Older adults (n = 113) participated in focus groups discussing their use of and attitudes about technology in the context of their home, work, and healthcare. Participants reported using a wide variety of technology items, particularly in their homes. Positive attitudes (i.e., likes) outnumbered negative attitudes (i.e., dislikes), suggesting that older adults perceive the benefits of technology use to outweigh the costs of such use. Positive attitudes were most frequently related to how the technology supported activities, enhanced convenience, and contained useful features. Negative attitudes were most frequently associated with technology creating inconveniences, unhelpful features, as well as security and reliability concerns. Given that older adults reported more positive than negative attitudes about the technologies they use, these results contradict stereotypes that older adults are afraid or unwilling to use technology. These findings also highlight the importance of perceived benefits of use and ease of use for models of technology acceptance. Emphasizing the benefits of technology in education and training programs may increase future technology adoption. Technology; Older Adults; Work; Healthcare; Home Technology adoption is becoming imperative to function in modern day society because it is pervasive across all domains of life. Moreover, technology can facilitate everyday tasks enabling older adults (i.e., 65 years of age or older) to remain independent longer. Over 90% of adults over the age of 65 live independently (U.S. Census Bureau, 2000) , and most of the older population prefers to remain in their own homes as long as they are able (AARP, 1996). The majority of older adults' activities occur within the home environment (Baltes, Maas, Wilms, Borchelt, & Little, 1999) , and technology can support aging in place. Technology can support many home-based tasks such as cooking, cleaning, and yard * Corresponding author: Tracy L. Mitzner, School of Psychology, Georgia Institute of Technology, Atlanta, GA 30332-0170, Phone: 404-385-0798, tracy@gatech.edu. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access Comput Human Behav. Author manuscript; available in PMC 2011 November 1. Technology also has the potential to assist in monitoring and maintaining health as well as managing health conditions and diseases. Older adults may particularly benefit from using health technologies given that the likelihood of having a disability or health condition increases with age. In fact, 34% percent of adults aged 65 and over report having a health condition or disability, and 37% of adults over 75 report having three or more chronic conditions (CDC, 2006). Survey data suggest that older adults are aware that health technologies can support their preference for remaining independent and living in their own homes (AARP, 2008). Three-fourths of the AARP survey respondents reported a willingness to use telemedicine as a means for healthcare professionals to diagnose or monitor health conditions remotely. Furthermore, technology has the potential to reduce medication and illness mismanagement, which could significantly impact society as a whole. Costs due to medication mismanagement alone for people 65 and older in the U.S. were estimated to be $887 million in (Field, Gilman, Subramanian, Fuller, Bates, & Gurwitz, 2005 . Technological interventions that defray these costs could dramatically lessen the burden on the healthcare system. Although older adults report a willingness to adopt technology, usage data suggest that older adults are part of the "digital divide," (NTIA, 2004) The goal of this study was to explore the details of older adults' attitudes about technology broadly to better understand trends that may be generalizable across different contexts, types of technology, and diverse groups of older adults. In this study we examined 1) the range of technologies older adults use in their homes, for work, and for healthcare, 2) their attitudes about those technologies, and 3) the degree to which the range of technology use and attitudes toward technology vary as a function of domain. We employed a focus group methodology because this approach affords a relatively open and exploratory method for collecting qualitative data on technology use, providing insight into the details of actual usage, as well as perceived advantages and disadvantages of technology in different domains (Krueger, 1994) . Although this study is not designed to directly test models of technology acceptance (e.g., TAM), our results can contribute to their specification by providing information about the reasons that drive the factors of these models. A total of 113 community-dwelling older adults participated in 18 focus groups, ranging in size from 4 to 9 participants in each group (M = 6; SD = 1.65). The focus groups were conducted at local senior centers and university conference rooms at three sites:  NIH-PA Author Manuscript NIH-PA Author Manuscript participants) and female participants ranged in age from 65 to 85 years (M = 73; SD = 5.50). All participants reported English as their primary language. Race/ethnicity varied between sites ensuring a diverse sample: 33% African American seniors from Atlanta, GA, 30% Caucasian seniors from Tallahassee, FL, and 37% Hispanic seniors from Miami, FL. For each testing location, education level varied between focus groups. Participants in the low education groups had less than a college degree (46% of participants), whereas those in the high education groups had obtained a college degree or higher (54% of participants). Most participants reported living in a house, apartment, or condominium (76%) or independent senior housing (19%); the remaining 5% reported living with relatives, in lowincome housing, or in assisted living. As expected for this age range, the majority of participants were retired (74%); the remaining participants reported occupational status as part-time (9%), full-time (4%), homemaker (4%), or volunteer (3%); the