Keywords

1 Introduction

The number of people aged 60 years and over has almost doubled in 2017 (962 million) compared to 1980 (382 million) [1]. UN expects that by 2050 the number of persons over the age of 60 will get close to 2.1 billion. Following this prediction, in 2050, older people will account for 35% of the population in Europe. Life expectancy increased dramatically over the last 150 years, from 30 to 65, and it continually grows [2, 3]. According to some estimates, life expectancy will exceed 100 years before 2100 [2].

As Neves and Vetere [4] noted, new technologies could have a crucial role in meeting the needs and interests of older people. New technology could help older people to expand their social support through better communication with family and friends [5, 6]. Also, it could help older people to gain important health information, to compensate for memory lapses and cognitive decline, as well as to explore additional resources related to fun and leisure. The use of new technologies, such as e-banking and online shopping, is closely related to the wide range of services that are almost imperative in the modern world. The service sector relies heavily on technology solutions, viewing it as a competitive advantage, but without paying proper attention to older users. Taking into the account the rising number of older employees in the global workforce [7], and the fact that training methods heavily rely on technology-based instruction [8], the acceptance and adjustment of new technology to older users is imperative.

Even though the acceptance and usage of new technology have increased, older people are still less prone to keep pace with digital development. Usually they are dropping out with age. Consequently, the conceptualization of older/old age is, apart from other frameworks, also shaped in relation to technological context as being ‘too old’ for adjusting to new technology [4].

The cognitive and physical changes that come with aging tend to become more noticeable around the age of 65 [8]. However, many researchers found that the main obstacle for older people to embrace ICT is not related to skill deficits, but rather to negative attitudes [9]. Personality dimensions could improve the acceptance of technology, with the most significant predictors being extraversion, openness to experiences, and emotional stability [10]. Nevertheless, in a number of studies [11,12,13], attitude toward computers stood out as the most significant predictor for their use. In the study of Rosenthal [14] where she analyzed obstacles and factors that influence some older women to accept computers and to become ‘computer literate’, nearly half of the women (48%) reported being anxious or stressed when beginning to learn how to use a computer. Based on being perceived as anxious when facing new technologies, older people are usually considered as ‘technophobic’. However, as Lee et al. [6] pointed out, this is usually dispelled when benefits of adoption of new technology are more prominent then potential costs.

The term older adult is defined in different ways [15]. Whether some adult would be treated as older highly depends on the context in which the observation is made [15]. In the workplace context, the term older adult generally refers to workers over 50. At the same time, employees over 50 are the age group whose labor participation is among the most scrutinized. For example, the share of employees aged 50 years and older has risen from 24% to 31% over a period of 10 years, 2005–2015 [7], but still there is a need to rise their labour participation. As Lee et al. [6] stated, researchers divide seniors into following stages: the young-old (65–74), the old-old (75–85), and the oldest-old (85 years and beyond). The group of 50–64 years of age is considered as pre-seniors or pre-retirees, and they are also sometimes included in the analyses of constraints of using technological devices among seniors [6].

ICT design for older people was until recently perceived as something on the outskirt of the designing trends [16]. The concept of ‘inclusive design’ [16], as well as ‘gerontechnology’ [17] has emerged as a strong trend aiming at embracing the needs of older users and overcoming the ‘digital divide’ [17] between generations. Thus understanding the needs, capabilities and experiences of older people is crucial in developing successful inclusive design [17].

The aims of this study were to: 1). analyze middle-aged and older adults’ computer proficiency taking into the account intelligence, personality traits and attitudes towards computers (Study 1); 2). analyze middle-aged and older adults’ intention to use online services in relation to their attitudes towards computers on the example of online payment (Study 2); 3). explore enabling factors of using digital devices among older people (Study 3). The overall aim of the paper was to propose a way to better introduce and integrate older people to the digital world as digital newcomers.

2 Study 1

2.1 Sample and Procedure

The sample comprised of 120 persons. The average age was 63 years (57% women), 78% of respondents were above the 55 years, with the majority of them having high school diploma (42%). Respondents filled out paper-and-pencil tests and scales. The participation was voluntary, anonymous and not remunerated.

