Usability of a New eHealth Monitoring Technology That Reflects
Health Care Needs for Older Adults with Cognitive Impairments and
Their Informal and Formal Caregivers
Fatma Cossu-Ergecer
2,3
, Marit Dekker
1
, Bert-Jan F. van Beijnum
2
and Monique Tabak
1,2
1
Roessingh Research and Development, Telemedicine Group, Enschede, The Netherlands
2
University of Twente, Telemedicine Group, Enschede, The Netherlands
3
TriviumMeulenbeltZorg, Enschede, The Netherlands
Keywords: Health Monitoring, Subjective Monitoring, Cognitive Impairment, Technology, Ehealth, Informal
Caregiver, Formal Caregiver, Home Care, Health Informatics.
Abstract: The aim of this study was to evaluate an eHealth monitoring application (HELMA) that provides insight in
the health status of older adults with cognitive impairments (CI) independently living at home and their
caregivers. A mixed-method approach was used to collect data on Usability (System Usability Scale) and
Actual Use (Log data). Besides, a subgroup of participants were randomly selected and interviewed about
their experiences with HELMA (Ease of Use, Perceived Usefulness, Behavioural Intention to Use and
Attitude). Fifty-four older adults, fifteen formal and fourteen informal caregivers participated in this study.
Results showed that HELMA is a useful supplement in the current care for older adults with cognitive
impairments. The average SUS score of HELMA of formal caregivers indicated “good” usability. The
questions of HELMA are clear. However, older adults lacked digital skills to use HELMA by themselves.
Most of the participants (80%) used HELMA according to protocol, for a minimum of 4 weeks. The attitude
towards willingness to learn and to use a technology were negative for almost all older adults. More
attention to different implementation strategies is needed to increase the eHealth literacy of older adults with
CI, to improve independent use of HELMA in the future.
1 INTRODUCTION
The prevalence of people with cognitive
impairments (dementia) is increasing worldwide.
The economic impact of dementia is high. People
with dementia are confronted with a syndrome that
increasingly affects their memory, thinking,
behavior and ability to perform everyday activities
(Burns, Jacoby, and Levy 1990; Jacoby and Levy
1990). This has severe implications on older adults’
independence and quality of life (Urwyler et al.
2017). Dementia is overwhelming not only for the
people who suffer from it, but also for their
caregivers and families and impacts them physically,
psychologically and economically (Nijhof 2013;
Cahill, Begley, et al. 2007; Carswell et al. 2009).
In the Netherlands, a large number of older
adults with cognitive impairments (CI) receive home
care, allowing older adults to maintain their
independence and quality of life. Home care takes
place at the older adult's home. The care system is
based on the active role and collaboration of various
persons around the older adult, such as family
members, caregivers, neighbors and general
practitioners (Paganelli and Giuli 2011). However,
this current home care system gives particular
limitations. The consequences and chronic nature of
cognitive impairments causes different care needs
for the older adults (Boletsis and McCallum 2014).
Therefore, some older adults may need more
frequent visits than others, based on the severity of
their physical and cognitive functioning (Cahill,
Macijauskiene, et al. 2007). In the current care
system, formal caregivers and informal caregivers
get insight in the health status of the older adult
during home visits of the older adult. However, most
of the changes in symptoms happen in the absence
of informal and formal caregivers and often older
adults try to conceal their disability (Steeman et al.
2006). In addition, older adults have to provide
information to the informal and formal caregivers
Cossu-Ergecer, F., Dekker, M., Beijnum, B-J. and Tabak, M.
Usability of a New eHealth Monitoring Technology That Reflects Health Care Needs for Older Adults with Cognitive Impairments and Their Informal and Formal Caregivers.