remaining 6% did not specify. Most participants (82%) rated their general health to be good or excellent (1 = Poor and 5 = Excellent), M = 3.26, SD = .92. In sum, participants varied with respect to education level and race/ethnicity, however most reported living independently and being generally healthy. General materials-Standard CREATE materials (Czaja et al., 2006a) were used for assessing study eligibility and for collecting demographic, health, and technology experience information. These materials included a telephone prescreening interview, Background Questionnaire, and Technology Experience Questionnaire (available in Czaja et al., 2006b ). The script was designed to facilitate discussion about the range of older adults' technology use and their attitudes about technology in the domains of home, work, and health (full script is available from the first author). The script was pilot tested with two groups of older adults (n= 10) to ensure that the discussion questions were clear and prompted discussion relevant to the issues of immediate interest. Technology was defined as "electronic or digital products and services." We first asked, "What technologies do you use [in the context of home, work, or health]?" which was followed by discussion prompts tailored to each domain. For the home domain, participants were given a strategy of doing a mental walk through their homes to think about the technologies in each room and were instructed to think about occasions when they used technology items. For the work domain, participants were instructed to consider "work" in a broad sense, including volunteer work and past work experiences. Participants were asked to think about technologies they use for performing their jobs, communicating with other people while at work, or learning new job skills or training. For the health domain, participants were asked to think about technology broadly and not be limited to technologically advanced items. Participants were instructed to think about occasions when they used technology for healthcare, such as using medical devices, communicating with healthcare professionals, or gathering information about diseases.  NIH-PA Author Manuscript NIH-PA Author Manuscript questions were followed by a discussion of training, which is not the focus of the present paper (see Mitzner et al., 2008) . Prior to participation, participants completed the telephone prescreening interview. When eligible participants reported to the focus group site, they first provided informed consent. Next, the moderator summarized the general goals of the study and outlined rules for the discussion (e.g., to speak one at a time and contribute their own unique ideas and experiences). Each group discussed technology use in the context of two of the three domains (domain order was counterbalanced). Following an icebreaker question during which participants provided their first name and favorite hobby, the moderator introduced the first domain of discussion. After completing discussion of the first domain, participants were given a five minute break and then asked to complete the Background Questionnaire. Next, the moderator introduced the second domain for discussion. When discussion was completed, participants were given another five minute break and then asked to complete the Technology Experience Questionnaire. Participants were debriefed and paid $25 for participation. Discussions were audio recorded for later transcription. Results The audio recordings were professionally transcribed verbatim with personal information omitted. Transcripts were segmented into units of analysis by four independent coders. A segment was defined as a unique idea in a single, uninterrupted speaker turn, related to an attitude toward technology (i.e., an association between technology and a valenced evaluation) with which the speaker has had personal experience. The segmenting process was calibrated by conducting an initial round of independent segmenting of one randomly selected transcript followed by discussion of discrepancies between coders. A second round of independent segmenting on a different transcript yielded reliability estimates ranging from r = .79 -.87. The remaining transcripts were divided among the four coders to segment independently. The coding scheme was developed by reviewing a random sample of the transcripts from each domain and extracting common themes, as well as incorporating the experiences older adults reported having with technology (Czaja et al., 2006a) . Every attitude segment was coded on each of three dimensions: the technology item that was discussed, the attitude valence (i.e., like, dislike, or unclear), and the attitude reason (see Table 1 for the attitude coding scheme). Coders were calibrated by conducting three rounds of independent coding on the same three randomly selected transcripts followed by discussion of discrepancies and revisions to the coding definitions. The final round of reliability yielded estimates ranging from r = .79 -.92. The remaining transcripts were divided among the four coders to code independently. Chi-square tests of homogeneity were conducted to determine if there were significant differences between category frequencies (frequencies less than one were excluded from all analyses). Analyses of residuals were conducted to confirm which categories accounted for the significant effects (i.e., a residual greater than 2.00 indicates the factor was a major influence for the significant chi-square test statistic). Education differences were minimal at the attitude category level; therefore we collapsed across education for the remaining analyses. Table 2 ). Significantly more technologies were reported in the context of the home (M = 19 per group) compared to work (M = 13 per group). A greater number of technologies were reported in the context of work compared to health (M = 7 per group). These data suggest that older adults are willing to use various types of technology in different facets of their