Today's electronic technologies, including computers, cell phones, Internet, and electronic organizers, hold great promise for individuals with intellectual disabilities, yet little research has been conducted to explore patterns of use among this population. Drawing upon a survey of 83 adults with intellectual disabilities, we examined factors affecting use for three key electronic technologies: computer, Internet, and electronic organizers. Forty-one percent of participants used a computer; 25%, the Internet; and 11%, electronic organizers. Age, work setting, and self-perceived ability to manually copy information affected likelihood of use. Primary barriers reported by participants included lack of access, training and support, and expense of technologies. Interest in using such technologies was high, and participants offered suggestions for improved accessibility.
Research on technology and disability is typically focused on specialized or adapted technologies designed for use by people with disabilities. More and more, however, specialized technologies (e.g., ergonomic equipment, “good grip” utensils, closed captioning) are entering mainstream markets, and generic technologies (e.g., cell phones, computers, electronic organizers) are being used by people with disabilities to enhance their quality of life. The increasing usability of generic technology may lead to important benefits for people with disabilities; products designed for mass markets tend to be more easily available, less expensive, and less stigmatizing than specialized technology.
Today's electronic technologies, including computers, cell phones, Internet, and electronic organizers, hold great promise for individuals with disabilities (Hart, O'Neil-Pirozzi, & Morita, 2003), allowing communication with people around the globe, the conduct of work at home during flexible hours, effective organization and retrieval of information, and access to mainstream culture. The potential of electronic technologies may be particularly great for persons who experience difficulties processing, learning, and remembering information (Wade & Troy, 2001). For students with intellectual disabilities, electronic technologies have been shown to create more conducive learning environments by allowing students to learn at their own pace, repeat steps as necessary, develop a feeling of control over the learning process (Pantelidis, 1993; Salem-Darrow, 1995), and learn effective systems of organization (Bauer & Ulrich, 2002; Epstein, Willis, Conners, & Johnson, 2001), ultimately enhancing their academic skills (Scruggs & Mastropieri, 1997; Tjus, Heimann, & Nelson, 1998).
Researchers have also begun to document the benefits of electronic technologies for adults with intellectual disabilities. For example, Tabor (2003) found that cell phones served as a community safety tool when people were taught to call for assistance; in Stockholm, Renblad (1999, 2000) reported that video phones used by participants increased community participation and social networking; and in the United Kingdom, Standen, Brown, and Cromby (2001) successfully developed and tested virtual environments in which computer-based instruction was used for teaching community skills in the United States. Langone, Clees, Rieber, and Matzko (2003) replicated this finding.
Of particular interest in this study, portable electronic organizers seem to hold great potential for people with disabilities. They are affordable, can be easily integrated into the school and workplace, and perform many organizational and memory functions that are key to workplace success (Abell, Bauder, Simmons, & Sharon, 2003). For example, Furniss, Lancioni, and Nelson (2001) documented the success of using palmtop-based devices in a United Kingdom sheltered workshop for increasing the accuracy and performance of complex work tasks by persons with intellectual disabilities. Similarly, Davies, Stock, and Wehmeyer (2002a, 2002b, 2004) showed improved task accuracy, time management, and scheduling as well as decreased use of external verbal prompts when performing vocational tasks using an electronic organizer.
Despite the potential to enhance independence and the increased academic interest in technology development for people with disabilities, this population is far less likely to own and use today's cutting edge technologies as compared to Americans without disabilities. Whereas 51.7% of Americans without disabilities have a computer in their home, only 23.9% of people with disabilities do (Kaye, 2000). An even greater gap exists in the use of the Internet: 38.1% of individuals without disabilities as compared to only 10% of those with disabilities. Even controlling for income, the effect of disability remains; among persons with low incomes, people with disabilities are half as likely to own a computer and one quarter as likely to use the Internet.
