbidity summary measures, including number of serious difficulties (0e5 index variable); health conditions (0e12 from list); and prescription medications. The absence of a bar indicates a zero value (e.g., no health conditions for ID 111), whereas a bar that extends the full length of the cell indicates the maximum sample value (e.g., 5 serious difficulties for ID 106). For participants reporting the greatest numbers of serious difficulties (top 10%; n ¼ 18), the average number was 3.4 (SD ¼ 0.61; Range 3e5). Mobility difficulty was reported among all participants, with upper body difficulty being the next most common, affecting all but two individuals. Participants in the top decile reported an average of 5.6 health conditions (SD ¼ 3.6; Range ¼ 0e12) and 7.2 daily prescriptions (SD ¼ 5.9; Range ¼ 0e22). Participant 106 represents the extreme example of comorbidity among the sample, reporting 5 serious difficulties, 10 health conditions, and 22 prescriptions. Participants with the least number of serious difficulties (bottom 10%; n ¼ 18) presented a very different picture. Serious difficulties ranged from 0 to 1 (M ¼ 0.8; SD ¼ 0.4), with 15 individuals reporting only 1. Participants reported an average of 3 health conditions (SD ¼ 1.7; Range 0e6) and 3.2 daily prescription medications (SD ¼ 2.3; Range ¼ 0e8). Vision and mobility were the most prevalent serious difficulties, reported by 9 and 4 individuals, respectively. Only 1 person reported serious difficulty in each of the hearing and cognitive domains; no one reported upper body serious difficulty. As the extreme example for the bottom decile, participant 163 reported no serious difficulties and only one health condition and daily prescription medication. The individual cases at the tails of the distribution of the index variable shed light on the potentially misleading nature of aggregated data when only unimodal measures of function, ability, or impairment are obtained. All three summary measures of comorbidity illustrated considerable comorbidity for those in the top decile of “serious difficulties” and more than double compared with the bottom, the former providing a glimpse of frailty and disability, the latter of relatively healthy aging.
Nearly 40% (n ¼ 69) of the overall sample reported serious difficulty seeing (85.5% of them reported difficulty seeing in both eyes). Mean age of onset for vision difficulty was 16 ± 17 years (n ¼ 66; 3 missing responses). On average, participants had vision difficulty for 50.9 years (SD ¼ 18.5). An average of 1.8 total serious difficulties was reported among the vision difficulty subsample (SD ¼ 0.95; Range 1e5). 49% reported other serious difficulties, including mobility (affecting 30% of the sample), followed by upper body (23%), hearing (17%), and cognition (7%). 51% of the vision subsample had no other comorbid difficulties. Although many participants had fairly high levels of functional capacity as measured by the level of difficulty on eight “standardized” tasks (Fig. 4), on average half of the sample reported they “cannot do” any of these tasks, ranging from 43% to 62% on each task. Nearly three-quarters of the sample had “a lot” of difficulty or “could not do” four of the eight tasks (i.e., reading a telephone directory, seeing street signs when crossing a street, reading medicine labels, reading prices when shopping), whereas more than 60% had “a lot of difficulty/could not do” three others. Reading your own mail was the task with the lowest percentage of participants who reported they cannot do it (43%), followed by seeing cars crossing the street (48%). “Quite a lot” of difficulty was least commonly reported for reading the large print headlines in the newspaper. Internal consistency of all 13 vision functional task items was high, as indexed by the Cronbach’s alpha (0.98). There was a significant difference in mean functional vision task difficulty scores between those who reported serious vision difficulty and those who did not (t68.86 ¼ 7.63, p < .001). On average, participants reported using 2.8 visual aids from the list of 10 specified types plus “other” (Range ¼ 0e7; SD ¼ 2.4); 6% reported using none. Over 70% used white canes and computer equipment (e.g., scanners, optical character recognition). The next most commonly used aids were audio description (65%), screen readers (58%) and Braille (46%). Most participants with serious vision difficulty rated their health as good (48%), very good, or excellent (36%), suggesting generally positive health perceptions among the subsample. Further analysis to cross-tabulate subjective health between those with and without vision difficulties (x2 1.7, 2, 0.42), failed to reveal a relationship between serious vision difficulties and global subjective health. However, a different picture emerged when factoring in one or more comorbidities. Fig. 5 shows the same trichotomized GSH variable analysis for the vision difficulty subsample grouped by number of comorbid difficulties: vision difficulty only, vision þ1 difficulty, vision þ2 or more difficulties. For those with vision þ1 or more difficulty, a significant relationship with GSH emerged (x2 25.2, 4, 0.000). Among participants with vision plus 2 or more serious difficulties, half rated their health as poor or fair and only 7% reported very good or excellent health. Conversely, the majority of those with only vision difficulty (56%) rated their health as very good or excellent. No participants reporting serious difficulty only with vision rated their health as poor or fair.
Analysis of Global Health Another aspect of health is perception; that is, how individuals perceive their health. We examined overall global subjective health and health compared to others (Fig. 3) and saw an optimistic picture of the sample, with 84% rating their overall health as “good”, “very good,” or “excellent” and 82% rating their health compared to others the same way. Bivariate correlations of the global subjective health (GSH) question with the other subjective health items confirmed the measures were related and reliable (p < .001); GSH was positively related to satisfaction with present health (r ¼ 0.62) and health compared to others (r ¼ 0.85). We conducted bivariate correlations of the GSH variable with the summary health variables: serious difficulties, health conditions, and Rx medications. GSH was negatively related (all p ¼ .001) to number of serious difficulties (r ¼ 0.40), health conditions (r ¼ 0.31), and prescription medications (r ¼ 0.38). Those with fewer difficulties, diagnoses, and/or fewer medications perceived their health as better.
Discussion We conducted a series of analyses to demonstrate the potential usefulness and value of the Minimum Battery as a research tool in exploring characteristics of people aging with disability. Consistent with the literature,3,7,22 the sample of older adults with long-term disabilities exhibited a fair degree of comorbidity overall, with regard to aggregate numbers of serious difficulties, health conditions, and prescription medications. The combination of these comorbidity factors, however, were highly individualized, with great
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Fig. 2. Illustration of the variation in comorbidities with regard to number of serious difficulties, health conditions, and prescription medications as well as type of serious difficulties for participants reporting the greatest and least number of serious difficulties.
variation in type and number among participants in the extreme ends of the distribution (i.e., those with most and least number of difficulties; Fig. 2). This finding underscored the remarkable heterogeneity in disability characteristics as well as the experience of disability among older adults with long-term disabilities as suggested by prior research.4,16,38 Despite the high prevalence of comorbid difficulties and conditions among the sample, global health findings were in concert with considerable evidence that older people tend to have and
maintain fairly high ratings of self-reported health.39 As depicted in Fig. 3, the majority of the sample rated their health in general as good or better, even in comparison to others own age. In line with prior research, many people aging with disability are resilient, maintaining a positive outlook and quality of life in spite of stress and disability-related challenges.40 However, this is not the case for all, as lower subjective health scores were correlated with other negative health indicators, including additional comorbid serious difficulties (Fig. 5).
