The meaning and value of digital technology adoption for older adults with sight loss: A mixed methods study

Abstract

BACKGROUND:

Sight loss adversely affects older adults’ ( $>$ 65 years) ability to complete daily activities. Digital technology can support functional performance but literature focusing on its use by older people with sight loss is limited.

OBJECTIVE:

To explore the meaning of digital technology, including factors influencing its adoption, from the perspectives of older adults with sight loss.

METHOD:

In-depth data was generated via a focus group ( $n=$ 4) and analysed using thematic analysis. In addition, a questionnaire survey ( $n=$ 30) increased breadth of knowledge regarding digital device adoption.

RESULTS:

Following thematic analysis, digital technology was equated with complexity. Portable, easy-to-use technology and devices enabling meaningful outcomes were favoured. Barriers to adoption included: high cost, lack of accessible information, unreliability and constantly changing products. Conversely, resource exchange and an interest in technology facilitated acceptance. Physical properties, user interface, accessibility and practical experience concurrently hindered and supported device use. Survey results indicate that most non-digital adopters were $>$ 80 years old, and commonly cited reasons were ‘lack of interest’ and ‘too difficult to use’.

CONCLUSION:

Older adults with sight loss may be at particular risk of deeming digital technology to be inaccessible. Family and/or peer influence and experimenting with a device could challenge negative preconceptions.

Keywords

Low vision age-related sight loss older adults digital technology mixed methods

1. Introduction

As the population of older adults rises globally and in the United Kingdom (UK), so too does the personal and economic burden of age related disease [1]. One condition that becomes more prevalent with age is sight loss, and age related macular degeneration is the leading cause [2]. In the UK, 20% of individuals aged 75 and over have non-correctable visual deficits and by 2050, a twofold increase in the visually impaired population is predicted, primarily due to age-related eye conditions [3].

Impaired vision negatively impacts independence during Activities of Daily Living (ADLs) [4, 5]. Complex occupations such as meal preparation and managing finances present the greatest challenge, as successful task performance is more reliant on visual function [6]. Decline in functional ability may also be exacerbated by other factors such as psychological status. Studies indicate that compared to their fully sighted peers, older adults with sight loss are more likely to experience low mood, leading to increased reliance on others for support with everyday tasks [7, 8]. To help address practical difficulties linked to visual deterioration and promote feelings of wellbeing, compensatory strategies to maximise independence, such as Assistive Technology (AT), are essential.

Within the field of sight loss, AT is commonly used to refer to visual aids that support functional performance but conceptualisations vary [9]. Broad definitions incorporating simple and complex devices and more specific constructs encompassing electronic and computing technology only have been devised [10, 11]. Assistive technology has also been categorised into ‘high’ (talking book player) and ‘low’ technology (envelope guide) or ‘traditional AT’ (mobility aids, screen readers) and ‘modern mobile AT’ (smartphones and tablets) [12, 13].

Adoption of conventional AT by older adults with sight loss is known to be positively influenced by informal information exchange, technological ability and perceived benefits. Conversely, a product’s size and weight, cost, access to training, usability and lack of information hinder acceptance [14, 15]. Knowledge and insight specific to use of digital technology by older adults with sight loss is currently limited. Survey data indicates that 77% of people registered as sight impaired in the UK have never used a computer [15]. Older adults with vision loss who do access the internet appear to favour tablet computers above smartphones, whilst e-mail and sourcing information are common online activities [15, 16, 17]. With increasing numbers of seniors accessing the internet, further research is vital to enhance understanding about the potential of digital devices in the everyday lives of older adults with impaired vision [18].

The aim of this project was to undertake a preliminary exploration into the value and adoption of digital technology by older adults ( $>$ 60 years old) with sight loss.

