The Voice of the Consumer: A Survey of Veterans and Other Users of Assistive Technology

The Voice of the Consumer: A Survey of Veterans and Other Users of Assistive Technology Abstract Introduction A total of 3.6 million Americans and over 250,000 veterans use wheelchairs. The need for advancements in mobility-assistive technologies is continually growing due to advances in medicine and rehabilitation that preserve and prolong the lives of people with disabilities, increases in the senior population, and increases in the number of veterans and civilians involved in conflict situations. The purpose of this study is to survey a large sample of veterans and other consumers with disabilities who use mobility-assistive technologies to identify priorities for future research and development. Materials and Methods This survey asked participants to provide opinions on the importance of developing various mobility-assistive technologies and to rank the importance of certain technologies. Participants were also asked to provide open-ended comments and suggestions. Results A total of 1,022 individuals, including 500 veterans, from 49 states within the USA and Puerto Rico completed the survey. The average age of respondents was 54.3 yr, and they represented both new and experienced users of mobility-assistive technologies. The largest diagnostic group was spinal cord injury (SCI) (N = 491, 48.0%). Several themes on critical areas of research emerged from the open-ended questions, which generated a total of 1,199 comments. Conclusion This survey revealed several themes for future research and development. Advanced wheelchair design, smart device applications, human–machine interfaces, and assistive robotics and intelligent systems emerged as priorities. Survey results also demonstrated the importance for researchers to understand the effects of policy and cost on translational research and to be involved in educating both consumers and providers. Introduction A total of 3.6 million Americans1 and over 250,000 veterans use wheelchairs. (Personal communications among Penny Nechanicky [National Director], Ru Gakhar [Prosthetic Program Manager], Prosthetic and Sensory Aids Service, Department of Veterans Affairs, Rory Cooper, and Brad Dicianno. July 24, 2015.) Mobility-assistive technologies such as wheelchairs and scooters improve function, home and community integration,2–5 quality of life,6,7 and comfort.6,8 The number of users of these technologies is continually growing due to advances in medicine and rehabilitation that preserve and prolong the lives of people with disabilities, increases in the senior population, and increases in the number of veterans and civilians involved in conflict situations.1,9,10 Despite the availability of mobility-assistive technologies to the various populations in need, The World Health Organization (WHO) estimates that over 1 billion people currently need assistive technologies, but that only 1 in 10 have access. They estimate that by 2050, due to the growth of disability populations, 2 billion people will be in need.11 In cooperation with the United States Agency for International Development (USAID), the United Nations, and other agencies, WHO established the Global Cooperation on Assistive Technology (GATE), which is a global effort to improve access to high-quality affordable assistive products.11 In order to reach the goal of global access, a research agenda for assistive technologies must first be developed. The need for additional support for mobility is also a top priority of veterans with disabilities. A report by Paralyzed Veterans of America (PVA) named mobility and independence among the top three health concerns of female veterans who were injured or diagnosed with a neurological condition.12 We are not aware of a similar study conducted on men. Simpson et al. published a systematic review13 that summarized 24 studies (5,262 total participants with spinal cord injury [SCI]) that directly surveyed individuals with SCI about their health and function priorities. This review revealed that within the health domain, motor function, bowel and bladder function, and sexual function were the top three priorities. Those with paraplegia prioritized mobility, whereas those with tetraplegia prioritized hand function. General health and relationships were also cited as priorities. Another systematic review of six studies (1,222 total participants with SCI) revealed that mobility was a top concern after SCI. Research and development to advance mobility-assistive technologies could begin to address these concerns. In two hearings before Subcommittees of the Appropriations Committee of the House of Representatives, testimony was given by high ranking government officials about the importance of research on mobility-assistive technologies. Vice Admiral Matthew Nathan, the 37th Surgeon General of the Navy and Chief of the Navy’s Bureau of Medicine and Surgery, stressed the need to continue funding for research specifically geared to improve the mobility of injured veterans.14 Robert A. MacDonald, Secretary, Department of VA, requested support of Congress for Veteran health care and research.15 Additionally, in testimony before the Subcommittee on Social Security, Committee on Ways and Means, Robert E. Robertson, Director, Education, Workforce, and Income Security Issues, specifically mentioned wheelchair design as a scientific advancement that has allowed individuals with disabilities to participate in society, including seeking and maintaining employment.16 The Social Security Administration, with encouragement from the Office of Management and Budget, commissioned the National Academy of Medicine (NAM) to conduct a study on advances in wheelchairs and other mobility devices on employability of people with disabilities. Because of this growing need for better technology, research aims must be outlined and prioritized. The National Academies of Sciences, Engineering, and Medicine (NAS), in collaboration with the Social Security Administration, provided a report analyzing the use of current assistive technologies and called for development of research priorities.17 The President’s Council of Advisors on Science and Technology (PCAST) report recommended that the VA and Centers for Medicare and Medicaid Services create a “road map” for mobility-assistive technology research and that more federal support of research be made available.18 However, this road map has yet to be developed. We began to develop such a road map in our preliminary work. We conducted a pilot study of 112 individuals who use mobility-assistive technologies to characterize their needs and opinions.19 In parallel, we also surveyed 161 professionals involved in the provision of mobility devices both within and outside VA.31 These surveys revealed several themes that helped us to construct a preliminary road map, but a larger and more diverse sample of users was needed. The purpose of the present study was to evaluate the opinions of over 1,000 users of mobility-assistive technologies to inform a research agenda and identify priorities that are aligned with the goals and desires of the users. Methods The survey (see Appendix 1) was developed by experts in the field of assistive technology at the Human Engineering Research Laboratories (HERL) in Pittsburgh, PA, USA. The VA Pittsburgh Healthcare System Veterans Engineering Resource Center (VERC) assisted the team in establishing content validity. The study was approved by the Institutional Review Board of the University of Pittsburgh as an expedited study. The survey was administered through the Research Electronic Data Capture (REDCap) system (Vanderbilt University, Nashville, TN, USA), a secure, web-based software system sponsored by the Clinical Translational and Science Institute at the University of Pittsburgh. The survey was designed to take less than 10 min to complete and was based on a previously conducted survey.19 Participants could complete the survey online using a computer or any mobile device. Alternately, they had the option to contact a study coordinator to complete the questionnaire by phone or mail. The home page provided a brief description of the project and an overview of informed consent, asking the participant to answer whether they consented to taking the survey. Participants were asked to provide basic demographic information and to choose from a list of pre-defined diagnoses or list their own diagnosis under “other.” Participants were allowed to list multiple diagnoses. Some personally identifiable information was collected in the questionnaire to ensure that there were no repeat responses; however, the questionnaire was anonymized by the coordinator prior to analysis. Participants were asked how important it is to carry out certain activities if technology could accommodate them. The next set of questions asked participants to provide individual rankings of importance of developing various technologies that were ranked highly in our previous survey.19 The survey also required participants to rank these items against each other in terms of order of importance. Participants were asked how often they play an active role in the decision-making process when getting new mobility equipment and how often they receive adequate support to be able to maintain their assistive technology long term. Participants were also asked to respond to several open-ended questions or statements, including identifying barriers when obtaining new mobility-assistive technologies. Inclusion criteria were age 18 yr or older, U.S. citizen, an individual who uses mobility-related assistive devices, and answers “yes” to providing consent to participating in the survey. There were no specific exclusion criteria. Referral sampling was used for this study wherein initial participants were asked to distribute recruitment materials to their own networks. Participants were recruited in person at athletic events, advocacy meetings, and at meetings of veteran service organizations for veterans and people with disabilities. Flyers were sent via email to personal contacts and professional listservs at disability and veteran service organizations, veteran support groups, health care agencies, hospitals, clinics, government organizations, and universities. Personal contacts then distributed recruitment materials through social media and email outreach. Flyers were posted on our own organization’s website and social media pages. Participants were also recruited from our local research registries, which contain contact information of individuals who have expressed interest in participating in research. Recruitment materials were advertised in magazines, targeted social media ads, and newsletters and also mentioned in radio broadcasts. Potential participants were directed to access the web link directly or to contact a study coordinator. Descriptive statistics for each multiple-choice item were reported using frequency counts and percentages. Average rankings were examined for sets of items that were placed in order by respondents. For respondents with SCI, a sub-analysis was performed to compare differences in the research and development priorities of those with paraplegia versus tetraplegia. Chi-squared tests of independence were used to determine the relationship between the rankings of each item and group membership. All descriptive statistics were performed using SPSS v24.0 (IBM Corp., Armonk, NY, USA). Open-ended responses were examined in detail to identify overall patterns and themes, as well as unique, creative solutions to the issues of mobility. Results A total of 1,127 individuals were sent recruitment materials and asked to distribute further to their own contacts. Also, targeted social media ads reached 41,129 unique people. Referral sampling resulted in 1,178 potential participants. Figure 1 displays an exclusion diagram demonstrating inclusion of 1,022 participants based on aforementioned criteria. Table I displays demographic characteristics of participants. Average age was 54.3 (STD 14.6, range 19–95) yr. A total of 500 (48.9%) were veterans. Participants lived in 49 different states within the U.S. and Puerto Rico. Four individuals required