Given that persons with intellectual disabilities experience limitations in skills perceived as important for the use of electronic technologies, such as reading and processing information, and may experience other sociopsychological and cultural barriers to computer and Internet use, they are probably among the least likely to access this type of technology. Very little research has been conducted on the prevalence of technology use by people with intellectual disabilities. Wehmeyer's (1998, 1999) study drew upon 516 surveys of family members to examine the use and barriers to use of assistive technology by students (ages 1 to 21) with mental retardation. He found 68% of participants owned household computers, a figure even higher than the national figure for persons without disabilities. Surveying 680 adults with mental retardation in Arkansas, Parette and VanBiervliet (1992) found only 21% reported using computers. Given the lack of consistent data, we can only suggest that these technologies seem underutilized among individuals with intellectual disabilities.
Similar to other studies on assistive technology (Augusto & Schroeder, 1995; National Council on Disability, 2000), cost (Perlman, 1993; Wehmeyer, 1998), and ease of use (Perlman, 1993) were found to be among the most important barriers to obtaining and using electronic technology. Researchers have also found that after technology is obtained, there is a high rate of nonuse or “device abandonment” (Pape, Kim, & Weiner, 2002; Phillips & Zhao, 1993). Riemer-Reiss and Wacker (2000) found that successful use of technology is augmented by consumer involvement in the entire selection and purchasing process. Research on assistive technology suggests that limited knowledge held by families and persons with disabilities (Augusto & Schroeder, 1995; Bryant, Erin, Lock, Allan, & Resta, 1998; Kintsch & DePaula, 2002; North Carolina State Department, 1995) and by professionals (Behrmann, 1995; Brodin, 1997; Espe, 1998; Lesar, 1998) as well as negative attitudes towards technology (Kintsch & DePaula, 2002) and a lack of knowledge by families (Lindstrand, 2002) may be important factors for explaining lack of access and abandonment of technologies, but the barriers have yet to be adequately explored.
There are also significant design and accessibility issues who limit the adoption and successful use of electronic organizers by people with disabilities. The small size of electronic organizers increases their portability, yet makes their use difficult in other ways (National Center on Accessible Technology in Education, 2002; Rainger, 2002). Research based on the Palm school demonstration projects, in which the Palm Company awarded sets of handheld computers to over 175 classrooms throughout the United States, suggested that although special education teachers were enthusiastic about the use of Palms in the classroom, they had difficulty with breakage, loss of devices, and battery life (Vahey & Crawford, 2002).
Research on disability and technology usage has expanded tremendously in the past several years, but it is still a young field. As such, many gaps exist in our knowledge. There appears to be no research in which investigators examine prevalence for some generic electronic technologies, such as cell phones or electronic organizers. Moreover, investigators have not yet documented the types of activities commonly performed with these technologies nor have they extensively examined the factors that affect the likelihood of use. In this study our goal was to fill in some of the gaps in research on technology use with individuals who have intellectual disability by exploring the following questions: (a) What technologies are adults with intellectual disabilities using on a regular basis? (b) What factors affect technology use? (c) How do the factors that affect use vary by type of technology? (d) How and why are individuals using computers, the Internet, and electronic organizers? (e) What problems are experienced by users? (f) What barriers are reported by those who do not use electronic technologies?
This project was developed as part of the Assistive Technology and Cognitive Disability Collaborative (ATCDC), funded by the National Institute on Disability Rehabilitation Research. As a partnership among the Brain Injury Association of America, University of Akron, Temple University, Moss Rehab, and Spaulding Hospital, this collaborative group seeks to examine the potential of electronic organizers to enhance the independence of persons with cognitive disabilities. The first stage of their research agenda included a survey of adults and children with intellectual disabilities and traumatic brain injury in order to examine the use of and preferences related to electronic organizers. Data were collected across three research sites, one focusing on adults with intellectual disabilities, one focusing on adults with traumatic brain injury, and one focusing on children with intellectual disabilities and traumatic brain injury. For the purposes of this article, we draw upon survey data involving adults with intellectual disabilities.
In designing data collection across three research sites with different subject populations, the research team sought to collect reliable, comparable data while allowing for flexibility in addressing specific population needs. Therefore, the ATCDC research team developed a “core” survey that was focused on the use of electronic organizers to be employed by researchers at each data collection site, supplemented with additional questions designed for a subset of the sample.
