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Health policy 130 (2023) 104751
Available online 14 February 2023
0168-8510/© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-
nc-nd/4.0/).
Caregivers’ willingness to pay for digital support services:
Comparative survey
Alhassan Yosri Ibrahim Hassan, BEng, MSc, MPH, Ph.D.
a
,
b
,
*
, Marco Cucculelli
b
,
Giovanni Lamura
a
a
INRCA IRCCS - National Institute of Health and Science on Ageing, Centre for Socio-Economic Research on Ageing, Ancona, Italy
b
Department of Economics and Social Sciences, Faculty of Economics “Giorgio Fu`
a”, Marche Polytechnic University, Ancona, Italy
ARTICLE INFO
Keywords:
Health economics
Health policy
Willingness to pay
Digital health
Home care
Informal caregivers
Digital technologies
Family caregivers
Patients
Digital support
Health information
Informatics
COVID-19
Pandemic
ICT
eHealth
Public health
ABSTRACT
Background: Considering the substantial information needs experienced by informal caregivers, the increased
availability of digital support services for caregivers as well as the potential they offer, further understanding of
caregivers’ willingness to pay for digital support services is needed.
Objective: The aim of this study is to identify associations between informal caregiver’s characteristics and their
willingness to pay for digital support services in two countries: Italy and Sweden.
Methods: A sample of 378 respondents participated in a cross-sectional survey. Respondents were recruited by the
Italian National Institute of Health and Science on Ageing and the Swedish Family Care Competence Centre. A
two-part regression model was used. In the rst part, logistic regression analysis was applied to investigate the
association between willingness to pay and sets of independent variables (caregiver’s demographics, caregiver’s
socioeconomic resources and caregiving context). In the second part, a generalized linear model (log-link and
gamma distribution) was applied to determine the adjusted mean willingness to pay.
Results: More than half of the participants from both countries of our study were willing to pay out of pocket for
digital support services. A recommendation by a healthcare professional was the top factor that may motivate
caregivers’ willingness to pay an additional amount for a paid version of a digital support service. In both
countries, the majority of the respondents believe that the government should allocate more funds for digital
support services and for improving digital infrastructures. Caregiver’ s gender, care recipient relationship to the
caregiver, care duration, the total household income and the amount spent per month on professional caregiving
services are all associated with willingness to pay. For every additional 10 Euro increase in the amount spent per
month on professional caregiving services, the odds of willingness to pay an additional Euro for a digital support
service increased by 0.60 % in the Italian sample (p=0.002, 95% CI: 1.002, 1.009) and 0.31% in the Swedish
sample (p=0.015, 95% CI: 1.006, 1.057).
Conclusions: Factors such as demographics, socioeconomic resources and the caregiving context may play a role
in caregivers’ willingness to pay for digital support services. The digital and social divide may negatively affect
caregivers’ willingness to pay for digital support services. Policy makers and insurance providers should consider
innovative policies to fund digital support services that have been shown to be effective at supporting and
improving caregivers’ health outcomes via subsidies or other incentives. Future research that evaluates the cost-
effectiveness of digital support services is needed in a context of a growing number of informal caregivers and
ever scarcer resources.
1. Introduction
Informal caregivers are relatives, friends, and neighbors who, on a
voluntary basis, care for older adults but are not trained or paid to
provide care contrary to formal caregivers, who offer paid professional
services [1,2]. In Europe, 80% of all care is provided by informal
Abbreviations: WTP, Willingness to pay; ICT, Information and communications technology.
* Corresponding author at: INRCA IRCCS - National Institute of Health and Science on Ageing, Centre for Socio-Economic Research on Ageing, Via Santa Mar-
gherita, 5, 60124, Ancona, Italy.
E-mail addresses: hassanyousri@hotmail.com, a.y.i.hassan@pm.univpm.it (A.Y.I. Hassan).
Contents lists available at ScienceDirect
Health policy
journal homepage: www.elsevier.com/locate/healthpol
https://doi.org/10.1016/j.healthpol.2023.104751
Received 21 April 2022; Received in revised form 24 January 2023; Accepted 10 February 2023
Health policy 130 (2023) 104751
2
caregivers who are often females, either providing care to a spouse,
parent or parent-in-law, and a large share is provided by individuals who
are older than standard retirement age [3–5]. Estimates on the economic
value of unpaid informal care in the European Union (EU) Member
States range from 50% to 90% of the overall costs of formal long-term
care provision [5]. The available estimates of the number of informal
caregivers ranges from 10% up to 25% of the total population in Europe
[6]. In 2013, the estimated economic value of unpaid informal care in
the United States was $470 billion [7]. Informal caregivers save Cana-
da’s health care system between $24 and $31 billion annually [8].
