Understanding Trust in Medical Technologies

Wiktoria Wilkowska and Martina Ziefle

Human-Computer Interaction Center, RWTH Aachen University, Campus Boulevard 57, Aachen, Germany

Keywords: Trust, Medical Technology, Ambient Assisted Living, User Diversity, Age, Gender.

Abstract: This paper aims to extend knowledge with respect to trust in health-related technology and deals with an

exploration of this topic and the validation of the findings using multi-method research. The empirical

approach aimed at the evaluation of the opinions and attitudes towards the importance of trust conditions

(reliability, trustworthiness, operability and easing) and trust “mediators” (physician as a role model,

scientific evidence, exchange with peers and hands-on experience), and assessed the relevance of different

system features among different users. User factors such as age, gender and the perceived health condition

were taken under consideration as representative indicators of the diversity among the (potential) users.

Results showed a significant influence of age and gender on the examined trust indicators and underline the

importance of considering the users’ diversity in the research of trusted – and thus accepted – medical

systems in home environments.

1 INTRODUCTION

Electronic health technology (eHealth) in the context

of Ambient Assisted Living (AAL) represents one of

the biggest shifts in healthcare today. Innovative

advancements in digital technology allow healthcare

organizations to change the way healthcare is

delivered, and users to reframe their view on how

they can maintain their health and well-being more

independently. Currently, many institutions and

stakeholders are making efforts to optimize and/or

improve the infrastructure in this regard to ensure

the widespread use of the common health-supporting

technologies at home.

Therefore, health-related technological devices

which monitor the relevant vital parameters and

offer support to manage the well-being of people

outside of traditional medical institutions have a

great potential to rapidly become common tools to

support health-care in people’s homes. However, the

success of the adoption of such ambient medical

technologies largely depends on the extent to which

users trust, and can rely on, the equipment. In

addition, it is crucial to understand how people will

trust in ambient medical technology systems while

achieving and maintaining their privacy (Little et al.,

2007). Especially in the field of medical technology,

it is therefore important to adapt the devices to the

special needs and – if possible – to wishes of the

(potential) users which, naturally, requires a careful

examination of the differences between the users.

1.1 The Phenomenon of Trust

Research with respect to the integration of

information systems indicates that trust plays an

important role in helping users to overcome

perceptions of risk and uncertainty in the use and

acceptance of new technologies (Li et al., 2008;

Pavlou and Grefen, 2004). Despite the broad

consensus that trust in technology is one of the most

important factors in the technology saturated society

(Lewis and Weigert, 1985; Falcone and

Castelfranchi, 2001), the phenomenon of trust is

anything but clear and consistent in the relevant

literature. It does not only concern the different

contexts of the computerized society (e.g.,

information and communication technologies, e-

commerce, intelligent physical environments, virtual

reality, etc.) but also people’s trust in a secure digital

infrastructure, sources of information, data, personal

assistants, and processes and software.

Trust is not easily defined. The extensive amount

of research regarding trust leads to a certain

fuzziness of the definition of trust, resulting in some

difficulties to clearly understand the term. The main

reason for this is its multidisciplinary and multi-

contextual nature. For instance, Boon and Holmes

Wilkowska, W. and Zieﬂe, M.

Understanding Trust in Medical Technologies.

DOI: 10.5220/0006734500620073

In Proceedings of the 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2018), pages 62-73

ISBN: 978-989-758-299-8

(1991) defined it as “a state involving confident

positive expectations about another’s motives with

respect to oneself in situations entailing risk” (p.

194). Within the field of e-commerce, trust is related

to three perceptual factors that have an impact on

online trust: perception of credibility, ease of use

and risk (Corritore, 2003). Then again, Wang and

Emurian (2005) identify four elements of online

trust regarding interface design features, which

relate to graphic, structure, content and social-cue

design. The evidence that the design of an interface

can significantly impact the perceived

trustworthiness of a system also applies to mobile

technologies (Siau and Shen, 2003). Thus,

researchers often conceptualize trust according to

the features of a particular context (Sillence et al.,

2006).

Studies involved in the development of a

framework for the construct of trust in the context of

medical technology proved that the trust in medical

technology empirically differs from the general trust

in technology (Montague et al., 2009). The

phenomenon of trust seems to be more indispensable

when health-relevant aspects are technology-

mediated (Wilkowska, 2015). The concept is multi-

faceted and includes different factors which might

be important for understanding how the acceptance

and long-term adoption of health-enhancing

technologies can be ensured; these factors concern,

among others, personalization, motivation, expertise,

familiarity, predictability, sensitivity, and the source

of the information.