Information gathered in the core survey focused on the following topics: (a) participant's demographic background; (b) self-perceived abilities related to technology use (e.g., ability to read, spell, copy information, push buttons), (c) current organizational strategies and satisfaction with these strategies, (d) the broad range of technology used by participants, and (e) characteristics of electronic organizer use and non-use, including (a) descriptive information on the use of electronic organizers (e.g., frequency, duration, types of use, reasons for non-use), (b) learning styles and supports, and (c) electronic organizer functions and features desired. For the purposes of the survey, an electronic organizer was defined as an electronic device that is small (can fit in a pocket or purse), portable, and designed to organize information.
For adults with intellectual disabilities, we developed additional questions on learning style, supports, education, and work history. We also added sets of questions, parallel to the questions on electronic organizer use, related to cell phone, computer, and Internet use. Flash cards were created pictorially displaying the answer categories to assist persons in remembering and understanding the potential answers and to assist those who communicate nontraditionally. The survey was designed to be administered in a face-to-face interview and to take approximately an hour.
As noted, data collection occurred at three sites. To focus on sampling and recruitment of adults with intellectual disabilities, we potentially included individuals in the sample if they were (a) identified as having “mental retardation” by state organizations or professionals working with this population; (b) capable of communicating answers to simple, closed-ended questions about their experiences with and attitudes related to technology; (c) 18 years of age or older; and (d) lived in Pennsylvania. No technology experience was required.
Because the research team did not have access to a comprehensive list of such persons to use as a sampling frame, random sampling was not feasible. Instead, we developed a convenience sampling strategy designed to maximize diversity among participants, targeting diversity with regard to ability level, type and level of support (e.g., competitive work setting, supported work, and sheltered workshop), race and ethnicity, and gender. To construct the sampling frame, we mailed invitations to approximately 370 disability organizations and professionals serving people with intellectual disabilities in the Philadelphia area and across Pennsylvania. In these invitations we explained the purpose of the research, the basic details of the interview (approximately an hour, at a place of their convenience), and offered an honorarium of $25. Organizations and professionals were asked to distribute these flyers to individuals and assist them in calling, mailing, or faxing contact information. Approximately 125 persons submitted applications to be interviewed from a total of 30 disability organizations and individuals.
All requests were sorted by location. Sampling concentrated on the Philadelphia area but also provided small sets of between 5 and 10 interviews in cities across Pennsylvania (Harrisburg, Allentown, Scranton, Erie, and Pittsburgh). Organizations were categorized to ensure that we interviewed individuals in independent living situations, group homes, nursing homes, competitive work sites, sheltered work sites, and self-advocacy organizations. A cap of 5 individuals was placed on each organization; if more than 5 people expressed interest per site, agencies were asked to either randomly select 5 participants or to maximize the diversity of participants. Finally, selection was based on date of submission of contact information and ease of scheduling.
Project staff conducted 86 interviews. Data from 3 of the interviews were excluded from analysis due to participant's lack of ability to communicate answers, resulting in a final sample of 83 individuals. Interviews were conducted in private settings convenient for the individuals. All participants were paid, regardless of whether they completed the survey. Our recruitment strategy makes it impossible to estimate a meaningful response rate. The demographic profile of the sample is shown in Table 1.
Because reliability may be a concern when interviewing individuals with limited intellectual capacities, the research team incorporated a consistency question into the design of the survey. Both at the beginning and at the end of the organizational strategies section of the survey, the interviewer asked the participant to select the primary organizational strategy used to keep track of appointments. Seventy-two percent of participants provided the same answer. Although this may seem a low rate of consistency, we hope some of the inconsistency is due to the fact that many people used multiple organizational strategies (i.e., a paper calendar one time and a person to remind them other times), and, therefore, some participants may have offered another strategy used.