DOI: 10.5220/0006639301970207
In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 5: HEALTHINF, pages 197-207
ISBN: 978-989-758-281-3
Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
197
during the home visits, but since they suffer from
cognitive impairments, this information cannot be
considered as fully trustworthy and valid (Smith et
al. 2005). Consequently, in the current care system,
important information about the health status of the
older adult might be missed and the care does not
perfectly fit the needs of the older adult which
decreases the quality of care, eventually increasing
the healthcare costs (Wimo et al. 2013; Comas-
Herrera et al. 2011). To improve the quality of care,
a more frequent and targeted approach that fits the
needs of the older adult seems important (Boletsis,
McCallum, and Landmark 2015).
A promising method to overcome the limitations
of current care are assistive technologies that can
provide information about the real-time needs of the
older adult. In the context of the globally aging
population, many studies have underlined the
possibilities of e-Health applications, due to
increased easily usable internet connection and the
advantages of accessibility, flexibility and
personalized applications (Blusi, Dalin, and Jong
2014; Bujnowska-Fedak and Pirogowicz 2014;
McKechnie, Barker, and Stott 2014). E- health is
defined as “health services and information
delivered or enhanced through the Internet and
related technologies” (Eysenbach 2001). Research
indicated that the use of eHealth in the home setting
is successful at supporting older adults with
cognitive impairments and their caregivers by earlier
detection of needs, increasing self-monitoring and
thereby encouraging (Topo 2009; Nijhof et al. 2009;
Lauriks et al. 2007). As such, eHealth can help in
identifying care needs, risks and monitor disease
progression (Lyons et al. 2015).
Although promising results regarding the use of
e-health in this population of older adults,
implementation is difficult as this is mostly an old
population not familiar with these kinds of
technologies and they suffer from cognitive
impairments (Czaja et al. 2006). Different eHealth
application frameworks show the importance of
involving users early in the development process to
get their perspective during continuous and
systematic evaluations. This way, usability problems
can be prevented and higher attrition rates can be
achieved (Catwell and Sheikh 2009; van Gemert-
Pijnen et al. 2011). As such, we used a user-centered
design approach, involving all stakeholders in the
development of a new e-health technology. We
initiated a workshop at the elderly home
TriviumMeulenbeltZorg (TMZ) in Enschede. The
objective was to gather information with regards to
older adults’ daily needs and how technology could
help to monitor this. As a result of this workshop,
HELMA has been developed. HELMA is a remote
health monitoring application that reflects health
care needs of older adults with cognitive
impairments in four health and well-being domains
(physical, mental, environmental and social). The
aim was to provide insight and detect changes
(decline or progress) in the overall health status and
well-being of older adults, which makes it possible
to intervene more adequately when necessary and as
such improving the quality of care. HELMA is based
on the theoretical framework of OMAHA (Martin
2004; Koster and Harmsen 2015). OMAHA is used
for problem classification to onset and changing of
the care plan, at least once in six months.
The aim of this study was to evaluate HELMA
focusing on Perceived Usefulness, Ease of Use and
Actual Use. We evaluated HELMA following the
framework of DeChant et al (DeChant et al. 1996) in
which the type of assessment is tailored to the
development life cycle of the technology. We used a
stage 1 approach in which we evaluated HELMA on
technical efficacy and in terms of access and quality
of HELMA.
2 METHODS
2.1 Study Design
A mixed method study was performed. We
conducted a qualitative usability study (interviews
and questionnaires), complemented with a quantita-
tive study (datalog-analysis).
2.2 Participants and Setting
This study was performed at home care clients and
informal and formal caregivers of TMZ. TMZ is a
healthcare organization in the Netherlands especially
for elderly with physical and/or cognitive
impairments.
Participants recruited for this study were older adults
with CI, formal and informal caregivers. Inclusion
criteria for older adults were: 1) receiving home care
of TMZ; 2) having cognitive impairments or
dementia; 3) living independently at home. All
formal caregivers were employees of TMZ.
To recruit participants, the first author organized
workshops to inform formal caregivers about
HELMA and asked them if they and the person they
cared for were willing to participate. The formal
caregivers were also informed about the inclusion
criteria and based on that they asked the older adults
HEALTHINF 2018 - 11th International Conference on Health Informatics
198
and informal caregivers to participate in this study.
