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Assistive Technology
The Official Journal of RESNA
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/uaty20
Smartphone usage among people living with
severe visual impairment and blindness
Carl Halladay Abraham, Bert Boadi-Kusi, Enyam Komla Amewuho Morny &
Prince Agyekum
To cite this article: Carl Halladay Abraham, Bert Boadi-Kusi, Enyam Komla Amewuho Morny &
Prince Agyekum (2021): Smartphone usage among people living with severe visual impairment and
blindness, Assistive Technology, DOI: 10.1080/10400435.2021.1907485
To link to this article: https://doi.org/10.1080/10400435.2021.1907485
Published online: 03 May 2021.
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Smartphone usage among people living with severe visual impairment and blindness
Carl Halladay Abraham, MSc, OD, ProfCertLV , Bert Boadi-Kusi, PhD, Mphil, OD ,
Enyam Komla Amewuho Morny, PhD, OD , and Prince Agyekum, OD
Department of Optometry and Vision Sciences, University of Cape Coast, Cape Coast, Ghana
ABSTRACT
Low vision care and rehabilitation is often limited by access to assistive devices, especially in low-
resourced countries, due to their high cost and unavailability. Smartphones have the potential to serve
as an alternative assistive device for people living with severe visual impairment and blindness (SVIB). This
study aims to investigate the use of smartphones among people living with SVIB. The study was a cross-
sectional study of 166 people living with SVIB in a low resourced setting. The participants were recruited
from two tertiary institutions and four eye care facilities. A questionnaire was administered to all
respondents and for those who could not read prints they were read out to them and their responses
recorded. The majority of respondents (n = 88, 53.1%) either had no phone or used a basic phone. The
prevalence of smartphone usage among people living with SVIB was found to be 46.90% (n = 78). Most
respondents use their smartphones to interact on social media [n = 75 (96%)] and web browsing
[n = 69,92%]. The most frequently demanded [n = 22 (44%)] smartphone functionality by the respondents
was the image and color description feature. Most participants were unaware that 90% of their function-
ality demands already existed and were compatible with current smartphones. A signicant number of
people living with SVIB in this study used smartphones; however, most users are unaware of its full
functionality and assistive capabilities.
ARTICLE HISTORY
Accepted 16 March 2021
KEYWORDS
activities of daily living;
usability; visual impairment;
smartphone and low vision
Introduction
Globally, estimated 1.3 billion people live with some form of
vision impairment. Out of which 188.5 million people have
a mild vision impairment, 217 million have moderate to severe
vision impairment, and 36 million people are blind (Bourne
et al., 2017; Flaxman et al., 2017). These numbers are expected
to increase along with the projected increases in global popula-
tion and the aging demographics, regardless of the preventive
measures and management methods (Ackland et al., 2018).
Remarkably, the burden of visual impairment is unequally
distributed as 90% of visually impaired people live in low-
and middle-income countries (LMIC)(Bourne et al., 2017)
like Ghana, a Sub-Saharan African country with approximately
1.5 million people living with visual impairment (Wiafe, 2015).
Visual impairment, like other impairments, impacts the
lives of individuals and can be a hindrance in completing and
accomplishing activities of daily living, such as safe mobility,
commence, self-care, and accessing information (Jacobs et al.,
2005; Jones et al., 2019; Vu et al., 2005). This results in social
exclusion and participation restriction (Kasiram & Subrayen,
2013; Tobias & Mukhopadhyay, 2017) culminating in deepen-
ing levels of poverty.
The issues of societal integration and social equity for peo-
ple living with visual impairment have become a global con-
cern (WHO, 2011; Wiafe, 2015). This is also echoed in the
sustainable development goal ten (10) that aims to reduce
inequalities (WHO, 2020). One major solution has been the
advocacy for the inclusion of vision rehabilitation in primary
health-care systems across the world. Vision rehabilitation
improves independence and productivity in individuals with
visual impairment by maximizing the use of their residual
vision. It has been shown to be effective and significantly
improve the quality of life of persons that benefit from it
(Ovenseri-Ogbomo et al., 2016; Stelmack, 2001). Vision aids
and assistive devices or assistive technology devices are major
tools used in the rehabilitation centers. Assistive technology
devices or assistive devices refer to any item, piece of equip-
ment, or product system, whether acquired commercially,
modified, or customized, that is used to increase, maintain, or
improve functional capabilities of individuals with disabilities
by enhancing an individual’s independence in performing any
activity of daily living or instrumental activity of daily living
(Act, 1998). These devices include magnifiers, telescopes, biop-
tics, electronic vision enhancement systems (EVES), and navi-
gating systems (Jutai et al., 2009). There is a high demand for
assistive devices globally with estimated 1 billion persons with
disability needing one or more assistive devices to enhance
their livelihood(Mclnnes et al., 1994; Tebbutt et al., 2016).