To summarize descriptive data, we relied on frequencies. To examine the potential impact of various factors on technology use, we used t tests, chi-square, and backward conditional logistic regression. Chi-square was used to examine the impact of a categorical independent variable (e.g., gender, race) on a categorical dependent variable (e.g., yes/ no answer to “Do you use computers?). We used t tests to examine the impact of a categorical independent variable on a ratio dependent variable (i.e., the mean number of technologies used). In addition to independent sample t tests, we employed backward conditional logistic regression to examine the impact of a variety of factors on the mean number of technologies used. Independent sample t tests indicate the effect of individual factors on technology use but cannot examine the simultaneous effect. Increasing the number of t tests increases the likelihood of finding significance due to error. Logistic regression alleviates both these weaknesses; however, it might be suspect with a small sample size. Using both techniques allows one to assess whether similar patterns emerge across techniques.
Participants were asked whether they used each of 16 types of technologies on a regular basis, defined as at least several times for a period of 2 weeks or more. Table 2 lists the percentage of participants who reported using each of 13 types of technology. The most common technologies used included regular telephone (89%) and remote control (83%); fewer than 5% of participants used a two-way pager, a voice organizer, or a medication reminder. No one reported use of global positioning software. Participants reported using from 0 to 11 types of technology, with a mean of 3.98 and a median of 3.00 types of technology.
To examine the impact of a variety of factors on the mean number of technologies used, we utilized independent sample t tests as well as backward conditional logistic regression. Independent sample t tests indicate the effect of individual factors on technology use but cannot be used to examine the simultaneous effect. As one increases the number of t tests, one increases the likelihood of finding significance due to error. Logistic regression alleviates both these weaknesses; however, it might be suspect with a small sample size. However, both analyses show similar results.
Factors examined were (a) key conceptual variables, including attitude towards technology and level of independence in work and residential setting; (b) demographic variables, including age, race, gender, and type of education; and (c) self-perceived ability levels. We were not able to examine the impact of income because the response rate for income questions was below 20%. (Participants in general did not know their personal or household income.) Only age, work setting, and self-perceived ability to manually copy information (e.g., copy an address from a business card to one's address book) significantly affected the number of technologies used, ps < .01. Younger participants used more technology than did older participants (Ms = 4.39 versus 2.35), t = 3.13; those in competitive employment and those who were unemployed used more technology than those in sheltered workshops (Ms = 4.82 and 4.68 vs. 2.94, respectively), ts = 2.90 and−2.99; and those who reported no difficulties copying information used a greater number of technologies than those who reported some difficulties (Ms = 4.89 and. 3.23), t = 3.00.
Table 3 displays the results from the backward conditional logistic regression (factors removed from model at >.1). Similar to the above results, work type, age, and ability to copy were significant in predicting the mean number of technologies used.
Comparison of Factors Affecting Technology Use
Do the factors affecting adoption vary for specific technologies? In this section we focus on three technologies: computers, Internet, and electronic organizers. Participants were asked to respond yes or no as to whether they had ever used these technologies. We conducted chi-square analysis to examine the impact of factors on these dichotomous variables. Table 4 summarizes these analyses (due to the long list of self-reported abilities tested, only those abilities indicating significance at the .01 level or higher are included in the table). Across the three types of technology, significant factors include the overall number of technologies used and self-perceived ability to copy information, such that those who used more types of technologies and those who had no difficulties copying information were more likely to use each type of technology. Additional factors varied in their effect across technologies. Age and employment status had a significant effect on 2 of 3 technologies (employment showed no effect on electronic organizer use; age showed no effect on Internet use). Race, gender, attitude towards technology, and several of the abilities impacted one type of technology.
Characteristics of Computer Use
With regard to questions concerning computer use, 66% of participants had used a computer at some point in their lives, and 42% were currently using a computer on a regular basis. Among current users, 44% reported using their computer every day, 31% several times each week, and 25% several times per month or less frequently. Sixty-five percent had a computer where they lived, and 82% reported using a computer somewhere other than their home, including a day activity center (34%), work or volunteer setting (28%), public library (19%), someone else's home (12%), school (10%), or rehabilitation facility (10%). Sixty-two percent of participants reported receiving regular assistance when using the computer. Current users most commonly employed computers to play games (54%), listen to music (43%), word process (40%), and use the Internet (38%).