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Fig. 3. Subjective health ratings.
Analyses of the subsample with vision difficulty (N ¼ 69) highlighted the value of capturing multi-faceted aspects of disability. For instance, although many participants reported “no” to “some” difficulty with the functional vision tasks (Fig. 4), roughly half of the sample reported they cannot do any of these tasks, suggesting they are likely blind. The subsample included participants who were intentionally recruited into TechSAge studies for being long-term blind or low vision, as well as participants with other types of long-term disabilities, who happen to also have vision difficulty; these groups have distinct experiences of vision disability and we would expect less variability in functional abilities among subgroups with similar characteristics (e.g., blind only, low vision only, those with similar durations of impairment). Nevertheless, the data underscored the potential variation in type, degree, and duration of vision impairment among older adults, and
demonstrated the value of assessing support needs on an individual basis as recommended in recent research on supporting individuals aging with disability.9,18,38 There are limitations to note about the TechSAge Minimum Battery and the current analyses. First, data are self-report, and therefore subject to potential participant bias, such as omissions or exaggerations, and cannot be independently verified. Notably, among those in bottom 10% of the sample in terms of “serious difficulties” (Fig. 2), we identified at least three legally deaf participants who responded “no” to the hearing difficulty question and two legally blind subjects who respond “no” to the vision question. It should be reiterated, that the question was phrased “Do you have serious difficulty [seeing, hearing, etc.]?”. These cases illustrate the value of assessing multi-faceted aspects of disability experience and paying close attention to language, given the subjective and
Fig. 4. Functional capacity for visual tasks among participants reporting with serious vision difficulty.
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Fig. 5. Global subjective health for participants reporting vision difficulty (N ¼ 69) grouped by number of comorbid difficulties.
highly personal nature of disability and health.15 Second, this was a cross-sectional study and we cannot determine causation among variables. In future work, the Minimum Battery could be collected longitudinally to assess trends among individuals and subsamples as well as trajectories of aging with disability. No strategic sampling efforts were made for the current dataset, which functions as a central repository for data collected in individual TechSAge studies. As such, the characteristics of the convenience sample reflect the variability of the individual studies and findings are not generalizable to the diverse population of people aging with disability. Despite efforts to enroll underrepresented groups, the sample is predominately white/Caucasian with high education. For individuals in minority populations, and particularly those with low education, we would expect the impact of disability on everyday activities to be greater due to known health disparities and limited access to supportive services.41 Although the Minimum Battery represents a sampling of key measures, the length of the survey is a limitation. A streamlined version of the Minimum Battery with fewer questions could be developed to facilitate use among broader audiences, such as clinicians. At the same time, no questionnaire is fully comprehensive, and there were gaps in the assessment that are relevant to the goal of understanding the experience of aging with a disability such as depression, falls, and use of emerging technologies. We are refining the assessment to eliminate unnecessary items and incorporate additional measures of interest for version 2.0.
Conclusions As a compilation of multi-dimensional measures of aging and disability, the TechSAge Minimum Battery provides an integrated assessment method to gain a holistic understanding of people aging with disability. The current paper presented a series of analyses that demonstrated the multi-morbidity and heterogeneity among individuals aging with disability. Analyses of the subsample with vision difficulty revealed the depth of contextual information about a specific disability (e.g., capabilities, limitations, and support needs) that can be realized through the Minimum Battery. Detailed insights are available in the data set for other subsamples (e.g., persons with mobility and hearing difficulties). The Minimum Battery was designed to focus on the individual. Among the current sample, the only common thread between certain participants may be having a disability for a prolonged period of time, with all other factors being unique. Research all too often focuses on aggregates and averages, which can be particularly
misleading in describing older adults with disabilities, given the potential for heterogeneity and the likelihood for multi-morbidities as we observed in our dataset. In essence, the Minimum Battery replicates what a clinician would do, collecting an array of relevant information about an individual (N ¼ 1) to better understand their unique health characteristics and support needs. The bridging of aging and disability measures, as in the Minimum Battery, holds potential to expand the knowledge base about individuals aging with disability, ultimately advancing innovation, practice, and service delivery to better meet the needs of this growing population.7,18,42 In RERC TechSAge, we are using the Minimum Battery to inform the development of new technologies and environmental solutions for people aging with disability as well as to assess the impact of technology interventions and to understand potential factors underlying their use or adoption. The Minimum Battery could also be used to identify targeted interventions for an individual based on the multi-faceted data on sensory and mobility capabilities and current technology use and experience. The integrated collection of aging and disability measures represented in the Minimum Battery could be especially useful to provide insights for professionals in allied health and social work, who are often on the front lines of helping individuals navigate between the silos of aging and disability resources. Funding The contents of this publication were developed under a grant from the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR grant number 90REGE0006-0100) under the auspices of the Rehabilitation and Engineering Research Center on Technologies to Support Aging-in-Place for People with Long-Term Disabilities (RERC TechSAge; www.rerctechsage. org). NIDILRR is a Center within the Administration for Community Living (ACL), Department of Health and Human Services (HHS). Disclaimer The contents of this publication do not necessarily represent the policy of NIDILRR, ACL, or HHS, and you should not assume endorsement by the Federal Government. Prior presentation The current manuscript represents the first article submitted for publication on The Minimum Battery. The questionnaire was
Please cite this article as: Remillard ET et al., The TechSAge Minimum Battery: A multidimensional and holistic assessment of individuals aging with long-term disabilities, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100884