lives, particularly in their homes. A primary goal of this study was to gain a better understanding of older adults' attitudes related to using different technologies. Number of attitudes-A total of 2360 segments were coded as attitudes. The number of attitude segments varied by domain: home (n = 1119), work (n = 785), and health (n = 560). That is, more attitudes were produced when discussing technology use in the home as compared to work, and more attitudes were elicited when discussing technology use for work compared to health. Older adults may have more attitudes about technologies used in their homes compared to work and health because they use a wider variety of technologies in the home and spend most of their time there. Attitude segments were coded for the technology item to which they were referring. Technology items associated with 5% or more of the total attitude segments within a domain are listed in Table 3 . These technologies represent those most commonly mentioned, serving as the basis for the discussions and, therefore, provide the specific context for the following data. Relative proportion of likes and dislikes-Of particular interest was the relative proportion of like and dislike attitudes. Excluded from further analyses were attitude segments coded as unclear (4%), such as "I can't think of any [likes or dislikes]."and "I don't know whether it's a like or dislike." Counter to the stereotype that older adults hold negative opinions about technology, participants expressed significantly more likes than dislikes when discussing technologies used in the home (60% vs. 36% of the total segments, χ 2 (1) = 69.07, p < .01), for work (59% vs. 37%, χ 2 (1) = 40.88, p < .01) and for health (60% vs. 35%, χ 2 (1) = 37.79, p < .01). Note that due to the phrasing of the question it is possible that participants were primed to produce more likes because the word "like" preceded the word "dislike." Nonetheless, the majority of older adults' attitudes were positive, suggesting that they perceived the benefits of using technology to outweigh the costs, regardless of domain. This finding is consistent with the results of Melenhorst, Rogers, and Bouwhuis (2006), which showed that perception of benefit was more indicative of acceptance than perception of cost. We were also interested in the reasons provided for having positive or negative attitudes about technology. Some responses only contained an attitude without an additional reason (e.g., "I like using the computer"). This was true for 8% of the like segments for the home domain, 4% for work, and 6% for health. These segments were excluded from the following analyses. Why people liked technology-With respect to the reasons mentioned for having positive attitudes about technology, the specific category frequencies differed within each of  NIH-PA Author Manuscript NIH-PA Author Manuscript the three domains (see Fig. 1 ). However, across all domains older adults consistently focused on support for activities, convenience, and features as the top three reasons for why they like technology. Segments in these three categories were also coded on a subcategory level (see Tables 4-6 for percentages and example quotes). Like: Support for activities-When discussing what they liked about technology, participants frequently mentioned its ability to provide support for activities. Some activities were mentioned significantly more than others in the home, χ 2 (10) = 105.40, p < .01, for work, χ 2 (8) = 189.50, p < .01, and for health, χ 2 (7) = 186.30, p < .01. In the context of the home, older adults focused on communication (e.g., emailing, calling friends and family), cooking (e.g., microwaves), leisure, hobby, and entertainment activities (e.g., VCRs, computer games), and research (e.g., searching for information on the Internet) which together accounted for 68% of the support for activities data. In the work domain, the most frequently reported activities for which participants reported liking to use technology were communication (e.g., conference calls, exchanging documentation), administrative tasks (e.g., copying, executing mass mailings), and research (e.g., finding information on the Internet, profession-specific research tasks), accounting for 79% of the data. In the health domain, research (e.g., finding information about physicians, health conditions, and medications) and health monitoring and maintenance (e.g., checking blood pressure and monitoring weight) were the most frequently reported activities for which participants reported liking to use technology, accounting for 73% of the data. These data show clearly that older adults perceived technology that can support their research activities to be a significant benefit, regardless of domain. In addition, older adults perceived technological support for administrative tasks and communication as important advantages in the home and at work. These data reveal that the activities for which participants liked to use technology were more varied in the home than at work or for health, which may reflect that the home is a broader domain encompassing a wider range of activities. Like: Convenience-Convenience was another frequently reported benefit of technology use. Significant differences emerged between the convenience subcategory frequencies for home, χ 2 (7) = 75.50, p < .01, work, χ 2 (5) = 102.30, p < .01, and health, χ 2 (6) = 46.83, p < . 