The Medical Ethical Committee of Medisch
Spectrum at Twente declares that this study does not
meet the criteria necessary for an assessment by a
Medical Ethical Committee according to Dutch law.
Informed consent was obtained from all participants.
After that, participants were instructed about the use
of HELMA and they received their log-in accounts.
They could start using HELMA after that.
Eleven homecare teams from Enschede, Almelo and
Borne were asked to participate in this study.
2.3 HELMA
HELMA helps to monitor the older adults’
healthcare problems through a digital questionnaire
which can be filled in by (1) the older adults; (2)
informal caregivers and (3) formal caregivers. Main
objectives of HELMA are: (1) providing insight in
(changes in) health status of the older adult and (2)
improving the quality of care of older adults.
HELMA is web-based, therefore it is accessible
through various devices: PC, laptop, tablet and
smartphone. HELMA is used online in the home
setting and results can be accessed via a secure web
portal by the participants. HELMA consists of 24
questions about the general health, physical, mental,
social, and environmental aspects of the older adult,
based on the Omaha system (Koster and Harmsen
2015). For the older adult, a decision tree has been
made so that older adults with CI are not overloaded
with questions each time. HELMA always starts
with one question each time (how are you feeling
today?) and an accompanying question (did you use
your medication?). Dependent on the answer of this
first question (good/not good), older adults are asked
to fill in more questions to specify their feelings on
the specific four domains (mentally, socially,
physically, environmentally). Depending on their
answers, older adults receive a minimum of 2 and a
maximum of 24 questions. Formal and informal
caregivers fill in all 24 questions about the older
adult every time. Formal caregivers were instructed
to use HELMA at least ones a week and the informal
caregiver were free to use HELMA.
The informal and formal caregivers and older
adults are presented a global status overview of the
health status of the older adult during the last week.
A full view of all answers of both the caregivers and
the older adults is presented and answers of both the
caregivers and the older adults are compared. As
such, informal and formal caregivers can see in a
quick overview whether something has changed in
the status of the older adult and whether he needs to
adjust care and/or contact the person.
2.4 Procedure
HELMA is used between 23-11-2016 to 22-05-2017.
Participants were instructed to use HELMA for a
minimum of four weeks and at least once a week.
Older adults had the opportunity to use HELMA as
often as they wanted. The caregivers use HELMA
when they visit the older adult at home. If older
adults did not own a technology to use HELMA,
they had the opportunity to use a laptop provided by
the caregiver. Informal caregivers were not obligated
to use HELMA, only if they wanted to.
2.5 Outcome Measures
2.5.1 Demographic Variables and
Technology Use
We collected demographic variables including age,
sex, cognitive functioning, and ADL functioning at
baseline by means of a questionnaire as well as data
about the use of technology of the participants.
Cognitive functioning was measured with the Mini
Mental State Exam (MMSE) (Folstein, Folstein, and
McHugh 1975; Kurlowicz and Wallace 1999). The
range of MMSE score is from 0 (highest cognitive
impairments) to 30 (not cognitive impaired)
(Murden et al. 1991). Self-report of the ability to
perform activities of daily living (ADLs) were
assessed with the Katz ADL (Katz et al. 1963).
Older adults were scored on a scale of I to IV for
independence in each of the six functions. A Score
of I indicated full function, II indicate partial
dependency and III or IV indicated depending on
care (Demotte 2004). Higher scores on this scale
indicated lower ability to perform activities of daily
living.
2.5.2 Usability
To gain insight in the usability of HELMA, the
System Usability Scale (SUS) is measured after the
use of HELMA by older adults and informal and
formal caregivers when used independently. The
System Usability Scale (SUS) is a short ten items
questionnaire to investigate the satisfaction with the
application (Brooke 1996). Rating of the SUS is
from one (disagree totally) to five (agree totally) and
the range is a score from 0 to 100. A score higher
than 70 is considered as good usability, a score of 85
or higher as excellent usability and a score of 90 or
Usability of a New eHealth Monitoring Technology That Reflects Health Care Needs for Older Adults with Cognitive Impairments and
Their Informal and Formal Caregivers
199
higher indicates best imaginable. A score of 50 or
lower is considered as poor or unacceptable usability
(Bangor, Kortum, and Miller 2009; Held et al.