2. Methods

2.1 Design

A mixed methods design was adopted, using qualitative and quantitative approaches to address interrelated but different aspects of technology use. As both methods were intended to offer mutually illuminating findings, integration occurred at the interpretation stage [19, 20]. Purposive and snowball sampling strategies were used to recruit focus group members and convenience sampling was employed on site over a three day period to identify survey respondents.

2.2 Participants

To access potential participants, gatekeepers were identified at Sheffield Royal Society for the Blind (SRSB) and Blind Veterans UK. The study was advertised in SRSB’s monthly newsletter. To be eligible, individuals had to be $>$ 60 years old, have non-correctable sight loss and be able to give informed consent. Those not meeting criteria, or who had a cognitive impairment, were excluded.

2.3 Data collection

After obtaining written informed consent, a focus group was conducted which comprised four activities to stimulate discussion about daily living challenges and digital adoption. Data was audio and video recorded, transcribed verbatim and anonymized. In addition, a bespoke questionnaire was designed and administered face-to-face at SRSB following verbal consent. Areas covered in the questionnaire were informed by the literature, research aims, and American Occupational Therapy Association IADL classification codes [21].

2.4 Data analysis

Qualitative data was analysed using Framework Analysis to increase transparency and credibility of findings [22, 23]. This method delineates five stages: i) data familiarisation and identification of recurring themes ii) development of a conceptual framework/index iii) labelling and linking data to the index iv) formulation of thematic charts and v) use of the charts to produce descriptive and/or explanatory accounts. Substantive content was prioritised but interactions relevant to identified themes were also coded using the index. A reflexive approach was adopted to help evaluate the researcher’s role in influencing co-construction of meaning. Descriptive statistics were used to summarise quantitative data. Answers to open ended questions about technology use were coded according to type of activity. SPSS statistics version 22 was used to support the analytical process.

This project was reviewed and approved by the University of Sheffield research ethics procedure (011590/ 20.10.2016).

Table 1
Characteristics of focus group participants

Participant	Age	${}^{*}$ Visual function	Health	Previous occupation	Digital devices currently used
P1	68	Problems with vision since the age of 15. Registered severely sight impaired. Macular degeneration.	Sarcoidosis	Computer technology	Owns a desktop, laptop, tablet computer and smartphone.
P2	68	Cataracts removed from both eyes. Impaired detailed vision.	Heart problems	Manager of engineering stores	Owns a desktop computer. Does not use a tablet or smartphone.
P3	75	Registered severely sight impaired following a stroke 20 years ago. Peripheral vision affected.	${}^{**}$ CVA in 1997, Meniere’s disease	Engineer/machinist	Owns a desktop and tablet computer. Does not use a smartphone.
P4	84	Vision started to deteriorate over 10 years ago. Registered severely sight impaired. Age related macular degeneration	Heart bypass	Machinist in cutlery factory	Owns a desktop. Does not use a tablet or smartphone.

${}^{*}$ Visual function as described by informants, ${}^{**}$ CVA $=$ cerebral vascular accident.

3. Results

3.1 Focus group findings: Participant demographics

Four male participants took part in the focus group, ranging in age from 68 to 84 years (see Table 1). The focus group lasted 1 hour 38 minutes. Following data analysis, five main themes were identified: technology taxonomy, supporting independence, barriers to technology adoption, facilitators to technology adoption, and factors that concurrently limit/support technology adoption. Each principal theme encompassed a number of sub-themes to enhance understanding of the phenomena of interest.

3.2 Technology taxonomy

‘Technology’ was initially equated with innovative, complex electronic devices whilst basic electronic products were considered lesser technologies. This was revised however when a non-electronic device was also deemed to fulfil criteria.