2.2 Instruments

Cognitive Abilities.

Cognitive abilities were assessed using the nonverbal general intellectual ability test BEG-SERIES [18]. The test consists of two sub-tests: the matrices and the combining shapes test. The reliability of the matrices test, determined by the Spearman-Brown method was .88, and by the test-retest method .76. The reliability of the combining shapes test predicted by the Spearman-Brown formula was .86, and the test-retest reliability was .89. The combining shapes test is mostly saturated with the perceptual reasoning factor, while the matrices are most saturated by the “G” factor. The test is suitable for older people as well as for the people with a lower educational level [18].

Personality Traits.

Personality traits were assessed using the Big Five Inventory [19]. The BFI consists of 44 items rated on a five-point Likert scale (from 1 – completely disagree, to 5 – completely agree). Three dimensions previously shown to be relevant for the research of older people and ICT adoption and usage were included in this research, i.e. Openness to experiences (10 items), Extraversion (8 items) and Neuroticism (8 items).

Attitude Toward Computers.

Attitude toward computers was assessed using the Computer Attitude Measure for Young Students (CAMYS) [20]. CAMYS was originally intended to evaluate the attitudes of students, age from 10 to 13. However, the primary goal of CAMYS authors was to use the instrument to evaluate attitudes of respondents with limited or no experience in working on a computer. Therefore it was suitable for use with older respondents. This questionnaire covers three dimensions: perceived ease of use, affect toward computers and perceived usefulness, 12 items in total (four items for each factor), each accompanied by five-point Likert scale (from 1 – completely disagree, to 5 – completely agree).

Computer Proficiency.

The Computer Proficiency Questionnaire (CPQ) [21] was used to assess computer proficiency. It consists of six subscales covering different activities with a computer, such as using a printer and the Internet, or using a computer for entertainment. For the purposes of this research, a shorter version of the questionnaire (CPQ-12) was used. It consisted of 12 items (2 items for each subscale). Respondents rated their performance on a five-point scale from 1 – never tried, to 5 – being completely successful in the activity.

2.3 Results and Discussion

Table 1 summarizes the descriptive statistics and correlation analysis. Computer proficiency was positively and significantly correlated with general ability, neuroticism, openness to experience and computer attitudes. The strongest correlation was found between computer proficiency and computer attitude, while there was no significant correlation between extraversion and computer proficiency.

Table 1. Descriptive statistics for cognitive abilities, personality traits, attitudes toward computer and computer proficiency and correlation of computer proficiency with remaining variables.
Full size table

A three-stage hierarchical multiple regression was conducted with computer proficiency as a criterion variable. Sociodemographic variables (gender, age and education) were entered at step one of the regression to control for these differences. The intelligence and personality dimensions were entered at step two, and, finally computer attitude at step three. The hierarchical multiple regression revealed that at step one, sociodemographic variables contributed significantly to the regression model, F(3,114) = 14.02, p < .01 and accounted for 27% of the variation in computer proficiency. Introducing the intelligence and personality variables explained an additional 18.4% of variation in computer proficiency FChange(5,109) = 7.33, p < .001. Adding computer attitude to the regression model explained additional 31% of the variation in computer proficiency FChange(1, 108) = 139.598, p < .001. When all six independent variables (apart from sociodemographic ones) were included in stage 3 of the regression model, it was shown that only the following predictors remained significant; i.e. combining shapes (beta = .217, p < .01), openness to experiences (beta = .135, p < .05) and the attitude toward computers, as the strongest of the remaining significant predictors (beta = .621, p < .01).