Nineteen participants suggested changes that would make a computer easier or better for them to use: accessibility features related to larger and easier to see and touch buttons and screen (6), more personal assistance to learn (4), easier commands (3), and better/more software appropriate for people with disabilities (2).
Characteristics of Internet Use
Thirty-eight percent of current computer users (24% of the entire sample) used the Internet. The most common uses included searching for travel-related information (65%), searching for social event information (65%), playing Internet games (60%), and reading the news (55%).
Twelve current Internet users described changes that would make the Internet easier and/or better for them to use, including making it easier to enter commands and addresses (4 participants); improving interaction with the user, including word prediction (i.e., software that predicts what word one is typing based on the initial letters, thereby reducing the typing involved), voice input and voice output (3); and speeding up connections (2).
Characteristics of Electronic Organizer Use
Eleven participants (13%) had used an electronic organizer at some time, and 7 (8%) identified themselves as current users. Of these, 4 used their organizer at least weekly, and 2 used it less frequently. Six current electronic organizer users (86%) had used their organizer for over a year; 2 current users (29%) reported receiving assistance on a regular basis, and 5 (71%) reported that the level of support they received was sufficient for their needs.
Considering both former and current users (n = 11), we grouped them according to the difficulty of their electronic organizer. Four users felt that their electronic organizer was easy to use, 3 believed it was in-between, and 3 felt considered it difficult (1 did not respond). Five users reported having their electronic organizer lost, broken, or stolen; 4 reported their organizer had been lost; 4 said it had been broken, and 3 reported it had been stolen. Four users had multiple misfortunes happen to their device.
Only 3 current or former electronic organizer users (27%) chose their own electronic organizer, and each of these participants paid for it themselves. Other users received their electronic organizer as a gift from friends or family (2), through work (3), or from “another source” (2). Five participants reported the cost of their electronic organizers ranged in price from $13 to $400 ($13, $40, $45, $300, $400). When asked about benefits of using this device, users said it helped organize and store their appointments (3), reminded them of when they needed to do things (2), and stored important telephone numbers (1).
Participants who did not use computers or electronic organizers were asked to provide the reason(s) for non-use. Expense was a barrier for both types of technologies (10% listed expense for computers, and 7% listed expense for electronic organizers). Those who did not use computers most commonly reported that they did not have a computer anywhere accessible for them to use (26.8%), lacked someone to teach or support them in computer use (12.2%), or thought that computers were too expensive (10%). For those who did not use electronic organizers, the vast majority (61%) reported that they simply did not know enough about them, 7% reported that they were too expensive, and 7% reported that they had not gotten around to purchasing one yet.
Electronic organizer users were most likely to use the calculator on their device. Two electronic organizer users reported employing the full range of features: using the electronic organizer to link with the Internet and e-mail. Among non-users, interest in electronic organizers was high; 52% of those not currently using one reported they would definitely be interested in it, 25% said they would probably be interested, and 23% reported maybe, probably not, or definitely not. As displayed in Table 5, participants expressed greatest interest in the music function (91%), followed by calculator (90%), use with telephone (78%), and games (77%).
Importance of Features in Selecting New Devices (n = 83)
All participants (current, former, and non-users) were provided a list of features and asked how important each of these features would be if selecting an electronic organizer to purchase for personal use. Table 6 displays the percentage of participants who reported on a 4-point scale the importance of using these devices: not at all important (1) to very important (4). The most important features included a battery that lasts a long time (74%) and good technical support (70%).