“When George said I was going to say no it’s not technology, the long cane but he made the point about the ball and I thought well yes it is because it’s engineered specifically” (P1)

Participants subsequently identified two ‘branches’ of technology: devices dependent on electronic parts and those that are engineered or manufactured specifically. The value attached to a device’s benefits appeared to influence decision making. One participant believed that an over-arching determinant of technology was innovation:

“…you could use many other things to do more or less the same thing as the bump-on [tactile marker] erm and err so to me, I personally wouldn’t describe it as technology” (P1)

3.3 Supporting independence

Specialist and mainstream technological solutions were adopted to maximise independence during ADLs. Sight related products generally targeted a specific vision related barrier whilst computing devices supported multiple ADLs via the internet: communication; shopping; information sourcing; leisure and financial management. Technology that negated input from others thus enhancing personal autonomy and control was highly valued:

“I just type in where I’m going to on the bus and I just let I err so when it [GPS] tells me how close you are and everything so I know I’m getting near” (P1)

Availability of a range of digital devices enabled individuals to tailor solutions to vision related challenges according to their visual needs and preferences. One participant used his residual vision to read short emails on a large desktop monitor but chose text to speech translation via his tablet computer for longer messages.

3.4 Barriers to technology adoption

The relentless pace of digital technological developments impeded individuals’ ability to benefit from current innovations:

“…things are moving on so fast, it’s, it’s almost impossible to keep up with anything like the latest developments” (P1)

whilst the rapid expansion of mobile applications lead to uncertainty about what was available.

Identification of methods to maximise independence during ADLs was hindered due to limited information in an accessible format. Images of technology in magazines were often inaccessible, and options for tangible interaction with products were preferred:

“two or maybe three times a year different companies come in [to SRSB] and they have an exhibition day so you can come in and actually try out things with their experts here” (P1)

The high price of technology, particularly niche products, necessitated a cost versus benefit analysis which often resulted in unmet needs. Peripheral costs associated with device use were also prohibitive:

“if I wanted to go down the route of having a phone, Apple, would I have to pay err err a fee in fact if I bought the phone could I use it just as a gadget to read text?” (P4)

Problem solving strategies were used to bypass expensive items which entailed exploration of mainstream alternatives. Two participants considered using a smartphone to avoid purchasing a costly reading device, even though previously one member had felt that this option was too expensive:

P1: That’s why I mean it maybe makes the buying an iphone option that will take this other piece of kit [text to speech mobile application] for 70 quid or 80 quid basically it does the same thing [as the spectacle mounted camera] P4: It does the same thing P1: Erm you know so and it’s cheaper maybe I’ve got a justification to buy

Uncertainly about the reliability of products was a key concern. One member used a non web enabled mobile phone as “it can’t fail” and preferred the iPad rather than desktop as he had “never had a virus or anything like that”. Another participant expressed reservations about the accuracy of dictation software on a smartphone, stating “I can’t guarantee how good it will be”.

3.5 Facilitators to technology adoption

Practical demonstration of technology by others raised awareness of available products, encouraging use of devices and software. Sight impaired peer support was an invaluable information source for three members:

“I think this is the beauty of our group with bowling and things like [that] is you get to know things what other people have got and this is the main, you don’t, you might never know, until like George says look at this what I’ve got” (P3)

All participants reported that next of kin used portable computing devices; one member stated that his daughter had given him an iPad. Interest in technology increased motivation to find out about products available and their associated benefits.

3.6 Factors that concurrently limit and support technology adoption

Design of technology influenced adoption. All participants valued small, portable devices which could be used beyond the home environment. Fixed technology was particularly isolating for one participant:

P4: I’m up there on the computer [desktop] she’s down in the house doing something else P3: Yes P4: She might be knitting or reading so it does affect your home life

Preference for screen size differed according to visual functions affected. Individuals experiencing central vision loss increased text size via a large desktop monitor whilst one member with peripheral loss stated that the iPad was the “ideal size”. Laptop keyboards presented a physical barrier for individuals who needed to be in close proximity to the screen whilst reading.