However, there is limited access to such assistive devices.
Only one (1) in ten (10) persons living with visual impairment
globally has access to such devices. Ghana is a low resourced
country and the availability and access to assistive devices
is low (Pei-Chia Chiang, 2009) despite the numerous
interventions made by the Ghana Health Service and
World Health Organization (Tangcharoensathien et al.,
2018; WHO, 2015)
CONTACT Carl Halladay Abraham carl.abraham@ucc.edu.gh Department of Optometry and Vision Sciences, University of Cape Coast, Cape Coast, Ghana.
ASSISTIVE TECHNOLOGY
https://doi.org/10.1080/10400435.2021.1907485
© 2021 RESNA
Optical vision aids play a very significant role in low vision
rehabilitation. In recent times, electronic alternatives which are
collectively known as Portable electronic vision enhancement
systems (p-EVES) have become popular. They have been found
to be cost-effective (Bray et al., 2017), but in developing countries,
the cost of such assistive devices remains prohibitive (Al-Mouh &
Al-Khalifa, 2015). However, smartphones, which are mobile
phones that include advanced functionality beyond making
phone calls and sending text messages, are endowed with some
assistive features for the visually impaired person (Crossland et al.,
2014; Pal et al., 2017), which is comparable to other p-EVES.
Most smartphones can display photos, play videos, e-mailing
services, and browse the internet. Modern smartphones can run
third-party applications, which provides potentially limitless func-
tionality (Christensson, 2010; Islam & Want, 2014). Universal
designs of smartphones have been motivated by studies
(Rodriguez-Sanchez et al., 2014) that demonstrated the limited
use of smartphones by people with visual impairment due to small
font sizes and displays. Universally designed models that became
available in the early 2000s have large font sizes, speech output, and
other accessibility features (Watanabe et al., 2008).
Smartphone usage among visually impaired users is grow-
ing and mobile phone manufacturers are continuously striving
to improve the touch screen interfaces and make it more
accessible to those with vision loss (Luthra & Ghosh, 2015).
Key accessibility features for vision-related impairment include
assistive screen reading applications like Voiceover for iOS or
Talkback for Android, which supports a variety of touch ges-
tures for performing basic functions and commands (Luthra &
Ghosh, 2015). Currently, the most predominant operating
systems for touchscreen computers, such as iOS (Apple) or
Android (Google) ensure accessibility for people with visual
impairments. Functions like screen magnification software and
reader functions have improved with newer versions (Miura
et al., 2014).
This study sought to investigate the use of smartphones
among people living with severe visual impairment and blind-
ness in the Central Region of Ghana.
Method
The study used a descriptive cross-sectional study design
and was conducted in the Central Region of Ghana. The
study participants were purposively sampled from two set-
tings; the educational institutions which includes two uni-
versities and the health-care setting which were made up
of four eye care facilities evenly distributed across the
region. The study participants were people living with
SVIB; based on the WHO, International Classification of
Diseases (ICD)-10 (WHO, 2017). The ICD-10 categorizes
people with severe visual impairment as having a visual
acuity of worse than 6/60(1.0 LogMAR) to 3/60(1.3
LogMAR) and blindness as worse than 3/60 to no light
perception (NLP). At the educational institutions, the school
coordinators arranged a meeting where the researcher was
introduced to the participants. All participants who were
found to be living with SVIB after the screening and agreed
to be part of the study were recruited. In the health facilities,
participants were recruited when they reported to the facility
for their routine eye examination and satisfied the inclusion
criteria of the study. Participants visiting the facilities for the
first time were excluded from the study.
Institutional approval to conduct the study was obtained
from the University of Cape Coast Institutional Review
Board. The study adhered to the guidelines enshrined in
the declaration of Helsinki on the use of human subjects
for research. A detailed explanation of the procedure, pur-
pose, content, and benefit of the study was given to all the
participants. Participants who could read prints were pro-
vided a large print format of the questionnaire, others who
could read braille or were illiterate in English and Fanti had
it read to them. All participants were required to verbally
acknowledge in principle that they fully understood the
reason for the study and what would be required of them
before signing an informed consent form. Some participants
had to be aided by a writing guide and a small section of
them thumb printed the forms with the coordinator or
a guardian as a witness.
Data collection
The first part of the data collection entailed the assessment of
the visual acuity and functional vision of participants. The
visual acuity of participants was assessed with a LogMAR
acuity chart and recorded. Functional vision was determined
if the individual reported that they could use their vision for
some activity or navigation.