Caregivers often experience high levels of need for information and
services. New technologies are being developed for informal caregivers
and these tools may well offer benets to many of them. Available
literature points to the importance of novel technology solutions as a
promising approach for empowering and supporting informal caregivers
[9–11]. Digital support services for informal caregivers are services
provided by any private or public organization that address caregivers
and/or care recipients’ needs through technological devices that are
integrated or not into a wider intervention program [12]. Digital support
services may provide informal caregivers with remote access to infor-
mation and training about care and caring-related issues through web-
sites, mobile applications, and online training materials [13]. These
solutions may contribute to a more positive caregiving experience and
may help to strengthen informal caregivers’ sense of social inclusion and
belonging [14]. Digital support services also have macro-level benets
as these solutions may help in the integration of informal and formal
care through better care coordination and a reduction in unnecessary
hospitalizations and lengths of stay [11–15]. Consequently, the
deployment of these solutions may generate savings and contribute to
the sustainability of care systems [11–15].
For digital support services to become part of care systems, it is
necessary to understand their affordability and perceived value by
caregivers [16–23]. Considering the substantial information needs
experienced by informal caregivers, the increased availability of digital
support services for caregivers as well as the potential they offer, further
understanding of caregivers’ willingness to pay for digital support ser-
vices is needed. Economic evaluation is a health economics tool used to
support informed decisions in healthcare budget allocation and reim-
bursement of healthcare interventions [24]. Willingness to pay, based
on contingent valuation methodology, represents a key tool that can
inform policy makers as to the affordability and the value of an inter-
vention as perceived by end users [18–28]. The contingent valuation
method is a widely used technique within the economic evaluation
framework to draw out a monetary estimate for the perceived value of a
service with no market value [29]. In contingent valuation studies,
participants are asked to consider a scenario for a hypothetical service
and state the maximum amount they would pay for this given service
[30]. Existing literature showed that individuals’ demographic and so-
cioeconomic characteristics have an impact on willingness to pay values
[18–34]. These factors may also include consumers’ attitudes about who
is responsible for the payment. In healthcare, consumers may feel that
digital health technologies are entitlements and, therefore, the govern-
ment and not the individual consumer, are the appropriate payers
[19–23].
While informal caregivers have been identied as a population group
which could benet from the provision of digital support services, there
is limited specic data on how factors such as demographics, socio-
economic resources and the caregiving context may inuence care-
givers’ willingness to pay for digital support services. In the literature,
very few studies exclusively focus on caregivers’ willingness to pay for
digital support services. Mapping the sociodemographic and socioeco-
nomic proles of informal caregivers who are willing to pay and those
who are not willing to pay for digital support services could help
improve the quality of these services available to them. The aim of this
study is therefore to identify associations between informal caregiver’s
characteristics and their willingness to pay for digital support services in
two countries: Italy and Sweden. Italy and Sweden represent two Eu-
ropean extremes with respect to several dimensions. These include:
familistic/universalistic orientation of care system (Italy: family-based,
Sweden: universal); the level of overall digital skills (low in Italy:
42%, high in Sweden: 72%); and that of Internet use for health
information-seeking (low in Italy: 35%, high in Sweden: 62%) [35–38].
However, both Italy and Sweden are high income countries and repre-
sent two of the oldest populations in Europe [39,40]. They also report an
almost similar, high life expectancy at birth, estimated at 83 and 82
years for Italy and Sweden, respectively [39,40]. Estimates on the
prevalence of informal care in Italy ranges from 14% up to 26% of the
country’s population [41]. In Sweden, it is estimated that 18% of the
18+population provides informal care on a regular basis, corresponding
to over 1.3 million people overall [42]. Exploring informal caregivers’
willingness to pay for digital support services in these two countries
could inform future reforms of the healthcare systems, provide guidance
to the decision makers on the affordability of these services as perceived
by caregivers and boost caregivers’ access to information, services and
support via new technologies in accordance to their needs.
2. Methods
2.1. Study design
This study followed a cross-sectional online survey design to identify
associations among informal caregiver’s characteristics and their will-
ingness to pay for digital support services in two countries: Italy and
Sweden. The data presented here were collected as part of a project that
aimed to evaluate technology-based support services for informal care-
givers. The data were collected through the support of a partnership of
different stakeholders belonging to the Eurocarers’ network (European
Association Working for Carers). They represent national level caregiver
organizations as well as research centers working on these topics, such
as the Centre for Socio-Economic Research on Ageing of INRCA IRCCS
(Italy’s National Institute of Health and Science on Ageing), the Swedish
Family Care Competence Centre, the University Medical Center Gro-
ningen (Netherlands), and Marche Polytechnic University (Italy).