Because of the rising number of older people,

and thus presumably those with rather frail health,

patient’s trust in medical technology may be an

important factor of functionally working systems;

especially since health care work systems move to a

higher reliance on and use of medical technologies

(Montague, 2010). As a fundamental attribute in the

adoption of health-supporting technologies, trust

refers to a variety of relationships: interpersonal trust

(e.g., in the patient-physician communication), trust

in the environment and in the infrastructure (Falcone

and Castelfranchi, 2001), social trust (e.g., in a

healthcare institution) and the trust in automation

(Muir, 1994).

In the context of emerging AAL-environments,

where technology is meant to assist people in their

everyday life and support them in terms of their

health (e.g., monitoring devices, measurement of

vital parameters, sensors recording fall detection,

etc.), trust is a particularly important phenomenon,

which has been barely researched yet. Individuals

are confronted with situations, in which they have to

trust the medical devices that are incorporated in an

ambient technology system and which, depending on

how much their health impairments have them rely

on this technology, become part of their life. In this

context, trust is more likely to be a dynamic process,

which might change depending on the users’

characteristics (e.g., age, gender), current health

conditions or the changing circumstances of their

lives. Considering the differences between the

(potential) users is, therefore, of utmost importance.

1.2 The Differences in the Users

For a long time, the scientific studies of information

technology have perceived that individual

differences exert a major force in determining its

success (Zmud, 1979). Accordingly, a lot of

scientific evidence shows that differences in socio-

demographic characteristics, computer experience,

cognitive abilities, and personality are significant

factors in explaining both technology acceptance

and user behaviour (e.g., Gefen and Straub, 1997;

Rogers and Fisk, 2000; Ong and Lai, 2006;

Wilkowska and Ziefle, 2009).

Especially age, as a factor of user diversity, plays

an enormous role in the explanation of the

variability in system acceptance and performance.

Not only the users’ belonging to a particular

technology generation (e.g., Sackmann and Winkler,

2013) and the connected know-how, perceived self-

efficacy and attitudes towards technology, but also

the users’ mental and physical state can decisively

influence their trust in, and use of, a certain

technology system. Therefore, the development of

age-sensitive and age-appropriate interfaces is

highly challenging because aging itself is a very

complex and differential process. The same applies

to the users’ gender and the resulting differences

with respect to technology perceptions and

behaviours (e.g., Schumacher and Morahan-Martin,

2001; Broos, 2005; Gaul et al., 2010). Changes in

health conditions or stressful life events can also

have a strong impact on the perception of, and

intention to use, assistive technology (e.g.,

Wilkowska, 2015).

Recent research dealing with the acceptance of

technology in the context of health-supporting

technologies in the domestic settings, increasingly

considers different users and their different needs in

the development and design process (e.g., Demiris et

al., 2004; Klack et al., 2011; Wilkowska and Ziefle,

2011; Ziefle et al., 2016a). Since this technology is

primarily intended for the elderly, disabled and/or

people with a chronic disease, it must be taken into

Understanding Trust in Medical Technologies

account that their trust in such an assistive

technology may largely differ from the trust of

younger, healthy and carefree users.

1.3 Questions Addressed

Based on the described considerations, the present

research examined the concept of trust contextually

regarding the increasingly used medical technology

in home environments. The approach was performed

in two empirical steps: First, using a qualitative

research method to explore the topic of trust in the

upcoming context from scratch. For this, participants

should discuss different trust aspects of the

integration of the technology in the living

environment (socio-technical system) and the trust

in a system or institution which manages the health

data (social trust), over the interpersonal trust (e.g.,

in the communication with the physician in charge)

through to the perceived reliability and demands

regarding technical device or system (technological

trust). After that, the qualitative results were

validated using quantitative method to ascertain the

generalisability of the findings. Unlike in the

previous research, special focus was thereby directed

to the user diversity which was assumed to

considerably influence the trust itself.

2 METHOD

The content described in this paper are part of a

wider range of studies conducted to explore the

users’ perceptions and requirements regarding

medical assistive technologies in home

environments (see Wilkowska, 2015).

The concept of the described empirical studies

uses a user-centred design approach, the main goal

of which is to reveal how technical systems must be

designed for, and adapted to, the individual concepts

and mental models of the (potential) users.

In this study on the trust in, and the perception of

privacy towards, electronic health technology,

opinions regarding the characteristics that are

perceived as necessary to the use of (and trust in)

medical devices, as well as conditions for the use of

such devices, were collected. For this purpose, a

multi-method empirical approach was pursued

which is described in more detail hereafter.