help from a clinical coordinator to complete the survey via phone and one via mail; the rest completed the survey electronically. Figure 1. View largeDownload slide Exclusion flow chart. Figure 1. View largeDownload slide Exclusion flow chart. Table I. Demographic Information for Consumers (n = 1,022)   n  %  Types of assistive devices used (participants could choose more than one)   Manual wheelchair  596  58.3   Power wheelchair  481  47.1   Scooter  98  9.6   Lower extremity prosthesis  49  4.8   Lower extremity orthosis (brace)  134  13.1   Assistive device (e.g., cane, crutch, and walker)  387  37.9   Other  99  9.7  Length of time device(s) used   1 yr or less  58  5.7   2–5 yr  235  23.0   6–10 yr  168  16.4   11–15 yr  135  13.2   More than 15 yr  423  41.4   Missing/did not answer  3  <1.0  Gender   Female  367  35.9   Male  655  64.1  Highest level of education   Associate’s degree  218  21.3   Bachelor’s degree  284  27.8   Doctorate level degree – MD, DO, PhD  60  5.9   High school diploma or equivalent (GED)  245  24.0   Master’s degree  178  17.4   Other advanced degree  36  3.5   Missing  1  <1.0  Veteran of US Armed Forces   No  520  50.9   Yes  500  48.9   Missing  2  <1.0  Type of community setting in which you live   Rural (country)  232  22.7   Suburban  460  45.0   Urban (city)  322  31.5   Missing  8  <1.0  Ethnicity   Hispanic or Latino  63  6.2   Not Hispanic or Latino  954  93.3   Missing  5  <1.0  Race   White/Caucasian  841  82.3   Black or African American  78  7.6   Two or more races  49  4.8   Other  32  3.1   American Indian or Alaskan Native  9  <1.0   Asian  7  <1.0   Native Hawaiian or other Pacific Islander  4  <1.0   Missing  2  <1.0  If a veteran, obtain assistive devices through VA   Yes  439  87.8   No  59  11.8   Missing  2  <1.0  Household income   Under $15,000  115  11.3   $15,000–$24,999  109  10.7   $25,000–$49,999  195  19.1   $50,000–$74,999  150  14.7   $75,000–$100,000  117  11.4   Over $100,000  149  14.6   I don’t know  28  2.7   I prefer not to answer  158  15.5   Missing  1  <1.0    n  %  Types of assistive devices used (participants could choose more than one)   Manual wheelchair  596  58.3   Power wheelchair  481  47.1   Scooter  98  9.6   Lower extremity prosthesis  49  4.8   Lower extremity orthosis (brace)  134  13.1   Assistive device (e.g., cane, crutch, and walker)  387  37.9   Other  99  9.7  Length of time device(s) used   1 yr or less  58  5.7   2–5 yr  235  23.0   6–10 yr  168  16.4   11–15 yr  135  13.2   More than 15 yr  423  41.4   Missing/did not answer  3  <1.0  Gender   Female  367  35.9   Male  655  64.1  Highest level of education   Associate’s degree  218  21.3   Bachelor’s degree  284  27.8   Doctorate level degree – MD, DO, PhD  60  5.9   High school diploma or equivalent (GED)  245  24.0   Master’s degree  178  17.4   Other advanced degree  36  3.5   Missing  1  <1.0  Veteran of US Armed Forces   No  520  50.9   Yes  500  48.9   Missing  2  <1.0  Type of community setting in which you live   Rural (country)  232  22.7   Suburban  460  45.0   Urban (city)  322  31.5   Missing  8  <1.0  Ethnicity   Hispanic or Latino  63  6.2   Not Hispanic or Latino  954  93.3   Missing  5  <1.0  Race   White/Caucasian  841  82.3   Black or African American  78  7.6   Two or more races  49  4.8   Other  32  3.1   American Indian or Alaskan Native  9  <1.0   Asian  7  <1.0   Native Hawaiian or other Pacific Islander  4  <1.0   Missing  2  <1.0  If a veteran, obtain assistive devices through VA   Yes  439  87.8   No  59  11.8   Missing  2  <1.0  Household income   Under $15,000  115  11.3   $15,000–$24,999  109  10.7   $25,000–$49,999  195  19.1   $50,000–$74,999  150  14.7   $75,000–$100,000  117  11.4   Over $100,000  149  14.6   I don’t know  28  2.7   I prefer not to answer  158  15.5   Missing  1  <1.0  View Large Table I. Demographic Information for Consumers (n = 1,022)   n  %  Types of assistive devices used (participants could choose more than one)   Manual wheelchair  596  58.3   Power wheelchair  481  47.1   Scooter  98  9.6   Lower extremity prosthesis  49  4.8   Lower extremity orthosis (brace)  134  13.1   Assistive device (e.g., cane, crutch, and walker)  387  37.9   Other  99  9.7  Length of time device(s) used   1 yr or less  58  5.7   2–5 yr  235  23.0   6–10 yr  168  16.4   11–15 yr  135  13.2   More than 15 yr  423  41.4   Missing/did not answer  3  <1.0  Gender   Female  367  35.9   Male  655  64.1  Highest level of education   Associate’s degree  218  21.3   Bachelor’s degree  284  27.8   Doctorate level degree – MD, DO, PhD  60  5.9   High school diploma or equivalent (GED)  245  24.0   Master’s degree  178  17.4   Other advanced degree  36  3.5   Missing  1  <1.0  Veteran of US Armed Forces   No  520  50.9   Yes  500  48.9   Missing  2  <1.0  Type of community setting in which you live   Rural (country)  232  22.7   Suburban  460  45.0   Urban (city)  322  31.5   Missing  8  <1.0  Ethnicity   Hispanic or Latino  63  6.2   Not Hispanic or Latino  954  93.3   Missing  5  <1.0  Race   White/Caucasian  841  82.3   Black or African American  78  7.6   Two or more races  49  4.8   Other  32  3.1   American Indian or Alaskan Native  9  <1.0   Asian  7  <1.0   Native Hawaiian or other Pacific Islander  4  <1.0   Missing  2  <1.0  If a veteran, obtain assistive devices through VA   Yes  439  87.8   No  59  11.8   Missing  2  <1.0  Household income   Under $15,000  115  11.3   $15,000–$24,999  109  10.7   $25,000–$49,999  195  19.1   $50,000–$74,999  150  14.7   $75,000–$100,000  117  11.4   Over $100,000  149  14.6   I don’t know  28  2.7   I prefer not to answer  158  15.5   Missing  1  <1.0    n  %  Types of assistive devices used (participants could choose more than one)   Manual wheelchair  596  58.3   Power wheelchair  481  47.1   Scooter  98  9.6   Lower extremity prosthesis  49  4.8   Lower extremity orthosis (brace)  134  13.1   Assistive device (e.g., cane, crutch, and walker)  387  37.9   Other  99  9.7  Length of time device(s) used   1 yr or less  58  5.7   2–5 yr  235  23.0   6–10 yr  168  16.4   11–15 yr  135  13.2   More than 15 yr  423  41.4   Missing/did not answer  3  <1.0  Gender   Female  367  35.9   Male  655  64.1  Highest level of education   Associate’s degree  218  21.3   Bachelor’s degree  284  27.8   Doctorate level degree – MD, DO, PhD  60  5.9   High school diploma or equivalent (GED)  245  24.0   Master’s degree  178  17.4   Other advanced degree  36  3.5   Missing  1  <1.0  Veteran of US Armed Forces   No  520  50.9   Yes  500  48.9   Missing  2  <1.0  Type of community setting in which you live   Rural (country)  232  22.7   Suburban  460  45.0   Urban (city)  322  31.5   Missing  8  <1.0  Ethnicity   Hispanic or Latino  63  6.2   Not Hispanic or Latino  954  93.3   Missing  5  <1.0  Race   White/Caucasian  841  82.3   Black or African American  78  7.6   Two or more races  49  4.8   Other  32  3.1   American Indian or Alaskan Native  9  <1.0   Asian  7  <1.0   Native Hawaiian or other Pacific Islander  4  <1.0   Missing  2  <1.0  If a veteran, obtain assistive devices through VA   Yes  439  87.8   No  59  11.8   Missing  2  <1.0  Household income   Under $15,000  115  11.3   $15,000–$24,999  109  10.7   $25,000–$49,999  195  19.1   $50,000–$74,999  150  14.7   $75,000–$100,000  117  11.4   Over $100,000  149  14.6   I don’t know  28  2.7   I prefer not to answer  158  15.5   Missing  1  <1.0  View Large Supplemental Table 1 displays diagnoses of participants. The largest diagnostic group was spinal cord injury (SCI) (N = 491, 48.0%). Of the participants with SCI, 290 (59.1%) had paraplegia, 188 (38.3%) had tetraplegia, and 13 (2.6%) did not report this classification. A total of 212 (43.2%) reported complete SCI, 252 (51.3%) reported incomplete SCI, and 27 (5.5%) did not report completeness of lesion. Some individuals indicating “other” diagnoses were reclassified into one of the pre-defined categories if clinically appropriate. When asked about how important it would be to carry out certain activities if technology could accommodate them, the majority of respondents identified all four categories of activities as critical/important (Supplemental Table 1). Participants were also asked how important it would be for researchers to develop specific technologies. Although most technologies were rated as critical or important, wheelchairs and components that could self-adjust or could assist in overcoming obstacles gained the most critical ratings (Table II). Table II. Ranking of Key Areas for Research from Critical to not Important, n (%)   Missing Response  Critical  Important  Minor Importance  Not Important  Develop portable powered transfer devices that a person with a disability could use independently?  2 (0.2)  416 (40.7)  439 (43)  100 (9.8)  65 (6.4)  Develop sport or recreation technology to help you meet your fitness or weight loss goals?  2 (0.2)  375 (36.7)  429 (42)  160 (15.7)  56 (5.5)  Decrease the amount of time it takes to provide customized wheelchair components (i.e., 3D printed on site)?  1 (0.1)  331 (32.4)  413 (40.4)  201 (19.7)  76 (7.4)  Develop wearable or mobile technologies that can provide health or other information to users or their clinicians?  2 (0.2)  273 (26.7)  420 (41.1)  243 (23.8)  84 (8.2)  Develop wheelchairs and components that can self-adjust or can assist in overcoming obstacles  2 (0.2)  513 (50.2)  395 (38.6)  86 (8.4)  26 (2.5)    Missing Response  Critical  Important  Minor Importance  Not Important  Develop portable powered transfer devices that a person with a disability could use independently?  2 (0.2)  416 (40.7)  439 (43)  100 (9.8)  65 (6.4)  Develop sport or recreation technology to help you meet your fitness or weight loss goals?  2 (0.2)  375 (36.7)  429 (42)  160 (15.7)  56 (5.5)  Decrease the amount of time it takes to provide customized wheelchair components (i.e., 3D printed on site)?  1 (0.1)  331 (32.4)  413 (40.4)  201 (19.7)  76 (7.4)  Develop wearable or mobile technologies that can provide health or other information to users or their clinicians?  2 (0.2)  273 (26.7)  420 (41.1)  243 (23.8)  84 (8.2)  Develop wheelchairs and components that can self-adjust or can assist in overcoming obstacles  2 (0.2)  513 (50.2)  395 (38.6)  86 (8.4)  26 (2.5)  Table II. Ranking of Key Areas for Research from Critical to not Important, n (%)   Missing Response  Critical  Important  Minor Importance  Not Important  Develop portable powered transfer devices that a person with a disability could use independently?  2 (0.2)  416 (40.7)  439 (43)  100 (9.8)  65 (6.4)  Develop sport or recreation technology to help you meet your fitness or weight loss goals?  2 (0.2)  375 (36.7)  429 (42)  160 (15.7)  56 (5.5)  Decrease the amount of time it takes to provide customized wheelchair components (i.e., 3D printed on site)?  1 (0.1)  331 (32.4)  413 (40.4)  201 (19.7)  76 (7.4)  Develop wearable or mobile technologies that can provide health or other information to users or their clinicians?  2 (0.2)  273 (26.7)  420 (41.1)  243 (23.8)  84 (8.2)  Develop wheelchairs and components that can self-adjust or can assist in overcoming obstacles  2 (0.2)  513 (50.2)  395 (38.6)  86 (8.4)  26 (2.5)    Missing Response  Critical  Important  Minor Importance  Not Important  Develop portable powered transfer devices that a person with a disability could use independently?  2 (0.2)  416 (40.7)  439 (43)  100 (9.8)  65 (6.4)  Develop sport or recreation technology to help you meet your fitness or weight loss goals?  2 (0.2)  375 (36.7)  429 (42)  160 (15.7)  56 (5.5)  Decrease the amount of time it takes to provide customized wheelchair components (i.e., 3D printed on site)?  1 (0.1)  331 (32.4)  413 (40.4)  201 (19.7)  76 (7.4)  Develop wearable or mobile technologies that can provide health or other information to users or their clinicians?  