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highlighted in a brief (10 min) presentation as part of the RERC TechSAge annual symposium at the 2018 Gerontological Society of America conference in Boston, MA; a 1 paragraph abstract was published online in the society’s online publication Innovation in Aging (https://academic.oup.com/innovateage/article/2/suppl_1/ 624/5171443). The conference presentation provided a high-level overview of the Minimum Battery and did not include data reported in the current analysis. Declaration of competing interest The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Acknowledgements The authors would like to thank Sara Bowman and other members of the TechSAge research team for their contributions to the development of the Minimum Battery as well as Sarah Melgen for her assistance with graphic design. References 1. GBD 2015 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1545e1602. https://doi.org/ 10.1016/S0140-6736(16)31678-6. 2. Institute of Medicine. The Future of Disability in America. Washington, DC: The National Academies Press; 2007. 3. Field M, Jette A. Secondary conditions and aging with disability. In: Field M, Jette A, eds. The Future Of Disability In America (136e161). Washington, DC, USA: The National Academies of Science Press; 2007. ISBN 978-0-309-10472-2. 4. Verbrugge LM, Yang L. Aging with disability and disability with aging. J Disabil Policy Stud. 2002;12:253e267. https://doi.org/10.1177/104420730201200405, 2002. 5. LePlante MP. Key goals and indicators for successful aging with early-onset disability. Disabil Health J. 2014:S44eS50. https://doi.org/10.1016/ j.dhjo.2013.08.005. 6. Molton IR, Terrill AL, Smith AE, et al. Modeling secondary conditions in adults aging with physical disability. J Aging Health. 2014;26(3):335e359. https:// doi.org/10.1177/0898264313516166. 7. Campbell ML, Putnam M. Reducing the shared burden of chronic conditions among persons aging with disability and older adults in the United States through bridging aging and disability. Healthcare. 2017;5:56. https://doi.org/ 10.3390/healthcare5030056. 8. Czaja SJ, Boot WR, Charness N, Rogers WA. Designing for Older Adults: Principles and Creative Human Factors Approaches. third ed. Boca Raton, FL: CRC Press; 2019. 9. Mitzner TL, Sanford JA, Rogers WA. Closing the capacity-ability gap: using technology to support aging with disability. Innov Aging. 2018;2(1):1e8. https://doi.org/10.1093/geroni/igy008. 10. Preusse KC, Gonzalez ET, Singleton JL, Mitzner TL, Rogers WA. Understanding the needs of individuals ageing with impairment. Int J Hum Factors Ergon. 2016;4:144e168. 11. Groah SL, Charlifue S, Tate D, et al. Spinal cord injury and aging: challenges and recommendations for future research. Am J Phys Med Rehab. 2012;91:80e93. https://doi.org/10.1097/PHM.0b013e31821f70bc. 12. Stern M, Sorkin L, Milton K, Sperber K. Aging with multiple sclerosis. Phys Med Rehabil Clin N Am. 2010;21:403e417. https://doi.org/10.1016/ j.pmr.2009.12.008. 13. Campbell ML, Sheets D, Strong PS. Secondary health conditions among middleaged individuals with chronic physical disabilities: implications for unmet needs for services. Assist Technol. 1999;11(2):105e122. https://doi.org/ 10.1080/10400435.1999.10131995. 14. World Health Organization. International Classification of Functioning, Disability and Health. Geneva, Switzerland: World Health Organization; 2001. Retrieved from http://www.who.int/classifications/icf/en/. 15. Verbrugge LM. Disability experience and measurement. J Aging Health. 2016;28(7):1124e1158. https://doi.org/10.1177/0898264316656519. 16. Freedman VA. Research gaps in the demography of aging with disability. Disabil Health J. 2014;7:S60eS63.
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17. Putnam M, Molton IR, Truitt AR, Smith AE, Jensen MP. Measures of aging with disability in U.S. secondary data sets: results of a scoping review. Disabil Health J. 2016;9:5e10. https://doi.org/10.1016/j.dhjo.2015.07.002. 18. Putnam M. Bridging network divides: building capacity to support aging with disability populations through research. Disabil Health. 2014;7:S51eS59. https://doi.org/10.1016/j.dhjo.2013.08.002. 19. Lawton MP, Nahemow L. Ecology and the aging process. In: Eisdorfer C, Lawton MP, eds. Psychology of Adult Development and Aging. Washington, DC: American Psychological Association; 1973:619e674. 20. World Health Organization. World Report on Ageing and Health. Geneva, Switzerland: World Health Organization; 2015. Retrieved from http://apps. who.int/iris/bitstream/10665/186463/1/9789240694811_eng.pdf?ua¼1. 21. Gonzalez ET, Mitzner TL, Sanford JA, Rogers WA. TechSAge Minimum Battery: Overview Of Measures (TechSAge-TR-1601). Atlanta, GA: Georgia Institute of Technology, Rehabilitation Engineering Research Center on Technologies to Support Successful Aging with Disability; 2016. 22. Erickson W, Lee C, von Schrader S. Disability Statistics from the American Community Survey (ACS). Ithaca, NY: Cornell University Yang-Tan Institute (YTI); 2017. Retrieved from Cornell University Disability Statistics website www.disabilitystatistics.org. 23. Crews & Campbell. Health conditions, activity limitations, and participation restrictions among older people with visual impairments. J Vis Impair Blind (JVIB). 2001;95(8):453e467. https://doi.org/10.1177/0145482X0109500802. 24. Steinman. Health outcomes associated with self-reported vision impairment in older adults. J Vis Impair Blind (JVIB). 2016;110(6):385e398. 25. Brault MW, U.S. Census Bureau. Review of changes to the measurement of disability in the 2008 American Community Survey. Retrieved from http:// www.census.gov/people/disability/files/2008ACS_disability.pdf; 2009. 26. Hendershot GE, Larson S, Lakin KC. An overview of the national health Interview survey on disability. In: Altman BM, Barnartt SN, Hendershot GE, Larson SL, eds. Research in Social Science and Disability, Volume 3: Using Survey Data to Study Disability: Results from the National Health Interview Survey on Disability. Oxford: Elsevier; 2003:9e40. 27. Czaja SJ, Charness N, Fisk AD, et al. Factors predicting the use of technology: findings from the center for research and education on aging and technology enhancement (CREATE). Psychol Aging. 2006;21:333e352. 28. Tate DG, Charlifue S, Forchheimer M, et al. Comorbidities and age related conditions among persons with spinal cord injury/disease (SCI/D). Arch Phys Med Rehabil. 2015;96(10):e49. 29. Centers for Medicare and Medicaid Services. Chronic Conditions Among Medicare Beneficiaries Chartbook 2012 Edition. 2012 (Baltimore, MD). 30. Barg-Walkow LH, Mitzner TL, Rogers WA. Technology Experience Profile (TEP): Assessment And Scoring Guide (HFA-TR-1402). Atlanta, GA: Georgia Institute of Technology, School of Psychology, Human Factors and Aging Laboratory; 2014. 31. Crews JE, Lollar DJ, Kemper AR, et al. The variability of vision loss assessment in federally funded sponsored surveys: seeking conceptual clarity and comparability. Am J Ophthalmol. 2012;154:S31eS44. 32. Horowitz A, Teresi JE, Cassels LA. Development of a vision screening questionnaire for older people. J Gerontol Soc Work. 1991;17:37e56. 33. Noble W, Jensen NS, Naylor G, Bhullar N, Akeroyd MA. A short form of the Speech, Spatial and Qualities of Hearing scale suitable for clinical use: the SSQ12. Int J Audiol. 2013;52(6):409e412. 34. Haley SM, Jette AM, Coster WJ, et al. Late-life function and disability instrument: II. Development and evaluation of the function component. J Gerontol: Med Sci. 2002;57A(4):M217eM222. 35. Prakash A, Mostafa A, Mitchell DB, Rogers WA. Understanding older adults’ health and social memory needs in the home. In: Proceedings of the Human Factors and Ergonomics Society 58th Annual Meeting. Santa Monica, CA: HFES; 2014:155e159. 36. Gilewski M, Zelinski E, Schaie K. The Memory Functioning Questionnaire for assessment of memory complaints in adulthood and old age. Psychol Aging. 1990:482e490. 37. Choi YM, Sabata D, Todd R, Sprigle S. Building a consumer network to engage users with disabilities. In: Langdon P, Clarkson J, Robinson P, eds. Designing Inclusive Futures (55-62). London: Springer; 2008. 38. Iezonni LI. Policy concerns raised by the growing U.S. Population aging with disability. Disabil Health J. 2014;7(10):S64eS68. https://doi.org/10.1016/ j.dhjo.2013.06.004. 39. Diener E, Suh E. Subjective well-being and age: an international analysis. In: Schaie KW, Lawton MP, eds. Annual Review of Gerontology and Geriatrics. New York: Springer; 1997:304e324, 1997. 40. Terrill AL, Molton IR, Ehde DM, et al. Resilience, age, and perceived symptoms in persons with long-term physical disabilities. J Health Psychol. 2016;21(5): 640e649. 41. Meeting the unique needs of minorities with disabilities. In: Leung P, Wright TJ, eds. A Report to the President and the Congress. Washington, D.C.: National Council on Disability; 1993. 42. Molton IR, Ordway A. Aging with disability: populations, programs, and the new paradigm. Introd Spec Issue. 2019;31(10s):3Se20S. https://doi.org/ 10.1177/0898264319880120.
