Chronically ill patients’ preferences for a financial incentive in a lifestyle intervention. Results of a discrete choice experiment
Chronically ill patients' preferences for a financial incentive in a lifestyle intervention. Results of a discrete choice experiment
Claudia MolemaID 0 1 2 3
Jorien Veldwijk 1 2 3
Wanda Wendel-Vos 1 2 3
Ardine de Wit 1 2 3
Ien van de Goor 0 2 3
Jantine Schuit 1 2 3
0 Tilburg University, Department of Tranzo, Scientific Center for Care and Welfare , Tilburg , the Netherlands
1 National Institute for Public Health and the Environment, Centre for Nutrition, Prevention and Health Services, Bilthoven, the Netherlands, 3 Centre for Research Ethics and Bioethics, Uppsala University , Uppsala , Sweden , 4 University Medical Center Utrecht, Julius Center for Health Sciences and Primary Care, Utrecht, the Netherlands, 5 VU University, Department of Health Science and EMGO institute for Health and Care Research , Amsterdam , the Netherlands
2 Editor: Sukumar Vellakkal , BITS Pilani , INDIA
3 Data Availability Statement: Data may be available upon request due to legal restrictions imposed by the National Institute of Public Health (RIVM) and Tilburg University. Interested researcher may
The preferences of diabetes type 2 patients and cardiovascular disease patients for a
financial incentive added to a specified combined lifestyle intervention were investigated.
A discrete choice experiment questionnaire was filled out by 290 diabetes type 2 patients
(response rate 29.9%). Panel-mixed-logit models were used to estimate the preferences for
a financial incentive. Potential uptake rates of different financial incentives and relative
importance scores of the included attributes were estimated. Included attributes and levels
were: form of the incentive (cash money and different types of vouchers), value of the
incentive (ranging from 15 to 100 euros), moment the incentive is received (start, halfway, after
finishing the intervention) and prerequisite for receiving the incentive (registration,
attendance or results at group or individual level).
Prerequisites for receiving the financial incentive were the most important attribute,
according to the respondents. Potential uptake rates for different financial incentives ranged
between 37.9% and 58.8%. The latter uptake rate was associated with a financial incentive
consisting of cash money with a value of ?100 that is handed out after completing the
lifestyle program with the prerequisite that the participant attended at least 75% of the
schedThe potential uptake of the different financial incentives varied between 37.9% and 58.8%.
The value of the incentive does not significantly influence the potential uptake. However, the
Competing interests: The authors have declared
that no competing interests exist.
Abbreviations: DCE, discrete choice experiment;
HPFI, health promoting financial incentive.
potential uptake and associated potential effect of the financial incentive is influenced by the
type of financial incentive. The preferred type of incentive is ?100 in cash money, awarded
after completing the lifestyle program if the participant attended at least 75% of the
Physical inactivity and a poor diet contribute to the development of a range of chronic diseases
and explain part of the variation in premature mortality [
]. Many people do not meet the
standards for physical activity levels developed by the World Health Organization and are
physically inactive [2, 3]. Patients with diabetes mellitus type 2 or with coronary heart disease
are groups with relatively high prevalence of physical inactivity [
Health care providers seek effective ways to change this unhealthy behavior. One way to do
so is by offering (chronically ill) patients a lifestyle program that includes physical activity and
improving eating behavior, called combined lifestyle interventions (CLIs) [
participation rates in lifestyle programs vary considerably. Some programs have good
participation rates, others struggle with low participation rates. For example, the participation rates of
diabetes mellitus type 2 patients in lifestyle programs, mainly implemented in primary care,
range from 10% to 80% and multiple studies mentioned that boosting the motivation of
participants requires more attention [
Health promoting financial incentives (HPFI) might increase patients? participation rates
and adherence to lifestyle programs and are increasingly implemented by public authorities
and health insurance companies to promote healthy behaviors [
]. However, the
effectiveness of financial incentives added to lifestyle programs in the health care setting for individuals
is still inconclusive [
]. HPFI are cash or cash-like rewards or fines, provided contingent
on (non-) performance of healthy behaviors. The two main categories are positive (e.g. reward
or discount) and negative (e.g. a fine or a higher contribution to the lifestyle program or health
insurance premium) incentives [
]. Within these two categories, the incentive can vary on
different characteristics. For example, they can vary in value, the moment that the participants
receive their incentive (before the intervention or afterwards), conditions that have to be
fulfilled to receive the incentive, and many more characteristics (e.g. provider of the incentive,
lottery system or guaranteed reward). The incentive can be targeted at the participation rate, at
compliance with instructions, or at outcome measures such as a higher physical activity level, a
healthier diet or weight loss.