2.1 Multi-method Approach

Considering the user-centred design of the

conducted qualitative and quantitative studies,

special attention was paid to user diversity (e.g.,

user’s age, gender, physical/health condition, etc.)

and the dynamics of personal biographies (e.g., the

onset of an illness). Therefore, some of these criteria

were decisive for the composition of the focus

groups which represented the first step of the

empirical procedure.

2.1.1 Focus Groups

Focus groups were arranged to gather qualitative

information about the designated topic. This method

was chosen because group interactions may

accentuate members’ similarities and differences in

a particular context and provide rich information

about the range of perspectives, opinions, cognitive

beliefs and experiences (Lambert and Loiselle,

2008). The idea was to initially explore the topic of

trust and acceptance in the context of the use of

different medical technology devices in a domestic

setting. Therefore, a relevant part – next to the topic

of privacy in the context of eHealth technology –

were the discussions about the aspects which are

relevant, or even indispensable, for a trustable and

accepted (daily) use.

In three focus groups sessions (N=15), women

(60%) and men of different ages (age range: 23-64

years) exchanged their views on the following

questions: “In your opinion, which characteristics of

a health-related technology which is used in a home

environment are essential?” and “Which conditions

would have to be fulfilled for you to use (and trust) a

medical-support device which has to be used at

home?”. Considering the preceding discussions

about the thematically related topics of ’trust’ and

’privacy’ when dealing with health-supporting

equipment, and after the introduction of the related

topics, like chronic diseases (e.g., cardio-vascular

conditions, diabetes, etc.), the process of ageing and

the need for care, participants presented their

requirements, reservations and conditions of usage.

The objective was to find out which basic

characteristics of the devices are expected and which

conditions are required by the (potential) users to trust

and rely on the interaction with such devices, in order

to increase their acceptance and the adoption in the

long run. The resulting expected characteristics of

health-supporting devices which are used in home

environments are summarized in Table 1. In Table 2,

the conditions for trusted usage are presented.

Methodologically, focus groups allow a deeper

insight into the nature of such sensitive and,

somehow, difficult-to-grasp topics. However, the

restrictions of the method refer to a comparably

ICT4AWE 2018 - 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health

small sample size and personally coloured results

which are unrepresentative. To scientifically

ascertain the representativeness of the findings, the

outcomes of the focus groups were taken as an

empirical base for the subsequent construction of

survey items to allow further quantitative data

collection with a larger sample.

Table 1: Expectations for eHealth devices for domestic

use.

Item description Scale

1. Unconditional reliability

Six-point

Likert scale

ranging

from 1

(‘not at all

important’)

to 6 (‘very

important’)

2. Ease of use

3. Low price

4. Seal of approval / test label

5. Attractive / fashionable design

6. Unobtrusiveness

7. Officially recognized manufacturer

8. Recommendation of the physician

9. Financial support of the health

insurance for procurement,

maintenance, etc.

10. State of the art

11. Strict access control to the health

data (e.g., by fingerprint)

2.1.2 Quantitative Survey

In the next step of the empirical approach a

questionnaire was conducted to quantitatively

validate the most interesting findings.

The questionnaire was divided in three parts: In

the first part, the participants answered questions

about their socio-demographic profiles (e.g., age,

gender, professional background, health condition

etc.). They also reported their experience with

health-supporting devices in their daily lives. The

second part focussed on privacy in the context of

health-supporting technology in domestic

environments, but will not be analysed or discussed

further in the present paper. The last part of the

survey collected data on the trust in eHealth

technology. To do so, respondents had to work on

the following questions: 1) features and

characteristics expected/required for the devices, 2)

trust-conditions that must be met for accepted usage,

and 3) complementary statements, retrieved from the

focus group discussions, about what else makes the

medical technology at home trustworthy.

The participants were recruited through

advertisements in local newspapers, social networks

on the Internet and collaboration with targeted

societal groups (e.g., retirement home). Some of the

respondents were also reached through the authors’

personal contacts. There was an online version and a

paper-based version of the questionnaire (from the

latter especially the older participants benefited). On

average, it took 15-20 minutes to complete the

questionnaire and the data collection lasted for about

four weeks.

2.2 Research Approach

In accordance with the concept of user-centred

design (e.g., Abras et al., 2014; Mao et al., 2005),

the research variables focus on different

characteristics and health biographies of the users on

the one side, and on their expectations and

requirements for trusted health-supporting

equipment at home, on the other.

2.2.1 Independent Variables

Technology users do not only hugely differ in their

socio-demographic characteristics, but also in their

sensory and cognitive skills, physical and motoric

capabilities, and their different requirements (e.g.,

those linked to aging) which complicate an easy-

going interaction with modern technical solutions

(Wilkowska, 2015).