2 (0.2)  273 (26.7)  420 (41.1)  243 (23.8)  84 (8.2)  Develop wheelchairs and components that can self-adjust or can assist in overcoming obstacles  2 (0.2)  513 (50.2)  395 (38.6)  86 (8.4)  26 (2.5)  When asked to rank four areas of technology development, five “futuristic inventions” and four “futuristic mobility/transportation inventions” from least to most important using a 4- or 5-point scale (Tables III–V), smart wheelchair design, transfer devices, smart home technology, exoskeletons, and new power sources for wheelchairs received the highest rankings. Table III. Ranking Four Areas of Technology Development from Least Important to Most Important, n (%)   Missing Response  Most Important  Important  Somewhat Important  Least Important  Wearable or mobile technologies  49 (4.8)  195 (19.1)  219 (21.4)  272 (26.6)  287 (28.1)  Human–machine Interfaces  40 (3.9)  121 (11.8)  279 (27.3)  349 (34.1)  233 (22.8)  Smart wheelchair design  30 (2.9)  515 (50.4)  239 (23.4)  157 (15.4)  81 (7.9)  Alternative power sources  18 (1.8)  155 (15.2)  267 (26.1)  209 (20.5)  373 (36.5)    Missing Response  Most Important  Important  Somewhat Important  Least Important  Wearable or mobile technologies  49 (4.8)  195 (19.1)  219 (21.4)  272 (26.6)  287 (28.1)  Human–machine Interfaces  40 (3.9)  121 (11.8)  279 (27.3)  349 (34.1)  233 (22.8)  Smart wheelchair design  30 (2.9)  515 (50.4)  239 (23.4)  157 (15.4)  81 (7.9)  Alternative power sources  18 (1.8)  155 (15.2)  267 (26.1)  209 (20.5)  373 (36.5)  Table III. Ranking Four Areas of Technology Development from Least Important to Most Important, n (%)   Missing Response  Most Important  Important  Somewhat Important  Least Important  Wearable or mobile technologies  49 (4.8)  195 (19.1)  219 (21.4)  272 (26.6)  287 (28.1)  Human–machine Interfaces  40 (3.9)  121 (11.8)  279 (27.3)  349 (34.1)  233 (22.8)  Smart wheelchair design  30 (2.9)  515 (50.4)  239 (23.4)  157 (15.4)  81 (7.9)  Alternative power sources  18 (1.8)  155 (15.2)  267 (26.1)  209 (20.5)  373 (36.5)    Missing Response  Most Important  Important  Somewhat Important  Least Important  Wearable or mobile technologies  49 (4.8)  195 (19.1)  219 (21.4)  272 (26.6)  287 (28.1)  Human–machine Interfaces  40 (3.9)  121 (11.8)  279 (27.3)  349 (34.1)  233 (22.8)  Smart wheelchair design  30 (2.9)  515 (50.4)  239 (23.4)  157 (15.4)  81 (7.9)  Alternative power sources  18 (1.8)  155 (15.2)  267 (26.1)  209 (20.5)  373 (36.5)  Table IV. Ranking Five Futuristic Inventions from Least Important to Most Important, n (%)   Missing  Most Important  Important  Neutral  Somewhat Important  Least Important  Personal robot servant  46 (4.5)  124 (12.1)  156 (15.3)  220 (21.5)  248 (24.3)  228 (22.3)  Brain implant  41 (4)  83 (8.1)  147 (14.4)  242 (23.7)  272 (26.6)  237 (23.2)  Smart home technology  45 (4.4)  330 (32.3)  353 (34.5)  162 (15.9)  108 (10.6)  24 (2.3)  Transfer devices  22 (2.2)  402 (39.3)  258 (25.2)  165 (16.1)  136 (13.3)  39 (3.8)  Virtual reality  17 (1.7)  44 (4.3)  91 (8.9)  195 (19.1)  215 (21)  460 (45)    Missing  Most Important  Important  Neutral  Somewhat Important  Least Important  Personal robot servant  46 (4.5)  124 (12.1)  156 (15.3)  220 (21.5)  248 (24.3)  228 (22.3)  Brain implant  41 (4)  83 (8.1)  147 (14.4)  242 (23.7)  272 (26.6)  237 (23.2)  Smart home technology  45 (4.4)  330 (32.3)  353 (34.5)  162 (15.9)  108 (10.6)  24 (2.3)  Transfer devices  22 (2.2)  402 (39.3)  258 (25.2)  165 (16.1)  136 (13.3)  39 (3.8)  Virtual reality  17 (1.7)  44 (4.3)  91 (8.9)  195 (19.1)  215 (21)  460 (45)  Table IV. Ranking Five Futuristic Inventions from Least Important to Most Important, n (%)   Missing  Most Important  Important  Neutral  Somewhat Important  Least Important  Personal robot servant  46 (4.5)  124 (12.1)  156 (15.3)  220 (21.5)  248 (24.3)  228 (22.3)  Brain implant  41 (4)  83 (8.1)  147 (14.4)  242 (23.7)  272 (26.6)  237 (23.2)  Smart home technology  45 (4.4)  330 (32.3)  353 (34.5)  162 (15.9)  108 (10.6)  24 (2.3)  Transfer devices  22 (2.2)  402 (39.3)  258 (25.2)  165 (16.1)  136 (13.3)  39 (3.8)  Virtual reality  17 (1.7)  44 (4.3)  91 (8.9)  195 (19.1)  215 (21)  460 (45)    Missing  Most Important  Important  Neutral  Somewhat Important  Least Important  Personal robot servant  46 (4.5)  124 (12.1)  156 (15.3)  220 (21.5)  248 (24.3)  228 (22.3)  Brain implant  41 (4)  83 (8.1)  147 (14.4)  242 (23.7)  272 (26.6)  237 (23.2)  Smart home technology  45 (4.4)  330 (32.3)  353 (34.5)  162 (15.9)  108 (10.6)  24 (2.3)  Transfer devices  22 (2.2)  402 (39.3)  258 (25.2)  165 (16.1)  136 (13.3)  39 (3.8)  Virtual reality  17 (1.7)  44 (4.3)  91 (8.9)  195 (19.1)  215 (21)  460 (45)  Table V. Ranking Four Mobility/Transportation Futuristic Inventions from Least Important to Most Important, n (%)   Missing Response  Most Important  Important  Somewhat Important  Least Important  Self-driving or robotic powered wheelchair  49 (4.8)  165 (16.1)  224 (21.9)  291 (28.5)  293 (28.7)  New power sources for wheelchairs  36 (3.5)  313 (30.6)  336 (32.9)  236 (23.1)  101 (9.9)  Manual wheelchair that would fold or disassemble to fit in a suitcase  21 (2.1)  187 (18.3)  266 (26)  262 (25.6)  286 (28)  Exoskeleton for daily mobility  15 (1.5)  321 (31.4)  177 (17.3)  197 (19.3)  312 (30.5)    Missing Response  Most Important  Important  Somewhat Important  Least Important  Self-driving or robotic powered wheelchair  49 (4.8)  165 (16.1)  224 (21.9)  291 (28.5)  293 (28.7)  New power sources for wheelchairs  36 (3.5)  313 (30.6)  336 (32.9)  236 (23.1)  101 (9.9)  Manual wheelchair that would fold or disassemble to fit in a suitcase  21 (2.1)  187 (18.3)  266 (26)  262 (25.6)  286 (28)  Exoskeleton for daily mobility  15 (1.5)  321 (31.4)  177 (17.3)  197 (19.3)  312 (30.5)  Table V. Ranking Four Mobility/Transportation Futuristic Inventions from Least Important to Most Important, n (%)   Missing Response  Most Important  Important  Somewhat Important  Least Important  Self-driving or robotic powered wheelchair  49 (4.8)  165 (16.1)  224 (21.9)  291 (28.5)  293 (28.7)  New power sources for wheelchairs  36 (3.5)  313 (30.6)  336 (32.9)  236 (23.1)  101 (9.9)  Manual wheelchair that would fold or disassemble to fit in a suitcase  21 (2.1)  187 (18.3)  266 (26)  262 (25.6)  286 (28)  Exoskeleton for daily mobility  15 (1.5)  321 (31.4)  177 (17.3)  197 (19.3)  312 (30.5)    Missing Response  Most Important  Important  Somewhat Important  Least Important  Self-driving or robotic powered wheelchair  49 (4.8)  165 (16.1)  224 (21.9)  291 (28.5)  293 (28.7)  New power sources for wheelchairs  36 (3.5)  313 (30.6)  336 (32.9)  236 (23.1)  101 (9.9)  Manual wheelchair that would fold or disassemble to fit in a suitcase  21 (2.1)  187 (18.3)  266 (26)  262 (25.6)  286 (28)  Exoskeleton for daily mobility  15 (1.5)  321 (31.4)  177 (17.3)  197 (19.3)  312 (30.5)  Less than half of the participants (n = 471, 46.1%) felt that people with disabilities often (n = 349, 34.1%) or always (n = 122, 11.9%) play an active role in the decision-making process when getting new mobility equipment. Furthermore, the majority (n = 647, 63.3%) also said that people with disabilities rarely (n = 572, 56.0 %) or never (n = 75, 7.3%) receive adequate support to be able to maintain their assistive technology long term. Similar responses were seen between those with tetraplegia and paraplegia except for two distinct instances. More participants with tetraplegia ranked human–machine interfaces as important or most important than those with paraplegia (47.3% versus 33.4%, respectively; p = 0.017). More participants with paraplegia ranked a “manual wheelchair that would fold or disassemble” as important or most important than those with tetraplegia (49.6% versus 33.5%, respectively; p < 0.001). The most commonly cited barrier to obtaining new mobility-assistive technologies was the funding and procurement process, particularly cost, followed by knowledge of the user and the provider (Supplemental Table 3). Several themes on critical areas of research emerged from open-ended questions that generated a total of 1,199 comments (Supplemental Table 4). Additionally, 73 individuals provided more information about their own personal disability or medical condition and 16 provided comments about ways to improve the survey. Discussion This survey of over 1,000 consumers of mobility-assistive technologies can be used to develop a research and development “road map” that has been called for by PCAST and NAS. Consumers felt that mobility technology is important for all aspects of their lives. Participants also emphasized the importance of research and development on mobility-assistive technologies and the need to include people with disabilities in research and development. This latter concept is nicely summarized by two insightful quotes from participants: “A futurist once told me that tech design should include disabled people the same way the military includes test pilots. Test pilots are trained for their job evaluating planes and they are, mostly, listened to.” “Clinicians and researchers need to listen to veterans and people with disabilities. They should not make assumptions as to what is important. People with disabilities are smart too.” Open-ended responses revealed an opportunity for improving dissemination and education pathways to teach consumers about advances in assistive technology research. Some participants recommended developing products that are already on the market, suggesting that they were unaware of their availability. Other participants suggested specific ways consumers could be educated about technologies on the market, including expos, websites, or other tools. Participants felt that both consumers and providers needed education. Open-ended responses also emphasized the need for new and better technology but at lower cost. Participants felt that cost was a barrier to obtaining new devices, insofar as it affected availability of funding. The process of obtaining equipment was in many cases identified as laborious and inefficient. This places a responsibility on researchers to mitigate cost when developing devices and understanding how insurance policies may affect translation of the technology into the hands of consumers. Based on the results of the survey, a conceptual framework for mobility-assistive technology research and development was produced (Fig. 2). The process is person-centered and should be conducted with an understanding of the broader concepts of universal design, policy, clinical practice, and cost. Four research thrust areas represent mobility-assistive technology research and development priorities. Education, dissemination and knowledge transfer, and standards and reliability are critical outputs that must occur alongside the development and clinical testing of mobility-assistive technology. Not represented in this figure are the views regarding other research domains, such as regenerative medicine and devices to assist self-management. As this survey was specifically designed to elicit feedback on technology used for mobility, more in-depth surveys would be needed to develop similar frameworks for other domains. Some of this work has been reported elsewhere.20,21 Figure 2. View largeDownload slide Framework for mobility-assistive technology research and development. Figure 2. View largeDownload slide Framework for mobility-assistive technology research and development. All four research thrust areas identified for mobility-assistive technology have been noted as opportunities for rehabilitation research in an expert report published by the US Department of Veterans Affairs Office of Research and Development.22 The first thrust is “advanced wheelchair design.” Participants placed emphasis on technology that can avoid collisions or help to negotiate obstacles; lighter weight, folding, or smaller wheelchairs; and alternative power sources for wheelchairs. Maneuverability and transportability were seen as critical for mobility in the home, in the community, and during travel. Participants expressed a frustration with current transportation, a desire for expanded options in the field of accessible driving, and a need for change in airline policies and accessibility. The requests for alternative power sources was not surprising, given that batteries and electrical components are the most common components to fail and need replacement.23,24 Second, “smart device applications” that consumers can use in their home or wear are needed to help users track information and control their environments. Participants were particularly interested in smart