A financial incentive is an extrinsic motivation. A well-known argument for not using
financial incentives is the crowding-out effect. This refers to the mechanism that extrinsic
motivation in the form of financial incentives might undermine and replace the intrinsic
motivation. However, in the field of health related behavior, so far no evidence has been found to
support this possibility [
]. A plausible explanation is that individuals eligible for a CLI do
not have any intrinsic motivation to change their health behavior. Therefore, intrinsic
motivation cannot be replaced by extrinsic motivation. By adding an extrinsic motivation to start
participating in a CLI, participants may develop intrinsic motivation during the course of the
program, for example because they develop a better physical condition.
To prevent the implementation of an ineffective or even counterproductive HPFI, insight
into the preferences of the target population with regard to the HPFI is of crucial importance.
To date, in the design phase of a new intervention that includes a financial incentive, hardly
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any research (if any) has been performed into the target populations? preferences regarding the
characteristics of the financial incentive. Previous studies do however provide some general
information about preferences regarding incentives. For example, the study by Gneezy et al.
shows that if a financial incentive is not high enough, it might justify or even promote
undesirable behavior [
]. The study by Barte et al. shows that there is a need for more insight into the
effectiveness of the different types and components of a financial incentive and that for
example unconditional financial incentives do not affect physical activity [
One way to determine preferences with regard to HPFI is by performing a Discrete Choice
Experiment (DCE). This is a quantitative technique and a frequently used tool in (public) health
research to estimate possible participation rates in interventions or medical treatments and to
provide knowledge on the components of the programs that determine the participation rates
]. The DCE methodology is based on the Random Utility Theory and assumes that any
intervention or treatment can be described by its characteristics (i.e. attributes, such as the form
of the incentive). In this study, a discrete choice experiment is performed to identify which
financial incentive is preferred by diabetes mellitus type 2 patients to be added to a specific
lifestyle intervention that aims to improve the participant?s physical activity level and eating habits.
Material and methods
This study does not fall under the scope of the Dutch Medical Research Involving Human
Subjects Act (in Dutch; WMO) and therefore did not need to undergo a review by a Medical
Ethical Committee. Since an Institutional Review Board (IRB) approval is only needed when
daily life of participants is influenced or participants should perform specific actions an IRB
approval was not warranted and therefore not obtained. The data were anonymized prior to
the moment that the authors received the data. The authors did not have access to any
identifying information. This DCE was conducted as preparatory part of an intervention study aimed
at evaluating the efficacy and feasibility of a financial incentive added to a lifestyle intervention.
The results of this experiment were used to design the financial incentive that was added to a
lifestyle intervention. The lifestyle intervention aimed to improve the participants? physical
activity behavior and eating habits. This lifestyle intervention was designed for patients at least
18 years of age, with diabetes mellitus type 2 and/or cardiovascular disease, who received
integrated care in the primary care setting in the region of a care group in the southern part of the
Netherlands. In this section, the methods of the DCE are described.
The study population for the DCE was part of the study population of the main project and
was selected based on a geographic area. The area of the care group was divided into four
parts. Three subareas were selected for the intervention study in which the CLI and a financial
incentive would be implemented. One subarea was excluded from the intervention study and
the patients living in this area were invited to fill out the questionnaire. All selected patients
were at least 18 years of age, with diabetes mellitus type 2 and/or cardiovascular disease who
receive integrated care in the primary care setting for their diseases. They received the DCE
questionnaire by conventional mail, with a reminder sent two weeks after the first mailing. As
respondents completed their questionnaire anonymously, no information about
non-responders is available.