To deepen the understanding of the diversity

among the (potential) eHealth users, as well as of

their different needs and requirements, it is crucial to

consider different points of view regarding the trust

in such a technology. In the present statistical

analyses, three independent variables, which refer to

the participants’ diversity, will be considered:

 Age [young (≤44 years; 50%) vs. middle-aged

and older (45 years and older; 50%)];

 Gender [women (46%) vs. men (54%)];

 Perception of the own health condition [good

(44%) vs. moderate (46%) vs. poor (10%)].

2.2.2 Dependent Variables

The dependent variables refer to the perceived trust

in the eHealth technologies which are used in

people’s home environments for health monitoring,

prevention and rehabilitation.

First, the required features and characteristics

for eHealth devices (see Table 1) are considered as

dependent variables. After that, the conditions of

trust regarding health-supporting technology in

domestic settings are examined. The items were

evaluated using a six-point Likert scale ranging from

1 (‘strongly disagree’) to 6 (‘strongly agree’). For a

better overview, thematically related aspects are

merged into categories (see Table 2). Next to the

device’s reliability, three other main categories of

Understanding Trust in Medical Technologies

trust conditions were generated (the internal

consistency of the particular categories is indicated

between brackets):

 Trustworthiness (Cronbach’s alpha α=.71;

min=3, max=18);

 Operability (Cronbach’s alpha α=.73; min=3,

max=18;

 Easing of the burden of the disease (Cronbach’s

alpha α=.83; min=2, max=12).

Table 2: Formed trust categories of eHealth technology.

Category Item description

“I would trust the medical device

if…

Reliability

…it would immediately provide

feedback about incorrect information

and asks me to repeat the

measurement.”

Trust-

worthiness

…I would know that it comes from

an approved and trustworthy

manufacturer.”

…its reliability would be confirmed

by a recognized testing institution.”

…I would rarely have to see the

doctor thanks to the device.”

Operability

…I would intuitively understand how

to handle the device.”

…I would be able to count on

customer service in case I experience

difficulties.”

…it would allow me to take it

anywhere to make measurements.”

Easing

…it would be integrated in my daily

life so that I feel relieved from my

illness.”

…it would give me the feeling of

independence despite my illness.”

Moreover, four additional statements on what else

makes the use of a health-supporting technology at

home trustworthy were added as dependent

variables. Likewise, participants expressed their

level of agreement (6=‘strongly agree’) or

disapproval (1=‘strongly disagree’) regarding the

aspects presented in Table 3.

Table 3: Additional statements regarding trust in eHealth.

Item description

Short

description

“If my doctor relies on medical

technology, I trust it.”

doctor as a

role model

“I consider medical devices whose

quality and functionality are confirmed

by scientific studies to be trustworthy.”

scientific

evidence

“I consider medical equipment, which

functionality I can try out for a while

without paying, to be trustworthy.”

hands-on

experience

“My trust in medical devices would be

greater if I could exchange with peers.”

exchange

with peers

2.3 Participants

The sample intended to cover different population

groups including young, middle-aged and older

people with different skills, professional

backgrounds and levels of experience with

technology.

This study collected and analysed the data of

N=104 participants (ages ranged between 21-98

years). More than 40% of the respondents reported

to suffer from chronic health conditions (e.g.,

cardiovascular diseases, diabetes mellitus, asthma).

Overall, more than half of them reported experience

with health-supporting devices in everyday life: the

most participants used blood pressure meters (32%),

followed by those who used blood sugar meters

(10%) and 9% used heart rate monitors; a few (6%)

also reported to use hearing aids and insulin pumps.

Different professions (including teachers,

engineers, economists, psychologists and

mechanics) and different educational levels were

represented in the sample; there was a quite high

average level of education though. The participation

in the study was voluntary and respondents were not

compensated for participating.

3 RESULTS

For the statistical examination of the independent

variables’ significant influence on trust, multiple

analyses of variance (MANOVA) were executed and

the significance of omnibus F-Tests was taken from

Pillai values. For descriptive analyses, the means

(M) and standard deviations (SD) are reported, and

the parameter partial eta squared (

) was calculated

for the effect sizes according to Cohen (1988). For

the continuous trust variables, Pearson’s product-

moment correlations (r) were calculated. The level

of statistical significance (p) was set at the

conventional 5%.

3.1 Expected Features for eHealth

In the first step, the influence of independent

variables on the expected trust characteristics is

statistically examined. A multivariate analysis of

variance revealed a significant omnibus effect of age

ICT4AWE 2018 - 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health

[F(11,76)=2.1, p=0.033;

=.23] and gender

[F(11,76)=2.6, p=0.007;

=.27].