A 30-item questionnaire which was developed in English
and translated into the Fante language which was the dominant
language of the communities from which the participants were
recruited was then administered. The Questionnaire had both
closed and open-ended questions which were grouped into
four main categories.
The first section, which was made up of 8 items, was
designed to obtain information on the demographic and visual
state of the participant. This category elicited information on
age, gender, educational level, employment status, visual
acuity, functional vision, and duration of diagnosis.
The second part of the questionnaire had 14 items and it
focused on phone ownership. The questions here involved
ownership of mobile and smartphone, type and brand, rea-
sons for ownership and phone types. The third category of
questions had 7 items that probed the types of applications
used by the participants and adaptations that had been made
to facilitate ease of usage and accessibility. The final part of
the questionnaire was a single-item category. It explored the
various functionality demands that the participants believed
their ideal phone should have to make it more useful to
them.
The questionnaires were delivered by hand to the respon-
dents at the afore mentioned collection points of the study
setting. The delivery of the questionnaire to the participants
was done by the researcher and one research assistant who
underwent a 3-day training to administer the questionnaire to
2C. H. ABRAHAM ET AL.
all the participants. The questionnaires were not in braille and
hence had to be read to participants who could not read prints
and their responses were noted accordingly.
Data analysis
Data were entered into and analyzed using the Statistical Package
for Social Sciences for Windows (version 22.0; SPSS Inc, Chicago,
Illinois, USA). Descriptive statistics were used to describe the
characteristics of the participants involved in the study and to
check the variables for any violation of the assumptions underlying
the statistical tests. Summaries of data were represented in fre-
quencies and percentages with central tendencies presented by
modes with their respective inter-quartile ranges (IQR). Pearson
chi-square was computed for the categorical variables studied to
identify significant differences between groups. Statistical signifi-
cance was drawn at an alpha level of 0.05
Results
A total of 166 participants (40.4% female) living with SVIB
took part in the study. About half of the participants were
students in the university [91 (54.8%)]. The modal age
observed was 26 years (IQR 26.0-71.3) with an age range of
19 to 94 years. Table 1 provides the demographics of the
population studied and their level of visual impairment.
According to the ICD–10 classification most of the participants
(65.7%) were blind (had a visual acuity of 2.00 LogMAR to
NPL). A greater proportion of participants [130 (78.3%)] pre-
sented with some level of functional vision.
Phone usage
Table 2 presents data on the general phone and smartphone use
among participants. The majority (140 (84.3%)) of participants
owned a phone. Some demographic and visual parameters signifi-
cantly influenced phone ownership among participants. It was
more likely for a participant to own a phone if they were a male
(χ
2
(1) = 8.019,P = .005), had tertiary education (χ
2
(3) = 51.329,
P < .0001), aged 18–34 (χ
2
(4) = 45.556,P < .0001), was blind
(χ
2
(1) = 16.648,P < .0001) and had some functional vision
(χ
2
(1) = 7.719,P = .005). Only 26 participants did not use
a phone at all, and this was mostly attributed to the condition of
the eye [9(36%)], affordability [5(20%)], and lack of interest
[4(16%)].
Only about half [78 (46.9%)] of the phones used were smart-
phones. Table 2 shows that 71 (76.3%) out of 93 participants
within the ages of 19–34 used smartphones compared to only 1
(1.6%) smartphone users out of 63 participants aged 50 and
above. None of the participants above age group 50–64 used
a smartphone (χ
2
(4) = 86.838, P < .0001). About 61.5% of
participants categorized as being blind were smartphone users.
Less than one third of participants [11(6.6%) out of 39] categor-
ized as SVI who owned phones were smartphone users compared
to two thirds [67(40.6%) out of 101] of participants who were
categorized as blind (χ
2
(1) = 26.720,P < .0001).
The majority [69 (88.5%)] of the participants started using
the smartphone after their vision loss. Most of the participants
[44 (56.4)] indicated that they self-taught themselves in the use
of smartphones, and in 29.5% of cases, friends provided them
with the training required to use a smartphone (Figure 1).
Figure 2 shows the most often assessed functions and appli-
cations on smartphones by participants living with SVIB. Apart
from making and receiving calls, most participants who used
smartphones interacted on social media platforms (n = 75 out
of 78). Less than half of participants who used smartphones
used it to watch movies (n = 36 out of 78) and play games
(n = 14 out of 78). The smartphones’ functions used by the
participants enabled them to engage in education and commu-
nication, commence and recreational tasks
The study explored the accessibility features on smart-
phones that were used by persons with SVIB and the findings
are shown in Figure 3. The most used accessibility feature was
the talkback or voice over (n = 73 out of 78). Less than 10
participants used increased backlight, magnification, color
inversion, and improved contrast.