2.2. Survey administration
The sample was identied from the registries of the Italian National
Institute of Health and Science on Ageing and the Swedish Family Care
Competence Centre. The online survey link was disseminated from
November 2020 till April 2021 through the different communication
channels of the Italian National Institute of Health and Science on
Ageing and the Swedish Family Care Competence Centre. Study par-
ticipants were included provided they were:
•informal caregivers of dependent adult individuals living at home.
•18 years old and above.
•and either resident in Italy and able to understand Italian (for par-
ticipants answering the Italian version of the questionnaire), or
resident in Sweden and able to understand Swedish (for participants
answering the Swedish version of the questionnaire).
Exclusion criteria were as follows:
•informal caregivers of pediatric patients.
•professional or paid caregivers.
The study sample included respondents who classied themselves as
informal caregivers based on the survey question: “Do you provide un-
paid care at home to an adult relative, neighbor or friend to help them
take care of themselves?”. Participants were asked to answer this
question with “yes” or “no,” and if they answered “yes,” then they were
asked to continue with the questionnaire. A unique identication
A.Y.I. Hassan et al.
Health policy 130 (2023) 104751
3
number was provided to each participant and stored together with the
survey results, to eliminate duplicate entries. The participants were
given the option to save their responses and return to complete the
survey, or they could edit or clear the replies and initiate the survey
another time. Data was recorded in the system using a password-
protected data extraction form.
2.3. Variables and measurement
Guided by Wilson’s model of information-seeking behavior [43], the
previous survey on services for supporting family carers of older
dependent people in Europe “EUROFAMCARE” [44], and empirical
evidence in the literature [18–34,45–56], this study included the
following sets of independent variables: caregiver’s demographics;
caregiver’s socioeconomic resources; caregiving context and caregiver’s
use of digital support service. The dependent variable in this study is
informal caregivers’ willingness to pay for digital support services. In
accordance with contingent valuation studies, we provided a scenario to
our participants for a hypothetical digital service such as a website /
mobile application that may provide them with remote access to infor-
mation and training about care and caring-related issues. Caregivers
were asked the following willingness to pay question: “Assume that there
is a service that addresses some of your needs as a caregiver and/or your care
recipient’s needs through digital technology. This digital technology solution
may provide you with remote online access to information and training about
caring-related issues. Would you be willing to pay for this digital support
service? If the answer is yes, what is the highest amount you would be willing
to pay each month out of your own pocket for this digital support service?”
Three demographic measures were included: caregiver’s age, care-
giver’s gender, and caregiver’s health status. Ages were measured in
chronological years. Gender was measured nominally and was grouped
into male and female. Caregiver’s health status was grouped into poor,
fair and good. Measures of social and economic circumstances were the
caregiver’s educational attainment and their total household income.
Educational attainment was grouped into primary, secondary, bache-
lor’s degree and higher than bachelor’s degree. Income was assessed by
asking the caregiver about their “monthly household net income from all
sources’’. In order to enhance the cross-national comparability of results
between the two countries involved in this study, Italy and Sweden, we
referred to the ofcial gures from the European Commission’s Euro-
pean statistical system “Eurostat” and applied the European central
bank’s exchange reference average rate for the period of the study
1
[38].
Caregiving context was assessed using the following variables:
monthly expenses for external/professional caregiving services, re-
ported number of weekly hours of care provided to the care recipient;
reported number of years spent providing care; age and gender of the
care recipient; relationship between the care recipient and the caregiver;
and the level of dependency of the care recipient. Monthly expenses for
external/professional caregiving services were assessed by asking the
caregiver about their “monthly expenses for external/professional care-
giving services? for example, out-of-pocket care costs”. Responses con-
cerning the average number of weekly hours of caregiving have been
grouped into four categories: 1) 10 hours or less, 2) 11 to 20 hours, 3) 21
to 40 hours and 4) more than 40 hours. Care duration was measured on
the basis of the caregiver’s reported length of care provision to the care
recipient (in number of years), and respondents were classied into two
groups: those caring for two years or less; and those caring for a longer
time. The age of the care recipient was reported in chronological years.
The gender of care recipients was grouped into male and female. Care-
givers were requested to provide information about the person whom
they care for, in order to assess the relationship with the care recipient
(e.g., parents / parents-in-law, spouse/partner, friend/neighbor, child or
other relative). The level of dependency of the care recipient on the
caregiver was clustered in 2 groups: high dependency and low de-
pendency. In the survey, caregivers were asked to report how frequently
they are using digital support services. Those using the Internet at least
once per week to access digital support services were classied as
“frequent users”, while those accessing it less often were classied as
“infrequent users”.