The effects of age on the between-subject level

resulted for the following characteristics: ease of use

[F(1,98)=7.6, p=0.007;

=.08], low price

[F(1,98)=5.9, p=0.017;

=.06], officially recognized

manufacturer [F(1,98)=7.3, p=0.008;

=.08] and the

state of the art [F(1,98)=6.9, p=0.01;

=.07]. The

resulting means are depicted in Figure 1. It is evident

that the middle-aged and older participants expect

significantly higher standards for medical equipment

in domestic settings than the young participants.

Ease of use Low price Officially

recognized

manufac

ure

State of the

art

Attributed Importance (max=6)

Young Middle-aged and old

Figure 1: Effect of age on expectations regarding eHealth

technology in home environments.

Considering the impact of gender the on expectations,

the particular effects on the between-subject level

result for unconditional reliability [F(1,98)=4.6,

p=0.035;

=.05], seal of approval [F(1,98)=7.7,

p=0.007;

=.08], ease of use [F(1,98)=20.1,

p≤0.001;

=.19] and recommendation of physician

[F(1,98)=5.6, p=0.021;

=.06]. Descriptive data

(Figure 2) demonstrate that women have higher

expectations regarding health-supporting devices

than men. According to the effect sizes, the impact

of gender is especially meaningful for the ease of

use of the medical technology.

3.2 Trust Conditions for eHealth

In the next step, the independent variables’ influence

on the usage conditions of health-supporting

technologies in domestic settings were examined.

Analyses of variance revealed a significant main

effect of gender on the condition of flawless

operability of the digital medical technology in an

AAL environment [F(1,101)=4.2, p=0.043;

=.04].

The influence of gender on the trust condition of

operability is evident in Figure 3 (left).

Unconditional

reliability

Seal of approval Ease of use Recommendation

of physician

Attributed Importance (max=6)

Men Wo

Figure 2: Effect of gender on expectations regarding

eHealth technology in home environments.

Degree of Agreement (max=18)

Operability

Wom e

Degree of Agreement (max=18)

Thrustworthiness

Wom

Figure 3: Main effect of gender on the conditions of

operability (left) and trustworthiness (right) when using

eHealth technology in home environments.

A similar pattern is noticeable regarding the

conditions that form the trustworthiness

[F(1,100)=4.4, p=0.039; partial

=.05]. The mean

values are depicted on the right in Figure 3. Even

when, according to the rather small effect sizes, the

impact of gender is minor in both cases, the results

indicate that women demand more stringent

conditions for medical equipment than men.

In addition, the univariate ANOVA revealed

moderate interacting effects of age and gender

[F(1,100)=8.7, p=0.004; partial

=.09], as well as

of gender and perceived health conditions

[F(2,100)=4.4, p=0.014; partial

=.09], on the

trustworthiness in health-supporting technology.

Especially in the younger age group, men (M=11.1,

SD=0.8) and women (M=15.1, SD=0.8) differ

significantly, whereby women demand higher

standards of trustworthiness in this context. As

opposed to this, the differences in the group of

middle-aged and older participants are not so evident

between women (M=14.3, SD=0.8) and men (M=15,

SD=0.7). The interaction is presented on the left in

Figure 4. Moreover, visible at the right side of

Understanding Trust in Medical Technologies

Figure 4, the additional influence of health condition

especially splits the opinions of those who report

bad health: Whereas women require very high

standards of trustworthiness (M=16, SD=1.5), men

with poor health do not pay as much attention to this

condition (M=10.1, SD=1.3). On the contrary, in the

groups of good and moderate health both genders do

not significantly differ in their opinions, both

reaching high means for the condition of

trustworthiness.

Men Women

Degree of Agreement (max=18)

Young Middle-aged and old

Good Moderate Poor

Degree of Agreement (max=18)

Health Condition

Men Wo me n

Figure 4: Interaction effects on the conditions of

trustworthiness: age and gender (left), gender and health

condition (right).

Furthermore, the statistical analyses of the trust

conditions of reliability and of the easing of the

burden of the disease, yielded no significant

influences of age, gender or health condition.

According to this, independent from the user

diversity, all participants wished for highly reliable

medical equipment which serves the purpose of

exoneration.

3.3 Additional Aspects of Trust for

eHealth

To complete the analyses related to trust in the

context of health-supporting technologies at home,

additional aspects which resulted from the

aforementioned group discussions (see Table 3)

were taken under consideration. The technique of

three-way analysis of variance was chosen for the

statistical evaluation.

Considering the aspect ‘doctor as a role model’

as relevant for the trust in medical devices, an

ANOVA with the factors age, gender and health

condition revealed a significant effect of the

participants’ age [F(1,102)=4.1, p=0.046;

=.04].