Another hierarchical multiple regression analysis was conducted with computer proficiency as a criterion variable and different dimensions of attitudes - perceived ease of use, affect toward computers and perceived usefulness as predictors. Sociodemographic variables (gender, age and education) were entered at step one of the regression (as in the first model). The perceived ease of use, affect toward computers and perceived usefulness were entered at step two. Sociodemographic variables contributed significantly to the regression model, F(3,114) = 14.03, p < .01 and accounted for 27% of the variation in computer proficiency. Introducing the attitudes dimensions explained additional 44.2% of variation in computer proficiency FChange(3,111) = 56.86, p < .001. Nevertheless, not all dimensions of attitudes were significant. Namely, it was shown that most significant predictors were perceived ease of use (beta = .396, p < .00) and affect toward computers (beta = .222, p < .05).

3 Study 2

3.1 Sample and Procedure

The sample comprised of 86 adults (62% women); their average age was 62 years, while 91% of respondents were above the age of 55 years. Respondents filled out a questionnaire in paper-and-pencil form. The participation was voluntary, anonymous and not remunerated.

3.2 Instruments

Attitude Toward Computers.

Attitude toward computers was assessed using the Computer Attitude Measure for Young Students (CAMYS) [20].

Intention to Use the Electronic Payment of Bills.

Intention for electronic bill payment was assessed using a 3-item scale from the study of Lian and Yen [22], which was initially developed for assessing drivers and barriers to online shopping. The items were adapted for the electronic payment of bills; examples of items were: I intend to pay bills electronically in the future; I predict I would pay bills electronically in the future; I intend to continue paying bills electronically.

3.3 Results and Discussion

Table 2 summarizes the descriptive statistics and correlation analysis. As can be seen from Table 2, computer attitude is strongly and positively correlated with the intention to use electronic bill payment.

Table 2. Intention for electronic bill payment and attitude toward computers: descriptive statistics and intercorrelations.
Full size table

A hierarchical multiple regression analysis was conducted with the intention to pay bills electronically as a criterion variable and different dimensions of attitudes toward the computer, i.e. perceived ease of use, affect toward computers and perceived usefulness as predictors. Sociodemographic variables (i.e. gender and age) were entered at step one of the regression, as in the previous study. The perceived ease of use, affect toward computers and perceived usefulness were entered at step two. Sociodemographic variables did not contribute significantly to the regression model, F(2,83) = 0.819, p = .444. Introducing the dimensions of attitudes in step 2 explained additional 48.2% of variation in the intention to pay bills electronically FChange(3,80) = 25.764, p < .001. When all three dimensions of attitude towards computer were included in step 2, it was shown that only perceived ease of use remained a significant predictor (beta = .459, p < .00).

4 Study 3

4.1 Sample and Procedure

The qualitative sample encompassed 30 adults, age 56 years and older (average age was 65 years). Data were collected using semi-structured interviews. The research participation was voluntary, anonymous and not remunerated.

4.2 Instruments

The semi-structured interview covered attitudes toward using digital devices (desktop computers, laptops, smartphones and tablets), and drivers and barriers for their usage.

4.3 Results and Discussion

Digital devices are mainly used for fun (interests and hobbies), communications (especially with family and friends living abroad) and following news. Main drivers are social pressure as everyone uses them and ease of doing things (as research participants put it: “Information is easily accessible and you do not have to try hard to collect them”; “It is faster and easier and relaxing for the brain”). Usage of various digital devices is more easily spread among those that started using computers at work. Having close support, such as family members and friends, on one side, and a learning buddy on the other, are powerful drivers in mastering new electronic devices and software. One of the strongest barriers to using online services is the wish of older people to maintain social contacts in person while using traditional services.

Main identified barriers were related to lack of skills. Using digital devices is sometimes perceived “as a waste of time”, mainly because older users are not skilled enough, and it takes them more time to do something. One of the barriers related to acquiring IT skills is fear of failure. Likewise, the process of mastering skills brings problems as usually younger, informal trainers (i.e. family members, friends and colleagues) easily get impatient if they have to repeat instructions, to quote one respondent: “If I forget how to do something and ask again, they get annoyed”. Concerning lack of skills and knowledge about devices, there is also widespread fear of damaging the device, “making a mess”, or as one of the participants said, “If I spoil something, I get frustrated, and I am not able to touch it for several days”. Poor command of English (as it is a foreign language), presents a significant barrier for truly embracing the digital world.