Favoured devices were easy to operate and enabled an individual to retain control during use. Basic input/output user interfaceswere valued by all participants whilst audible feedback facilitated device interaction. Individuals requiring magnification found some aspects of interactive screens problematic:

“occasionally my nose touches the screen [when reading text] and what I was looking at is gone” (P1) “I’ve tried to touch the screen and pressure was that much by the time I took my finger off I’d taken 20 odd photos” (P4)

Due to problems viewing mainstream product displays, adapting a device to access information was essential. Accessibility was a paramount concern for computer users with reduced acuity, who required magnification software or inbuilt accessibility options. One member dismissed portable computing devices, deeming them inaccessible:

“One of the reasons why I’ve never been able to have a smartphone is I’ve never been flaming able to see what to do” (P2)

To view technologies with a small screen, one person used a hand-held magnifier when reading his smartphone and GPS displays. Trial and error learning enhanced understanding of a product’s benefits and participants found that interacting with a device increased their competence:

“[talking about the iPad] you just learn by making mistakes someone said you can’t do anything wrong if you make a cock up switch it off and switch it back on and over the time I have learnt” (P3)

3.7 Survey findings: Participant demographics

Thirty questionnaires were completed in total (see Table 2). The mean age of respondents was 85.4 years (SD $=+$ / $-$ 7) and 70% of individuals had been living with impaired vision for 5 years or longer.

Table 2
Characteristics of survey participants

Participant characteristics	$n$ (% to nearest whole number)
( $n=$ 30)
Gender
Female	19 (63%)
Male	11 (37%)
Age in years
60–69	1 (3%)
70–79	4 (13%)
80–89	17 (57%)
90+	8 (27%)
Self-reported eye condition
ARMD	15 (50%)
Stroke related sight loss	4 (13%)
Cone dystrophy	1 (3%)
Corneal dystrophy	1 (3%)
Other	3 (10%)
Don’t know	6 (20%)
Duration of sight loss
$<$ 5 years	7 (23%)
5–10 years	10 (33%)
11–20 years	6 (20%)
$>$ 20 years	5 (17%)
Don’t know	2 (7%)

3.8 Non computer users

In total, 24 participants did not use a computing device. Within this group, ten ( $n=$ 5 males) reported that they did not use any digital technology whilst the remainder owned a non-web enabled mobile phone. Frequent explanations for non-adoption were: ‘too difficult to use’ ( $n=$ 17), ‘lack of interest’ ( $n=$ 11) and ‘no perceived benefits’ ( $n=$ 5). The majority (88%) were not interested in computer training.

3.9 Digital adopters

Six individuals used a computing device, four aged between 62 and 78 years and two in their 90s. Three respondents who had lived with sight loss for over 40 years used multiple computer technologies, whilst both nonagenarians owned a tablet computer and non-web enabled phone only. The most commonly adopted technology was a tablet computer ( $n=$ 5), followed by a smartphone ( $n=$ 4) and desktop/laptop ( $n=$ 3). In response to the question “how did you start using this device?” one person was introduced by a friend, two by family, and 2 initiated acquisitions themselves.

3.10 Online activities and mobile applications

Tablet computers were most frequently reported for leisure ( $n=$ 4) and communication ( $n=$ 3) activities whilst smartphones were predominantly used for sourcing bus and taxi information ( $n=$ 3) and contacting others ( $n=$ 2). Compared to their younger counterparts, internet users in their 90s accessed fewer web based activities.

To support ADLs, three respondents used mobile applications or apps. Participants with residual vision ( $n=$ 2) valued apps for leisure and sourcing information but differed in choice of other applications. The third mobile app user had no useful vision and used popular software to aid communication, social participation, safety/emergency maintenance and health management. This participant was also an extensive user of specialist apps to support ADLs: text to speech translation, object recognition via crowdsourcing and a money reader.

4. Discussion

The purpose of this study was to provide a preliminary understanding of the use and value of digital technology. This entailed exploration of how technology is viewed and defined, which devices are valued when performing ADLs, and factors that hinder or support adoption.