Figure 5 shows the differences between the average

values reached for both age groups. Even if the

differences in the perceptions are small, the outcome

shows that the middle-aged and older (M=3.6,

SD=1.5) confide in the opinion of the doctor, who

relies on the technology, more than young people

(M=4.2, SD=1.5).

Degree of Agreement (max=6)

Young M

ddle-aged and ol

Figure 5: Main effect of age on the trust aspect ‘doctor as

a role model’ for using eHealth technology at home.

In addition, for the aspect of ‘scientific evidence’ the

analysis of variance showed a moderate and strong

influence of the user factors: (1) main effect of age

[F(1,101)=6.1, p=0.015;

=.06]; (2) main effect of

gender [F(1,101)=4.5, p=0.036;

=.05]; and (3) an

interacting effect of gender and health condition

[F(1,101)=6.1, p=0.003;

=.12]. The descriptive

data for both main effects are depicted in Figure 6.

The moderate effect of age (on the left side of the

graph) shows that middle-aged and older people

(M=4.9, SD=1.2) perceive medical devices whose

quality and functionality is confirmed by scientific

studies as more trustworthy than the younger

participants (M=4.1, SD=1.4). Regarding the

influence of gender (on the right in Figure 6),

women’s average values (M=4.9, SD=1.2) exceed

those of men (M=4.1, SD=1.5), meaning that

women’s trust in medical equipment at home is

slightly more shaped by scientific studies.

Figure 6: Main effect of age (left) and gender (right) on

the trust aspect ‘scientific evidence’ for using eHealth

technology at home.

Degree of Agreement (max=6)

Young Middle-aged and old

Degree of Agreement (max=6)

Men Wo me n

ICT4AWE 2018 - 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health

Next to the influence of age and gender, an

interacting effect of gender and the perceived health

condition resulted for the aspect of ‘scientific

evidence’; Figure 7 depicts the means of the

particular groups. Interestingly, for both genders the

biggest differences in this regard result for those,

who report poor health conditions, whereby women

with poor health (M=5.7, SD=0.5) attach

significantly higher importance to scientific

evidence than men (M=3, SD=2) with the same

health status.

Good Moderate Poor

Degree of Agreement (max=6)

Health Condition

Men Wom en

Figure 7: Interacting effect of gender and health condition

on the trust aspect ‘scientific evidence’ for using eHealth

technology at home.

Finally, a significant interaction effect of gender and

health condition results for the trust aspect of

‘exchange with peers’ [F(2,102)=4.3, p=0.016;

=.09]. The pattern is similar to the previous

analysis: Compared to people with good and

moderate health conditions in both genders, the

opinions change for men and women with poor

health conditions. Thereby, women (M=5, SD=0.8)

consider it to be more important to exchange their

opinions with peers than men (M=2.9, SD=1.6). The

mean differences are showed in Figure 8.

Good Moderate Poor

Degree of Agreement (max=6)

Health Condition

Men Wo me n

Figure 8: Interacting effect of gender and health condition

on the trust aspect ‘exchange with peers’ for using eHealth

technology at home.

For the aspect of ‘hands-on experience’ the results

are neither age-, gender-, nor health status-specific.

3.4 Special Case of Trust – the

Reliability

In the final step of the statistical analyses, the

interrelations between the researched trust variables

and their association with the perceived usefulness –

as a correlate of acceptance – of health-supporting

technologies in home environments are presented.

0.71**

Trustworthiness

Reliability

Scientific

Evi dence

Perceived Usefulness

Operability

H ands-on

exper i ence

Exchange

with peers

0.31*

0.54**

0.58**

Easing of the

Bur den of

the Disease

0.41**

0.57**

0.51**

0.34**

Doctor as a

Role M odel

Figure 9: Interrelations of the research variables with the

perceived usefulness.

As the previous analyses showed, the condition of

reliability was not influenced significantly by the

independent variables (i.e., age, gender and health

condition). However, the results of the correlation

analysis showed strong and moderate associations

with the other trust factors mostly ranging from

r=.40 (e.g., for the easing of the burden of the

disease), to r=.67 (for operability), to r=.90 (for

trustworthiness).

In the correlation analysis we additionally

included the variable ‘perceived usefulness’ of

health-related technologies to see how this

acceptance indicator is connected to the trust

variables elaborated in the presented studies. The

results are astonishing, showing rather weak

coefficients oscillating around r=.3 (e.g., with

trustworthiness, reliability, scientific evidence).

These findings suggest that trust in medical

technology does not mean that people accept it, but

– in accordance with relevant literature in this

context – additional components are necessary for a

high user acceptance.