Participants were asked to identify the functions or applica-
tions their ideal smartphone should have to make it more useful
to them. Table 3 shows that the majority of the functions (90%,
45 out of 50) the participants needed their smartphones to have
already existed. Fifty out of the 78 smartphone owners responded
to this question. The highest functionality demand was picture
and color description (44%) which was requested by 22 out of 50
respondents, and the least was identifying unauthorized usage
and incorporating a brailed keyboard. A total of 14 participants
demanded talk back or automated response features, including
the addition of familiar accents. The functionality demands were
all software-based except 2 which are “fast application response
time” and “enhanced screen brightness and battery life”.
Discussion
This study sought to investigate smartphone usage among
people living with SVIB.
The findings showed that out of the number of persons living
with SVIB who used a mobile phone, the majority of them used
a smartphone. This may be due to the growing global access to
Table 1. Demographic data and visual status of the study population.
Educational
Facilities
(N = 91)
Health
Facilities
(N = 75)
Total
(N = 166)
n(%) n(%) n(%)
Gender Male 59(35.5) 40(24.1) 99(59.6)
Female 32(19.3) 35(21.1) 67(40.4)
Age 19–34* 86(51.8) 7(4.2) 93(56.0)
35–49 5(3.0) 4(2.4) 9(5.4)
50–64 0(0.0) 13(7.8) 13(7.8)
65–79 0(0.0) 31(18.7) 31(18.7)
>79 0(0.0) 20(12.0) 20(12.0)
Educational Level No Formal
Education
0(0.0) 33(19.9) 33(19.9)
Basic 0(0.0) 25(15.1) 25(15.1)
Secondary 0 (0.0) 8(4.8) 8(4.8)
Degree 91(54.8) 9(5.4) 100(60.2)
Employment status Unemployed 7(4.2) 51(30.7) 58(34.9)
Self Employed 10(6.0) 19(11.4) 29(17.5)
Employed 6(3.6) 3(1.8) 9(5.4)
Student 68(41.0) 2(1.2) 70(42.2)
Visual Impairment Severe Visual
Impairment
10(6.0) 47(28.3) 57(34.3)
Blindness 81(48.8) 28(16.9) 109(65.7)
ASSISTIVE TECHNOLOGY 3
smartphones. The younger population used smartphones more
than aged, but SVIB was more prevalent among the aged who have
limited access to smartphones, according to the findings. Age–
smartphone relationship has been reported in other studies, which
claim that the younger population adapts to technology the most
and older people are less positive toward embracing technology
(Bianchi & Phillips, 2005). The massive global adoption of smart-
phones may have the potential of changing this trend. This is
exemplified by an increase in smartphone use from 9% to 80%
from 2012 to 2019 among persons aged 55-64 in the UK (O’Dea,
2015). A similar trend is expected to be seen in most sub-Saharan
African countries in the immediate future since the young people
category presently reported in this study may have had longer
exposure and experience with smartphones, assistive features, and
even newer and more resourceful features in their old age. This will
result in a more even distribution of smartphone use among the
aged groups. The potential dependence on smartphones among
the aged in the future will make smartphone-based vision assistive
technology a cardinal part of vision rehabilitation. There will be
a shift from the need to read printed text to digital prints and
conducting most activities of daily living like shopping, banking,
etc. in a digital space. A third factor that will potentially contribute
Table 2. Distribution of ownership of basic phones and smartphones among study participants.
Phone Users Smartphone Users
Yes No Yes NO
N = 140 n(%) N = 26 n(%) p-value N = 78 n(%) N = 88 n(%) P–value
Participants Location Educational Facility 90(54.2) 1(0.6) .000* 70(42.2) 21(12.7) 000*
Health Facility 50(30.1) 25(15.1) 8(4.8) 67(40.4)
Gender Male 90(54.2) 9(5.4) .005* 52(31.3) 47(38.3) .082
Female 50(30.1) 17(10.2) 26(15.7) 41(15.7)
Age 19–34 92(55.4) 1(0.6) .000* 71(42.8) 22(13.3) .00
35–49 8(4.8) 1(0.6) 6(3.6) 3(1.8)
50–64 10(6.0) 3(1.8) 1(0.6) 12(7.2)
65–79 21(12.7) 10(6.0) 0(0.0) 31(18.7)
>79 9(5.4) 11(6.6) 0(0.0) 20(12.0)
Educational Level None 16(9.6) 17(10.2) .000 0(0.0) 33(19.9) .00
Basic 18(10.8) 7(4.2) 2(1.4) 23(13.9)
Secondary 7(4.2) 1(0.6) 2(1.4) 6(3.6)
Tertiary 99(59.6 1(0.6) 74(53.2) 26(15.7)
Employment status Unemployed 39(23.5) 19(11.4) .000 10(6.0) 48(28.9) .000
Self Employed 24(14.5) 5(3.0) 9(5.4) 20(12.0)
Employed 8(4.8) 1(0.6) 4(2.4) 5(3.0)
Student 69(41.6) 1(0.6) 55(33.1) 15(9.0)
Visual Impairment SVI 39(23.5) 18(10.8) .000 11(6.6) 46(27.7) .000
Blindness 101(60.8) 8(4.8) 67(40.6) 42(25.3)
Functional Vision Yes 115(69.3) 15(9.0) .005* 63(38.0) 67(40.4) .470
No 25(15.1) 11(6.6) 15(9.0) 21(12.7)
0
10
20
30
40
50
60
70
80
Before the Condition After the condition Self-taught Friends Family Other
The inception of phone use Source of smartphone tutelage before use
Frequency
Inception and source of training of smartphone use
Figure 1. Inception and source of training of smartphone use among persons with SVIB.