2.4. Data analysis
The data analysis was conducted in three stages. It began with uni-
variate analyses including percentages to describe the characteristics of
this sample of caregivers. At the second stage, the relationship between
the outcome variable and the independent variables was examined using
Pearson’s chi-squared test with Yates’ continuity correction. Contin-
gency tables have been assessed, before proceeding to logistic regres-
sion, to ensure there were no cells with expected frequencies of fewer
than 5 to prevent biased estimates [57].
At the last stage, a two-part regression model was used to investigate
the association between willingness to pay and the independent vari-
ables and to determine the adjusted mean willingness to pay. In the rst
part, logistic regression analysis was used to establish the ability of each
variable to predict caregivers’ willingness to pay for digital support
services while controlling the effects of other variables. Variables
identied as statistically signicant in the bivariate analysis were
entered into logistic regression analysis for each measure of willingness
to pay for digital support services. The logistic regression analyses
produced odds ratios with 95% condence intervals to identify pre-
dictors of each measure. Results are reported in odds ratios, which can
be interpreted as the ratio of the probability that caregivers with a
particular characteristic (e.g., male gender) will be willing to pay for
digital support services, over the probability they will be willing to pay
for digital support services, had they not this characteristic. Odds ratios
that are higher than 1 indicate a positive association between a given
variable and willingness to pay for digital support services, while an
odds ratio lower than 1 indicates a negative association. In the second
part, a generalized linear model (log-link and gamma distribution) was
used in which the outcome represented the amount a caregiver was
willing to pay for digital support services. As described in the literature
[58,59], healthcare cost data have some unique characteristics that have
consequences for statistical modeling. The amount of willingness to pay
for healthcare support services tends to be skewed to the right, with a
large portion of observations having low expenditures but a fraction
having very large expenditures [58,59]. Considering these unique
characteristics and testing the functional form of candidate models, a
generalized linear model (log-link and gamma distribution) has been
used where the domain is restricted to only positive continuous
numbers. Statistical analyses were performed using SPSS software
version 28.0 (IBM, Armonk, NY, USA).
2.5. Ethics approval and informed consent
Permission to conduct the study was granted by the ethics committee
of the faculty of economics, Marche Polytechnic University and was
approved by the executive board on November 2, 2020 (1026353).
Informal caregivers expressing interest in participating in the study were
informed about the aim of the study, the expected time to complete the
questionnaire, and that data would be stored by the Centre for Socio-
Economic Research on Ageing of the Italian National Institute of
Health and Science on Ageing. The technical functionality of the online
questionnaire had been tested before elding the questionnaire. The
estimate time for survey completion was 10-15 minutes. Informed
consent was obtained from all participants. No personal information
about the participants such as their name or their IP address were
collected. All the responses were anonymous.
1
The exchange rate applied was 1 Euro =10.1546 Swedish Krona.
A.Y.I. Hassan et al.
Health policy 130 (2023) 104751
4
3. Results
3.1. Sample description
A total of 378 informal caregivers, 219 from Italy and 159 from
Sweden, participated in the survey by completing the online question-
naire. Table 1 presents the overall characteristics of the sample. Females
represented a majority of respondents in the Italian group. The median
age of caregivers was 54 years while the median age of care recipients
was 73 years. Most Italian participants were providing care to a parent
(n =82, 37.4%), to a female care recipient (n=126, 57.5%), spent more
than 40 hours per week providing care (n=78, 35.6%) and had
completed secondary school or lower (n =136, 62.1%). Nearly half of
the participants (n=111, 50.7%) had an annual household income of
less than 19658 Euro. The big majority of caregivers in the Italian
sample (n=177, 80.8%) reported a fair or poor health status, provided
care to a highly dependent care recipient (n=176, 80.4%) and had been
providing care for more than 2 years (n=149, 68%) (Table 1).
When compared to their Italian counterparts, Swedish participants
had a higher median age of 60 and their care recipients had a similar
median age of 73 years. Females made up a majority of participants in
the Swedish sample. Most of the Swedish respondents reported
providing care to a spouse/partner (n=56, 35.2%), a male care recipient
(n=81, 50.9%), spent less than 10 hours per week providing care (n=69,
43.4%) and had completed a secondary school or lower (n =89, 56%).
Nearly half of the participants in the Swedish group (n=77, 48.4%) had
annual household incomes less than 26826 Euro. The majority of the
caregivers in the Swedish sample (n=129, 81.1%) had a fair or poor
health status, were caring for a highly dependent care recipient (n=83,
52.2%) and had been providing care for more than 2 years (n=93,
58.5%) (Table 1).
