*2.2.5 Some health issues can improve*

Ageing also has some basic physiological aspects: it is related to changes in the cardiovascular and cardiopulmonary systems; however deficits can be reduced by training, practice, aerobic exercise and these also may improve the efficiency of neural processes, which we can see in healthier older adults' increased take-up of technology [44–46].

### *2.2.6 Summary of non-cognitive changes*

Therefore we can say that increasing age is associated with more positive attitudes and emotions and an optimistic bias; self-awareness of functional decline leads to many age-counteracted or self-regulatory behaviours; resistance to change is the default position and slowly increases through adulthood; older people have a lower self-assessment of skills and abilities; increased lack of confidence, fear and anxiety with regard to new technologies, perceived less comfort with, efficacy or control over computers, dehumanisation all affect motivation to engage with new technology. Attitudes change [to new technology] requires reinforcement otherwise it will decay. Self-efficacy is predictive of better health in older people- relevant to adopting new technology.

### **2.3 How do people learn new technologies or resist becoming "tech-savvy"**

### *2.3.1 Age related factors*

Learning of new technologies is a complex challenge for many older adults if it does not suit individual capabilities; reasons include perceived loss of control, lack of confidence, not seeing the need, wanting to retain the status quo and so on, many articulated in this chapter already [47–51]. Reasons for adoption of new technology *de facto* follow the reverse of these, and would include feeling confident and in control, perceiving a current need and recognising a future need plus past relevant experience [52, 53].

Since much information technology only began to become commercially available in the mid-1980s, so younger people have a 'head start' and often tend to be good at digital technologies; they invariably use them at school or at work in the form of computers, laptops or smartphones, and even internet access in households with an adult aged 65+ have now risen to 80% in 2020, and online shopping has increased massively especially in 2020 [54]. Those older adults whose occupations involved computer use, e.g. engineers [52, 53] are more likely to perceive the need for and be able to learn and use new technologies with confidence.

However the evidence is that most people, across all ages, are a long way from being tech-savvy, and that also includes a large proportion of older people; as technology develops, it may always be ahead of older people, although if the development rate levels off this may be less of an issue in years to come.

#### *2.3.2 The digital divide*

An international study by OECD [1] attempted to quantify the differences between the broad population and the technology elite: data collected from over 200,000 people aged 16–65 in 33 countries yielded four levels of technology proficiency. The findings suggest that over 65% of UK adult population are at Level 1 (can do tasks typically requiring the use of widely available and technologies, applications such as email software or a web browser") or below. The OECD average

**61**

*Attitudes and Behaviours in Relation to New Technology in Transport and the Take-Up…*

for level 0 or 1 is 69% with Japan 66%, USA 67% and New Zealand 56%. So there is a clear *technology- divide across all ages*, which can be proposed to be larger than any

Therefore for designers to target a broad consumer audience at any age,

• keep it extremely simple, meaning little/no navigation required to access

More importantly for our considering older people here, the OECD study did not include people aged over 65, where the percentages of being Level 1 or below should be considerably higher. It is clear that there is a responsibility- and benefitfor designers of current and future ICT to make it accessible, affordable, anxietyfree and helpful so older adults can use it [55]. Most ergonomists and gerontologists would agree that designing for the disable user would be similarly useful to all.

Page [50] suggested that whilst older users may show a keen interest in learning and using technology, they often do not feel fully equipped to do so. Motivation to learn may also be a function of utility; this means that over-complexity may present

One key area for non-engagement with technology relates to user confidence in own abilities, fear and anxiety [53, 56]. Technology has been shown to be a source of anxiety amongst older users, for example concerning loss of privacy, lack of confidence, a perceived lack of need and an unwillingness to learn through trial and

Working with computers, tablets or smartphones inherently requires working memory and fluid intelligence, the ability to reason and solve new problems independently of previously acquired knowledge, which are also predictive of each other, along with attention-switching (e.g. [59]). Whilst training on working memory can improve general fluid intelligence, the effect is dosage-dependent, so the more training, the greater the improvement. The implications of this for training older people in new technology are therefore considerable (e.g. [60, 61]).

Instructions and manuals are often not clear, difficult to follow, and need to be improved; there is some research on this already, but more is needed. Examples of where this has been done to very good effect, in the commercial and Government areas, is the work on instructional text of James Hartley (e.g. [62]); examples of this approach can be seen in the design of entirely visual passenger safety information in airplanes and some instruction formats. Too much instructional information in a manual or Web Page, or too much hierarchical and negative searching can lead to

In summary, *there is and will continue to be a digital divide in tech-savviness*albeit not total illiteracy on the lower side but a divide nevertheless, which extends currently down to 16–25 year olds. Older people may be less confident and poorly motivated to take on new technology, but there is a strong role for additional training to help with working memory and fluid intelligence and a need to develop

• allow identification of content and operators through simple match

information or commands required to solve a problem;

• have few steps or operations, few monitoring demands;

• include no need to contrast or integrate information.

older users with a problem beyond what they can manage [29].

*DOI: http://dx.doi.org/10.5772/intechopen.94963*

*age-divide*.

they must:

error [55, 57, 58].

cognitive load issues [63, 64].