Discrete choice experiment
The attributes and levels included in the current study (Table 1) were determined in a stepwise
manner. First, a list of characteristics of financial incentives was compiled, based on available
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The fitness test includes measuring Body Mass Index, body fat percentage, waist circumference, maximum hand
grip strength, maximum leg press and VO2 max.
research literature [
]. This list was discussed in three focus group interviews (eleven
participants in total) to ensure that the most important attributes for the decision-making process
were included. The focus groups consisted of patients with diabetes mellitus type 2 and/or
cardiovascular disease. Since no new attributes were mentioned during the focus groups, the
existing list of potential attributes was sent to a new subsample of patients in a different
geographical location in the northern part of the Netherlands. We believe the patients of this
subsample are comparable to patients in our study as patients in all Dutch care groups receive
similar diabetes care, based on Dutch general practitioners? guidelines. These patients were
asked to rank the attributes from most to least important. In total, 30 individuals filled out the
ranking forms, of which eleven had participated in the focus group interviews. This process
led to the inclusion of four attributes of which one had three levels (moment), two had four
levels (form and value) and one had five levels (prerequisite). The levels were chosen based on
the feasibility in practice. See Table 1 for the levels and attributes that were included in this
Study design. A full factorial design with the identified attributes and levels as described
in Table 1 would test all possible combinations of attributes and levels and would therefore
consist of 240 (3 4 4 5) different scenarios. Due to obvious methodological (bias) and
cognitive (burden on participants) reasons, not all these scenarios were included.
After pilot testing our original orthogonal DCE design, NGene 1.0 (ChoiceMetrics, 2011)
software was used to develop a D-efficient design, which entails a design with an optimal
variance-covariance matrix [
]. The design was restricted because not all combinations of
attribute levels are possible in real life. For example, when the reward is given at the start of the
intervention the only requirement that can be met is registration for the lifestyle program. Our
final design consisted of 18 unique choice tasks. To limit the burden for the respondents,
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NGene divided these 18 choice tasks into two sets of nine choice tasks and each set was
disseminated among half of the study population.
Questionnaire. The questionnaire consisted of two parts (S1 and S2 Files). In the first
section the participant had to fill out 29 questions about age, gender, socioeconomic status,
nationality, physical activity level, eating habits, quality of life (EQ-5D questionnaire; score
between 0 and 1), health literacy [
], and attitude towards lifestyle programs. The second
part of the questionnaire consisted of the actual DCE. Every respondent was presented a series
of choice tasks. These choice tasks consisted of two different financial incentives described by
means of varying levels of the included four attributes (Table 1). In the questionnaire,
definitions for all attributes were specified. Every choice task started with the question: ?Imagine that
your physician recommends that you participate in the lifestyle program as described above.
Which financial incentive would motivate you most to participate in the lifestyle program and to
complete it?? An example of a choice task is shown in Fig 1.
Following each of the nine choice tasks, the participant was asked whether the financial
incentive of their choice would actually motivate them to participate in and finish the lifestyle
program or not (opt-out question). This option was included, because in real life people also
have the option not to participate in the program. After completing the nine choice tasks,
patients had to fill out six questions about their attitude and opinion regarding financial
incentives. Response options were the characteristics of financial incentives in the choice tasks.
Questions were asked about their opinion about using financial incentives, whether they
believe it could motivate them or other people to work on their health, which attribute is most
important in their choice for accepting or declining a financial incentive, and which form and
prerequisites they prefer most.
The questionnaire was pilot tested in the development phase to make sure the target group
was able to fill out the questionnaire as intended. Respondents of the pilot questionnaire
(n = 30) were able to give comments on the choice of words, the length of the questionnaire
and the layout, of the final questionnaire. The respondents did not report any lack of clarity, so
we did not change the text of the questionnaire.
Direct attribute ranking. Before respondents answered the choice tasks, they were asked
by means of a multiple-choice question which characteristic (i.e. attribute) of a financial
incentive they found most important when choosing to accept or decline a financial incentive. The
results of this question are reported as percentages of the respondents who rank a certain
attribute as most important.
Preferences with regard to the incentive. To estimate the preferences of the target
population with regard to a financial incentive, data was analyzed using panel-mixed-logit
(PanelMIXL) models. These models adjust the results for the multilevel structure of the data; every
respondent completed nine choice tasks, therefore their answers may be correlated, which is
accounted for using these analytical models. The following equation was tested using these
U = V + ? = ?0 + ?1 voucher exchangeable in multiple stores + ?2 voucher exchangeable
in multiple restaurants + ?3 voucher for theater- or concert tickets + ?4 value + ?5 after the
lifestyle program + ?6 halfway (50%) and after completing (50%) the lifestyle program + ?7
75% attendance at individual level + ?8 75% attendance at group level + ?9 individual result
fitness test + ?10 group result fitness test + ?