home technology. Our own research on monitoring and coaching technologies has demonstrated ways that wearable devices and coaching technologies can be used by individuals with disabilities to promote health and physical activity.25 A third notable thrust is “human–machine interfaces.” Participants with limited arm or hand movement wanted alternative ways to control wheelchairs using the voice or face. Our own research in this area has focused on control strategies that are shared between the user and the device,26 universal interfaces that can control multiple devices, and better software algorithms.27,28 Finally, “assistive robotics and intelligent systems” were seen as a high priority. Participants highlighted the need for self-driving wheelchairs and navigation assistance, better exoskeleton technology for ambulation, and devices that assist with transfers of people or devices into and out of vehicles, or that transfer people into and out of wheelchairs. We plan to address this thrust by investigating how navigation, sensing, and control systems can adapt to the needs of the user and how they can learn from the user.28,29 We also plan to advance the field by developing devices that assist with transfers to and from wheelchairs and beds30 and that aim to improve safety of caregivers who perform the transfers.25,28 Consumers tended to agree with providers of technology31 with a few exceptions. Consumers placed priority on the same technologies as providers (devices that aid transfers and alternative power sources for wheelchairs), but they also emphasized a few more: smart home technology, exoskeletons, and smart wheelchair design. The majority of providers perceived that their clients play an active role in obtaining their assistive technologies. The majority of consumers, on the other hand, felt they rarely or never play an active role. This mismatch in perceptions suggests that providers may need to place more emphasis on patient-centered care and inclusiveness. However, the majority of providers and users (68.3% and 63.3%, respectively) agreed that people with disabilities rarely or never receive adequate long-term support to maintain their technologies. This suggests that access to rehabilitation technicians and engineers and training programs32 to teach consumers and providers how to perform basic maintenance are needed. The differences seen in opinions of those with tetraplegia and paraplegia were expected and likely reflect their respective functional needs. The majority of individuals with paraplegia used manual wheelchairs and were thus interested in more compact or folding manual wheelchairs. Those with tetraplegia and loss of arm function were more likely than those with paraplegia and full use of their arms to be interested in human–machine interfaces to help them control other devices. A few limitations to this research study deserve discussion. First, because this study involved completion of an online survey, we may have oversampled those who are technologically savvy or those who have Internet access. However, we did provide alternate means for completing the survey. Second, we sampled only a small proportion of the individuals in the U.S. who use mobility-assistive technologies. However, the participants ranged in age from 19 to 95 yr, used a variety of assistive technologies, and represented 98% of U.S. states and Puerto Rico. Respondents represented a wide range of experiences with technology, from those who were novices to those who used technology for 15 yr or more. We also sampled a large population of veterans. Third, participants can sometimes be over-enthusiastic about many items in a survey if they feel strongly about a topic. To address this potential bias in responses, we asked participants to rank technologies against each in order to stratify the importance of some devices over others. Fourth, responses on surveys can be biased toward the organization’s mission, especially if participants want to please the surveyor or feel strongly about the topic. We therefore consulted with the VERC to establish content validity, provided several open-ended questions to allow participants to provide feedback and ideas not mentioned in the survey, and based the content of the survey on responses provided by participants in our prior work.19 Qualitative data from open-ended questions was factored heavily into the conceptualization of the research thrusts. In order to ensure that results of this survey accurately reflect current consumer needs, it should be repeated frequently. Future surveys will assess needs and opinions of families and caregivers about mobility-assistive technology research and will measure consumer and provider awareness of available products, research outputs, and clinical practice guidelines and whether they are being used. Such information should drive research and development projects and program priorities. We also anticipate that these findings will be helpful in allowing consumer needs and wants to drive innovation in the field. The current study focused on participants of both veteran and civilian status, across a wide range of diagnoses, and with broad demographic range. A goal of future surveys should be to provide more specific research to explore how priorities differ between unique sets of individuals. Future researchers in the field of mobility-assistive technologies should take heed of one survey participant’s comment: “The biggest challenge with technology is not inventing or making it. It is making it reliable and simple enough for everyone.” Conclusion This survey of consumers who use mobility-assistive technologies can drive research and development priorities. Advanced wheelchair design, human–machine interfaces, smart device applications, and assistive robotics and intelligent systems are top priorities for future research efforts. Survey results also demonstrated the importance for researchers to understand the effects of policy and cost on translational research and to be involved in educating consumers and providers. Supplementary Material Supplementary material is available at Military Medicine online. Acknowledgments VAPHS Veterans Engineering Resource Center (VERC) and Paralyzed Veterans of America. Funding/COI This study was funded by the VA Center of Excellence on Wheelchairs and Associated Rehabilitation Engineering (B9250-C), the Paralyzed Veterans of America, and the National Institutes of Health (UL1-TR-001857). References 1 Brault MW: Americans with Disabilities: 2010 . Washington, DC, Census Bureau, 2012. Current Population Report P70–131. https://www2.census.gov/library/publications/2012/demo/p70-131.pdf. Accessed September 21, 2017. 2 Chaves ES, Boninger ML, Cooper R, Fitzgerald SG, Gray DB, Cooper RA: Assessing the influence of wheelchair technology on perception of participation in spinal cord injury. Arch Phys Med Rehabil  2004; 85( 11): 1854– 8. Google Scholar CrossRef Search ADS PubMed  3 Laferrier JZ, McFarland LV, Boninger ML, Cooper RA, Reiber GE: Wheeled mobility: factors influencing mobility and assistive technology in veterans and service members with major traumatic limb loss from Vietnam war and OIF/OEF conflicts. J Rehabil Res Dev  2010; 47( 4): 349– 60. Google Scholar CrossRef Search ADS PubMed  4 Salminen AL, Brandt A, Samuelsson K, Toytari O, Malmivaara A: Mobility devices to promote activity and participation: a systematic review. J Rehabi Med  2009; 41( 9): 697– 706. Google Scholar CrossRef Search ADS   5 Scherer MJ: Assistive Technology: Matching Device and Consumer for Successful Rehabilitation , Ed 1, American Psychological Association (APA), Washington, DC, December 31, 2002. Google Scholar CrossRef Search ADS   6 Davies A, De Souza LH, Frank AO: Changes in the quality of life in severely disabled people following provision of powered indoor/outdoor chairs. Disabil Rehabil.  2003; 25( 6): 286– 90. Google Scholar CrossRef Search ADS PubMed  7 Edwards K, McCluskey A: A survey of adult power wheelchair and scooter users. Disabil Rehabil Assist Technol  2010; 5( 6): 411– 9. Google Scholar CrossRef Search ADS PubMed  8 Trefler E, Fitzgerald SG, Hobson DA, Bursick T, Joseph R: Outcomes of wheelchair systems intervention with residents of long-term care facilities. Assist Technol.  2004; 16( 1): 18– 27. Google Scholar CrossRef Search ADS PubMed  9 Greer N, Brasure M, Wilt TJ: AHRQ Comparative Effectiveness Reviews. In: Wheeled Mobility (Wheelchair) Service Delivery . Rockville (MD), Agency for Healthcare Research and Quality (US), 2012. 10 LaPlante MP, Kaye HS: Demographics and trends in wheeled mobility equipment use and accessibility in the community. Assist Technol  2010; 22( 1): 3– 17; quiz 19. Google Scholar CrossRef Search ADS PubMed  11 Organization WH. Global Cooperation on Assistive Technology (GATE). 2017; http://www.who.int/phi/implementation/assistive_technology/en/. Accessed November 9th, 2017. 12 Paralyzed Veterans of America. 2016 Women Veterans Case Study.(online). Accessed May 27, 2016. 13 Simpson LA, Eng JJ, Hsieh JT, Wolfe DL: The health and life priorities of individuals with spinal cord injury: a systematic review. J Neurotrauma  2012; 29( 8): 1548– 55. Google Scholar CrossRef Search ADS PubMed  14 Department of Defense Appropriations for 2016. Hearings before a subcommittee of the Committee on Appropriations. House of Representatives. 114th Congress. First Session. Subcommittee on Defense. U.S. Government Publishing Office. Chairman, R. Frelinghuysen. Washington, 2015. Pages 280– 1. 15 Military Constructions, Veterans Affairs, and Related Agencies Appropriations for 2016. Hearings before a subcommittee of the Committee on Appropriations. House of Representatives. 114th Congress. First Session. Subcommittee on Military Constructions, Veterans Affairs, and Related Agencies. Chairman, C. Dent. Washington, 2015. Pages 733– 4. 16 United States General Accounting Office: Testimony before the Subcommittee on Social Security, Committee on Ways and Means. House of Representatives. 114th Congress. SSA Disability Programs. Fully Updating Disability Criteria has Implications for Program Design. Director, R. Robertson. GAO-02-919T. Page 1. 17 National Academies of Sciences, Engineering, and Medicine: The Promise of Assistive Technology to Enhance Activity and Work Participation. http://nationalacademies.org/hmd/reports/2017/promise-of-assistive-technology-to-enhance-activity-and-work-participation.aspx. Accessed October 16, 2017. 18 Executive Office of the President: President’s Council of Advisors on Science and Technology. Report to the President. Independence, Technology, and Connection in Older Age. March 2016. 19 Kelleher A, Dicianno BE, Eckstein S, Schein RM, Pearlman J, Cooper RA: Consumer feedback to steer the future of assistive technology research and development: a pilot study. Top SCI Rehabil  2017; 23( 2): 89– 97. 20 van Middendorp JJ, Allison HC, Ahuja S, et al.  : Top ten research priorities for spinal cord injury: the methodology and results of a British priority setting partnership. Spinal Cord  2016; 54( 5): 341– 6. Google Scholar CrossRef Search ADS PubMed  21 Anderson KD: Targeting recovery: priorities of the spinal cord-injured population. J neurotrauma  2004; 21( 10): 1371– 83. Google Scholar CrossRef Search ADS PubMed  22 Ommaya AK, Adams KM, Allman RM, et al.  : Opportunities in rehabilitation research. J Rehabil Res Dev  2013; 50( 6): vii. Google Scholar CrossRef Search ADS PubMed  23 Toro ML, Worobey L, Boninger ML, Cooper RA, Pearlman J: Type and frequency of reported wheelchair repairs and related adverse consequences among people with spinal cord injury. Arch Phys Med Rehabil  2016; 97( 10): 1753– 60. Google Scholar CrossRef Search ADS PubMed  24 Worobey L, Oyster M, Nemunaitis G, Cooper R, Boninger ML: Increases in wheelchair breakdowns, repairs, and adverse consequences for people with traumatic spinal cord injury. Am J Phys Med Rehabi  2012; 91( 6): 463– 9. Google Scholar CrossRef Search ADS   25 Cooper RA, Koontz AM, Ding D, Kelleher A, Rice I, Cooper R: Manual wheeled mobility – current and future developments from the human engineering research laboratories. Disabil Rehabil  2010; 32( 26): 2210– 21. Google Scholar CrossRef Search ADS PubMed  26 Cowan RE, Fregly BJ, Boninger ML, Chan L, Rodgers MM, Reinkensmeyer DJ: Recent trends in assistive technology for mobility. J Neuroeng Rehabil  2012; 9: 20. Google Scholar CrossRef Search ADS PubMed  27 Dicianno BE, Cooper RA, Coltellaro J: Joystick control for powered mobility: current state of technology and future directions. Phys Med Rehabil Clin North Am  2010; 21( 1): 79– 86. Google Scholar CrossRef Search ADS   28 Cooper RA: Wheelchair research progress, perspectives, and transformation. J Rehabil Res Dev  2012; 49( 1): 1– 5. Google Scholar CrossRef Search ADS PubMed  29 Cooper RA, Cooper R: Quality-of-life technology for people with spinal cord injuries. Phys Med Rehabil Clin North Am  2010; 21( 1): 1– 13. Google Scholar CrossRef Search ADS   30 Sivaprakasam A, Wang H, Cooper RA, Koontz AM: Innovation in transfer assist technologies for persons with severe disabilities and their caregivers. IEEE Potentials  2017; 36( 1): 34– 41. Google Scholar CrossRef Search ADS   31 Brad E, Dicianno MJJ, Sergeant G, et al.  : The future of the provision process for mobility assistive technology: a survey of providers. Disabil Rehabil Assist Technol  2018. In press. 32 Toro ML, Bird E, Oyster M, et al.  : Development of a wheelchair maintenance training programme and questionnaire for clinicians and wheelchair users. Disabil Rehabil Assist Technol  2017; 12( 8): 843– 51. Google Scholar CrossRef Search ADS PubMed  Author notes The contents of this publication do not represent the views of the Department of Veterans Affairs or the United States Government. Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2018. This work is written by (a) US Government employee(s) and is in the public domain in the US. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Military Medicine Oxford University Press