4C. H. ABRAHAM ET AL.
75
69
66
60 58 56
63
36
14
3
9
12
18 20 22
15
42
64
0
10
20
30
40
50
60
70
80
Social media Web browsing Voice Chatting News emails Financial
Transactions
Music Movies Games
Education and communication Commence Recreation
ycneuqerF
Usage of smartphones
Yes No
Figure 2. Smartphone applications used among people living with SVIB.
5889
45
7373
70 70 69
33
5
0
10
20
30
40
50
60
70
80
Increased Backlight
Illumination
Magnification Colour Inversion Improved Contrast Voice recognision Talk back or Voice Over
ycneuqerF
Accessibility features used by persons with SVIB
Yes
No
Figure 3. Smartphone accessibility features used by people living with SVIB.
Table 3. Smartphone functionality demands made by people living with SVIB.
Functionality demand Frequency Available applications/solutions
Picture and color description 22 Seeing AI, BeSpecular,Aipoly Vision, iDentifi, TapTap See
Automated voice response systems (digital assistants) 5 Siri, Alexa, Cortana
Improved accuracy of text to speech with familiar accents 5 Google TalkBack
Location indicator and obstacle identifier 5 AWARE, PERCEPT, SIDEWALK
Preinstalled talk back and dictionary 4 Talkback and Google Assistant
Fast application response time 3 Newer models of phones
Enhanced screen brightness and battery life 2 Newer models of phones
Identify unauthorized usage 1 Don’t touch my phone application
Brailed keypad 1 BrailleBack, Brailliac etc
Total 50
ASSISTIVE TECHNOLOGY 5
to the rise in smartphone use among the aged is the progressive
phasing out of basic phones by phone manufacturing companies.
Though the likely benefit of smartphone-based vision assistive
technology to the aged population could be enormous. It is unli-
kely that introducing persons within this age group (above 70) to
smartphones now will be very successful due to technology, lan-
guage, and literacy gap.
A critical look at the data indicates that most of the participants
either did not use a phone or used a basic phone. One major factor
may be that approximately one in five respondents had no formal
education. This serves as a barrier to the use of the phones and
especially smartphones because the relevant applications and the
systems language are in English and may have contributed to the
lack of interest in the use of smartphones.
Samsung was the most commonly used smartphone brand
among people living with SVIB in the central region. This choice
was mostly influenced by peers, with the belief that the brand
possesses superior assistive features than the other smartphone
brands. This thought by the participants may be inaccurate in the
context of the use of assistive functions. The android operating
system provides similar accessibility features regardless of the
phone model. All other assistive applications are third-party appli-
cations which can be installed based on the preference of the user.
There is a need to study the actual usage of the various models of
smartphones, as well as the ease of use of the third-party applica-
tions among persons living with SVIB to fully determine which
phones or applications may offer this population with the best
accessibility.
The majority of the participants did not receive any form
of training on the use of their smartphones (Rodriguez-
Sanchez et al., 2014). This may be a sign of living indepen-
dently or it could be due to lack of the needed support. The
modes of smartphone use tutelage (self-taught or taught by
friends) may not enable the participants to harness the full
potential of the smartphone compared to being guided by
a rehabilitation or social worker.
Social media seems to have gained popularity among people
living with SVIB, as observed in this study. Most of the participants
that used smartphones mostly used their phones to engage on
social media platforms. Social media use is directly linked to
increased social inclusion and participation (Boulianne, 2015).
The three domains that underpin social inclusion are participa-
tion, connectedness and a sense of belonging and citizenship.