V describes the measurable utility of a specific financial incentive based on the attributes
that were included in the DCE. ?0 represents the alternative specific constant and ?1 - ?10 are
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Fig 1. Example of a choice task.
the attribute level estimates that indicate the relative importance of each attribute. The opt-out
option was modelled as having a utility of zero. Finally, ? describes the unmeasured and
unmeasurable variation in the respondents? preferences.
All non-linear variables are coded using effects coding. In contrast to dummy coding, the
reference category is coded as -1. The coefficient for the reference category is therefore -1
(sum of the ? of the other attribute levels within the same attribute).
Based on the results of the model fit tests (Log Likelihood ratio test and AIC), all attributes
were included as random parameters with a normally distributed standard deviation. By doing
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this, the model accounts for the heterogeneity in respondents? preferences concerning those
Relative importance scores of the attributes. The relative importance scores of the
attributes represent the relative distance of all attributes to the most important attribute on a scale
of 0?1. Since the coding of the data influences the estimates of the model, a new model was
used to calculate the relative importance scores, in which all attribute levels have been coded
similarly (-1 to 1).
The attribute with the highest relative importance score is most decisive in the choice for a
financial incentive. To calculate these relative importance scores, first the difference between
the largest and the smallest attribute level estimate had to be calculated for each attribute. An
importance score of 1 was given to the attribute with the largest difference value. The other
relative importance scores were calculated by dividing the difference values by the largest
difference value, resulting in a relative distance of all attributes to the most important attribute.
Potential uptake of different incentives. The potential uptake of a financial incentive
that consists of a specific set of attributes was estimated. Since all attributes were included as
random parameters in the analyses and their standard deviation had to be taken into account,
simulation was used to calculate the choice probabilities. The mean participation rates of all
simulations (n = 10,000) was estimated by taking the average of all simulated participation rate
probabilities, which were calculated as 1/(1+exp-v).
The questionnaire was sent to 971 individuals and 290 questionnaires were returned in total
(response rate of 29.9%). The mean age of the respondents was 69.4 years (range 38 to 92
years) and 60.4% were male. About half of the participants had a low educational level.
Participants scored their health-related quality of life (EQ-5D) on average with a score of 0.84 for
men and 0.79 for women (overall score of 0.82), while 12.2% of the respondents had an
inadequate health literacy (score 2; self-reported). Almost a quarter of the participants believed
that using financial incentives to motivate people to improve their health would be useful and
42.7% considered it not useful. In total, 16.9% of the respondents reported that a financial
incentive would personally motivate them to improve their health while 64.2% reported that it
would not motivate them (Table 2).
Direct attribute ranking
Most of the respondents (52.5%) reported that the prerequisites for receiving the incentive
were the most important attribute for them, followed by the form of the incentive (22.1%) and
the value of the incentive (14.9%). Finally, the smallest number of respondents (10.5%) marked
the moment of awarding the incentive as the most important attribute (Fig 2).
Preferences with regard to the incentive
Respondents preferred cash money over all other forms of incentives, while a voucher for
theater or concert tickets was the least preferred. The higher the value of the incentive, the more
individuals preferred the incentive. Respondents preferred to receive the incentive after
completing the lifestyle program over receiving it at any other point in time. Finally, respondents
preferred the prerequisite of 75% attendance at individual level over all other prerequisites.
The least preferred prerequisite for receiving the incentive was the group result of the fitness
test (Table 3).
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Respondents? opinion whether a financial incentive would motivate them to improve their health
(n = 254)
Less than ?1000
?1000 to ?2000
?2000 to ?3000
?3000 to ?4000
?4000 to ?5000
?5000 or more
Overall (n = 275)
Men (n = 167)
Women (n = 108)
Health literacy score (range 0?4)
(n = 287)
Inadequate health literacy (n = 287)
Very useful / Useful
Not very useful / Not useful at all
Yes, it would motivate me
No, it would not motivate me
Mean (SD) Percentage
Relative importance scores of the attributes
Respondents reported that a prerequisite for receiving the incentive was the most important
attribute (score 1.00). The moment of receiving the incentive was about half as important
(0.52) and the value of the incentive has the lowest relative importance score. Fig 3 shows the
results in more detail.