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Original Article
The TechSAge Minimum Battery: A multidimensional and holistic assessment of individuals aging with long-term disabilities Elena T. Remillard a, *, Patricia C. Griffiths a, Tracy L. Mitzner a, Jon A. Sanford a, Brian D. Jones b, Wendy A. Rogers c a b c
Center for Inclusive Design and Innovation, Georgia Institute of Technology, Atlanta, GA, USA Interactive Media Technology Center, Georgia Institute of Technology, Atlanta, GA, USA College of Applied Health Sciences, University of Illinois Urbana-Champaign, Champaign, IL, USA
a r t i c l e i n f o
a b s t r a c t
Article history: Received 20 May 2019 Received in revised form 16 December 2019 Accepted 17 December 2019
Background: People with disabilities acquired in early to mid-life are living longer, contributing to growing numbers of older adults who are aging with disability, an understudied population likely to be underserved. Objectives: This paper demonstrates the usefulness of the TechSAge Minimum Battery as a holistic assessment of health for people aging with disabilities. Methods: Survey data of socio-demographic and health characteristics were collected from 176 older adults with long-term vision, hearing, and/or mobility disabilities. A series of descriptive and bivariate analyses were conducted to illustrate the heterogeneity of the sample. An in-depth analysis of the subsample with vision difficulty was conducted to highlight the tool’s value in assessing detailed contextual information for a specific disability. Results: Prevalence of health conditions (M ¼ 4.1; SD ¼ 2.5), prescription medications (M ¼ 4.1; SD ¼ 3.9), and serious functional difficulties (M ¼ 1.6; SD ¼ 0.85) indicated a fair degree of comorbidity, but with considerable variation in number and type among individuals. Subjective health ratings were high overall, but lower scores were correlated with additional comorbidities (r ¼ 0.31-0.40, p ¼<.001). Analyses of the subsample with vision difficulty demonstrated heterogeneity in functional capacity, degree of impairment, duration, and use of supportive aids. Conclusions: Findings highlighted the heterogeneity among people aging with disability and demonstrated the importance of capturing multi-dimensional factors inclusive of an individual’s capacity, context, and personal factors, which the Minimum Battery provides in an integrated assessment. Potential healthcare applications of the tool are discussed with implications for bridging aging and disability services. © 2019 Elsevier Inc. All rights reserved.
Keywords: Aging Disability Aging with disability Assessments Comorbidity
Introduction The number of older adults with disabilities has increased dramatically and will continue to grow as the world population ages.1,2 In the U.S., growing numbers of older adults with disabilities can be attributed to people who are either aging into disability due to late-life functional declines associated with “normal aging” or aging with disability living with the long-term effects of disabilities
* Corresponding author. Center for Inclusive Design and Innovation, Georgia Institute of Technology, 512 Means Street NW, Suite 300, Atlanta, GA, 30318, USA. E-mail address: [email protected] (E.T. Remillard).
acquired in early to mid-life.3,4 The latter represents a relatively new phenomenon of increased longevity for people with long-term disabilities that corresponds to advances in medicine and rehabilitation. An estimated 12e15 million Americans have a disability acquired prior to the age of 405; this aging population is understudied and likely underserved.4 Long-term disability has profound implications for the health and healthcare of older adults. Aging with long-term disability has been linked to secondary health conditions, such as pain, depression, and falls.3,6 Additionally, people with long-term disabilities are subject to normative, age-related health conditions (e.g., arthritis, mild cognitive impairment) and declines (e.g., in vision and hearing), which can create complex challenges for activities of
https://doi.org/10.1016/j.dhjo.2019.100884 1936-6574/© 2019 Elsevier Inc. All rights reserved.
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daily living.7e10 Adding to these challenges, a number of long-term health conditions (e.g., spinal cord injury, Multiple Sclerosis) are associated with “accelerated aging”, or the early onset of agerelated health conditions and impairments.11,12 Consequently, individuals with long-term disabilities are likely to experience increased disability for a longer period of time with greater unmet service needs than the general population.13 Aging vs. disability research There are substantial gaps in knowledge about the health needs of people aging with long-term disability, represented in Fig. 1 at the intersection of the aging and disability paradigms. Traditional research approaches to aging and disability have considered older adults and people with disabilities separately with distinct health-related needs defined by different constructs from the International Classification of Functioning, Disability and Health (ICF; 14); these differences have resulted in different intervention approaches, outcome goals, and scientific literatures. Age-specific research tends to focus on health conditions, with intervention approaches geared toward improving these conditions through medicine, surgery, or therapy. In contrast, rehabilitation and disability research primarily focuses on addressing impairments in body function and structure; common interventions, such as assistive technologies, aid individuals with a specific impairment in activity performance to facilitate participation. These differences have led to inconsistent definitions and measures that confound understanding and generalizability of health needs for people aging with disability. The great variation in how disability is defined and measured15 and the failure of population-based studies to assess disability duration or onset age provides limited opportunity to study subsamples of people aging with disability.16,17 There is a need for convergence in aging and disability measures to expand knowledge on the health needs of this understudied population.18 As a first step toward convergence, we developed the TechSAge Aging and Disability Model,9 which incorporates models of aging19,20 and disability14 to conceptualize differences in activity performance and participation between people who are aging or who have a disability and people who are aging and have a disability. The model depicts how people aging with disability are likely to have more environmental barriers and less access to effective facilitators, and ultimately experience
greater restrictions on activity and participation. TechSAge Minimum Battery Using the TechSAge Model as a conceptual framework, we developed the TechSAge Minimum Battery, the first self-report health questionnaire designed to provide a holistic understanding of the health and health needs of people aging with disability. The assessment was specifically designed for individuals aging with long-term vision, hearing, and mobility disabilities, coinciding with the 3 target populations of the RERC TechSAge project (Rehabilitation Engineering Research Center on Technologies to Support Agingin-Place for People with Long-Term Disabilities). Aging and disability measures of the Minimum Battery were strategically selected to map onto the basic ICF constructs,14 including health conditions, capacity (e.g., functional ability based on task performance in a range of daily activities), environmental context (e.g., use of supportive aids), and personal factors (e.g., demographics). The current paper presents a series of descriptive analyses that demonstrate the usefulness of the Minimum Battery in capturing the depth and complexity of health characteristics and support needs of people aging with disabilities. We provide aggregate and individual-level analyses of the overall sample to highlight the heterogeneity among people aging with disability. To illustrate the value of the Minimum Battery in gathering contextual information about a specific disability, we conducted an in-depth descriptive analysis of the subsample with vision difficulty as an example. Affecting nearly 7% of older Americans (ages 65þ), vision disability is associated with increased risk for a number of negative health outcomes (e.g., depression, hypertension, falls risk and injury, social isolation) that can compromise one’s ability to perform everyday activities and participate in society.22e24 As with other disabilities, the association between vision disability and health outcomes are numerous and complex, underscoring the importance of assessing broad aspects of health as in the Minimum Battery. Method Instrument The Minimum Battery is a self-report (168-item) questionnaire
Fig. 1. Conceptualization of the intersecting silos representing aging and disability research paradigms illustrating the knowledge gap for people aging with disability.