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Abstract

Abstract Introduction A total of 3.6 million Americans and over 250,000 veterans use wheelchairs. The need for advancements in mobility-assistive technologies is continually growing due to advances in medicine and rehabilitation that preserve and prolong the lives of people with disabilities, increases in the senior population, and increases in the number of veterans and civilians involved in conflict situations. The purpose of this study is to survey a large sample of veterans and other consumers with disabilities who use mobility-assistive technologies to identify priorities for future research and development. Materials and Methods This survey asked participants to provide opinions on the importance of developing various mobility-assistive technologies and to rank the importance of certain technologies. Participants were also asked to provide open-ended comments and suggestions. Results A total of 1,022 individuals, including 500 veterans, from 49 states within the USA and Puerto Rico completed the survey. The average age of respondents was 54.3 yr, and they represented both new and experienced users of mobility-assistive technologies. The largest diagnostic group was spinal cord injury (SCI) (N = 491, 48.0%). Several themes on critical areas of research emerged from the open-ended questions, which generated a total of 1,199 comments. Conclusion This survey revealed several themes for future research and development. Advanced wheelchair design, smart device applications, human–machine interfaces, and assistive robotics and intelligent systems emerged as priorities. Survey results also demonstrated the importance for researchers to understand the effects of policy and cost on translational research and to be involved in educating both consumers and providers. Introduction A total of 3.6 million Americans1 and over 250,000 veterans use wheelchairs. (Personal communications among Penny Nechanicky [National Director], Ru Gakhar [Prosthetic Program Manager], Prosthetic and Sensory Aids Service, Department of Veterans Affairs, Rory Cooper, and Brad Dicianno. July 24, 2015.) Mobility-assistive technologies such as wheelchairs and scooters improve function, home and community integration,2–5 quality of life,6,7 and comfort.6,8 The number of users of these technologies is continually growing due to advances in medicine and rehabilitation that preserve and prolong the lives of people with disabilities, increases in the senior population, and increases in the number of veterans and civilians involved in conflict situations.1,9,10 Despite the availability of mobility-assistive technologies to the various populations in need, The World Health Organization (WHO) estimates that over 1 billion people currently need assistive technologies, but that only 1 in 10 have access. They estimate that by 2050, due to the growth of disability populations, 2 billion people will be in need.11 In cooperation with the United States Agency for International Development (USAID), the United Nations, and other agencies, WHO established the Global Cooperation on Assistive Technology (GATE), which is a global effort to improve access to high-quality affordable assistive products.11 In order to reach the goal of global access, a research agenda for assistive technologies must first be developed. The need for additional support for mobility is also a top priority of veterans with disabilities. A report by Paralyzed Veterans of America (PVA) named mobility and independence among the top three health concerns of female veterans who were injured or diagnosed with a neurological condition.12 We are not aware of a similar study conducted on men. Simpson et al. published a systematic review13 that summarized 24 studies (5,262 total participants with spinal cord injury [SCI]) that directly surveyed individuals with SCI about their health and function priorities. This review revealed that within the health domain, motor function, bowel and bladder function, and sexual function were the top three priorities. Those with paraplegia prioritized mobility, whereas those with tetraplegia prioritized hand function. General health and relationships were also cited as priorities. Another systematic review of six studies (1,222 total participants with SCI) revealed that mobility was a top concern after SCI. Research and development to advance mobility-assistive technologies could begin to address these concerns. In two hearings before Subcommittees of the Appropriations Committee of the House of Representatives, testimony was given by high ranking government officials about the importance of research on mobility-assistive technologies. Vice Admiral Matthew Nathan, the 37th Surgeon General of the Navy and Chief of the Navy’s Bureau of Medicine and Surgery, stressed the need to continue funding for research specifically geared to improve the mobility of injured veterans.14 Robert A. MacDonald, Secretary, Department of VA, requested support of Congress for Veteran health care and research.15 Additionally, in testimony before the Subcommittee on Social Security, Committee on Ways and Means, Robert E. Robertson, Director, Education, Workforce, and Income Security Issues, specifically mentioned wheelchair design as a scientific advancement that has allowed individuals with disabilities to participate in society, including seeking and maintaining employment.16 The Social Security Administration, with encouragement from the Office of Management and Budget, commissioned the National Academy of Medicine (NAM) to conduct a study on advances in wheelchairs and other mobility devices on employability of people with disabilities. Because of this growing need for better technology, research aims must be outlined and prioritized. The National Academies of Sciences, Engineering, and Medicine (NAS), in collaboration with the Social Security Administration, provided a report analyzing the use of current assistive technologies and called for development of research priorities.17 The President’s Council of Advisors on Science and Technology (PCAST) report recommended that the VA and Centers for Medicare and Medicaid Services create a “road map” for mobility-assistive technology research and that more federal support of research be made available.18 However, this road map has yet to be developed. We began to develop such a road map in our preliminary work. We conducted a pilot study of 112 individuals who use mobility-assistive technologies to characterize their needs and opinions.19 In parallel, we also surveyed 161 professionals involved in the provision of mobility devices both within and outside VA.31 These surveys revealed several themes that helped us to construct a preliminary road map, but a larger and more diverse sample of users was needed. The purpose of the present study was to evaluate the opinions of over 1,000 users of mobility-assistive technologies to inform a research agenda and identify priorities that are aligned with the goals and desires of the users. Methods The survey (see Appendix 1) was developed by experts in the field of assistive technology at the Human Engineering Research Laboratories (HERL) in Pittsburgh, PA, USA. The VA Pittsburgh Healthcare System Veterans Engineering Resource Center (VERC) assisted the team in establishing content validity. The study was approved by the Institutional Review Board of the University of Pittsburgh as an expedited study. The survey was administered through the Research Electronic Data Capture (REDCap) system (Vanderbilt University, Nashville, TN, USA), a secure, web-based software system sponsored by the Clinical Translational and Science Institute at the University of Pittsburgh. The survey was designed to take less than 10 min to complete and was based on a previously conducted survey.19 Participants could complete the survey online using a computer or any mobile device. Alternately, they had the option to contact a study coordinator to complete the questionnaire by phone or mail. The home page provided a brief description of the project and an overview of informed consent, asking the participant to answer whether they consented to taking the survey. Participants were asked to provide basic demographic information and to choose from a list of pre-defined diagnoses or list their own diagnosis under “other.” Participants were allowed to list multiple diagnoses. Some personally identifiable information was collected in the questionnaire to ensure that there were no repeat responses; however, the questionnaire was anonymized by the coordinator prior to analysis. Participants were asked how important it is to carry out certain activities if technology could accommodate them. The next set of questions asked participants to provide individual rankings of importance of developing various technologies that were ranked highly in our previous survey.19 The survey also required participants to rank these items against each other in terms of order of importance. Participants were asked how often they play an active role in the decision-making process when getting new mobility equipment and how often they receive adequate support to be able to maintain their assistive technology long term. Participants were also asked to respond to several open-ended questions or statements, including identifying barriers when obtaining new mobility-assistive technologies. Inclusion criteria were age 18 yr or older, U.S. citizen, an individual who uses mobility-related assistive devices, and answers “yes” to providing consent to participating in the survey. There were no specific exclusion criteria. Referral sampling was used for this study wherein initial participants were asked to distribute recruitment materials to their own networks. Participants were recruited in person at athletic events, advocacy meetings, and at meetings of veteran service organizations for veterans and people with disabilities. Flyers were sent via email to personal contacts and professional listservs at disability and veteran service organizations, veteran support groups, health care agencies, hospitals, clinics, government organizations, and universities. Personal contacts then distributed recruitment materials through social media and email outreach. Flyers were posted on our own organization’s website and social media pages. Participants were also recruited from our local research