*2.3.3 Summary of section*

*Attitudes and Behaviours in Relation to New Technology in Transport and the Take-Up… DOI: http://dx.doi.org/10.5772/intechopen.94963*

for level 0 or 1 is 69% with Japan 66%, USA 67% and New Zealand 56%. So there is a clear *technology- divide across all ages*, which can be proposed to be larger than any *age-divide*.

Therefore for designers to target a broad consumer audience at any age, they must:


More importantly for our considering older people here, the OECD study did not include people aged over 65, where the percentages of being Level 1 or below should be considerably higher. It is clear that there is a responsibility- and benefitfor designers of current and future ICT to make it accessible, affordable, anxietyfree and helpful so older adults can use it [55]. Most ergonomists and gerontologists would agree that designing for the disable user would be similarly useful to all.

Page [50] suggested that whilst older users may show a keen interest in learning and using technology, they often do not feel fully equipped to do so. Motivation to learn may also be a function of utility; this means that over-complexity may present older users with a problem beyond what they can manage [29].

One key area for non-engagement with technology relates to user confidence in own abilities, fear and anxiety [53, 56]. Technology has been shown to be a source of anxiety amongst older users, for example concerning loss of privacy, lack of confidence, a perceived lack of need and an unwillingness to learn through trial and error [55, 57, 58].

Working with computers, tablets or smartphones inherently requires working memory and fluid intelligence, the ability to reason and solve new problems independently of previously acquired knowledge, which are also predictive of each other, along with attention-switching (e.g. [59]). Whilst training on working memory can improve general fluid intelligence, the effect is dosage-dependent, so the more training, the greater the improvement. The implications of this for training older people in new technology are therefore considerable (e.g. [60, 61]).

Instructions and manuals are often not clear, difficult to follow, and need to be improved; there is some research on this already, but more is needed. Examples of where this has been done to very good effect, in the commercial and Government areas, is the work on instructional text of James Hartley (e.g. [62]); examples of this approach can be seen in the design of entirely visual passenger safety information in airplanes and some instruction formats. Too much instructional information in a manual or Web Page, or too much hierarchical and negative searching can lead to cognitive load issues [63, 64].

#### *2.3.3 Summary of section*

In summary, *there is and will continue to be a digital divide in tech-savviness*albeit not total illiteracy on the lower side but a divide nevertheless, which extends currently down to 16–25 year olds. Older people may be less confident and poorly motivated to take on new technology, but there is a strong role for additional training to help with working memory and fluid intelligence and a need to develop

*Models and Technologies for Smart, Sustainable and Safe Transportation Systems*

Ageing also has some basic physiological aspects: it is related to changes in the cardiovascular and cardiopulmonary systems; however deficits can be reduced by training, practice, aerobic exercise and these also may improve the efficiency of neural processes, which we can see in healthier older adults' increased take-up of

Therefore we can say that increasing age is associated with more positive attitudes and emotions and an optimistic bias; self-awareness of functional decline leads to many age-counteracted or self-regulatory behaviours; resistance to change is the default position and slowly increases through adulthood; older people have a lower self-assessment of skills and abilities; increased lack of confidence, fear and anxiety with regard to new technologies, perceived less comfort with, efficacy or control over computers, dehumanisation all affect motivation to engage with new technology. Attitudes change [to new technology] requires reinforcement otherwise it will decay. Self-efficacy is predictive of better health in older people- relevant to

**2.3 How do people learn new technologies or resist becoming "tech-savvy"**

Learning of new technologies is a complex challenge for many older adults if it does not suit individual capabilities; reasons include perceived loss of control, lack of confidence, not seeing the need, wanting to retain the status quo and so on, many articulated in this chapter already [47–51]. Reasons for adoption of new technology *de facto* follow the reverse of these, and would include feeling confident and in control, perceiving a current need and recognising a future need plus past relevant

Since much information technology only began to become commercially available in the mid-1980s, so younger people have a 'head start' and often tend to be good at digital technologies; they invariably use them at school or at work in the form of computers, laptops or smartphones, and even internet access in households with an adult aged 65+ have now risen to 80% in 2020, and online shopping has increased massively especially in 2020 [54]. Those older adults whose occupations involved computer use, e.g. engineers [52, 53] are more likely to perceive the need

However the evidence is that most people, across all ages, are a long way from being tech-savvy, and that also includes a large proportion of older people; as technology develops, it may always be ahead of older people, although if the develop-

An international study by OECD [1] attempted to quantify the differences between the broad population and the technology elite: data collected from over 200,000 people aged 16–65 in 33 countries yielded four levels of technology proficiency. The findings suggest that over 65% of UK adult population are at Level 1 (can do tasks typically requiring the use of widely available and technologies, applications such as email software or a web browser") or below. The OECD average

for and be able to learn and use new technologies with confidence.

ment rate levels off this may be less of an issue in years to come.

*2.2.5 Some health issues can improve*

*2.2.6 Summary of non-cognitive changes*

technology [44–46].

adopting new technology.

*2.3.1 Age related factors*

experience [52, 53].

*2.3.2 The digital divide*

**60**

good instructional material to support this. Personalised and self-regulated learning should be available for all new technology.