Please cite this article as: Remillard ET et al., The TechSAge Minimum Battery: A multidimensional and holistic assessment of individuals aging with long-term disabilities, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100884
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Table 1 Source materials included in the minimum battery. Components Personal Demographics
Subjective Health Health Condition
General Technology Experience Capacity Vision
Assessment
CREATE Demographic and Background Questionnaire27
Select questions; modified CREATE Demographic and Background Select 27 Questionnaire questions; modified Comorbidities and Age-Related Conditions among Select Persons with Spinal Cord Injury/Disease (SCI/D; 28) questions; Based on: Centers for Medicare and Medicaid modified Services29 30 Technology Experience Profile (TEP; ) Full; modified
U.S. Census Bureau American Community Survey (ACS) Disability Questions25 U.S. Health and Retirement Study (HRS) Vision Questions.31 Lighthouse International Functional Vision Screening Questionnaire32
Hearing
Speech, Spatial and Qualities of Hearing scale (SSQ12; 33)
Mobility
Late-Life Function and Disability Instrument: Function component34 Memory Issues Checklist35; modified from the Memory Functioning Questionnaire36
Cognition
Environment Vision
CATEA Consumer Network Registry Questionnaire37 National Health Interview Survey (NHIS) on Disability26
Hearing
CATEA Consumer Network Registry Questionnaire37 National Health Interview Survey (NHIS) on Disability26
Mobility
Version Used Description of Measures * denotes measure reported in current analysis
CATEA Consumer Network Registry Questionnaire37 National Health Interview Survey (NHIS) on Disability26
Full; modified Select questions; modified Select questions; modified Select questions; modified Full; modified Select questions; modified Select questions; modified Select questions; modified Select questions; modified Select questions; modified Select questions; modified Select questions; modified
*age, *education, occupational status, *income, *ethnicity, *housing type
*perceptions of health and health functioning (subjective health)
*presence of health conditions diagnosed by a health professional
frequency of use for 36 technologies in categories including: communication (e.g., phones), computers, everyday technology (e.g., microwaves), health care (e.g., pedometer), recreation (e.g., stereo) and transportation (e.g., GPS) functional capacity for *vision, *hearing, *ambulatory, self-care, *cognition, independent living) near and far distance visual ability
*functional vision problems (non-diagnostic screening questionnaire)
hearing abilities in various task-based situations
difficulty with various activities without assistance from other people or aids/ equipment frequency of different types of memory failures and perceptions of seriousness of forgetting
*use of vision assistive technology
*use of vision supportive aids
use of hearing assistive technology
use of hearing supportive aids
use of mobility assistive technology
use of lower and upper body supportive aids
Note. See technical report “TechSAge Minimum Battery: Overview of Measures”, for detailed information on source materials, modifications, and the complete set of questions.21
that is a compilation of measures including: demographics, health, vision/hearing/mobility functional abilities, technology use (general and assistive) and cognition (see Table 1). The questionnaire is available in paper and online versions and takes approximately 30e40 min to complete. A technical report with detailed information on source materials, modifications, and questions is available (link to ancillary material; 21). The Minimum Battery was not intended to produce a total score or to be validated as a whole. Wherever possible, sections of valid and reliable standardized population-based surveys were used to construct the Minimum Battery, such as disability questions from the U.S. Census Bureau’s American Community Survey and the National Health Interview Survey on (NHIS; 25, 26). In some cases, modifications were made to these measures to provide clarity, reduce redundancy, and standardize formatting. Where standardized instruments did not exist, we adapted instruments used in prior work, such as from the Center for Research and Education on
Aging and Technology Enhancement (CREATE) background questionnaire.27 To minimize participant burden, we selected the most pertinent items from source questionnaires. Original items were added to address knowledge gaps relevant to the TechSAge target populations, such as use of hearing assistive technologies (e.g., Video Relay Service, VideoPhone) for Deaf/hard of hearing participants. Measures reported in this paper Measures included in the current analysis are described here. For detailed information on all measures, see the technical report (link to ancillary material; 21). Demographics. Basic demographic information, including age, gender, race, education, and household income was derived from the CREATE Demographic and Background Questionnaire.27 Health. Three subjective health measures27 were used to rate
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health in general (Global Subjective Health), “health in comparison to others their own age” on a five-point scale, ranging from “Poor” to “Excellent”, and “satisfaction with present health” on a 5-point scale where 0 is “Not at all” and 5 is “Extremely Satisfied”. This section included a 17-item checklist of health conditions from part one of the Comorbidities and Age-Related Conditions Questionnaire, developed to assess the presence of health conditions among people aging with spinal cord injury28; questions were originally based on the list developed by Medicare to assess chronic conditions among beneficiaries.29 Number of health conditions was used to develop a non-weighted, summary measure of comorbidity referred to as “Health Conditions” in the current analysis. Participants reported the total number of daily prescription medications they take (fill-the-blank question), creating a “Rx Medication” score that provides a comorbidity summary variable. Capacity. We assessed five domains of functional capacity, including four adapted from the U.S. Census Bureau’s American Community Survey (ACS; 25). These include having serious difficulty with the following: vision (seeing even when wearing glasses or contact lenses); hearing, mobility (walking or climbing stairs), and cognition (concentrating, remembering, or making decisions). Three questions were added as a measure of upper body capacity, including serious difficulty with: lifting ten pounds, reaching over one’s head, and using hands for writing, typing, or sign language. The domains were summed yielding a “serious difficulties” score ranging from 0 to 5, providing a non-weighted, summary subjective measure of comorbidity. Vision Functional Ability and Supportive Aids. Questions were adapted from the Lighthouse International Functional Vision Screening Questionnaire to assess level of difficulty (“0-none” to “5cannot do at all”) with 13 vision-related tasks.32 This section included a 10-item checklist of vision assistive technologies and supportive aids.26,37
Procedures The Minimum Battery was completed in 1 of 3 ways: 1) paper questionnaire mailed to participants with a self-addressed, prepaid return envelope; 2) screen-reader accessible online survey completed on a computer or tablet; 3) survey administered to a participant by a researcher or surrogate (i.e., family member). Data Analysis/Analytic Approach. To demonstrate the potential value of the Minimum Battery as a research tool, we report a systematically derived series of descriptive and bivariate analyses to highlight the heterogeneity of the TechSAge sample of people aging with disability and to illuminate the complexity and robustness of the data. Each successive analysis illustrates a different technique for using the dataset. 1. Sample Description. We conducted descriptive analyses of the socio-demographic characteristics and health measures of the sample, including means, standard deviations and percentages/ proportions of the aggregate data. 2. Visualization of Individual Health. Using individual-level health data, we developed a visual representation of the top and bottom deciles of the sample, in terms of the most and fewest numbers of serious difficulties, which demonstrates the multimorbidity and heterogeneity among sample. 3. Analysis of Global Health. We conducted descriptive and correlational analyses of overall subjective health based on global health and age-cohort comparisons to explore individual perceptions. 4. In-depth Analysis of Vision Subsample. We conducted in-depth analyses of the subsample of participants with vision difficulty as an example to illustrate how the Minimum Battery provides contextual information about a specific disability, including functional capacity, task-based performance difficulties, and use of supportive aids.