registries, which contain contact information of individuals who have expressed interest in participating in research. Recruitment materials were advertised in magazines, targeted social media ads, and newsletters and also mentioned in radio broadcasts. Potential participants were directed to access the web link directly or to contact a study coordinator. Descriptive statistics for each multiple-choice item were reported using frequency counts and percentages. Average rankings were examined for sets of items that were placed in order by respondents. For respondents with SCI, a sub-analysis was performed to compare differences in the research and development priorities of those with paraplegia versus tetraplegia. Chi-squared tests of independence were used to determine the relationship between the rankings of each item and group membership. All descriptive statistics were performed using SPSS v24.0 (IBM Corp., Armonk, NY, USA). Open-ended responses were examined in detail to identify overall patterns and themes, as well as unique, creative solutions to the issues of mobility. Results A total of 1,127 individuals were sent recruitment materials and asked to distribute further to their own contacts. Also, targeted social media ads reached 41,129 unique people. Referral sampling resulted in 1,178 potential participants. Figure 1 displays an exclusion diagram demonstrating inclusion of 1,022 participants based on aforementioned criteria. Table I displays demographic characteristics of participants. Average age was 54.3 (STD 14.6, range 19–95) yr. A total of 500 (48.9%) were veterans. Participants lived in 49 different states within the U.S. and Puerto Rico. Four individuals required help from a clinical coordinator to complete the survey via phone and one via mail; the rest completed the survey electronically. Figure 1. View largeDownload slide Exclusion flow chart. Figure 1. View largeDownload slide Exclusion flow chart. Table I. Demographic Information for Consumers (n = 1,022)   n  %  Types of assistive devices used (participants could choose more than one)   Manual wheelchair  596  58.3   Power wheelchair  481  47.1   Scooter  98  9.6   Lower extremity prosthesis  49  4.8   Lower extremity orthosis (brace)  134  13.1   Assistive device (e.g., cane, crutch, and walker)  387  37.9   Other  99  9.7  Length of time device(s) used   1 yr or less  58  5.7   2–5 yr  235  23.0   6–10 yr  168  16.4   11–15 yr  135  13.2   More than 15 yr  423  41.4   Missing/did not answer  3  <1.0  Gender   Female  367  35.9   Male  655  64.1  Highest level of education   Associate’s degree  218  21.3   Bachelor’s degree  284  27.8   Doctorate level degree – MD, DO, PhD  60  5.9   High school diploma or equivalent (GED)  245  24.0   Master’s degree  178  17.4   Other advanced degree  36  3.5   Missing  1  <1.0  Veteran of US Armed Forces   No  520  50.9   Yes  500  48.9   Missing  2  <1.0  Type of community setting in which you live   Rural (country)  232  22.7   Suburban  460  45.0   Urban (city)  322  31.5   Missing  8  <1.0  Ethnicity   Hispanic or Latino  63  6.2   Not Hispanic or Latino  954  93.3   Missing  5  <1.0  Race   White/Caucasian  841  82.3   Black or African American  78  7.6   Two or more races  49  4.8   Other  32  3.1   American Indian or Alaskan Native  9  <1.0   Asian  7  <1.0   Native Hawaiian or other Pacific Islander  4  <1.0   Missing  2  <1.0  If a veteran, obtain assistive devices through VA   Yes  439  87.8   No  59  11.8   Missing  2  <1.0  Household income   Under $15,000  115  11.3   $15,000–$24,999  109  10.7   $25,000–$49,999  195  19.1   $50,000–$74,999  150  14.7   $75,000–$100,000  117  11.4   Over $100,000  149  14.6   I don’t know  28  2.7   I prefer not to answer  158  15.5   Missing  1  <1.0    n  %  Types of assistive devices used (participants could choose more than one)   Manual wheelchair  596  58.3   Power wheelchair  481  47.1   Scooter  98  9.6   Lower extremity prosthesis  49  4.8   Lower extremity orthosis (brace)  134  13.1   Assistive device (e.g., cane, crutch, and walker)  387  37.9   Other  99  9.7  Length of time device(s) used   1 yr or less  58  5.7   2–5 yr  235  23.0   6–10 yr  168  16.4   11–15 yr  135  13.2   More than 15 yr  423  41.4   Missing/did not answer  3  <1.0  Gender   Female  367  35.9   Male  655  64.1  Highest level of education   Associate’s degree  218  21.3   Bachelor’s degree  284  27.8   Doctorate level degree – MD, DO, PhD  60  5.9   High school diploma or equivalent (GED)  245  24.0   Master’s degree  178  17.4   Other advanced degree  36  3.5   Missing  1  <1.0  Veteran of US Armed Forces   No  520  50.9   Yes  500  48.9   Missing  2  <1.0  Type of community setting in which you live   Rural (country)  232  22.7   Suburban  460  45.0   Urban (city)  322  31.5   Missing  8  <1.0  Ethnicity   Hispanic or Latino  63  6.2   Not Hispanic or Latino  954  93.3   Missing  5  <1.0  Race   White/Caucasian  841  82.3   Black or African American  78  7.6   Two or more races  49  4.8   Other  32  3.1   American Indian or Alaskan Native  9  <1.0   Asian  7  <1.0   Native Hawaiian or other Pacific Islander  4  <1.0   Missing  2  <1.0  If a veteran, obtain assistive devices through VA   Yes  439  87.8   No  59  11.8   Missing  2  <1.0  Household income   Under $15,000  115  11.3   $15,000–$24,999  109  10.7   $25,000–$49,999  195  19.1   $50,000–$74,999  150  14.7   $75,000–$100,000  117  11.4   Over $100,000  149  14.6   I don’t know  28  2.7   I prefer not to answer  158  15.5   Missing  1  <1.0  View Large Table I. Demographic Information for Consumers (n = 1,022)   n  %  Types of assistive devices used (participants could choose more than one)   Manual wheelchair  596  58.3   Power wheelchair  481  47.1   Scooter  98  9.6   Lower extremity prosthesis  49  4.8   Lower extremity orthosis (brace)  134  13.1   Assistive device (e.g., cane, crutch, and walker)  387  37.9   Other  99  9.7  Length of time device(s) used   1 yr or less  58  5.7   2–5 yr  235  23.0   6–10 yr  168  16.4   11–15 yr  135  13.2   More than 15 yr  423  41.4   Missing/did not answer  3  <1.0  Gender   Female  367  35.9   Male  655  64.1  Highest level of education   Associate’s degree  218  21.3   Bachelor’s degree  284  27.8   Doctorate level degree – MD, DO, PhD  60  5.9   High school diploma or equivalent (GED)  245  24.0   Master’s degree  178  17.4   Other advanced degree  36  3.5   Missing  1  <1.0  Veteran of US Armed Forces   No  520  50.9   Yes  500  48.9   Missing  2  <1.0  Type of community setting in which you live   Rural (country)  232  22.7   Suburban  460  45.0   Urban (city)  322  31.5   Missing  8  <1.0  Ethnicity   Hispanic or Latino  63  6.2   Not Hispanic or Latino  954  93.3   Missing  5  <1.0  Race   White/Caucasian  841  82.3   Black or African American  78  7.6   Two or more races  49  4.8   Other  32  3.1   American Indian or Alaskan Native  9  <1.0   Asian  7  <1.0   Native Hawaiian or other Pacific Islander  4  <1.0   Missing  2  <1.0  If a veteran, obtain assistive devices through VA   Yes  439  87.8   No  59  11.8   Missing  2  <1.0  Household income   Under $15,000  115  11.3   $15,000–$24,999  109  10.7   $25,000–$49,999  195  19.1   $50,000–$74,999  150  14.7   $75,000–$100,000  117  11.4   Over $100,000  149  14.6   I don’t know  28  2.7   I prefer not to answer  158  15.5   Missing  1  <1.0    n  %  Types of assistive devices used (participants could choose more than one)   Manual wheelchair  596  58.3   Power wheelchair  481  47.1   Scooter  98  9.6   Lower extremity prosthesis  49  4.8   Lower extremity orthosis (brace)  134  13.1   Assistive device (e.g., cane, crutch, and walker)  387  37.9   Other  99  9.7  Length of time device(s) used   1 yr or less  58  5.7   2–5 yr  235  23.0   6–10 yr  168  16.4   11–15 yr  135  13.2   More than 15 yr  423  41.4   Missing/did not answer  3  <1.0  Gender   Female  367  35.9   Male  655  64.1  Highest level of education   Associate’s degree  218  21.3   Bachelor’s degree  284  27.8   Doctorate level degree – MD, DO, PhD  60  5.9   High school diploma or equivalent (GED)  245  24.0   Master’s degree  178  17.4   Other advanced degree  36  3.5   Missing  1  <1.0  Veteran of US Armed Forces   No  520  50.9   Yes  500  48.9   Missing  2  <1.0  Type of community setting in which you live   Rural (country)  232  22.7   Suburban  460  45.0   Urban (city)  322  31.5   Missing  8  <1.0  Ethnicity   Hispanic or Latino  63  6.2   Not Hispanic or Latino  954  93.3   Missing  5  <1.0  Race   White/Caucasian  841  82.3   Black or African American  78  7.6   Two or more races  49  4.8   Other  32  3.1   American Indian or Alaskan Native  9  <1.0   Asian  7  <1.0   Native Hawaiian or other Pacific Islander  4  <1.0   Missing  2  <1.0  If a veteran, obtain assistive devices through VA   Yes  439  87.8   No  59  11.8   Missing  2  <1.0  Household income   Under $15,000  115  11.3   $15,000–$24,999  109  10.7   $25,000–$49,999  195  19.1   $50,000–$74,999  150  14.7   $75,000–$100,000  117  11.4   Over $100,000  149  14.6   I don’t know  28  2.7   I prefer not to answer  158  15.5   Missing  1  <1.0  View Large Supplemental Table 1 displays diagnoses of participants. The largest diagnostic group was spinal cord injury (SCI) (N = 491, 48.0%). Of the participants with SCI, 290 (59.1%) had paraplegia, 188 (38.3%) had tetraplegia, and 13 (2.6%) did not report this classification. A total of 212 (43.2%) reported complete SCI, 252 (51.3%) reported incomplete SCI, and 27 (5.5%) did not report completeness of lesion. Some individuals indicating “other” diagnoses were reclassified into one of the pre-defined categories if clinically appropriate. When asked about how important it would be to carry out certain activities if technology could accommodate them, the majority of respondents identified all four categories of activities as critical/important (Supplemental Table 1). Participants were also asked how important it would be for researchers to develop specific technologies. Although most technologies were rated as critical or important, wheelchairs and components that could self-adjust or could assist in overcoming obstacles gained the most critical ratings (Table II). Table II. Ranking of Key Areas for Research from Critical to not Important, n (%)   Missing Response  Critical  Important  Minor Importance  Not Important  Develop portable powered transfer devices that a person with a disability could use independently?  2 (0.2)  416 (40.7)  439 (43)  100 (9.8)  65 (6.4)  Develop sport or recreation technology to help you meet your fitness or weight loss goals?  2 (0.2)  375 (36.7)  429 (42)  160 (15.7)  56 (5.5)  Decrease the amount of time it takes to provide customized wheelchair components (i.e., 3D printed on site)?  1 (0.1)  331 (32.4)  413 (40.4)  201 (19.7)  76 (7.4)  Develop wearable or mobile technologies that can provide health or other information to users or their clinicians?  2 (0.2)  273 (26.7)  420 (41.1)  243 (23.8)  84 (8.2)  Develop wheelchairs and components that can self-adjust or can assist in overcoming obstacles  2 (0.2)  513 (50.2)  395 (38.6)  86 (8.4)  26 (2.5)    Missing Response  Critical  Important  Minor Importance  Not Important  Develop portable powered transfer devices that a person with a disability could use independently?  2 (0.2)  416 (40.7)  439 (43)  100 (9.8)  65 (6.4)  Develop sport or recreation technology to help you meet your fitness or weight loss goals?  2 (0.2)  375 (36.7)  429 (42)  160 (15.7)  56 (5.5)  Decrease the amount of time it takes to provide customized wheelchair components (i.e., 3D printed on site)?  1 (0.1)  331 (32.4)  413 (40.4)  201 (19.7)  76 (7.4)  Develop wearable or mobile technologies that can provide health or other information to users or their clinicians?  2 (0.2)  273 (26.7)  420 (41.1)  243 (23.8)  84 (8.2)  Develop wheelchairs and components that can self-adjust or can assist in overcoming obstacles  2 (0.2)  513 (50.2)  395 (38.6)  86 (8.4)  26 (2.5)  Table II. Ranking of Key Areas for Research from Critical to not Important, n (%)   Missing Response  Critical  Important  Minor Importance  Not Important  Develop portable powered transfer devices that a person with a disability could use independently?  