Social media has become a central arena where one can participate
in all these domains (Fuglerud et al., 2012) without the need to be
mobile or have physical interaction. However, most psychometric
measures of social inclusion tilt toward physical engagement with
other members of society. Therefore, the measures of social inclu-
sion and participation restriction may need modification to
include social media participation in order to obtain a more accu-
rate measure for persons with disability
Among the people living with SVIB, Text to Speech was the
main function used on the smartphone. This result reflects the
outcome of other studies (Lundh & Johnson, 2015), and even
those with partial sight would prefer to use the Text to Speech
feature, due to its comparative ease of usage. However, the Text to
Speech application is unable to describe images or colors. This
explains the high demand of participants for applications that will
enable them to describe images and colors. This is also closely
linked to the high rate of use of social media among the study
population. Social media, as an interactive arena as it is, uses
pictures and videos on a large scale, and for people living with
SVIB to fully participate, they need assistance to visualize the social
space in which they interact. Social media is described as part of
a modern culture that impacts self-esteem (Bianchi & Phillips,
2005) of users and seems to be an emerging index for social
integration and participation for people with SVIB.
Although almost all the functionality demands requested by
the participants in this study were existent and compatible with
the smartphone, a section of the study population had no idea
of their existence. This lack of familiarity with preexisting
technology to enhance the function of people with SVIB is
a worrying trend and not only limited to the use of smart-
phones. Current traditional assistive devices are reportedly
underused (Lundh & Johnson, 2015). Many factors may
account for this, but the lack of a comprehensive and multi-
disciplinary system for managing persons living with SVIB is
a significant factor. Hence, a high proportion of participants in
this study resorted to friends who may not know the full
accessibility features of the phone to tutor them on the use of
smartphones. One way to overcome this challenge is providing
the necessary education to eyecare workers, including low
vision practitioners, vision rehabilitation experts, and carers
on adapting the smartphone for use by people with SVIB.
Smartphone advertisements often focus primarily on specifica-
tions that are tailored toward the fully sighted populations.
Alternate promotions by smartphone companies of their pro-
ducts that will highlight the use of the accessibility functions
will help persons with SVIB be more informed on the choice of
phones and applications that will be of benefit to them.
Some of the participants also commented on the need to
have a familiar voice accent on the talkback feature. Apart from
the fact that current talk back features do not have any pre-
installed language which is indigenous to the population stu-
died, the various English language accents are also foreign.
Introducing languages or English language accents indigenous
to various populations across the world could help to improve
the accessibility of the android talkback application.
The study focused on the broad use of smartphones and did not
elicit information on the specific applications that the participants
were using. This is seen as a limitation of this study and therefore
recommends that future studies should investigate the exact appli-
cations used and their reason for such a preference.
Conclusion
Smartphones are highly prevalent among persons with SVIB in
institutions of learning. Social media platforms are the most
used applications leading to color and picture description,
being the highest functionality need for people living with
SVIB. Lack of expert training results in the inability to fully
use the accessibility features of the smartphone. The picture
and color description and the majority of the functionality
demands requested by people living with SVIB currently in
existence and compatible with the smartphone. Smartphones
are therefore equipped with major assistive features for people
6C. H. ABRAHAM ET AL.
living with SVIB, and hence it should be considered as an
alternative to traditional low vision aids.
ORCID
Carl Halladay Abraham http://orcid.org/0000-0003-1733-3509
Bert Boadi-Kusi http://orcid.org/0000-0002-4866-4960
Enyam Komla Amewuho Morny http://orcid.org/0000-0002-3008-
2970
References
Ackland, P., Resnikoff, S., & Bourne, R. (2018). World blindness and visual
impairment: Despite many successes, the problem is growing.
Community Eye Health Journal, 30(100), 71–73. https://fig.www.ceh-
journal.org/article/world-blindness-and-visual-impairment-despite-
many-successes-the-problem-is-growing/
Al-Mouh, N., & Al-Khalifa, H. S. (2015). The accessibility and usage of
smartphones by Arab-speaking visually impaired people. International
Journal of Pervasive Computing and Communications, 11(4), 418–435.
https://doi.org/10.1108/IJPCC-09-2015-0033
Bianchi, A., & Phillips, J. G. (2005). Psychological predictors of problem
mobile phone use. Cyberpsychology and Behavior, 8(1), 39–51. https://
doi.org/10.1089/cpb.2005.8.39
Boulianne, S. (2015). Social media use and participation: A meta-analysis
of current research. Information, Communication & Society, 18(5),
524–538. https://doi.org/10.1080/1369118X.2015.1008542
Bourne, R. R. A., Flaxman, S. R., Braithwaite, T., Cicinelli, M. V., Das, A.,
Jonas, J. B., Keeffe, J., Kempen, J., Leasher, J., Limburg, H., Naidoo, K.,
Pesudovs, K., Resnikoff, S., Silvester, A., Stevens, G. A., Tahhan, N.,
Wong, T., Taylor, H. R., Ackland, P., Arditi, A., Zheng, Y. (2017).