4.1 Taxonomy

A taxonomy of technology culminated in a gradation of devices which ranged from simple electronic products and items engineered for a specific purpose to comparatively ‘state of the art’ gadgets. Classification systems are evident in the AT literature. Cook and Polgar’s categorisation [24, p. 6] is particularly pertinent, reflecting complexity, manufacturing and innovation components:

“…inexpensive devices that are simple to make and easy to obtain are often described as ‘low’ technology and devices that are expensive, more difficult to make, and harder to obtain as ‘high’ technology”

This finding highlights the automatic association of digital technology with complexity, which may explain why 88% of non-technology users in the survey rejected computer training. Indeed, older adults who do not use computers may regard technology as intimidating or anxiety provoking [25]. Negative connotations of complexity may be associated with the term ‘technology’, therefore referring directly to the name of a product and emphasising its potential benefits could support device adoption.

4.2 Adoption

Technology did not always provide a perfect solution but was adopted if it enabled successful achievement of a desired goal, and often afforded psychological benefits such as feeling in control. According to Bender-Pape, Kim and Weiner [26], devices perceived to be beneficial and which lead to a valued outcome, such as independence, are more likely to be regarded as ‘meaningful’.

Taking into account survey demographics, the most popular internet device was the tablet computer. Previous study findings are mixed regarding older adults’ preferred digital device [17, 27, 28], but for people with low vision, proclivity towards mainstream products is dependent on accessibility. The iPad can fulfil sight specific preferences due to its size, customisation options and inbuilt accessibility [29]. Additionally, it may not be associated with comparatively complex desktop systems due to its portability [30]. This option could therefore prove more acceptable to older adults with sight loss.

Internet access was a valued outcome of computer use, and both sets of findings suggest that communication and leisure were popular online activities. Literature relating to the general and visually impaired older adult populations also found communication via the internet to be important, but recreational pursuits featured less highly [18, 27, 31, 32]. However, as sight related mobility restrictions may limit pastime options beyond the home, digital devices could help fulfil leisure needs.

A minority of participants used mobile apps, although software that was downloaded supported a variety of ADLs. Literature concerned with app use by older adults with impaired sight is scarce, although their role as an ADL support was recognised by Kaldenberg and Smallfield who incorporated them into an iPad training programme [29].

4.3 Barriers and solutions

Many survey respondents in their 80s or 90s did not use a computer but found a non-web enabled phone useful. This preference could be explained by familiarity, as this device is long established and learning may have occurred prior to visual deterioration. Questionnaire data revealed that over two thirds of non-computer users felt that digital technology was ‘too difficult to use’ and many did not discern any associated benefits to use. One explanation is that the twofold process of learning to use a computer and accessibility options may be considered too demanding [31].

Focus group data highlighted how ‘practical experience’ with a product increased user competence and enhanced appreciation of its benefits. “Playing around” with a device was found by Tsai, Shillair and Cotten to facilitate learning and encourage more positive appraisals of technology [33]. Understanding practical benefits afforded by technology may also increase usage [16]. As immediate family are often instrumental in supporting older adults to access technology, educating key individuals about accessibility may indirectly encourage adoption [34]. Provision of information or signposting to sight loss organisations may be helpful whilst information from visually impaired peers about innovations and software could inspire others to try new devices. Providing a forum to share knowledge and view products at a local level may also raise interest in technological solutions.

To profit from technological advances, keeping abreast of constant change, particularly in relation to mobile computing devices and software, was vital. This is not unique to older adults with sight loss, as younger visually impaired people also report struggling to remain current [35]. For older adults with impaired vision, this finding may restrict technology acceptance, as identifying suitable devices to support ADLs requires time and technical ability. Methods to effectively disseminate accessible information about new technology or apps which address specific ADL deficits may be helpful. This could be issued during routine visits conducted by sight loss professionals or involve signposting to the non-statutory sector.