Participants A total of 176 TechSAge participants 50 years or older with motor, vision, and/or hearing disabilities completed the Minimum Battery. The convenience sample includes individuals who completed this assessment as a part of a TechSAge research study, focusing on three target populations (i.e., older adults with longterm vision, hearing, or mobility disabilities). The characteristics of the current sample reflected multiple studies with distinct designs and enrollment goals. Some studies focused solely on people aging with mobility disabilities, whereas others included participants multiple disability groups. Across studies, participants were at least 50 years old and had a self-identified vision, hearing, or mobility disability for at least 10 years. Vision participants self-identified as Blind or Low Vision, operationally defined as “unable to see” or “having serious difficulty seeing even when wearing glasses or contact lenses.” Hearing participants self-identified as Deaf or hard of hearing, “having serious difficulty hearing even when wearing a hearing aid or other hearing device” and using American Sign Language (ASL) as their primary language for communication. Mobility participants selfidentified as having a mobility disability, either “having serious difficulty walking or climbing stairs” or requiring use of a mobility aid. TechSAge studies collecting Minimum Battery data received approval from the Institutional Review Board (IRB) and all participants provided informed consent. IRB protocols and consent forms outlined how data are de-identified and made accessible to other TechSAge researchers. Participants were recruited through outreach to local and national disability resource organizations, as well as conferences, and word of mouth.
Results Sample Description Of the 176 individuals included in the analysis, 65% completed the Minimum Battery themselves and 35% had another person record their answers. On average, participants were 67 years old, ranging from age 51 to 83 (SD ¼ 6.2). The sample was predominately female (62.5%). Race distribution was 77.7% White/Caucasian, 16% African American, 2.3% multi-racial, and 3% as other. Almost 60% reported having a college degree or higher and 99% having at least a high school education. Nearly 95% lived in residential housing, including 67.7% in single-family homes. 45% of the sample was married. There was a mixed distribution across annual income brackets, with 27% reporting household earnings of less than $25,000 and 20% reporting $75,000 or higher. Total number of health conditions ranged from 0 to 12 with an average of 4.1 conditions (SD ¼ 2.5). Participants report taking between 0 and 22 daily prescription medications (M ¼ 4.1; SD ¼ 3.9) and an average of 1.6 serious functional difficulties (SD ¼ 0.85; Range 0e5). Distribution of reported serious difficulties were mobility (53%); upper body (40%); vision (40%); hearing (28.7%); and cognitive (6.5%). The prevalence of health conditions and serious functional difficulties among the sample indicated a fair degree of comorbidity and could suggest moderately poor health or function. Despite these health issues, most (84%) rated their health as good (52%) very good (7%) or excellent (25%) and claimed to be somewhat or extremely satisfied with their present health (70%).
Please cite this article as: Remillard ET et al., The TechSAge Minimum Battery: A multidimensional and holistic assessment of individuals aging with long-term disabilities, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100884
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Visualization of Individual Health
In-depth assessment of individuals with vision difficulty
Fig. 2 depicts data for participants reporting the greatest (top 10%) and least (bottom 10%) number of serious difficulties in the top and bottom sections of the figure, respectively. Data are sorted in descending order from most5 to least (0) number of serious difficulties. Each row represents a participant. For the 5 difficulty columns, a solid circle indicates serious difficulty (Yes), an open circle signifies “No”, and a blank cell indicates no response. The bars in the three left columns represent the magnitude of the comorbidity summary measures, including number of serious difficulties (0e5 index variable); health conditions (0e12 from list); and prescription medications. The absence of a bar indicates a zero value (e.g., no health conditions for ID 111), whereas a bar that extends the full length of the cell indicates the maximum sample value (e.g., 5 serious difficulties for ID 106). For participants reporting the greatest numbers of serious difficulties (top 10%; n ¼ 18), the average number was 3.4 (SD ¼ 0.61; Range 3e5). Mobility difficulty was reported among all participants, with upper body difficulty being the next most common, affecting all but two individuals. Participants in the top decile reported an average of 5.6 health conditions (SD ¼ 3.6; Range ¼ 0e12) and 7.2 daily prescriptions (SD ¼ 5.9; Range ¼ 0e22). Participant 106 represents the extreme example of comorbidity among the sample, reporting 5 serious difficulties, 10 health conditions, and 22 prescriptions. Participants with the least number of serious difficulties (bottom 10%; n ¼ 18) presented a very different picture. Serious difficulties ranged from 0 to 1 (M ¼ 0.8; SD ¼ 0.4), with 15 individuals reporting only 1. Participants reported an average of 3 health conditions (SD ¼ 1.7; Range 0e6) and 3.2 daily prescription medications (SD ¼ 2.3; Range ¼ 0e8). Vision and mobility were the most prevalent serious difficulties, reported by 9 and 4 individuals, respectively. Only 1 person reported serious difficulty in each of the hearing and cognitive domains; no one reported upper body serious difficulty. As the extreme example for the bottom decile, participant 163 reported no serious difficulties and only one health condition and daily prescription medication. The individual cases at the tails of the distribution of the index variable shed light on the potentially misleading nature of aggregated data when only unimodal measures of function, ability, or impairment are obtained. All three summary measures of comorbidity illustrated considerable comorbidity for those in the top decile of “serious difficulties” and more than double compared with the bottom, the former providing a glimpse of frailty and disability, the latter of relatively healthy aging.