Magnitude, temporal trends, and projections of the global prevalence
of blindness and distance and near vision impairment: A systematic
review and meta-analysis. The Lancet Global Health, 5(9), 888–897.
https://doi.org/10.1016/S2214-109X(17)30293-0
Bray, N., Brand, A., Taylor, J., Hoare, Z., Dickinson, C., & Edwards, R. T.
(2017). Portable electronic vision enhancement systems in comparison
with optical magnifiers for near vision activities: An economic evalua-
tion alongside a randomized crossover trial. Acta Ophthalmologica, 95
(5), e415–e423. https://doi.org/10.1111/aos.13255
Christensson, P. (2010). Smartphone definition. Tech Terms. Sharpened
Productions. https://techterms.com/definition/smartphone
Crossland, M. D., Silva, R. S., & Macedo, A. F. (2014). Smartphone, tablet
computer and e-reader use by people with vision impairment.
Ophthalmic and Physiological Optics, 34(5), 552–557. https://doi.org/
10.1111/opo.12136
Flaxman, S. R., Bourne, R. R. A., Resnikoff, S., Ackland, P., Braithwaite, T.,
Cicinelli, M. V., Das, A., Jonas, J. B., Keeffe, J., Kempen, J. H., Leasher, J.,
Limburg, H., Naidoo, K., Pesudovs, K., Silvester, A., Stevens, G. A.,
Tahhan, N., Wong, T. Y., Taylor, H. R., Ackland, P., Zheng, Y. (2017).
Global causes of blindness and distance vision impairment 1990–2020:
A systematic review and meta-analysis. The Lancet Global Health, 5(12),
1221–1234. https://doi.org/10.1016/S2214-109X(17)30393-5
Fuglerud, K. S., Tjøstheim, I., Gunnarsson, B. R., & Tollefsen, M. (2012).
Use of social media by people with visual impairments: Usage levels,
attitudes and barriers. Lecture Notes in Computer Science (Including
Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in
Bioinformatics), 7382 LNCS(PART 1), 565–572. https://doi.org/10.
1007/978-3-642-31522-0_85
Islam, N., & Want, R. (2014). Smartphones: Past, present, and future. IEEE
Pervasive Computing, 13(4), 89–92. https://doi.org/10.1109/MPRV.2014.74
Jacobs, J. M., Hammerman-Rozenberg, R., Maaravi, Y., Cohen, A., &
Stessman, J. (2005). The impact of visual impairment on health, func-
tion and mortality. Aging Clinical and Experimental Research, 17(4),
281–286. https://doi.org/10.1007/BF03324611
Jones, N., Bartlett, H. E., & Cooke, R. (2019). An analysis of the impact of
visual impairment on activities of daily living and vision-related
quality of life in a visually impaired adult population. British Journal
of Visual Impairment, 37(1), 50–63. https://doi.org/10.1177/
0264619618814071
Jutai, J. W., Strong, J. G., & Elizabeth, R. M. (2009). Effectiveness of
assistive technologies for low vision rehabilitation: A systematic
review. Journal of Visual Impairment and Blindness, 103(4), 210–222.
https://doi.org/10.1177/0145482x0910300404
Kasiram, M., & Subrayen, R. (2013). Social exclusion of students with
visual impairments at a tertiary institution in KwaZulu-Natal. South
African Family Practice, 55(1), 66–72. https://doi.org/10.1080/
20786204.2013.10874305
Lundh, A. H., & Johnson, G. M. (2015). The use of digital talking books by
people with print disabilities: A literature review. Library Hi Tech, 33
(1), 54–64. https://doi.org/10.1108/LHT-07-2014-0074
Luthra, V., & Ghosh, S. (2015). Understanding, evaluating and analyzing touch
screen gestures for visually impaired users in mobile environment BT -
Universal access in human-computer interaction. In M. Antona & C.
Stephanidis (Eds.), Access to interaction (pp. 25–36). Springer
International Publishing. https://doi.org/10.1007/978-3-319-20681-3_3
Mclnnes, P., Hailey, D., & Cowley, D. (1994). Assistive devices for people
with disabilities.pdf. Australian Government Publishing Services.