5. Conclusion

This study contributes to the development of a sight loss specific technology acceptance model for older adults to improve understanding of the multiple factors influencing acceptance and adoption of digital technology. Limitations include the small sample size and participant characteristics however this preliminary work does indicate areas for further investigation.

Mobile digital devices could potentially support multiple ADL needs. Currently, many visually impaired older adults are excluded from the benefits of technology for a plethora of reasons, including perceived ease of use. Opportunity to experiment with a device could counter negative attitudes by elucidating its benefits, but this process may be highly dependent on input from family/peers. To promote computer based interventions, a shift in focus from traditional rehabilitation approaches is required, but for many, cost and/or lack of interest may restrict technology adoption. For the current generation of older adults with sight loss, computing devices may never become meaningful but by extolling associated advantages, some, with support, will be ready to defy the ‘digital divide’.

Footnotes

Acknowledgments

The authors would like to extend their grateful thanks to all the people who participated in this research and to the staff at SRSB and Blind Veterans UK for their help with the recruitment of participants.

Conflict of interest

None to report.

References

World health Organisation [homepage on the internet]. Ageing and Health. Fact sheet No 404; 2015 [cited 2016 Nov 7]. Available from: http://www.who.int/mediacentre/factsheets/fs404/en/.

Ong

Ah-Fat

. Age related macular degeneration. British Journal of Hospital Medicine. 2016; 77(2): 18-21.

Royal National Institute for the Blind [homepage on the internet]. Key information and statistics; 2016 [cited 2016 Oct 4]. Available from: http:/www.rnig.org.uk/knowledge-and-research-hub/key-information-and-statistics.

Cimarolli

Jopp

. Sensory impairment and their associations with functional disability in a sample of the oldest-old. Quality of Life Research. 2014; 23: 1977-1984.

Kempen

GIJM

Ballemans

Ranchor

van Rens

GHMB

Rixt Zijlstra

. The impact of low vision on activities of daily living, symptoms of depression, feelings of anxiety and social support in community-living older adults seeking vision rehabilitation services. Quality of Life Research. 2012; 21: 1405-1411.

Berger

Porell

. The association between low vision and function. Journal of Ageing and Health. 2008; 20(5): 504-525.

Evans

Fletcher

Wormald

RPL

. Depression and anxiety in visually impaired older people. Ophthalmology. 2007; 114(2): 283-288.

Travis

Boerner

Reinhardt

Horowitz

. Exploring functional disability in older adults with low vision. Journal of Visual Impairment and Blindness. 2004; 98(9): 534-545.

Jutai

Strong

Russell-Minds

. Effectiveness of assistive technologies for low vision rehabilitation: a systematic review. Journal of Visual Impairment & Blindness. 2009; 103(4): 210-222.

10.

Copolillo

Teitelman

. Acquisition and integration of low vision assistive devices: understanding the decision-making process of older adults with low vision. The American Journal of Occupational Therapy. 2005; 59(3): 305-313.

11.

Royal National Institute for the Blind [homepage on the internet]. What Assistive Technology is available? 2014 [cited 2016 Oct 6]. Available from: https://help.rnib.org.uk/help/daily-living/technology/technology-assistive.

12.

Fok

Miller Polgar

Shaw

Jutai

. Low vision assistive technology device usage and importance in daily occupations. Work. 2011; 39: 37-48.

13.

Hakobyan

Lumsden

O’Sullivan

Bartlett

. Mobile assistive technologies for the visually impaired. Survey of Ophthalmology. 2012; 58(6): 513-528.

14.

McGrath

Astell

. The benefits and barriers to technology acquisition: understanding the decision-making processes of older adults with age-related vision loss (ARVL). British Journal of Occupational Therapy. 2017; 80(2): 123-131.

15.

Douglas

Corcoran

Pavey

. The role of the WHO ICF as a framework to interpret barriers and to inclusion: visually impaired people’s views and experiences of personal computers. The British Journal of Visual Impairment. 2007; 25(1): 32-50.