5 Overall Discussion and Intervention Proposal

Attitude towards computer was the strongest predictor of computer proficiency of older people (Study 1). Analyzing intention to use electronic services, i.e. electronic payment, only one dimension of attitude towards computers - perceived ease of use proved to be a significant predictor (Study 2). Most important findings from the qualitative research (Study 3) were: 1). desktop computers’ main advantages for older users are large screen and keyboard; external mouse was easier for use than laptop touchpad; 2). main benefits of using laptops for older users were their portability (as for smartphones), and screen size (larger than on smart phones); 3). smartphones are strongly preferred as portable, more intuitive and easier to use (on the other hand, the smaller size of the touch screen and consequently smaller touch targets make it easier for older users to make mistakes).

In line with previous research, family and friends are older persons’ most preferred source of support in acquiring new IT skills, not just because of their availability and as an impulse for highly valued social interaction with close ones [23], but also as a self-confidence building mechanism, especially for those that are more anxious [24]. The conclusion that the attitude towards digital devices turns out to be the strongest predictor of users’ digital proficiency supports Wolfson, Cavanagh and Kraiger’s [8] recommendation about the need for motivating and developing self-efficacy as part of training for older people. As peer education is already a widespread mechanism for acquiring IT skills among older people, the trainers should give them some additional understanding that would help pass the acquired knowledge to their older friends. Trainers should also encourage them to take part in coaching older friends. The future research should further explore, and later on evaluate, appropriate contents and training methods, as well as effects of different trainers (e.g. peer trainers or professional trainers) on computer proficiency of older training participants. Apart from that future research should explore the motivation of older people for taking part in IT skills training.

Problems that older people still encounter in using various digital tools prove that designers still rely on stereotypes about older users [25]. Though proposals about involving older persons into developing new IT tools right from the beginning could be found in the literature for quite some time [26], there is still a strong need to advocate for this. Qualitative findings are in line with findings of the change in cognitive capacities of older people that point to the need to tailor IT training of older people according to their capabilities [8].

Based on presented findings and the literature review, we propose an intervention that would enable older people to rely more heavily on ICT devices, mainly on a tablet as an adequate device for older people. One of the important long-term aims of the intervention should be advocating for involving older people in designing digital tools, both devices and programs. In order to be sustainable, this intervention should engage the relevant stakeholders: municipality officials, social care officials, Red Cross professionals and volunteers, social clubs and spaces for older people, IT and user experience experts, psychologists, producers and retailers of tablets, family of older people and their friends (both peers and younger).

Municipality officials, social care officials, Red Cross professionals and volunteers should support the program and enable all the needed resources (people, devices, training equipment, space). IT experts, user experience experts and psychologists should provide the expert knowledge base for the training, as well as setting tablets for older users. Family and friends of older people should be the trainers and first line of motivators and supporters.

The core of the intervention entails designing the training for older people and two levels of train the trainer program: 1. Train the trainer program for older persons’ family and friends, and 2. Train the trainer program for older persons that would be ‘focal points’ and those that would spread digital literacy among older peers. It is important to stress that, as family members and younger friends belong to the so-called “sandwich” generation that has to deal with numerous pressures, the training itself should be brief. It is of utmost importance to provide online tools and support and to stress the importance of specific issues of motivating older people to learn and to use digital tools. The training should also cover giving instructions and feedback to older people in line with their cognitive and motor functioning. For the long-term sustainability of the program, senior experts for spreading digital literacy among older peers should function as ‘focal points’. Senior focal persons should be active participants at social spaces for older people, both offline and online.

The proposed intervention may seem too complex and demanding. We should be aware that we live in the world of constant IT innovations. Under these circumstances, people of all ages are a sort of digital newcomers that have to keep pace with the constant development of new technologies. Older people will always be in a specially challenging position in this never-ending story. As an adequate response, it is important to develop a self-sustainable system of training through social spaces for older people, with, occasional support of relevant stakeholders.