According to our findings, the vast majority of our participants were using simple electronic technologies, such as the phone and TV remote control. Use of more sophisticated technologies, including computers (41%), video games (37%), cell phones (28%), and the Internet (25%), was also fairly common. In examining the factors affecting the mean number of technologies use, we found that age, employment status, and self-perceived ability to copy information significantly affected technology use. We can only hypothesize why, of 14 self-reported abilities, only the ability to copy information consistently was significant in impacting technology use. The ability to copy information may serve as a key threshold skill. One may not need to read, for example, to open a particular website, play a game, or find a phone number in an electronic organizer; however, one may need to copy information correctly to input the desired Internet address or phone number. That being said, the fact that other abilities did not prove significant suggests that the skill level for use of technology is quite low and that most persons with disabilities could use these technologies if given access.
Compared to national statistics of Americans without disabilities, which indicate that 51% of individuals without a disability regularly use a computer and 38% use the Internet, we found lower usage by a difference of 10% and 13%, respectively. In addition to low rates of use, we suggest that persons with intellectual disabilities may be less likely to effectively use this technology to reap many of the potential benefits. Current computer users in our sample were most likely to be using computers to play games (54%) or listen to music (43%), tasks that are fun but potentially less beneficial for overall quality of life than word processing (40%), e-mail (29%), or using the Internet for work or school (8%).
These survey findings may help us develop real-world strategies for effective use of electronic organizers by people with intellectual disabilities. For example, if individuals enjoy using electronic technologies for games and music, perhaps these features should be taught first or along with other features that are focused more on productivity and independence. If copying information serves as a threshold skill, perhaps supports can be built that minimize the need to copy information. Cost, lack of knowledge, lack of access, and lack of training/support were among the most commonly cited barriers to use; thus, these are key areas in which we need to focus to increase usage.
This exploratory study has several weaknesses that should be considered in interpreting findings and considering directions for future research. The sample is small (n = 83) and not randomly selected. Thus, we must be cautious about generalizing findings beyond this sample. Larger samples are needed to more accurately document prevalence of use among people with intellectual disabilities. Several weaknesses in the measures also limit the findings. Although income has been shown to be a key predictor of technology use, we were unable to examine its impact because participants were largely unable to provide us with income information. Also, we relied on self-perceived ability measures and do not know how closely these ratings correlate with objective measures of ability. Another issue is the low rate of consistency (72%) as measured by one consistency question. We would have benefited from including another, simpler question as a consistency measure to assess whether the inconsistency was rooted in the question or in the participant.
Because so many of the factors explored, such as level of independence, attitude towards technology, and most self-perceived abilities, were not significant, we are left wondering whether there are other more powerful and yet unexplored explanatory variables. Because this population is unlikely to use these technologies without assistance, the answer to who uses technology may lie more in one's social network and their interest in technology than in individual attitudes and characteristics. For example, income and ability may matter less than whether one's social supporters are interested in and encourage one to learn to use technology. The relative impact of individual skills (e.g., skills, motivation, attitude), social factors (e.g., income, access, integration), and relational factors (e.g., network, knowledge and attitude of support persons) requires further research. As technology continues its rapid evolution and diffusion across our society, future researchers should also continue to examine the benefits of technologies for people with intellectual disabilities in real world contexts. What are the factors that lead to successful use of technology? What supports are necessary? What are the barriers to sustained technology use?
People with intellectual disabilities express interest in using today's electronic technologies, and it seems clear that people benefit in their work, school, community, and leisure activities from these technologies. The challenge is to create effective systems of access and supports that allow them to utilize and benefit from these technologies.
This research was conducted by the Institute on Disabilities at Temple University, in partnership with the Assistive Technology and Cognitive Disability Collaborative, funded by the National Institute on Disability Rehabilitation Research. The authors thank everyone who participated by being interviewed for this research; our partners in the Collaborative for their work on the survey instrument; and Deborah Robinson, who assisted with interviewing and provided project feedback.
Authors: Allison C. Carey, PhD (firstname.lastname@example.org), Department of Sociology and Anthropology, 436 Grove Hall, Shippensburg University, Shippensburg, PA 17257. Mark G. Friedman, PhD, and Diane Nelson Bryen, PhD, Institute on Disabilities, 423 Ritter Hall Annex, Temple University, Philadelphia, PA 19122