16.

Crossland

Silva

Macedo

. Smartphone, tablet computer and e-reader use by people with vision impairment. Ophthalmic & Physiological Optics. 2014; 34: 552-557.

17.

van der Geest

van der Meij

van Puffelen

. Self-assessed and actual internet skills of people with visual impairments. Universal Access in the Information Society. 2013; 13(2): 161-174.

18.

Chang

McAllister

McCaslin

. Correlates of and barriers to internet use among older adults. Journal of Gerontological Social Work. 2015; 58(1): 66-85.

19.

Bryman

. Social Research Methods. 4th ed. Oxford; New York: Oxford University Press; 2012.

20.

O’Cathain

Thomas

. Combining qualitative and quantitative methods. In: Pope

Mays

, eds. Qualitative Research in Health Care. 3rd ed. Malden, Mass; Oxford: BMJ; 2006.

21.

American Occupational Therapy Association [homepage on the internet]. AOTA Classification Codes for Continuing Education Activities; 2014 [cited 2016 Oct 6]. Available from: https://www.aota.org/∼/media/Corporate/Files/EducationCareers/APP/AOTAClassificationCodesforCE-Companion.pdf.

22.

Doody

Slevin

Taggart

. Focus group interviews part 3: Analysis. British Journal of Nursing. 2013; 22(5): 266-269.

23.

Ritchie

Spencer

O’Connor

. Carrying out Qualitative Analysis. In: Ritchie

Lewis

, eds. Qualitative Research Practice: A Guide for Social Science Students and Researchers. London: Sage publications; 2003.

24.

Cook

Polgar

. Cook and Hussey’s Assistive Technologies: Principles and Practice. 3rd ed. St Louis, MO: Mosby Elsevier; 2008.

25.

Vroman

Arthanat

Lysack

. “Who over 65 is online?” Older adults’ dispositions toward information communication technology. Computers in Human Behaviour. 2015; 43: 156-166.

26.

Bender Pape

Kim

Weiner

. The shaping of individual meaning assigned to assistive technology: a review of personal factors. Disability and Rehabilitation. 2002; 24: 5-20.

27.

Gitlow

. Technology use by older adults and barriers to using technology. Physical and Occupational Therapy in Geriatrics. 2014; 32(3): 271-280.

28.

Pew Research Centre [homepage on the internet]. Smith A. Older adults and Technology Use; 2014 [cited 2017 Jan 30]. Available from: http://www.pewinternet.org/2014/04/03/older-adults-and-technology-use/.

29.

Kaldenberg

Smallfield

. Training older adults with low vision to use a computer tablet: a feasibility study. British Journal of Occupational Therapy. 2016; 80(2): 117-122.

30.

Barnard

Bradley

Hodgson

Lloyd

. Learning to use new technologies by older adults: Perceived difficulties, experimentation behaviour and usability. Computers in Human Behaviour. 2013; 29: 1715-1724.

31.

Piper

Brewer

Cornejo

. Technology learning and use among older adults with late-life vision impairments. Universal Access in the Information Society. 2016; October: 1-13.

32.

Wang

Pei-Luen

Salvendy

. Older adults’ acceptance of information technology. Educational Gerontology. 2011; 37: 1081-1099.

33.

Tsai

Shillair

Cotten

. Social support and “playing around”: an examination of how older adults acquire digital literacy with tablet computers. Journal of Applied Gernotology. 2015; 36(1): 29-55.

34.

Greenhalgh

Wherton

Sugarhood

Hinder

Procter

Stones

. What matters to older people with assisted living needs? A phenomenological analysis of the use and non-use of telehealth and telecare. Social Science & Medicine. 2013; 93: 86-94.

35.

Vanden Abeele

de Cock

Roe

. Blind faith in the web? Internet use and empowerment among visually and hearing impaired adults: a qualitative study of benefits and barriers. Communications. 2012; 37: 129-151.