2016).
2.5.3 Perceived Usefulness and Ease of Use
A subgroup of participants (older adults, formal and
informal caregivers) were randomly selected to be
interviewed about their experiences with HELMA
and more in-depth information about the Perceived
Usefulness and Ease of Use, after four weeks of
using HELMA (T1).
Perceived Usefulness and Ease of Use was evaluated
using the Technology Acceptance Model (TAM)
(Davis 1989) and the Unified Theory of Acceptance
and Use of Technology (UTAUT) (Venkatesh and
Davis 2000; Or et al. 2011) which are two of the
most common theories explaining acceptance of
technology in literature. For this study we focused
on four constructs of these models, being: Perceived
Usefulness, Ease of Use, Behavioural Intention to
Use and Attitude.
Perceived Usefulness and Ease of Use are
measured after four weeks of using HELMA (T1) by
means of an interview with a sub selection of older
adults and informal and formal caregivers. Older
adults, formal and informal caregivers were
randomly selected from the users list of HELMA.
Twenty participants, were interviewed to get
information about their experiences of HELMA.
This group consisted of ten older adults, five formal
caregivers and five informal caregivers.
2.5.4 Actual Use of HELMA
The results of using HELMA were saved in log data.
These log data contained information about the
number of login in HELMA for each participant, the
duration (e.g. how many minutes for filling in each
questionnaire) and the frequency of viewing the
weekly or monthly overview for informal and formal
caregivers.
3 DATA ANALYSIS
The results of HELMA were quantitatively analyzed
by using Excel. Graphs were made in Excel to show
the number of login, the duration (e.g. how many
minutes for each questionnaire) and the viewing the
weekly or monthly overview for informal and formal
caregivers.
The data of drop outs is not included in this study.
Only the data of participants who fully completed
four weeks of use were included.
The interviews were audio recorded, transcribed
and qualitatively analysed using thematic analysis
from Braun & Clarke (Meiland et al. 2014; Braun
and Clarke 2006). The transcriptions were re-read
and incremental coded by two researchers by noting
the number of the participants who answered a same
of response. The transcripts were read by both
researchers and provided a code independently
based on theories included in the UTAUT and TAM
model. In case of disagreement, a third coder could
be asked for advice. A coding scheme based on the
category, the code and description was made for the
interview questions. For example, the question ‘Did
the use of HELMA had an added value for you?’ of
the interview, was assigned to the code ‘added
value’. Some quotes from respondents, representa-
tive of the categories, were marked to add in the
results. The codes that are equal or correspond to
each other were assigned to one category. Several
main codes were sub coded as positive, neutral or
negative. Some transcripts were re-read by an
external researcher to ensure that the categories and
codes were correctly described in the coding
scheme. When all interviews were coded, the results
were analyzed.
4 RESULTS
A total of 54 older adults, 28 formal caregivers and
14 informal caregivers participated in the study.
However, a total of 28 formal caregivers made an
account and 15 of them completed the questionnaire.
None of the older adults were able to use
HELMA by themselves and needed help from their
informal and formal caregiver. As such, to be able to
participate in the study informal and formal
caregivers helped the older adults with completing
HELMA after their routine care moment. For this,
the caregiver opened the laptop or computer and
logged in on the older adults’ account. They read the
question out loud. The older adult responded to the
question asked and the caregiver filled in this answer
for the older adult on the computer. After this, the
formal caregiver had to log in on his own caregiver
account, to be able to fill in HELMA from his
perspective.