Potential uptake of different incentives
Potential uptake rates varied strongly, ranging from 37.9% to 58.8%, based on the
characteristics of the incentive. The financial incentive with the highest potential uptake (58.8%) was cash
money with a value of ?100 that is handed out afterwards with the requirement that the
individual has attended at least 75% of the appointments (Table 4). The incentive with the lowest
potential uptake (37.9%) was a voucher for theater or concert tickets of ?15 that is handed out
at the start with no requirements besides registration for the lifestyle program (Table 4).
We performed a discrete choice experiment to identify which financial incentive should
preferably be added to a combined lifestyle intervention among patients with diabetes type 2. This
study is, to our knowledge, the first to investigate preferences for a financial incentive added to
a lifestyle program.
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Fig 2. Direct attribute ranking.
The most preferred financial incentive resulting in the highest potential uptake based on
this DCE was cash money with a value of ?100, handed out after completing the lifestyle
program with the prerequisite that the participant had attended at least 75% of the appointments.
The prerequisite for receiving the financial incentive was the most important attribute when
patients had to decide whether or not to participate in a lifestyle program with an incentive,
while the monetary value of the incentive had the lowest relative importance score.
The range of the potential uptake of all incentives was between 37.9% and 58.8%. This
range is not very wide, taking into account the great variety of financial incentives that were
examined in this study. Still, these differences in potential uptake do matter in practice, which
makes this study relevant. It is a noticeable finding that the easiest requirement (registering for
the lifestyle program and receiving the incentive at the start of the program) showed quite low
potential uptake percentages (range between 37.9% and 45.4%). The study by Wanders et al.
describes differences in effect size between out-of-pocket costs and financial rewards on the
willingness to participate in a lifestyle program. In contrast to the results of our study, the
study by Wanders et al. showed that a reward with a higher value is not always preferred ,
and that individuals may be offended by the high values of the incentive that were offered. In
our study we used lower values for the incentive than the cut-off point of the study by Wanders
et al., since a higher value than ?100 was not feasible with a view to implementing the incentive
in practice. Overall, the value did not have much impact on the potential uptake of the
incentive (Table 3 & Table 4).
Sixty-two percent of the respondents have a household income between ?1000 and ?3000
per month. According to the OECD, the average household income in the Netherlands is
about ?2100 a month [
]. The average age of the respondents is 69.4 years, implying that
most people are retired and entitled to a state pension and possibly to a supplementary pension
scheme. In this group, it was found that the value of the financial incentive does not influence
the potential uptake to a large extent. We hypothesize that retired individuals might not have
very high costs, such as growing children or a mortgage, and may not need the money. The
prerequisite for the financial incentive might be a more important determinant of their choice,
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because receiving the incentive and appreciating the reward is more justifiable if they have
Our target population consisted of patients with diabetes type 2 and/or cardiovascular
disease. The average age was almost 70 years and half of the study population had a low level of
education. In our study, 12.2% of the respondents had a low health literacy level. According to
a report of the HLS-EU Consortium, about 29% of the Dutch population has an inadequate or
problematic health literacy [
]. This relatively low percentage of individuals with low health
literacy might be the result of selective response, since individuals with low health literacy might
also not understand the questionnaire and therefore not respond. Completing a DCE is quite a
complex task. One strength of our study is that the questionnaire was first pilot tested on
readability and intelligibility, which is recommended in order to obtain valid results [
doing this, we reduced the chance that participants did not understand the final questionnaire.
Furthermore, to limit the burden for the participants we divided the choice sets into two blocks.
There is little knowledge with regard to the response rates for DCE questionnaires. A study
by Watson et al. found that the response rate decreases as the cognitive burden of the
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Fig 3. Relative importance scores of the attributes included in the DCE.
questionnaire increases . The response rate in our DCE was 29.9%, which we believe is
quite good, taking into account the aforementioned characteristics of our target population
and the general complexity of the task. Overall, despite some limitations of the DCE technique,
it is now the most accepted method to identify people?s preferences.