Understanding Trust in Medical Technologies

4 DISCUSSION

In the present research, we focused on understanding

the trust in and trustworthiness of medical

technology which is increasingly used in home

environments. However, this topic is part of a

broader subject matter, regarding the acceptance of

medical technology. Facing the demographic change

and the increasing prevalence of medical technology

integrated into people’s lives and private spheres it

is of utmost importance that users really do accept

these technologies. However, acceptance is a truly

complex issue, which – especially in this sensitive

context – might not be easily described by the

traditional factors of technology acceptance (Davis

et al., 1989; Venkatesh, 2000). Plenty of usage

motives as well as usage barriers in the context of

medical technology are rather prevailing. In

addition, the motives and barriers heavily depend on

the situational context (e.g., when the medical

technology is life-saving with no usage alternatives),

the health status of the users (i.e., how severe is the

disease for which the medical technology is used),

and the personality of the user, including risk taking

behaviour, coping strategies, technical self-

confidence, media competence, etc. Moreover, as

outlined before, it has been shown that demographic

variables such as age, gender and education also

considerably impact the extent to which people are

willing to adopt and use medical technology.

Recent research uncovered the trust in, and

trustworthiness of, medical devices as major facets

of the acceptance of technology in the area of

medical technology. On the one hand, this is obvious

as the medical technology relates to sensitive and

fragile health constitutions which rely on a high trust

of users (Montague et al., 2009; Ziefle et al., 2011).

On the other hand, especially for older and

experienced people, one could assume that seniors

might be less sensitive in terms of acceptance of

technology, since they typically have no choice but

to use it. Still, the nature of the perception of the

trust in the area of medical technology and the

question on which requirements and usage

conditions might contribute to the perceived trust

and trustworthiness, is underdeveloped so far.

In the presented empirical studies, users of

different ages, of both genders and with different

health conditions shared their opinions and attitudes

towards the importance of trust “markers”

(reliability, trustworthiness, operability and easing)

and trust “mediators” (doctor as a role model,

scientific evidence, exchange with peers and hands-

on experience) and assessed the relevance of

different system features. Overall, the studies

disclosed findings, which turned out to be

insensitive to user diversity as well as findings in

which user profiles played a significant role.

Regarding the differences between the genders,

women attached a higher value to the ease of using

medical technology in contrast to men. Moreover,

women’s trust in medical technology at home relies

much more on scientific evidence, thus women

shape their trust in line with the validation by

science. When it comes to the impact of age, it was

found that middle-aged and older participants

significantly expect higher standards for medical

equipment than younger users. In addition, middle-

aged and older people confide in the opinion of the

doctor, who relies on the technology, to a higher

extent than younger people. An interesting finding

referred to the fact that especially women with a

poor health status report to rely on the exchange

with peers, while in the opinion of men the peer-

exchange is not that important for trustworthiness.

The findings for the trust conditions of reliability

and the easing of the burden of the disease yielded

no significant influences of age, gender or health

status. Apparently, there are deeply engrained

attitudes that are not formed by the diversity of

biographies and the change of values over the life-

span.

On a higher level, the presented outcomes

corroborate that user diversity, especially ageing and

frailness, should be a benchmark for the

development of medical technology. Technical

design, especially in the field of medical technology

field, should be aligned with the needs of the

respective end users. This does not only include an

understanding of the functional requirements of

medical technologies, but also the reframing of

traditional acceptance and usability benchmarks

(mostly concentrating on ease of use and

usefulness). In line with this, the perspective should

be broadened by including intimacy and trust

cognitions as a dictum for the design of a socially

responsible medical technology.

Of course, the empirical approach also has some

limitations which should be considered. The

perception of trust is a highly complex topic, and the

dimensions and facets which have been included in

our empirical approach are only a quite arbitrary

selection of attributes. It is obvious that there are

many more aspects which require a closer analysis

in future work.

Another limitation regards the impact of

demographic variables on the perception of trust.

Strictly speaking, one could argue that we only

ICT4AWE 2018 - 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health

superficially analysed the impact of the demographic

variables on the perception of trust and

trustworthiness in the area of medical technology.

Even though the results provide interesting insights,

age, gender and health condition are quite rough

categories that need a closer look. Characteristically,

the user factors age and gender are carriers for other

factors, like social and societal attitudes, life

experience, domain knowledge, skills and expertise,

and general wisdom (Ziefle and Schaar, 2011)

which, likewise, might be promising candidates

which shape the trust in the health-supporting

technology. Moreover, age is also connected to

different values on and perspectives of culturally and

societally anchored aging concepts. The moment

users feel old, and the moment they are old might

largely differ, depending on individual perspectives,

but also on cultural and economic dimensions

(Thiede, 2005; Hallenbeck, 2001).