4.1 Participants’ Demographics
In total, eleven older adults and four informal
caregivers dropped out during the study. The reasons
HEALTHINF 2018 - 11th International Conference on Health Informatics
200
for older adults dropping out were personal
circumstances, such as lack of motivation (n=4),
health problems (n=3), out of care (n=3) and one
older adult (n=1) passed away. The reason for
dropping out of informal caregivers were lack of
time (n=2) or not giving care to the older adult
anymore (n=2).
Demographic information at baseline for
participants is summarized in table 1. Most of the
older adults lived together with the partner. Only one
informal caregiver used HELMA. The mean age of
the older adults was 79.5, of the informal caregivers
64.0 and of the formal caregivers 31.0. Most of the
participants were female. Fifty-four percent of the
older adults indicated that they do not use a
computer or laptop, and 43% did not have a
technology (laptop, computer, tablet an, smartphone)
at all. In contrast, all formal caregivers had 1 or
more technologies at home or at work.
The mean MMSE score of older adults was 23.2,
indicating mild cognitive impairments. The mean
Katz ADL score of older adults was 2.3, indicating a
partial dependency of care.
Table 1: Results of study population by Age, Gender and
use of technology.
Type
Older
adults
(n=54)
Formal
Caregiver
(n=15)
Informal
Caregiver
(n=14)
Mean age in
years (SD)
79.5 (9.1)
31 (11.2)
64 (11.2)
Gender, n (%)
Male
20 (37)
1 (7)
5 (36)
Female
34 (63)
14 (93)
9 (64)
MMSE, mean
(SD)
23.2 (7.2)
—
—
ADL Katz,
mean (SD)
2.3 (1.2)
—
—
Use of technology, n (%)
Computer/
laptop
25 (46)
15 (100)
13 (93)
Tablet
11 (20)
8 (53)
8 (57)
Smartphone
6 (11)
15 (100)
6 (43)
None of above
mentioned
23 (43)
0 (0)
0 (0)
4.2 Usability
The System Usability Scale was completed from the
perspective of the formal caregivers. The SUS was
not filled in by any older adult or informal caregiver,
because they have not used HELMA by themselves.
The mean SUS score is 72.2, indicating “good”
usability of HELMA.
4.3 Actual Use of HELMA
HELMA was filled in from 51 different older adult
accounts and 28 formal caregiver accounts. 43 older
adults (80%) used HELMA at least four weeks.
Mean duration for each session was 1.6 minutes for
older adults and 3.3 minutes for formal caregivers.
The week overview is used by 21 formal caregivers
and month overview by 11 formal caregivers.
4.4 Perceived Usefulness and Ease of
Use
Ten older adults and five formal caregivers were
interviewed to gain insight in the Ease of Use,
Perceived Usefulness, Behavioural Intention to Use
and Attitude of HELMA.
Informal caregivers couldn’t be interviewed
about their experiences, as they didn’t make use of
HELMA.
4.4.1 Perceived Usefulness
The first reactions about HELMA were positive
(100%). Four older adults couldn’t answer the
question due to severe cognitive impairments.
All formal caregivers and 30% of older adults were
positive about one of the main aims of HELMA,
being providing insight in the health status of older
adults. All formal caregivers were positive about the
usefulness as they said that HELMA provided them
a good and clear overview about the needs at a
distance. As an example, a formal caregiver said:
‘you look at the overview of HELMA and you can
see how the older adult was feeling in the past
weeks’(FC2). Most formal caregivers (60 %) and
older adults (50%) were positive about the second
aim, being improving the quality of care because the
service gave information about the health status to
other informal and formal caregivers. Two formal
caregivers (40%) were negative about this, as an
example, a formal caregiver said: ‘Currently not,
because we were very busy with it. However, if
people are independent and can use it by themselves
the quality of care will improve’(FC3).
Furthermore, there are several advantages and
disadvantages mentioned (see table 2). Two formal
caregivers stated that the use of HELMA increased
their digital skills. However, formal caregivers
Usability of a New eHealth Monitoring Technology That Reflects Health Care Needs for Older Adults with Cognitive Impairments and
Their Informal and Formal Caregivers
201
(80%) stated the decision tree design as a disadvan-
tage because this design gives limited questions
when the older adult stated to be feeling good.