3.2. Unadjusted and adjusted caregivers’ willingness to pay per month for
digital support services
Among the Italian participants, 71.7% (157) indicated their will-
ingness to pay for digital support services. In this group of Italian par-
ticipants who indicated their willingness to pay, the mean unadjusted
caregivers’ willingness to pay per month for digital support services was
69.78 Euro. The mean adjusted caregivers’ willingness to pay per month
for digital support services obtained from the two-part model was 53.60
Euro (95% CI: 42.45, 67.68). In the Swedish sample, 60.4% (96) of the
participants reported that they are willing to pay for digital support
services. The mean unadjusted caregivers’ willingness to pay per month
for digital support services was 34.78 Euro. The mean adjusted care-
givers’ willingness to pay per month for digital support services obtained
from the two-part model was 29.57 Euro (95% CI: 22.22, 39.34).
2
3.3. Predictors of caregivers’ willingness to pay for digital support services
Table 2 summarizes the results of the logistic regression analysis
predicting caregivers’ willingness to pay for digital support services. For
the Italian sample, seven variables signicantly associated with will-
ingness to pay for digital support services in the bivariate analysis were
entered into logistic regression analysis to identify which were predic-
tive: caregiver’s gender, total household income, care recipient rela-
tionship to the caregiver, the level of dependency of the care recipient,
care duration, frequency of using digital support services and the
amount spent per month on professional caregiving services. The
multivariate analysis indicated that caregiver’s gender, care recipient
relationship to the caregiver, care duration and the total household in-
come remained signicant predictors. Male caregivers had 3.185 times
the odds of willingness to pay for digital support services compared to
female caregivers (p=0.007, 95%CI: 0.135-0.734). Caregivers who
spent up to two years providing care were almost 3 times more likely to
be willing to pay for digital support services in comparison with those
who spent more than two years providing care. Total household income
was a predictive factor; for every additional 10 Euro increase in the
monthly income, the odds of willingness to pay increased by 0.4% (p =
0.009, 95% CI: 1.001, 1.008). Regarding the relationship between the
caregiver and care recipient, caregivers providing care to parents /
parents-in-law had 4.464 times the odds of willingness to pay for digital
support services compared to those who provide care to a friend /
neighbor (p =0.017, 95% CI: 0.065-0.766). The logistic regression
analysis to predict the willingness to pay for digital support services
among Swedish participants consisted of the seven statistically signi-
cant factors identied in the bivariate analysis: caregiver’s age, health
status, number of hours providing care per week, care duration, fre-
quency of using digital support services, household income, amount
spent per month on professional caregiving service (Table 2). Care
duration remained a signicant predictor in the multivariate analysis for
the Swedish sample. Swedish respondents who spent up to two years
Table 1
Characteristics of the sample (total sample N =378).
Variables Italian sample n =
219
% (n)
Swedish sample n =
159
% (n)
Gender
Male
Female
27.9 (61)
72.1 (158)
28.9 (46)
71.1 (113)
Age
Median
54 60
Health Status
Good
Fair
Poor
19.2 (42)
41.1 (90)
39.7 (87)
22.6 (36)
58.5 (93)
18.9 (30)
Education
Primary
Secondary
Bachelor
Higher than bachelor’s degree
9.1 (20)
53.0 (116)
25.6 (56)
12.3 (27)
12.0 (19)
44.0 (70)
24.5 (39)
19.5 (31)
Care recipient relationship to
caregiver
Parents (In law)
Spouse/Partner
Child
Friend/Neighbor
Other
37.4 (82)
14.6 (32)
26.0 (57)
8.2 (18)
13.7 (30)
24.5 (39)
35.2 (56)
23.3 (37)
10.1 (16)
6.9 (11)
Gender of care recipient
Male
Female
42.5 (93)
57.5 (126)
50.9 (81)
49.1 (78)
Age of care recipient
Median 73 73
Level of dependency of the care
recipient
High dependency
Low dependency
80.4 (176)
19.6 (43)
52.2 (83)
47.8 (76)
Hours spend caring each week
10 hours or less
11-20 hours
21-40 hours
More than 40 hours
30.6 (67)
18.3 (40)
15.5 (34)
35.6 (78)
43.4 (69)
27.7 (44)
11.9 (19)
17 (27)
Number of years providing care
2 years or less
More than 2 years
32.0 (70)
68.0 (149)
41.5 (66)
58.5 (93)
2
Using the index of real expenditure per capita in purchasing power stan-
dards [38], we found that the real expenditure per capita in Italy is 8.87% lower
than Sweden. Using a purchasing power parity =13.18 between Sweden and
Italy and a nominal exchange rate of EXCH=10.1546 Krona to the Euro, the
price level index of Sweden would be about 29% higher than in Italy. Despite
signicant, this evidence only marginally affects the main ndings of the paper
which is mainly aimed at studying the inuence of predictors of willingness to
pay in separate samples of Italian and Swedish caregivers.
A.Y.I. Hassan et al.