01. In the home domain, effort and unspecified convenience were most frequently mentioned (50% of convenience data). Effort is analogous to ease of use and was defined to include physical and mental forms of effort. Participants reported liking technology (e.g., dishwasher or sprinkler system) because it reduced their own effort in performing household tasks. Unspecified convenience refers to general statements about convenience without specifying a type or form of convenience. In the work domain, effort and time (70% of convenience data) were the most frequently mentioned convenience-related reasons for liking a technology. Older adults expressed positive attitudes about using technology to reduce effort in their work tasks, which varied greatly (e.g., using a computer instead of writing by hand and using electric instead of manual hair clippers), as well as to increase work performance by reducing the time it takes to perform tasks (e.g., scanning barcodes rather than typing item numbers). In the context of health, the effort and home-based categories (63% of convenience data) accounted for the significant effect. Participants expressed positive statements about technology reducing their own effort for performing health-related tasks, such as using Comput Human Behav. Author manuscript; available in PMC 2011 November 1. NIH-PA Author Manuscript NIH-PA Author Manuscript automatic medication refill telephone systems rather than going to the pharmacy. Participants also liked that technology afforded them the ability to perform health-related tasks at home, such as checking their blood pressure. These convenience data demonstrate that older adults appreciated that technology can make their lives easier in general, as well as make specific tasks less effortful in their homes. Older adults also perceived the importance of being an efficient worker and understood that technology can facilitate efficiency. In sum, across all domains, the reduction of physical or mental effort was a major contributing factor to older adults' positive perceptions about the convenience introduced by technology. Like: Features-Participants expressed positive attitudes about many properties and characteristics of technology. Some features were discussed significantly more frequently than others in all domains: home, χ 2 (11) = 324.70, p < .01, work, χ 2 (9) = 130.70, p < .01, and health, χ 2 (9) = 20.90, p < .01. Specific features, speed, and number of features accounted for the significant effect in the home domain (69% of feature data). Examples of specific features were the water and ice dispenser (refrigerator); the timer and sleep mode (television); and the redial button, caller id, and voicemail features (telephone). Speed referred to the technology's ability to perform operations quickly, and the number category encompassed comments about number of features, quantity, or amount, including the number of programming options. In the context of work, specific features, speed, and access, storage and retrieval made the greatest contribution to the significant effect (72% of feature data). As seen in the home domain, participants reported liking specific features such as speakerphone and spell check. Again, older adults expressed positive attitudes about technologies performing operations quickly, such as faxing rather than mailing documents. Participants also spoke positively of the ability to access, store, and retrieve information, such as the computer's ability to perform these actions rather than having to rely on hard copies. For the health domain, specific features, and portability and size were significant contributors to the effect (39% of feature data). Specific features included date and time on medical devices and the ability to get a print out from a device. Portability and size characteristics were viewed positively as well, such as the design of hearing aids to fit inside the ear and the size and portability of blood glucose meters. The data about technology features reflect that older adults perceived the benefits of technology to include performing specific and quick actions, as well as offering many options. The perceived benefits of technology were similar for home and work domains (i.e., specific features and speed), although accessing, storing and retrieving information was an additional benefit for work. Participants spoke most frequently about their positive attitudes toward specific features of multi-function health technologies, and the characteristic of health technologies being small and portable. The feature data demonstrate that the older adult participants had preferences for the design of technology items, which is of particular importance for technology designers. Why people disliked technology-We were also interested in the reasons for which older adults reported disliking technology, as these details could provide insight into technology acceptance (i.e., the reasons for which a person might not adopt technology). The category frequencies varied within all domains (see Fig. 2 ). In comparison to the top three likes (support for activities, convenience, and features), when a reason was provided for disliking a technology, it was most frequently related to inconvenience brought on by using the technology and features of the technology, regardless of the domain being discussed. Security and reliability issues were also frequently mentioned as dislikes: Security emerged in the home and work domains, whereas reliability arose in all domains. Subcategories for inconvenience, features, and security provide more details about older adults' reasons for disliking technologies (see Tables 7-9 for percentages and example quotes); the reliability category did not have subcategories. Dislike: Inconvenience-Various types of inconvenience were frequently mentioned dislikes. There were significant differences among the frequencies of types of inconvenience discussed in the home, χ 2 (7) = 82.43, p < .01, for work, χ 2 (7) = 71.42, p < .01, and for health, χ 2 (5) = 21.11, p < .01. In the home domain, interruptions, financial issues, and effort accounted for 76% of inconvenience data. Participants mentioned technology causing interruptions in their lives (e.g., unwanted calls, commercials) and being expensive (e.g., the cost of ink cartridges and cellular phones). They also made negative comments about technology requiring or increasing effort, such as the computer requiring too much mental effort to use or having to carry around a cellular phone. In the work domain, the most frequently reported dislikes related to inconvenience were interruptions and effort (58% of