Table 2: Perceived Usefulness participants.
Topic
Older adults
Formal
caregivers
First reaction (n)
Positive
Neutral
Negative
Added value
6
0
0
5
0
0
Insight health status (n)
Positive
Neutral
Negative
3
2
3
5
0
0
Higher quality of care (n)
Positive
Neutral
Negative
4
4
1
3
0
2
Advantages (n)
- Personalized, better targeted care
- Improved social contact
- Create time to think about the older
adults’ health status
- Feel useful because of participating in
this study
- Gain digital skills
- Older adults’ reassurance
- Decreases demand of care
- Gives more freedom to older adult
- Insight of patterns in health status
- Create new ways of communicating
1
1
1
1
1
1
2
1
1
1
1
1
Disadvantages (n)
- Time consuming, lack of digital skills
older adult
- Impersonalized care
- Lack of historic Information
- Limited questions for the older adult
when they feel good
- Limited questions to reflect health status
for all domains
- Multiple interpretable questions
- Stressful to the older adult
1
1
1
1
4
4
1
1
4.4.2 Behavioral Intention to Use and
Attitude
Most of the participants were willing to continue
using HELMA in the future (50% older adults and
60% caregivers). Two of the formal caregivers
didn’t have the intention to continue using HELMA,
because they thought it would be too stressful for the
older adult (see table 3).
Most older adults’ Attitude towards willingness to
learn and to use a new technology were negative,
because it was too difficult to learn to use HELMA
with the current age, health status or digital skills.
For example, one older adult said: ‘No, I do not want
to learn that anymore. I am 89 years old. I cannot
learn that anymore’ (C3). However, all participants
stated that they would recommend HELMA to
others. Most of them (60% older adults and 60%
caregivers) were positive about using new
technologies that support efficient and effective
healthcare (see table 3).
Table 3: Behavioral Intention to Use and Attitude
participants.
Positive
Neutral
Negative
Missing
5
0
3
2
2
0
4
4
3
1
6
0
9
1
0
0
6
2
0
2
3
0
2
0
3
1
1
0
5
0
0
0
3
1
1
0
1
0
0
4
4.4.3 Ease of Use
All participants were positive about the Ease of Use
of HELMA (see table 4). They experienced the
questions of HELMA as simple, interesting and
clear, but it was impossible for the older adults to
work with the service by themselves. They needed
guidance from their formal or informal caregivers.
HEALTHINF 2018 - 11th International Conference on Health Informatics
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Table 4: Ease of Use participants.
Topic
Older
adults
Formal
caregivers
Ease of Use (n)
Positive
Neutral
Negative
Questions clear (n)
Positive
Neutral
Negative
9
0
0
7
0
0
5
0
0
5
0
0
Overview clear (n)
Positive
Neutral
Negative
-
-
-
4
0
0
5 DISCUSSION AND
RECOMMENDATIONS
The aim of this study was to evaluate the Perceived
Usefulness, Ease of Use and Actual Use of HELMA.
Results of the study showed that HELMA is a useful
supplement in the current care for older adults with
cognitive impairment. Most participants (60 %
formal caregivers, 40% older adults) indicated that
HELMA improved the quality of care. Besides,
formal caregivers indicated that HELMA provides
useful insight in the health status of older adults at a
distance, even when they are not with an older adult.
This gives them more information about the older
adult before the home visit, also improving the
quality of the care. These results are in line with
those of previous studies who indicated that the use
of eHealth in the home setting is successful at
supporting older adults with cognitive impairment
and their caregivers by earlier detection of needs
(Duff and Dolphin 2007; Topo 2009; Nijhof et al.
2009; Lauriks et al. 2007). Such an identification of
individual needs is the basis for a tailored
intervention, which is important in light of the
current demographic changes. Tailored and
personalized interventions can improve the quality
of care and enable older adults to live at home more
independently for a longer period of time (Lauriks et
al. 2007; Van Mierlo et al. 2012).