2 (0.2)  416 (40.7)  439 (43)  100 (9.8)  65 (6.4)  Develop sport or recreation technology to help you meet your fitness or weight loss goals?  2 (0.2)  375 (36.7)  429 (42)  160 (15.7)  56 (5.5)  Decrease the amount of time it takes to provide customized wheelchair components (i.e., 3D printed on site)?  1 (0.1)  331 (32.4)  413 (40.4)  201 (19.7)  76 (7.4)  Develop wearable or mobile technologies that can provide health or other information to users or their clinicians?  2 (0.2)  273 (26.7)  420 (41.1)  243 (23.8)  84 (8.2)  Develop wheelchairs and components that can self-adjust or can assist in overcoming obstacles  2 (0.2)  513 (50.2)  395 (38.6)  86 (8.4)  26 (2.5)    Missing Response  Critical  Important  Minor Importance  Not Important  Develop portable powered transfer devices that a person with a disability could use independently?  2 (0.2)  416 (40.7)  439 (43)  100 (9.8)  65 (6.4)  Develop sport or recreation technology to help you meet your fitness or weight loss goals?  2 (0.2)  375 (36.7)  429 (42)  160 (15.7)  56 (5.5)  Decrease the amount of time it takes to provide customized wheelchair components (i.e., 3D printed on site)?  1 (0.1)  331 (32.4)  413 (40.4)  201 (19.7)  76 (7.4)  Develop wearable or mobile technologies that can provide health or other information to users or their clinicians?  2 (0.2)  273 (26.7)  420 (41.1)  243 (23.8)  84 (8.2)  Develop wheelchairs and components that can self-adjust or can assist in overcoming obstacles  2 (0.2)  513 (50.2)  395 (38.6)  86 (8.4)  26 (2.5)  When asked to rank four areas of technology development, five “futuristic inventions” and four “futuristic mobility/transportation inventions” from least to most important using a 4- or 5-point scale (Tables III–V), smart wheelchair design, transfer devices, smart home technology, exoskeletons, and new power sources for wheelchairs received the highest rankings. Table III. Ranking Four Areas of Technology Development from Least Important to Most Important, n (%)   Missing Response  Most Important  Important  Somewhat Important  Least Important  Wearable or mobile technologies  49 (4.8)  195 (19.1)  219 (21.4)  272 (26.6)  287 (28.1)  Human–machine Interfaces  40 (3.9)  121 (11.8)  279 (27.3)  349 (34.1)  233 (22.8)  Smart wheelchair design  30 (2.9)  515 (50.4)  239 (23.4)  157 (15.4)  81 (7.9)  Alternative power sources  18 (1.8)  155 (15.2)  267 (26.1)  209 (20.5)  373 (36.5)    Missing Response  Most Important  Important  Somewhat Important  Least Important  Wearable or mobile technologies  49 (4.8)  195 (19.1)  219 (21.4)  272 (26.6)  287 (28.1)  Human–machine Interfaces  40 (3.9)  121 (11.8)  279 (27.3)  349 (34.1)  233 (22.8)  Smart wheelchair design  30 (2.9)  515 (50.4)  239 (23.4)  157 (15.4)  81 (7.9)  Alternative power sources  18 (1.8)  155 (15.2)  267 (26.1)  209 (20.5)  373 (36.5)  Table III. Ranking Four Areas of Technology Development from Least Important to Most Important, n (%)   Missing Response  Most Important  Important  Somewhat Important  Least Important  Wearable or mobile technologies  49 (4.8)  195 (19.1)  219 (21.4)  272 (26.6)  287 (28.1)  Human–machine Interfaces  40 (3.9)  121 (11.8)  279 (27.3)  349 (34.1)  233 (22.8)  Smart wheelchair design  30 (2.9)  515 (50.4)  239 (23.4)  157 (15.4)  81 (7.9)  Alternative power sources  18 (1.8)  155 (15.2)  267 (26.1)  209 (20.5)  373 (36.5)    Missing Response  Most Important  Important  Somewhat Important  Least Important  Wearable or mobile technologies  49 (4.8)  195 (19.1)  219 (21.4)  272 (26.6)  287 (28.1)  Human–machine Interfaces  40 (3.9)  121 (11.8)  279 (27.3)  349 (34.1)  233 (22.8)  Smart wheelchair design  30 (2.9)  515 (50.4)  239 (23.4)  157 (15.4)  81 (7.9)  Alternative power sources  18 (1.8)  155 (15.2)  267 (26.1)  209 (20.5)  373 (36.5)  Table IV. Ranking Five Futuristic Inventions from Least Important to Most Important, n (%)   Missing  Most Important  Important  Neutral  Somewhat Important  Least Important  Personal robot servant  46 (4.5)  124 (12.1)  156 (15.3)  220 (21.5)  248 (24.3)  228 (22.3)  Brain implant  41 (4)  83 (8.1)  147 (14.4)  242 (23.7)  272 (26.6)  237 (23.2)  Smart home technology  45 (4.4)  330 (32.3)  353 (34.5)  162 (15.9)  108 (10.6)  24 (2.3)  Transfer devices  22 (2.2)  402 (39.3)  258 (25.2)  165 (16.1)  136 (13.3)  39 (3.8)  Virtual reality  17 (1.7)  44 (4.3)  91 (8.9)  195 (19.1)  215 (21)  460 (45)    Missing  Most Important  Important  Neutral  Somewhat Important  Least Important  Personal robot servant  46 (4.5)  124 (12.1)  156 (15.3)  220 (21.5)  248 (24.3)  228 (22.3)  Brain implant  41 (4)  83 (8.1)  147 (14.4)  242 (23.7)  272 (26.6)  237 (23.2)  Smart home technology  45 (4.4)  330 (32.3)  353 (34.5)  162 (15.9)  108 (10.6)  24 (2.3)  Transfer devices  22 (2.2)  402 (39.3)  258 (25.2)  165 (16.1)  136 (13.3)  39 (3.8)  Virtual reality  17 (1.7)  44 (4.3)  91 (8.9)  195 (19.1)  215 (21)  460 (45)  Table IV. Ranking Five Futuristic Inventions from Least Important to Most Important, n (%)   Missing  Most Important  Important  Neutral  Somewhat Important  Least Important  Personal robot servant  46 (4.5)  124 (12.1)  156 (15.3)  220 (21.5)  248 (24.3)  228 (22.3)  Brain implant  41 (4)  83 (8.1)  147 (14.4)  242 (23.7)  272 (26.6)  237 (23.2)  Smart home technology  45 (4.4)  330 (32.3)  353 (34.5)  162 (15.9)  108 (10.6)  24 (2.3)  Transfer devices  22 (2.2)  402 (39.3)  258 (25.2)  165 (16.1)  136 (13.3)  39 (3.8)  Virtual reality  17 (1.7)  44 (4.3)  91 (8.9)  195 (19.1)  215 (21)  460 (45)    Missing  Most Important  Important  Neutral  Somewhat Important  Least Important  Personal robot servant  46 (4.5)  124 (12.1)  156 (15.3)  220 (21.5)  248 (24.3)  228 (22.3)  Brain implant  41 (4)  83 (8.1)  147 (14.4)  242 (23.7)  272 (26.6)  237 (23.2)  Smart home technology  45 (4.4)  330 (32.3)  353 (34.5)  162 (15.9)  108 (10.6)  24 (2.3)  Transfer devices  22 (2.2)  402 (39.3)  258 (25.2)  165 (16.1)  136 (13.3)  39 (3.8)  Virtual reality  17 (1.7)  44 (4.3)  91 (8.9)  195 (19.1)  215 (21)  460 (45)  Table V. Ranking Four Mobility/Transportation Futuristic Inventions from Least Important to Most Important, n (%)   Missing Response  Most Important  Important  Somewhat Important  Least Important  Self-driving or robotic powered wheelchair  49 (4.8)  165 (16.1)  224 (21.9)  291 (28.5)  293 (28.7)  New power sources for wheelchairs  36 (3.5)  313 (30.6)  336 (32.9)  236 (23.1)  101 (9.9)  Manual wheelchair that would fold or disassemble to fit in a suitcase  21 (2.1)  187 (18.3)  266 (26)  262 (25.6)  286 (28)  Exoskeleton for daily mobility  15 (1.5)  321 (31.4)  177 (17.3)  197 (19.3)  312 (30.5)    Missing Response  Most Important  Important  Somewhat Important  Least Important  Self-driving or robotic powered wheelchair  49 (4.8)  165 (16.1)  224 (21.9)  291 (28.5)  293 (28.7)  New power sources for wheelchairs  36 (3.5)  313 (30.6)  336 (32.9)  236 (23.1)  101 (9.9)  Manual wheelchair that would fold or disassemble to fit in a suitcase  21 (2.1)  187 (18.3)  266 (26)  262 (25.6)  286 (28)  Exoskeleton for daily mobility  15 (1.5)  321 (31.4)  177 (17.3)  197 (19.3)  312 (30.5)  Table V. Ranking Four Mobility/Transportation Futuristic Inventions from Least Important to Most Important, n (%)   Missing Response  Most Important  Important  Somewhat Important  Least Important  Self-driving or robotic powered wheelchair  49 (4.8)  165 (16.1)  224 (21.9)  291 (28.5)  293 (28.7)  New power sources for wheelchairs  36 (3.5)  313 (30.6)  336 (32.9)  236 (23.1)  101 (9.9)  Manual wheelchair that would fold or disassemble to fit in a suitcase  21 (2.1)  187 (18.3)  266 (26)  262 (25.6)  286 (28)  Exoskeleton for daily mobility  15 (1.5)  321 (31.4)  177 (17.3)  197 (19.3)  312 (30.5)    Missing Response  Most Important  Important  Somewhat Important  Least Important  Self-driving or robotic powered wheelchair  49 (4.8)  165 (16.1)  224 (21.9)  291 (28.5)  293 (28.7)  New power sources for wheelchairs  36 (3.5)  313 (30.6)  336 (32.9)  236 (23.1)  101 (9.9)  Manual wheelchair that would fold or disassemble to fit in a suitcase  21 (2.1)  187 (18.3)  266 (26)  262 (25.6)  286 (28)  Exoskeleton for daily mobility  15 (1.5)  321 (31.4)  177 (17.3)  197 (19.3)  312 (30.5)  Less than half of the participants (n = 471, 46.1%) felt that people with disabilities often (n = 349, 34.1%) or always (n = 122, 11.9%) play an active role in the decision-making process when getting new mobility equipment. Furthermore, the majority (n = 647, 63.3%) also said that people with disabilities rarely (n = 572, 56.0 %) or never (n = 75, 7.3%) receive adequate support to be able to maintain their assistive technology long term. Similar responses were seen between those with tetraplegia and paraplegia except for two distinct instances. More participants with tetraplegia ranked human–machine interfaces as important or most important than those with paraplegia (47.3% versus 33.4%, respectively; p = 0.017). More participants with paraplegia ranked a “manual wheelchair that would fold or disassemble” as important or most important than those with tetraplegia (49.6% versus 33.5%, respectively; p < 0.001). The most commonly cited barrier to obtaining new mobility-assistive technologies was the funding and procurement process, particularly cost, followed by knowledge of the user and the provider (Supplemental Table 3). Several themes on critical areas of research emerged from open-ended questions that generated a total of 1,199 comments (Supplemental Table 4). Additionally, 73 individuals provided more information about their own personal disability or medical condition and 16 provided comments about ways to improve the survey. Discussion This survey of over 1,000 consumers of mobility-assistive technologies can be used to develop a research and development “road map” that has been called for by PCAST and NAS. Consumers felt that mobility technology is important for all aspects of their lives. Participants also emphasized the importance of research and development on mobility-assistive technologies and the need to include people with disabilities in research and development. This latter concept is nicely summarized by two insightful quotes from participants: “A futurist once told me that tech design should include disabled people the same way the military includes test pilots. Test pilots are trained for their job evaluating planes and they are, mostly, listened to.” “Clinicians and researchers need to listen to veterans and people with disabilities. They should not make assumptions as to what is important. People with disabilities are smart too.” Open-ended responses revealed an opportunity for improving dissemination and education pathways to teach consumers about advances in assistive technology research. Some participants recommended developing products that are already on the market, suggesting that they were unaware of their availability. Other participants suggested specific ways consumers could be educated about technologies on the market, including expos, websites, or other tools. Participants felt that both consumers and providers needed education. Open-ended responses also emphasized the need for new and better technology but at lower cost. Participants felt that cost was a barrier to obtaining new devices, insofar as it affected availability of funding. The process of obtaining equipment was in many cases identified as laborious and inefficient. This places a responsibility on researchers to mitigate cost when developing devices and understanding how insurance policies may affect translation of the technology into the hands of consumers. Based on the results of the survey, a conceptual framework for mobility-assistive technology research and development was produced (Fig. 2). The process is person-centered and should be conducted with an understanding of the broader concepts of universal design, policy, clinical practice, and cost. Four research thrust areas represent mobility-assistive technology research and development priorities. Education, dissemination and knowledge transfer, and standards and reliability are critical outputs that must occur alongside the development and clinical testing of mobility-assistive technology. Not represented in this figure are the views regarding other research