Health policy 130 (2023) 104751
5
providing care were two times more likely to be willing to pay for digital
support services as opposed to those who spent more than two years
providing care (p =0.047, 95% CI: 0.235-0.991). The amount spent per
month on professional caregiving service also remained a signicant
predictor in the multivariate analysis. For every additional 10 Euro
spent monthly on professional caregiving service, the odds of willing-
ness to pay for digital support services increased by 4.2% (95% CI:
1.004, 1.081). In the second part of the two-part model, when the
dependent variable was the indicated amount of willingness to pay, for
every additional 10 Euro increase in the amount spent per month on
professional caregiving services, the odds of willingness to pay an
additional Euro increased by 0.60 % in the Italian group (p=0.002, 95%
CI: 1.002, 1.009). In the case of the Swedish sample, for every additional
10 Euro increase in the amount spent per month on professional care-
giving services, the odds of willingness to pay an additional Euro
increased by 0.31% (p=0.015, 95% CI: 1.006, 1.057).
3.4. Other factors inuencing caregivers’ willingness to pay for digital
support services
The participants were provided with another hypothetical scenario
where in this scenario the introduced digital support service would be
offered in two different versions: a free version and a paid one. They
were asked to indicate their willingness to pay an additional amount for
the paid version of the support service in each of the following cases: the
paid version is offered without advertisements compared to a free
version with advertisements; the paid version ensures data protection in
line with legislation compared to a free version with no information is
given about data protection; the paid version is recommended by a
healthcare professional; or the paid version is recommended by a care-
givers association. Although most of the participants in both countries
were not willing to pay an additional amount for a paid version, in case
of the availability of a free version of the service, a recommendation by a
healthcare professional was the top factor that may motivate caregivers’
willingness to pay an additional amount for a paid version of a digital
support service. Almost 30 % of the participants, in both groups, indi-
cated their willingness to pay an additional amount for a paid version if
Table 2
Multivariate regression models: caregivers’ willingness to pay for digital support services.
1
st
model
Predictors of willingness to pay for digital support services
2
nd
model
Predictors of the amount of willingness to pay for digital support
services
Italian sample
n =219
Swedish sample
n =159
Italian sample
n =157
Swedish sample
n =96
Variables
[1]
p
Value
OR 95%
CIs
p
Value
OR 95% CIs p
Value
OR 95% CIs p
Value
OR 95%
CIs
Age (in years) -
3
- - 0.505 0.991 0.965-1.017 - - - 0.001 1.040 1.025-
1.055
Health Status (Ref.: Poor)
Fair
Good
0.693
0.181
0.845
2.240
0.366-
1.9490.687-
7.300
0.891
0.853
0.959
1.068
0.529-
1.740
0.532-
2.144
Gender (Ref.: Male)
Female
0.007 0.314 0.135-
0.734
- - - 0.826 0.963 0.688- 1.347 - - -
Income 0.009 1.004 1.001-
1.008
0.163 1.002 0.999-1.004 0.627 1.000 0.999-
1.002
0.950 1.000 0.999-
1.001
Dependency (Ref.: High
dependency)Low
dependency
0.209 0.587 0.256-
1.347
- - - 0.882 1.032 0.678-1.571 - - -
Care recipient
relationship to
caregiver (Ref.: Parents
(In law))
Spouse/Partner
Child
Friend/NeighborOther
0.009
0.579
0.017
.635
0.2531.3000.2241.299 0.091-
0.705
0.515-
3.278
0.065-
0.766
0.442-
3.820
- - - 0.114
0.927
0.018
0.386
0.641
1.018
0.426
0.818
0.369-
1.1130.691
-1.501
0.210-0.864
0.519-1.289
- - -
Amount spent each
month on professional
caregiving services
0.203 1.005 0.997-
1.012
0.030 1.042 1.004-1.081 0.002 1.006 1.002- 1.009 0.015 1.031 1.006-
1.057
Care Duration (Ref.: 2
years or less)
More than 2 years
0.022 0.379 0.165-
0.872
0.047 0.482 0.235-0.991 0.706 0.934 0.656 -1.330 0.322 1.275 0.788
- 2.062
Frequency of accessing
digital support services
(Ref.: Less than once
per week)
Once per week or more
0.130 1.728 0.852-
3.505
0.431 1.359 0.634-2.915 0.786 1.046 0.756-1.448 0.176 0.734 0.469-
1.148
Hours spent caring each
week (Ref.: 20 hours or
less)
More than 20 hours
- - - 0.074 0.484 0.219-1.072 - - - 0.708 1.112 0.638-
1.941
Notes:
(1) Only variables signicantly associated with willingness to pay for digital support services in the bivariate analysis for each country were entered into multivariate
regression analysis
(2) Differences between groups were considered signicant at the 5% level (p ≤0.05)
3
Only variables signicantly associated with willingness to pay for digital support services in the bivariate analysis for each country were entered into multivariate
regression analysis
A.Y.I. Hassan et al.