Another limiting factor is the comparably small

sample size. Even though the sample size might be

methodologically and statistically appropriate for the

carried-out analyses, it is still clear that trust and

trustworthiness are inevitably intermingled with

lifelong-learning and the understanding of broader

user groups and cultural diversity. Future studies

should therefore concentrate on more aspects of

trust, using a larger sample size and addressing the

understanding of trust in an intercultural setting.

Last but not least, we should also be aware that

trust in medical technology and care has a policy

component (Mechanic, 1998). In this context, it

should be examined if the perceptions of trust and

trustworthiness also include the competence of the

medical treatments and the education of medical

professionals, the individuals’ confidence in the

national or international efforts for ethical human

care, and the diversity-fair treatment of patients at an

older age (Wilkowska et al., 2018).

5 RESEARCH DIRECTIONS

The mentioned limitations are necessary to outline

some research directions regarding the field of trust

in health-supporting technologies in home

environments.

Decidedly, patients’ trust is an inevitable

component of the future development of medical

innovations that are increasingly implemented in

domestic settings. Health and disease are inherent

parts of humankind, which directly affect people’s

well-being, personal identity formation and life-span

development. Therefore, any technology that seeks

to be supportive for medical treatment and care

needs to consider highly sensitive social issues,

regarding both, physical and mental conditions.

In many cultures being old and ill is perceived as

a stigma (Ziefle and Schaar, 2011) and is directly

related to ageism—the negative societal framing of

age and aging which is difficult to accept. Moreover,

the combination of old age and chronic disease is

closely related to end-of-life emotions, which are

personality issues the patients are highly sensitive to;

however, these also depend on different coping

strategies, framed by societal and cultural values

(Hamel et al., 2017).

In times of big data and the emerging relevance

of the transportation and storage of medical/health

data, electronic services and medical technology

evolve to an enormous marketing good which

contributes to the gain of knowledge on the one, and

marketing success on the other, hand (Vervier et al.,

2017; van Heek et al., 2018). The decision to share

private medical data is therefore a delicate question

for patients who need to weigh up between sharing

their health-related data (and thereby support the

societal medical gain of knowledge) and hiding their

personal data and thus preserving their privacy and

personal identity (Calero Valdez and Ziefle, under

revision; Ziefle et al., 2016b).

Against this background, the present study is

naturally only one drop in the ocean: Digital

medicine and electronic technologies which are

increasingly supporting people in domestic settings

should perpetuate research on trust, privacy, disease

management and aging and could include the

following important research topics:

1) Understanding the different perspectives of

stakeholders. This topic regards consideration of the

entire caring situation, and the different people and

roles as an integral part of it. So far, research

regarding the trust in medical technology mostly

considers the perspective of patients (e.g., Montague

et al., 2009; Wilkowska and Ziefle, 2011,

Wilkowska, 2015). However, the perspective of the

caring personnel, be it of the family or the

professionals, also represents an important point of

view which needs to be integrated in the concept of

trust towards medical technology and treatment.

2) Understanding the impact and course of

disease. The openness to trust and accept medical

technology necessarily depends on the health status.

In addition, it might be essential to consider different

types of disease and etiopathologies. Especially

patients who suffer from chronic and serious

diseases need to cope with the severity of the illness,

the frailness and the end-of-life cognitions in a much

Understanding Trust in Medical Technologies

deeper and complex manner than patients with a

temporary need for medical technology.

3) Understanding age and aging. Over time,

cultures form individual and societal values of

aging. These values change in line with economic,

political and societal changes. Therefore, trust in a

technology that supports caring naturally depends on

the societal framing of the value of aging and the

consideration of life-span developments. A recent

study (Hamel et al., 2017) showed that acceptance

patterns of, and trust in, medical care depend on the

culture and the country, the different trade-offs

between societally acknowledged caring mission of

the very old, as well as the aspect of their life-end

decisions (Bowling et al., 2002).

4) Personality of patients. Trust in the medical

technology does not only depend on the caring

context, the nature of the disease and the patients’

age. The ability to trust is also associated with the

personality and the available coping mechanisms of

the concerned person. This part of the research

agenda therefore addresses the patient’s personality

profiles towards trust and their openness for

technical innovations. Particularly, it should be

worked out whether these personal profiles are quite

stable over the life course, or, are rather changing

with age (Knowles et al., 2017).

ACKNOWLEDGEMENTS

The authors thank all participants for their patience

and openness to share opinions on trust in medical

technology. This work has been funded by

Excellence Initiative of Germany’s Federal Ministry

of Education and Research and the German

Research Foundation.

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