domains, such as regenerative medicine and devices to assist self-management. As this survey was specifically designed to elicit feedback on technology used for mobility, more in-depth surveys would be needed to develop similar frameworks for other domains. Some of this work has been reported elsewhere.20,21 Figure 2. View largeDownload slide Framework for mobility-assistive technology research and development. Figure 2. View largeDownload slide Framework for mobility-assistive technology research and development. All four research thrust areas identified for mobility-assistive technology have been noted as opportunities for rehabilitation research in an expert report published by the US Department of Veterans Affairs Office of Research and Development.22 The first thrust is “advanced wheelchair design.” Participants placed emphasis on technology that can avoid collisions or help to negotiate obstacles; lighter weight, folding, or smaller wheelchairs; and alternative power sources for wheelchairs. Maneuverability and transportability were seen as critical for mobility in the home, in the community, and during travel. Participants expressed a frustration with current transportation, a desire for expanded options in the field of accessible driving, and a need for change in airline policies and accessibility. The requests for alternative power sources was not surprising, given that batteries and electrical components are the most common components to fail and need replacement.23,24 Second, “smart device applications” that consumers can use in their home or wear are needed to help users track information and control their environments. Participants were particularly interested in smart home technology. Our own research on monitoring and coaching technologies has demonstrated ways that wearable devices and coaching technologies can be used by individuals with disabilities to promote health and physical activity.25 A third notable thrust is “human–machine interfaces.” Participants with limited arm or hand movement wanted alternative ways to control wheelchairs using the voice or face. Our own research in this area has focused on control strategies that are shared between the user and the device,26 universal interfaces that can control multiple devices, and better software algorithms.27,28 Finally, “assistive robotics and intelligent systems” were seen as a high priority. Participants highlighted the need for self-driving wheelchairs and navigation assistance, better exoskeleton technology for ambulation, and devices that assist with transfers of people or devices into and out of vehicles, or that transfer people into and out of wheelchairs. We plan to address this thrust by investigating how navigation, sensing, and control systems can adapt to the needs of the user and how they can learn from the user.28,29 We also plan to advance the field by developing devices that assist with transfers to and from wheelchairs and beds30 and that aim to improve safety of caregivers who perform the transfers.25,28 Consumers tended to agree with providers of technology31 with a few exceptions. Consumers placed priority on the same technologies as providers (devices that aid transfers and alternative power sources for wheelchairs), but they also emphasized a few more: smart home technology, exoskeletons, and smart wheelchair design. The majority of providers perceived that their clients play an active role in obtaining their assistive technologies. The majority of consumers, on the other hand, felt they rarely or never play an active role. This mismatch in perceptions suggests that providers may need to place more emphasis on patient-centered care and inclusiveness. However, the majority of providers and users (68.3% and 63.3%, respectively) agreed that people with disabilities rarely or never receive adequate long-term support to maintain their technologies. This suggests that access to rehabilitation technicians and engineers and training programs32 to teach consumers and providers how to perform basic maintenance are needed. The differences seen in opinions of those with tetraplegia and paraplegia were expected and likely reflect their respective functional needs. The majority of individuals with paraplegia used manual wheelchairs and were thus interested in more compact or folding manual wheelchairs. Those with tetraplegia and loss of arm function were more likely than those with paraplegia and full use of their arms to be interested in human–machine interfaces to help them control other devices. A few limitations to this research study deserve discussion. First, because this study involved completion of an online survey, we may have oversampled those who are technologically savvy or those who have Internet access. However, we did provide alternate means for completing the survey. Second, we sampled only a small proportion of the individuals in the U.S. who use mobility-assistive technologies. However, the participants ranged in age from 19 to 95 yr, used a variety of assistive technologies, and represented 98% of U.S. states and Puerto Rico. Respondents represented a wide range of experiences with technology, from those who were novices to those who used technology for 15 yr or more. We also sampled a large population of veterans. Third, participants can sometimes be over-enthusiastic about many items in a survey if they feel strongly about a topic. To address this potential bias in responses, we asked participants to rank technologies against each in order to stratify the importance of some devices over others. Fourth, responses on surveys can be biased toward the organization’s mission, especially if participants want to please the surveyor or feel strongly about the topic. We therefore consulted with the VERC to establish content validity, provided several open-ended questions to allow participants to provide feedback and ideas not mentioned in the survey, and based the content of the survey on responses provided by participants in our prior work.19 Qualitative data from open-ended questions was factored heavily into the conceptualization of the research thrusts. In order to ensure that results of this survey accurately reflect current consumer needs, it should be repeated frequently. Future surveys will assess needs and opinions of families and caregivers about mobility-assistive technology research and will measure consumer and provider awareness of available products, research outputs, and clinical practice guidelines and whether they are being used. Such information should drive research and development projects and program priorities. We also anticipate that these findings will be helpful in allowing consumer needs and wants to drive innovation in the field. The current study focused on participants of both veteran and civilian status, across a wide range of diagnoses, and with broad demographic range. A goal of future surveys should be to provide more specific research to explore how priorities differ between unique sets of individuals. Future researchers in the field of mobility-assistive technologies should take heed of one survey participant’s comment: “The biggest challenge with technology is not inventing or making it. It is making it reliable and simple enough for everyone.” Conclusion This survey of consumers who use mobility-assistive technologies can drive research and development priorities. Advanced wheelchair design, human–machine interfaces, smart device applications, and assistive robotics and intelligent systems are top priorities for future research efforts. Survey results also demonstrated the importance for researchers to understand the effects of policy and cost on translational research and to be involved in educating consumers and providers. Supplementary Material Supplementary material is available at Military Medicine online. Acknowledgments VAPHS Veterans Engineering Resource Center (VERC) and Paralyzed Veterans of America. Funding/COI This study was funded by the VA Center of Excellence on Wheelchairs and Associated Rehabilitation Engineering (B9250-C), the Paralyzed Veterans of America, and the National Institutes of Health (UL1-TR-001857). References 1 Brault MW: Americans with Disabilities: 2010 . Washington, DC, Census Bureau, 2012. Current Population Report P70–131. https://www2.census.gov/library/publications/2012/demo/p70-131.pdf. Accessed September 21, 2017. 2 Chaves ES, Boninger ML, Cooper R, Fitzgerald SG, Gray DB, Cooper RA: Assessing the influence of wheelchair technology on perception of participation in spinal cord injury. Arch Phys Med Rehabil  2004; 85( 11): 1854– 8. Google Scholar CrossRef Search ADS PubMed  3 Laferrier JZ, McFarland LV, Boninger ML, Cooper RA, Reiber GE: Wheeled mobility: factors influencing mobility and assistive technology in veterans and service members with major traumatic limb loss from Vietnam war and OIF/OEF conflicts. J Rehabil Res Dev  2010; 47( 4): 349– 60. Google Scholar CrossRef Search ADS PubMed  4 Salminen AL, Brandt A, Samuelsson K, Toytari O, Malmivaara A: Mobility devices to promote activity and participation: a systematic review. J Rehabi Med  2009; 41( 9): 697– 706. 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In: Wheeled Mobility (Wheelchair) Service Delivery . Rockville (MD), Agency for Healthcare Research and Quality (US), 2012. 10 LaPlante MP, Kaye HS: Demographics and trends in wheeled mobility equipment use and accessibility in the community. Assist Technol  2010; 22( 1): 3– 17; quiz 19. Google Scholar CrossRef Search ADS PubMed  11 Organization WH. Global Cooperation on Assistive Technology (GATE). 2017; http://www.who.int/phi/implementation/assistive_technology/en/. Accessed November 9th, 2017. 12 Paralyzed Veterans of America. 2016 Women Veterans Case Study.(online). Accessed May 27, 2016. 13 Simpson LA, Eng JJ, Hsieh JT, Wolfe DL: The health and life priorities of individuals with spinal cord injury: a systematic review. J Neurotrauma  2012; 29( 8): 1548– 55. Google Scholar CrossRef Search ADS PubMed  14 Department of Defense Appropriations for 2016. Hearings before a subcommittee of the Committee on Appropriations. House of Representatives. 114th Congress. First Session. Subcommittee on Defense. U.S. Government Publishing Office. Chairman, R. Frelinghuysen. Washington, 2015. Pages 280– 1. 15 Military Constructions, Veterans Affairs, and Related Agencies Appropriations for 2016. Hearings before a subcommittee of the Committee on Appropriations. House of Representatives. 114th Congress. First Session. Subcommittee on Military Constructions, Veterans Affairs, and Related Agencies. Chairman, C. Dent. Washington, 2015. Pages 733– 4. 16 United States General Accounting Office: Testimony before the Subcommittee on Social Security, Committee on Ways and Means. House of Representatives. 114th Congress. SSA Disability Programs. Fully Updating Disability Criteria has Implications for Program Design. Director, R. Robertson. GAO-02-919T. 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Phys Med Rehabil Clin North Am  2010; 21( 1): 1– 13. Google Scholar CrossRef Search ADS   30 Sivaprakasam A, Wang H, Cooper RA, Koontz AM: Innovation in transfer assist technologies for persons with severe disabilities and their caregivers. IEEE Potentials  2017; 36( 1): 34– 41. Google Scholar CrossRef Search ADS   31 Brad E, Dicianno MJJ, Sergeant G, et al.  : The future of the provision process for mobility assistive technology: a survey of providers. Disabil Rehabil Assist Technol  2018. In press. 32 Toro ML, Bird E, Oyster M, et al.  : Development of a wheelchair maintenance training programme and questionnaire for clinicians and wheelchair users. Disabil Rehabil Assist Technol  2017; 12( 8): 843– 51. Google Scholar CrossRef Search ADS PubMed  Author notes The contents of this publication do not represent the views of the Department of Veterans Affairs or the United States Government. Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2018. This work is written by (a) US Government employee(s) and is in the public domain in the US.

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Military MedicineOxford University Press

Published: Apr 4, 2018

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