Nearly 40% (n ¼ 69) of the overall sample reported serious difficulty seeing (85.5% of them reported difficulty seeing in both eyes). Mean age of onset for vision difficulty was 16 ± 17 years (n ¼ 66; 3 missing responses). On average, participants had vision difficulty for 50.9 years (SD ¼ 18.5). An average of 1.8 total serious difficulties was reported among the vision difficulty subsample (SD ¼ 0.95; Range 1e5). 49% reported other serious difficulties, including mobility (affecting 30% of the sample), followed by upper body (23%), hearing (17%), and cognition (7%). 51% of the vision subsample had no other comorbid difficulties. Although many participants had fairly high levels of functional capacity as measured by the level of difficulty on eight “standardized” tasks (Fig. 4), on average half of the sample reported they “cannot do” any of these tasks, ranging from 43% to 62% on each task. Nearly three-quarters of the sample had “a lot” of difficulty or “could not do” four of the eight tasks (i.e., reading a telephone directory, seeing street signs when crossing a street, reading medicine labels, reading prices when shopping), whereas more than 60% had “a lot of difficulty/could not do” three others. Reading your own mail was the task with the lowest percentage of participants who reported they cannot do it (43%), followed by seeing cars crossing the street (48%). “Quite a lot” of difficulty was least commonly reported for reading the large print headlines in the newspaper. Internal consistency of all 13 vision functional task items was high, as indexed by the Cronbach’s alpha (0.98). There was a significant difference in mean functional vision task difficulty scores between those who reported serious vision difficulty and those who did not (t68.86 ¼ 7.63, p < .001). On average, participants reported using 2.8 visual aids from the list of 10 specified types plus “other” (Range ¼ 0e7; SD ¼ 2.4); 6% reported using none. Over 70% used white canes and computer equipment (e.g., scanners, optical character recognition). The next most commonly used aids were audio description (65%), screen readers (58%) and Braille (46%). Most participants with serious vision difficulty rated their health as good (48%), very good, or excellent (36%), suggesting generally positive health perceptions among the subsample. Further analysis to cross-tabulate subjective health between those with and without vision difficulties (x2 1.7, 2, 0.42), failed to reveal a relationship between serious vision difficulties and global subjective health. However, a different picture emerged when factoring in one or more comorbidities. Fig. 5 shows the same trichotomized GSH variable analysis for the vision difficulty subsample grouped by number of comorbid difficulties: vision difficulty only, vision þ1 difficulty, vision þ2 or more difficulties. For those with vision þ1 or more difficulty, a significant relationship with GSH emerged (x2 25.2, 4, 0.000). Among participants with vision plus 2 or more serious difficulties, half rated their health as poor or fair and only 7% reported very good or excellent health. Conversely, the majority of those with only vision difficulty (56%) rated their health as very good or excellent. No participants reporting serious difficulty only with vision rated their health as poor or fair.
Analysis of Global Health Another aspect of health is perception; that is, how individuals perceive their health. We examined overall global subjective health and health compared to others (Fig. 3) and saw an optimistic picture of the sample, with 84% rating their overall health as “good”, “very good,” or “excellent” and 82% rating their health compared to others the same way. Bivariate correlations of the global subjective health (GSH) question with the other subjective health items confirmed the measures were related and reliable (p < .001); GSH was positively related to satisfaction with present health (r ¼ 0.62) and health compared to others (r ¼ 0.85). We conducted bivariate correlations of the GSH variable with the summary health variables: serious difficulties, health conditions, and Rx medications. GSH was negatively related (all p ¼ .001) to number of serious difficulties (r ¼ 0.40), health conditions (r ¼ 0.31), and prescription medications (r ¼ 0.38). Those with fewer difficulties, diagnoses, and/or fewer medications perceived their health as better.
Discussion We conducted a series of analyses to demonstrate the potential usefulness and value of the Minimum Battery as a research tool in exploring characteristics of people aging with disability. Consistent with the literature,3,7,22 the sample of older adults with long-term disabilities exhibited a fair degree of comorbidity overall, with regard to aggregate numbers of serious difficulties, health conditions, and prescription medications. The combination of these comorbidity factors, however, were highly individualized, with great
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Fig. 2. Illustration of the variation in comorbidities with regard to number of serious difficulties, health conditions, and prescription medications as well as type of serious difficulties for participants reporting the greatest and least number of serious difficulties.
variation in type and number among participants in the extreme ends of the distribution (i.e., those with most and least number of difficulties; Fig. 2). This finding underscored the remarkable heterogeneity in disability characteristics as well as the experience of disability among older adults with long-term disabilities as suggested by prior research.4,16,38 Despite the high prevalence of comorbid difficulties and conditions among the sample, global health findings were in concert with considerable evidence that older people tend to have and
maintain fairly high ratings of self-reported health.39 As depicted in Fig. 3, the majority of the sample rated their health in general as good or better, even in comparison to others own age. In line with prior research, many people aging with disability are resilient, maintaining a positive outlook and quality of life in spite of stress and disability-related challenges.40 However, this is not the case for all, as lower subjective health scores were correlated with other negative health indicators, including additional comorbid serious difficulties (Fig. 5).
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Fig. 3. Subjective health ratings.
Analyses of the subsample with vision difficulty (N ¼ 69) highlighted the value of capturing multi-faceted aspects of disability. For instance, although many participants reported “no” to “some” difficulty with the functional vision tasks (Fig. 4), roughly half of the sample reported they cannot do any of these tasks, suggesting they are likely blind. The subsample included participants who were intentionally recruited into TechSAge studies for being long-term blind or low vision, as well as participants with other types of long-term disabilities, who happen to also have vision difficulty; these groups have distinct experiences of vision disability and we would expect less variability in functional abilities among subgroups with similar characteristics (e.g., blind only, low vision only, those with similar durations of impairment). Nevertheless, the data underscored the potential variation in type, degree, and duration of vision impairment among older adults, and
demonstrated the value of assessing support needs on an individual basis as recommended in recent research on supporting individuals aging with disability.9,18,38 There are limitations to note about the TechSAge Minimum Battery and the current analyses. First, data are self-report, and therefore subject to potential participant bias, such as omissions or exaggerations, and cannot be independently verified. Notably, among those in bottom 10% of the sample in terms of “serious difficulties” (Fig. 2), we identified at least three legally deaf participants who responded “no” to the hearing difficulty question and two legally blind subjects who respond “no” to the vision question. It should be reiterated, that the question was phrased “Do you have serious difficulty [seeing, hearing, etc.]?”. These cases illustrate the value of assessing multi-faceted aspects of disability experience and paying close attention to language, given the subjective and
Fig. 4. Functional capacity for visual tasks among participants reporting with serious vision difficulty.
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Fig. 5. Global subjective health for participants reporting vision difficulty (N ¼ 69) grouped by number of comorbid difficulties.
highly personal nature of disability and health.15 Second, this was a cross-sectional study and we cannot determine causation among variables. In future work, the Minimum Battery could be collected longitudinally to assess trends among individuals and subsamples as well as trajectories of aging with disability. No strategic sampling efforts were made for the current dataset, which functions as a central repository for data collected in individual TechSAge studies. As such, the characteristics of the convenience sample reflect the variability of the individual studies and findings are not generalizable to the diverse population of people aging with disability. Despite efforts to enroll underrepresented groups, the sample is predominately white/Caucasian with high education. For individuals in minority populations, and particularly those with low education, we would expect the impact of disability on everyday activities to be greater due to known health disparities and limited access to supportive services.41 Although the Minimum Battery represents a sampling of key measures, the length of the survey is a limitation. A streamlined version of the Minimum Battery with fewer questions could be developed to facilitate use among broader audiences, such as clinicians. At the same time, no questionnaire is fully comprehensive, and there were gaps in the assessment that are relevant to the goal of understanding the experience of aging with a disability such as depression, falls, and use of emerging technologies. We are refining the assessment to eliminate unnecessary items and incorporate additional measures of interest for version 2.0.