Health policy 130 (2023) 104751
6
it is recommended by their healthcare professional (Fig. 1).
The participants were then asked whether they believe that the
government should allocate more funds for digital support services that
have proven effective in supporting informal caregivers and addressing
some of the needs of informal caregivers and their care recipients. They
were also asked whether they believe that the government should
allocate more funds for improving digital infrastructure to enhance
informal caregivers’ access to digital support services. As shown in
Figs. 2 and 3, in both countries, the majority of the participants agreed to
both statements although the level of the agreement was higher in the
Italian sample.
4. Discussion
The purpose of this study was to identify inuencing factors related
to caregivers’ willingness to pay for digital support services in Italy and
Sweden. Willingness to pay is one of the major components of the
consumer-based cost benet analysis. In this study, caregivers’ will-
ingness to pay for digital support services was estimated using the
contingent valuation method as a survey-based, hypothetical, and direct
method for elucidating a monetary value of digital health technologies
[60]. The ndings suggest that a number of demographic,
socio-economic and caring circumstances are associated with the will-
ingness to pay for digital support services among caregivers in both
countries. Multivariate regression analyses enabled the effect of con-
founding factors to be controlled for and predictors of willingness to pay
to be identied. In consistency with literature [18–34,45–56], our
ndings indicate that caregiver’s gender, care recipient relationship to
the caregiver, care duration, the total household income and the amount
spent per month on professional caregiving service are all associated
with willingness to pay. Our ndings contribute to a growing consensus
of the value of digital support services for caregivers.
As it is to be expected from given previous research on digital health
technologies [18–34,45–56], the digital divide may negatively affect
caregivers’ willingness to pay for digital support services. The socio-
economic status of users seems to be a signicant factor that increases
the digital divide in Southern European countries [62–64]. This was
apparent in our study, showing that the divide was more signicant in
the case of the Italian group compared to the Swedish one. While none of
the measures of socio-economic resources was signicantly associated
with the willingness to pay for digital support services in the Swedish
group, income was a predictor for willingness to pay in the Italian group.
Informal caregivers from lower socioeconomic backgrounds may be less
able to pay for digital support solutions, which might lead to health
inequality [55]. The literature identies a potential social justice issue if
governments do not value these digital support solutions and a “user--
pays” implementation—a pricing approach based on the idea that the
most efcient allocation of resources occurs when consumers pay the
full cost of the goods that they consume—must be used for digital
support services. In that case, only those who can afford to pay would
have access to these services [55].
Patterns of willingness to pay among caregivers in both countries
also seem to be shaped by the caring experience. Care duration was a
signicant predictor for the willingness to pay for digital support ser-
vices by participants in both countries. Caregivers who spent up to two
years providing care were more likely to be willing to pay for digital
support services in comparison with those who spent more than two
years providing care. Evidence from literature suggests that most care-
givers are open to incorporating technology into their care routine [65].
Nevertheless, digital support services must be offered early in the
caregiving process, and its support functions need to be adaptable over
the course of the caring trajectory. It is important also to foster contin-
uous development of digital competencies in informal caregivers and to
promote digital inclusion policies. Actions that build informal care-
givers’ technical skills early in the caregiving process are important for
optimal use of available digital support services [55].
The study shows that healthcare professional and caregiver organi-
zation recommendations increases caregiver’s willingness to pay for
Fig. 1. Willingness to pay for a paid version of the digital support service.
Fig. 2. The government should allocate more funds for digital support services
- the level of agreement.
Fig. 3. The government should allocate more funds for improving digital
infrastructure - the level of agreement.
A.Y.I. Hassan et al.
Health policy 130 (2023) 104751
7
digital support services. This suggests that the interaction with informal
caregivers by health care professionals and other parties with an interest
in supporting them (e.g., caregiver advocacy organizations) is an inte-
gral part of the value chain that supports both communication and co-
ordination of services. These parties should all be more engaged with
developing digital support services targeted at informal caregivers, and
carefully assess and identify their information and service needs.