Most of the older adults (80%) used HELMA
according to protocol, for a minimum of 4 weeks.
One interesting finding is that most of those older
adults (72%) indicated that they were feeling good,
despite the fact that they have many health problems
and receive home care. This result is in line with a
recent study indicating that concealing the memory
problems and presenting a hardfront to the world are
a common phenomenon in people with CI (Graff et
al. 2010; Nolte 2014). Although in some cases, the
collected information of the older adult cannot be
interpreted as objective data, it provides signals for
formal caregivers to address the change in answers
given over time. It can thus be suggested that
HELMA fits the need of frequent health monitoring
to detect the changes of health in absence of
informal caregivers and to detect when older adults
try to conceal their disability. These results
corroborate the ideas of Nolte (Nolte 2014), who
suggested that participants responded to questions
even when they did not understand the questions and
that information from informal and formal
caregivers is important to address to be able to check
the answers given by the older adults. This
underlines the importance of including different
perspectives in the health status of older adults as
was implemented in HELMA. These different
perspectives give a better insight in how the older
adults is feeling compared with the opinion of the
formal caregiver and highlights differences in
answers given by the older adult and his/her formal
caregiver.
All participants were positive about the Ease of
Use of HELMA, however none of the older adults
used HELMA by themselves. The use of HELMA
was very difficult for the older adults, as most of
them didn’t use a computer or laptop at home. These
results are in accordance with studies indicating that
a small number of older people over the age of 65 in
Europe own a laptop or computer (Irizarry,
Downing, and West 2002; Magnusson, Hanson, and
Borg 2004). In addition, sixty percent of the older
adults in our study were not willing to use a new
technology by themselves, because they thought that
they wouldn’t be able to learn it anymore and most
of them indicated a lack of digital skills. Computer
literacy is a major barrier in other studies as well
where e-health is being used independently by older
people (Lober et al. 2006; Charness and Boot 2009;
Tacken et al. 2005). This e-health literacy calls for
eHealth literacy interventions aiming at improving
older older adults' ability to access and use eHealth
applications, such as HELMA (Korda and Itani
2013; Segal et al. 2012). eHealth literacy refers to
the “set of skills and knowledge that are essential for
productive interactions with technology-based
health tools” (Chan and Kaufman 2011). This
should be taken into account when developing and
implementing e-health services, especially when
Usability of a New eHealth Monitoring Technology That Reflects Health Care Needs for Older Adults with Cognitive Impairments and
Their Informal and Formal Caregivers
203
they have cognitive impairments. It also highlights
the importance of a user-centered design approach as
suggested by van Gemert-Pijnen (van Gemert-Pijnen
et al. 2011). In our study, older adults did not use
HELMA, despite the user-centered design approach.
One explanation for this might be that we involved
them in the development of the content of HELMA,
and not in the technology choices, as we expected
them to be able to use a computer. In the future, this
e-health literacy should be tested at forehand before
implementing such new technologies. We
recommend to focus on this e-health literacy in the
implementation of HELMA by the older adults and
informal and formal caregivers to enable older adults
to make better use of HELMA in the future. This is
in line with the literature, as a significant result
found by Ellis and Allaire that a higher computer
knowledge was associated with less computer
anxiety and higher computer interest (Ellis and
Allaire 1999). In addition, higher involvement of
informal caregivers in the implementation of
HELMA can motivate the older adult to use
HELMA.
Despite the negative attitude towards learning
new technologies, older adults were positive towards
using new technologies by formal caregivers in
homecare. In addition, most of the participants were
willing to continue using HELMA in the future
(50% older adults and 60% caregivers). All
participants (all formal caregivers and 90% older
adults) would recommend HELMA to others since it
gives information about the older adults’ needs. This
indicates that the older adults have a positive attitude
towards using HELMA in their home care, but with
guidance of informal and formal caregivers.