Conclusions As a compilation of multi-dimensional measures of aging and disability, the TechSAge Minimum Battery provides an integrated assessment method to gain a holistic understanding of people aging with disability. The current paper presented a series of analyses that demonstrated the multi-morbidity and heterogeneity among individuals aging with disability. Analyses of the subsample with vision difficulty revealed the depth of contextual information about a specific disability (e.g., capabilities, limitations, and support needs) that can be realized through the Minimum Battery. Detailed insights are available in the data set for other subsamples (e.g., persons with mobility and hearing difficulties). The Minimum Battery was designed to focus on the individual. Among the current sample, the only common thread between certain participants may be having a disability for a prolonged period of time, with all other factors being unique. Research all too often focuses on aggregates and averages, which can be particularly
misleading in describing older adults with disabilities, given the potential for heterogeneity and the likelihood for multi-morbidities as we observed in our dataset. In essence, the Minimum Battery replicates what a clinician would do, collecting an array of relevant information about an individual (N ¼ 1) to better understand their unique health characteristics and support needs. The bridging of aging and disability measures, as in the Minimum Battery, holds potential to expand the knowledge base about individuals aging with disability, ultimately advancing innovation, practice, and service delivery to better meet the needs of this growing population.7,18,42 In RERC TechSAge, we are using the Minimum Battery to inform the development of new technologies and environmental solutions for people aging with disability as well as to assess the impact of technology interventions and to understand potential factors underlying their use or adoption. The Minimum Battery could also be used to identify targeted interventions for an individual based on the multi-faceted data on sensory and mobility capabilities and current technology use and experience. The integrated collection of aging and disability measures represented in the Minimum Battery could be especially useful to provide insights for professionals in allied health and social work, who are often on the front lines of helping individuals navigate between the silos of aging and disability resources. Funding The contents of this publication were developed under a grant from the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR grant number 90REGE0006-0100) under the auspices of the Rehabilitation and Engineering Research Center on Technologies to Support Aging-in-Place for People with Long-Term Disabilities (RERC TechSAge; www.rerctechsage. org). NIDILRR is a Center within the Administration for Community Living (ACL), Department of Health and Human Services (HHS). Disclaimer The contents of this publication do not necessarily represent the policy of NIDILRR, ACL, or HHS, and you should not assume endorsement by the Federal Government. Prior presentation The current manuscript represents the first article submitted for publication on The Minimum Battery. The questionnaire was
Please cite this article as: Remillard ET et al., The TechSAge Minimum Battery: A multidimensional and holistic assessment of individuals aging with long-term disabilities, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100884
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highlighted in a brief (10 min) presentation as part of the RERC TechSAge annual symposium at the 2018 Gerontological Society of America conference in Boston, MA; a 1 paragraph abstract was published online in the society’s online publication Innovation in Aging (https://academic.oup.com/innovateage/article/2/suppl_1/ 624/5171443). The conference presentation provided a high-level overview of the Minimum Battery and did not include data reported in the current analysis. Declaration of competing interest The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Acknowledgements The authors would like to thank Sara Bowman and other members of the TechSAge research team for their contributions to the development of the Minimum Battery as well as Sarah Melgen for her assistance with graphic design. References 1. GBD 2015 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1545e1602. https://doi.org/ 10.1016/S0140-6736(16)31678-6. 2. Institute of Medicine. The Future of Disability in America. Washington, DC: The National Academies Press; 2007. 3. Field M, Jette A. Secondary conditions and aging with disability. In: Field M, Jette A, eds. The Future Of Disability In America (136e161). Washington, DC, USA: The National Academies of Science Press; 2007. ISBN 978-0-309-10472-2. 4. Verbrugge LM, Yang L. Aging with disability and disability with aging. J Disabil Policy Stud. 2002;12:253e267. https://doi.org/10.1177/104420730201200405, 2002. 5. LePlante MP. Key goals and indicators for successful aging with early-onset disability. Disabil Health J. 2014:S44eS50. https://doi.org/10.1016/ j.dhjo.2013.08.005. 6. Molton IR, Terrill AL, Smith AE, et al. Modeling secondary conditions in adults aging with physical disability. J Aging Health. 2014;26(3):335e359. https:// doi.org/10.1177/0898264313516166. 7. Campbell ML, Putnam M. Reducing the shared burden of chronic conditions among persons aging with disability and older adults in the United States through bridging aging and disability. Healthcare. 2017;5:56. https://doi.org/ 10.3390/healthcare5030056. 8. Czaja SJ, Boot WR, Charness N, Rogers WA. Designing for Older Adults: Principles and Creative Human Factors Approaches. third ed. Boca Raton, FL: CRC Press; 2019. 9. Mitzner TL, Sanford JA, Rogers WA. Closing the capacity-ability gap: using technology to support aging with disability. Innov Aging. 2018;2(1):1e8. https://doi.org/10.1093/geroni/igy008. 10. Preusse KC, Gonzalez ET, Singleton JL, Mitzner TL, Rogers WA. Understanding the needs of individuals ageing with impairment. Int J Hum Factors Ergon. 2016;4:144e168. 11. Groah SL, Charlifue S, Tate D, et al. Spinal cord injury and aging: challenges and recommendations for future research. Am J Phys Med Rehab. 2012;91:80e93. https://doi.org/10.1097/PHM.0b013e31821f70bc. 12. Stern M, Sorkin L, Milton K, Sperber K. Aging with multiple sclerosis. Phys Med Rehabil Clin N Am. 2010;21:403e417. https://doi.org/10.1016/ j.pmr.2009.12.008. 13. Campbell ML, Sheets D, Strong PS. Secondary health conditions among middleaged individuals with chronic physical disabilities: implications for unmet needs for services. Assist Technol. 1999;11(2):105e122. https://doi.org/ 10.1080/10400435.1999.10131995. 14. World Health Organization. International Classification of Functioning, Disability and Health. Geneva, Switzerland: World Health Organization; 2001. Retrieved from http://www.who.int/classifications/icf/en/. 15. Verbrugge LM. Disability experience and measurement. J Aging Health. 2016;28(7):1124e1158. https://doi.org/10.1177/0898264316656519. 16. Freedman VA. Research gaps in the demography of aging with disability. Disabil Health J. 2014;7:S60eS63.
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Please cite this article as: Remillard ET et al., The TechSAge Minimum Battery: A multidimensional and holistic assessment of individuals aging with long-term disabilities, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100884