Miura, T., Sakajiri, M., Matsuzaka, H., Eljailani, M., Kudo, K.,
Kitamura, N., Onishi, J., & Ono, T. (2014). Usage situation changes
of touchscreen computers in Japanese visually impaired people:
Questionnaire surveys in 2011-2013. Lecture Notes in Computer
Science (Including Subseries Lecture Notes in Artificial Intelligence and
Lecture Notes in Bioinformatics), 8547 LNCS(PART 1), 360–368.
https://doi.org/10.1007/978-3-319-08596-8_56
O’Dea, S. (2015, September). Smartphone usage by age UK 2012-2019 |
Statista. Statista Inc. https://www.statista.com/statistics/300402/smart
phone-usage-in-the-uk-by-age/
Ovenseri-Ogbomo, G. O., Osafo-Agyei, H., Addy, J., & Ovenseri, E. O.
(2016). Impact of low vision services on the quality of life of low vision
patients in Ghana. African Vision and Eye Health, 75(1), 1–5. https://
doi.org/10.4102/aveh.v75i1.19
Pal, J., Viswanathan, A., Chandra, P., Nazareth, A., Kameshwaran, V.,
Subramonyam, H., Johri, A., Ackerman, M. S., & O’Modhrain, S. (2017,
May). Agency in assistive technology adoption: Visual impairment and
smartphone use in Bangalore. Conference on Human Factors in
Computing Systems – Proceedings (pp. 5929–5940). Denver, Co, USA.
https://doi.org/10.1145/3025453.3025895
Pei-Chia Chiang, P. (2009). The global mapping of low vision services (Issue
September). University of Melbourne.
Rodriguez-Sanchez, M. C., Moreno-Alvarez, M. A., Martin, E.,
Borromeo, S., & Hernandez-Tamames, J. A. (2014). Accessible smart-
phones for blind users: A case study for a wayfinding system. Expert
Systems with Applications, 41(16), 7210–7222. https://doi.org/10.1016/
j.eswa.2014.05.031
Stelmack, J. (2001). Quality of life of low-vision patients and outcomes of
low-vision rehabilitation. Optometry and Vision Science: Ocial
Publication of the American Academy of Optometry, 78(5), 335–342.
https://doi.org/10.1097/00006324-200105000-00017
Tangcharoensathien, V., Witthayapipopsakul, W., Viriyathorn, S., &
Patcharanarumol, W. (2018). Improving access to assistive technolo-
gies: Challenges and solutions in low-and middle-income countries.
WHO South-East Asia Journal of Public Health, 7(2), 84–89. https://doi.
org/10.4103/2224-3151.239419
Tebbutt, E., Brodmann, R., Borg, J., Maclachlan, M., Khasnabis, C., &
Horvath, R. (2016). Assistive products and the Sustainable
Development Goals (SDGs). Globalization and Health, 12(1), 79.
https://doi.org/10.1186/s12992-016-0220-6
Tobias, E. I., & Mukhopadhyay, S. (2017). Disability and social exclusion.
Psychology and Developing Societies, 29(1), 22–43. https://doi.org/10.
1177/0971333616689203
United States assistive technology acts 1998, Public Law 105-394, 112 STAT.
3627. (1998). https://www.govinfo.gov/content/pkg/PLAW-105publ178/
pdf/PLAW-105publ178.pdf
Vu, H. T. V., Keeffe, J. E., McCarty, C. A., & Taylor, H. R. (2005). Impact
of unilateral and bilateral vision loss on quality of life. British Journal of
Ophthalmology, 89(3), 360–363. BMJ Publishing Group Ltd. https://
doi.org/10.1136/bjo.2004.047498
ASSISTIVE TECHNOLOGY 7
Watanabe, T., Miyagi, M., Minatani, K., & Nagaoka, H. (2008). A survey on the
use of mobile phones by visually impaired persons in Japan. Lecture Notes in
Computer Science (Including Subseries Lecture Notes in Artificial Intelligence
and Lecture Notes in Bioinformatics), 5105 LNCS, 1081–1084. https://doi.
org/10.1007/978-3-540-70540-6_162
WHO. (2011). World report on disability: World Health Organization.
www.who.int/disabilities/world_report/2011/report
WHO. (2015) . WHO global disability action plan 2014-2021: Better health
for all people with disability. World Health Organization.
WHO. (2017). WHO | International classification of functioning, disability
and health (ICF). http://www.who.int/classifications/icf/en/
WHO. (2020). Sustainable development goals: Sustainable develop-
ment knowledge platform. https://sustainabledevelopment.un.org/?
menu=1300
Wiafe, B. (2015). Ghana blindness and visual impairment study 2015.
International Agency for the prevention of blindness (IAPB). https://
www.iapb.org/wp-content/uploads/Ghana-Study-BVIS-8_6_2017_-
Final-edit.pdf
8C. H. ABRAHAM ET AL.