Overall, 64.2% of the respondents reported that a financial incentive would not motivate
them to participate in and complete the lifestyle program. We sent this questionnaire to all
patients with diabetes type 2 that are registered with a regional care group. This population also
includes individuals who are sufficiently active. On the one hand, there might be selective
nonresponse, with these active individuals not completing the questionnaire because they do not
see the point of the program. On the other hand, the individuals who are sufficiently active and
did fill out the questionnaire might not be motivated by receiving a financial incentive. If the
respondents are not motivated by an incentive, does not mean that the wrong attributes were
chosen in this study. The attributes are characteristics of the incentive that influence the choice
for willing or not willing an incentive. We have chosen our attributes with input of our target
population, so the selection of attributes was evidence based. Moreover, our results show a large
heterogeneity in preferences. For example, the constant show that some respondent have a
strong preference for receiving an incentive, whether others have a strong preference for not
receiving an incentive. A similar pattern is seen for the value of the incentive. Some people
attach importance to the value of the incentive, whether others do not. Due to the sample size,
we were not able to specify the analyses, but it is likely that the heterogeneity could be explained
partly by the respondents who state that an incentive would not motivate them.
Although just a small amount of research has been performed on the preferences of the
target population for a financial incentive, it is becoming an increasingly important research area.
Financial incentives may improve the effectiveness of, for example, prevention programs. One
concern is that the implementation of financial incentives might pave the way for patients to
misuse the available resources [
]. This might result in negative opinions and resistance from
the public towards programs that contain financial incentives. In spite of the concerns that
individuals may misuse HPFI, research shows that under certain conditions a HPFI is accepted
more readily by the general public. These conditions are for example that the HPFI has to be
effective and cost-effective and that the HPFI is closely monitored and evaluated [
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PLOS ONE | https://doi.org/10.1371/journal.pone.0219112
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Despite the arguments above, it is still useful to perform research on the preferences for and
effectiveness of financial incentives. Lifestyle interventions can support good short-term
adherence (up to twelve weeks) to exercise programs for chronically ill patients, but long-term
adherence (up to four years) is poor and not well documented [
]. By completing lifestyle
programs that are extended enough to achieve behavioral change, the chance that individuals
will keep exercising in the long term might be higher. New and creative ways have to be found
to increase the adherence of the chronically ill to lifestyle programs. Financial incentives might
form one of these new instruments.
This study contributes to the knowledge of what chronically ill patients rate as more and
less important with regard to financial incentives in lifestyle programs. The results of this DCE
will be used in a study to evaluate the effectiveness of a financial incentive for improving the
health of diabetes patients. By first identifying the preferred financial incentive, the probability
that the financial incentive is effective will be maximized. In a broader perspective, this study
contributes to the knowledge of preferences of individuals with regard to financial incentives.
Among potential participants for a specified lifestyle program for the chronically ill, the most
preferred financial incentive is cash money with a value of ?100 that is handed out after the
lifestyle program is finished with the prerequisite that the participant has attended at least 75%
of the appointments. The potential uptake of the different financial incentives included in this
DCE varied from 37.9% up to 58.8%. The value of the incentive did not significantly influence
the potential uptake. However, the potential uptake and associated potential effect of the
financial incentive is influenced by the type of financial incentive.
S1 File. Questionnaire translated in English.
S2 File. Original questionnaire in Dutch.
We would like to thank care group Syntein for their efforts in the distribution of the
Conceptualization: Claudia Molema.
Data curation: Claudia Molema.
Formal analysis: Claudia Molema, Jorien Veldwijk.
Funding acquisition: Wanda Wendel-Vos, Ardine de Wit, Ien van de Goor, Jantine Schuit.
Investigation: Claudia Molema.
Methodology: Jorien Veldwijk, Ardine de Wit.
Supervision: Wanda Wendel-Vos, Ien van de Goor, Jantine Schuit.
Writing ? original draft: Claudia Molema.
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Writing ? review & editing: Claudia Molema, Jorien Veldwijk, Wanda Wendel-Vos, Ardine
de Wit, Ien van de Goor, Jantine Schuit.
14 / 15
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