More than half of the caregivers in both countries of our study were
willing to pay out of pocket for digital support services. Nevertheless,
they may not be able to afford a high amount to put toward such services
without government subsidies. The average willingness to pay in both
countries reects amounts in the normal range of healthcare co-
payments. In line with previous studies [45–56], our ndings high-
light the importance of funding digital support services as novel solu-
tions that improve the outcomes of informal care for both caregivers and
care recipients. This represents an opportunity for innovative policy that
can help caregivers access digital support services they value but cannot
afford [61]. The majority of the participants in both countries in our
study believe that the government should allocate more funds for digital
support services and for improving digital infrastructures. The level of
agreement was even higher among the Italian participants. This is in line
with previous research showing that caregivers believe that the gov-
ernment should pay half the costs of the technology-based support ser-
vices [21]. Caregivers from Southern European countries with a
family-based care system often lack support in terms of support ser-
vices and professional training from the government [66–68]. This
shortcoming of support may increase their need for information and
services. Previous studies suggested that caregivers from Southern Eu-
ropean countries are showing an increased interest in accessing new
technologies aiming to support them [69–72]. Hence, policy makers and
insurance providers should consider policies to fund digital support
services that have been shown to be effective at supporting and
improving informal caregiver health outcomes via subsidies or other
incentives. In this regard, an identication of sustainable business
models, exchange of good practices, collection of evidence, and a
transferability of optimal solutions among localities, regions, and
countries are all important to continue allocating public funding for
initiatives. Moreover, policy makers should allocate funding for
improving ICT and digital infrastructures in order to facilitate the
deployment of digital support services and improve informal caregivers
access to these services [55].
4.1. Limitations
Some limitations concerning this study warrant discussion. One of
the limitations of this and other studies on willingness to pay is that the
respondents were asked about a hypothetical service. As with contingent
valuation studies, participants responded to the question of the study
prior to having direct experience with the solution that could be offered
by the technology service so its potential benets may remain vague and
unknown. The risk of the typical sampling bias should also be mentioned
as more educated caregivers are more likely to participate in research
studies involving modern technologies, which was the case in our study.
Furthermore, the sample size, especially of the Swedish sample, pre-
vented us from carrying out more sophisticated statistical analyses.
Moreover, not all of those who provide informal caregiving and assis-
tance to others identify themselves as informal caregivers; consequently,
we may have failed to capture the experiences of these underrepresented
groups. Although the most important variables identied from empirical
evidence in the literature were included in the models, residual external
variables may still have inuenced our results. Conclusions drawn from
this study results must be tempered by the fact that respondents were
already possessing minimal digital skills that would enable them to ac-
cess online services. It is possible that those who are not interested or
involved with technology or those with limited digital access are less
likely to respond to online surveys; consequently, the data collected
online might be skewed and the sample might be less representative for
the population. These issues might have inuenced our ndings and
underline the need to interpret the ndings from this study and other
studies on caregivers with some caution when generalizing the ndings.
5. Conclusions
The ndings from this study can provide guidance and assistance for
the deployment of digital support services for informal caregivers.
Nevertheless, due to rapid technological innovation in the healthcare
sector, continuous research needs to be conducted and guidelines for
developing digital support services should be made adaptable to
ongoing and future changes. The care sector is undergoing a fast
transformation and expansion also due to the direct and indirect effects
of the COVID-19 pandemic. Health and social care delivery systems
experience a technologically supported transition towards home care. It
is widely acknowledged that caregivers are a group with high levels of
unmet needs when it comes to their access to information and other
services. New technologies are being developed for informal caregivers
and these tools may well offer benets to many of them. Factors such as
demographics, socioeconomic resources and the caregiving context may
play a role in caregivers’ willingness to pay for digital support services.
Future research that evaluates the cost-effectiveness of digital support
services is needed in a context of a growing number of informal care-
givers and ever scarcer resources.
When it comes to policy and practice in relation to caregivers,
similarly to other broad vulnerable groups, there is no ‘one size ts all’
approach, and it is therefore important to consider the specic charac-
teristics and needs of both caregivers and care recipients. Policy makers,
health care professionals and all parties with an interest in supporting
informal caregivers are encouraged to identify the outcomes that the
latter regard as helpful, and to identify the interventions that can ach-
ieve such outcomes in consultation with them. While digital support
services have the potential to meet some of the needs of the caregivers,
they cannot be seen as the only way to deliver information and support.
These services represent only one of many instruments in a toolbox and
should therefore be tailored in a coordinated way with other existing
services, such as respite care, access to training, and recognition of skills
and work-life balance measures.
Funding and grant number
This research was funded by the European Union’s Horizon 2020
Research and Innovation Program Under the Marie Skłodowska-Curie
grant agreement number 814072 for the 4-year innovative training
network ENTWINE informal care. This research was partially supported
by Ricerca Corrente funding from the Italian Ministry of Health to
IRCCS-INRCA.
Declaration of Competing Interest
None declared.
Contributorship: Alhassan Yosri Ibrahim Hassan developed the
research idea, designed the study, wrote the manuscript and is respon-
sible for the overall content as the guarantor. Marco Cucculelli
contributed to the rationale of the study, was involved in the concep-
tualization of the project and provided critical evaluation and approval
of the nal submitted manuscript. Giovanni Lamura was involved in the
conceptualization of the project and provided critical evaluation and
approval of the nal submitted manuscript.
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