inconvenience data). Just as in the home, participants discussed disliking interruptions (e.g., cell phones ringing at inappropriate times) and the effort required for using certain work technologies. In the health domain, the most frequently reported inconveniences fell into the physical and effort categories (57% of inconvenience data). Participants reported disliking the physical inconveniences of using certain technologies, such as having to prick a finger to use a blood glucose meter. Effort inconveniences included physical and mental effort required to use certain medical devices or other health-related technologies. The inconvenience data suggest that older adults perceived interruptions, financial expenses, and effort to be costs of using technology in their homes. Workplace technologies were disliked for some of the same reasons (i.e., interruptions and effort). Physical inconvenience was a complaint specific to healthcare technologies, which may be due to the fact that many measures of physical health status rely on some sort of physical intrusion or discomfort. Dislike: Features-Participants expressed negative attitudes about many features of technology. There were significant differences between the subcategories of features for home, χ 2 (10) = 56.70, p < .01, and for work, χ 2 (9) = 29.08, p < .01. There was not a significant difference between the subcategories for health, p = .17. In the home domain, number of features, content quality, and quality of output accounted for 63% of the feature data. Participants reported disliking when technology items had too many or too few features or programming options, poor content or programming quality (e.g., too much violence on television), and poor output quality, such as the quality of sound or the picture of a visual display (e.g., on a cellular phone). In the work domain, number (31% of feature data) accounted for the significant effect. In particular, older adults disliked work technologies with too many or too few features or programming options (e.g., telephones and fax machines). These data demonstrate that just as participants liked technologies that made them more efficient workers, they disliked technologies that reduced their efficiency. The feature-related data demonstrate that the older adult participants had specific ideas about features they view as costs in using technology. Moreover, features of technology constituted the majority of the older adults' dislikes. In the home and work domains, participants focused on the number of features as a common dislike. In the home domain content quality and output quality was also a frequent dislike. The relative frequencies of the  A thorough understanding of older adults' usage and perceptions of technology is essential for maximizing the potential that technology has to offer for facilitating independence in everyday life. The goal of this study was to explore in-depth a large and diverse sample of older adults and their attitudes about a wide range of technologies they use in a wide variety of contexts (i.e., their homes, for work, and for health). The findings from this study supplement past research that was limited with respect to the details about technology usage or the generalizability to different types of technologies, contexts, or users. The results elucidate some of the reasons behind older adults' attitudes toward technology, provide insight into how people define the constructs in technology acceptance models, and can enable designers to better meet older adults' needs and preferences. Stereotypes suggest that older adults are unable, unwilling, or afraid to use technology. Indeed, consistent with these stereotypes, several large scale usage studies have found that older adults do not use certain technologies to the extent that younger adults do (Adler, 2006; Pew, 2000). The older adults we interviewed used a wide variety of technologies, ranging from microwaves to cell phones to computers. Participants reported using the greatest number of technology items in their homes, a finding perhaps reflecting that our sample comprised mostly retired and healthy older adults. Older adults who have health problems would be expected to have more experience using health technologies and those who are still employed would be expected to have more experience with work-related technologies. By focusing on a broader range of technologies than that of large-scale surveys (e.g., Pew, 2000) and by employing qualitative methods, we were able to provide a more detailed depiction of older adults' attitudes about technology in general. Participants clearly perceived many benefits of using technology, regardless of domain, and they viewed those benefits as outweighing the costs, judging by the number of comments they made about the positive aspects of technologies. Benefits discussed related to technology supporting activities (i.e., communication, research, and health monitoring and maintenance), adding convenience (i.e., when technology reduces effort), and having useful features (i.e., specific features of technology). Although the benefits discussed were greater in number, costs or  NIH-PA Author Manuscript NIH-PA Author Manuscript dislikes of using technology were discussed as well. The dislikes were more varied than the likes and included technology causing inconvenience, features of technology, security issues, and reliability of technology. These data are consistent with the findings of Melenhorst et al., (2006) in that older users' motivation for using email technology was driven by perception of benefit more so than perception of costs associated with usage.
The older users generally consider that modern technology brings progress and many benefits; however, they are not sure of its benefits as they consider themselves not skilled enough to use such high-technology applications REF .
Older adults talk technology: Technology usage and attitudes
Computers in human behavior
Computers in human behavior
Computer Science Psychology Medicine