However, the negative attitude towards the
willingness to learn and the willingness to use
HELMA independently is important to take into
account when implementing HELMA into daily
practice of informal and formal caregivers. Many
studies show that training adapted to the learning
needs of older adults has a positive impact on
attitude towards technology (Czaja and Sharit 1998;
Jay and Willis 1992; Morris 1994; Kubeck 1999;
Magnusson and Hanson 2004). Besides, persuasive
elements should be used to support and motivate the
users. The persuasive system Design model (PSD-
model) (Kelders et al. 2012) and the Fogg Behavior
Model (FBM) (Fogg 2009) can be used to develop a
more persuasive eHealth design, because in terms of
PSD, computers are seen as interactive technologies
that can motivate and influence the older adult
(Oinas-Kukkonen and Harjumaa 2008). One of the
persuasive elements is tailoring and research showed
that tailoring as an intervention strategy is effective
in health (Broekhuizen et al. 2012; Wangberg,
Bergmo, and Johnsen 2008) and gives knowledge
about how the individual factors influence the health
outcomes (Neafsey et al. 2008; Ownby, Hertzog,
and Czaja 2012; Noureldin et al. 2012; Bosworth et
al. 2009). In this perspective, it should be beneficial
that HELMA tailors its content to the older adults‘
reading skills, technology experience, health
literacy, age and health issues. Besides, to be
successful in the future, the burden on the formal
caregivers should not be increased too much, but
should be supporting their care for the older adult.
Increased burden has influence on higher illnesses in
formal caregivers (Deeken et al. 2003; Dyck, Short,
and Vitaliano 1999). Therefore, the interaction with
the technology should be as minimal as possible, so
that older adults can use HELMA by themselves.
Different studies showed that other ways of
interacting with these technologies increased the
acceptance of eHealth services in low literacy people
(Thornberry et al. 2002; Wolpin et al. 2010; Kim
and Xie 2015). For example, a combination of text-
to-speech or using touchscreens might be useful to
integrate in HELMA to enable older adults to use
HELMA by themselves.
5.1 Strengths, Limitations and Future
Study
A strength of this study is that three different
evaluating methods are used. In addition, a
representative sample of older adults (54) in home
care was used. Furthermore, HELMA was evaluated
from different perspectives, namely older adults and
informal formal caregivers. Caregivers play a crucial
role in the success of the implementation of health
monitoring. They have the digital skills and ability
to learn to use HELMA rapidly (Chau and Hu 2002).
A limitation was that the older adults with high
level of digital skills were underrepresented in this
study. Older adults in this study with lack of digital
skill have generally less health literacy. The
literature shows that older people with less health
literacy are less willing to participate in a study that
uses questionnaires and are found to be less likely to
use health information (Nijman et al. 2014). In a few
years, the expectation is that the older people have
more experience with use of internet, computer,
smartphone and tablet. A future study is important,
because this might allow older adults to use
HELMA properly by themselves which might
enhance positive results on HELMA.
HEALTHINF 2018 - 11th International Conference on Health Informatics
204
6 CONCLUSIONS
Overall, the use of HELMA seems a useful option
for providing eHealth monitoring for the detection of
older adults’ needs for their caregivers. Older adults
with CI and formal caregivers are generally open
minded towards using new e-Health technologies in
home care. However, older adults lack the digital
skills needed to use HELMA by themselves. More
attention to different implementation strategies is
needed to increase the eHealth literacy of older
adults with CI, to improve independent use of
HELMA in the future.
ACKNOWLEDGEMENTS
We would like to thank the informal and formal
caregivers and clients of TriviumMeulenbeltZorg for
participating in the development of HELMA and the
actual study. Furthermore, the Roessingh Research
and Development for the development of HELMA.
This work was partly funded by the H2020 program
(PHC-20-2014) within the IN LIFE project (grant
no. 643442).
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Usability of a New eHealth Monitoring Technology That Reflects Health Care Needs for Older Adults with Cognitive Impairments and
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