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Contextual Design of a Motivated Medication Management Device

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DOI: 10.1177/1064804613508950
Many older adults find that they must manage one or more chronic illnesses entailing multiple medication regimens. These regimens can be daunting, with consequences for medication adherence and health outcomes. To promote adherence to medication regimens, we used contextual design to develop paper and digital prototypes of a medication management device. The design focused on enhancing users' motivation to adhere to medication therapy. Our design process and outcome suggest that contextual design might serve as an effective data-driven method that can account for the less tangible aspects of work activities, such as motivation.
ergonomics in design | January 2014
Contextual Design of a Motivated
Medication Management Device
Contextual design, real-world
observation by a multidisciplinary
team, a clear product vision, and
paper prototype development
reveal a promising new design.
Many older adults find that
they must manage one or more
chronic illnesses entailing
multiple medication regimens.
These regimens can be
daunting, with consequences
for medication adherence and
health outcomes. To promote
adherence to medication
regimens, we used contextual
design to develop paper
and digital prototypes of a
medication management
device. The design focused on
enhancing users’ motivation
to adhere to medication
therapy. Our design process
and outcome suggest that
contextual design might serve
as an effective data-driven
method that can account for the
less tangible aspects of work
activities, such as motivation.
product design methods, design
strategies, designing for older
adults, user-centered design,
emotional design, medical/
health products
By Erin Chiou, Vindhya Venkatraman, Kathleen Larson, Yaqiong Li,
Madeleine Gibson, & John D. Lee
Approximately 80% of Americans
age 65 or older manage at least one
chronic illness, and 50% manage at
least two (Centers for Disease Control and
Prevention, 2003; Federal Interagency Forum
on Aging-Related Statistics [FIFA], 2012).
For people living with chronic illnesses,
good health outcomes often depend on
self-management and appropriate use of
medicines. Although some older adults have
caregivers, a significant number live alone and
may need to manage their own medication
regimen. According to estimates from 2010,
19% of men and 37% of women older than
65 live alone (FIFA, 2012).
To address some of the cognitive and
emotional challenges of self-managing
complex medication regimens, our multi-
disciplinary team used contextual design
to develop a medication management tool
inspired by and grounded in real-world
data. Our resulting prototype focused on
improving users’ experiences with medica-
tion management and encouraging users’
adherence to medication therapy.
Many factors influence medication adher-
ence, and increased complexity caused by
multiple illnesses and therapeutic regimens
can lead to nonadherence (Elliot, Ross-
Degnan, Adams, Safran, & Soumerai, 2007;
Murray & Morrow, 2004). Medication
adherence is also affected by patients’ under-
standing of consequences and motivational
factors. Motivation is a complex process
that affects patient behavior in their health-
care activities. Multiple factors have been
predicted to affect motivation, including
locus of control, self-discipline, value placed
on health, socioeconomic factors, self-
esteem, social support, information about
medication, and therapy (Carter & Kulbok,
2002; Vlasnik, Aliotta, & DeLor, 2005). Here
we define motivation as “a force influencing
health behaviors” (Carter & Kulbok, 2002),
recognizing wide applicability of motivation
as a construct.
To aid older adults in their medication
regimens, commercial devices are avail-
able (for examples, see E-Pill Medication
Reminders, 2011). Many of these devices
focus on simplifying medication regimens
and act as reminder systems, which address
several barriers to adherence. However,
these devices often fail to improve long-
term medication adherence (Foo, Chua,
& Ng, 2011). Recent work on medication
self-management suggests that a medication-
dispensing device adaptable to older adults
and the diverse challenges of independent
living could help to address the shortcom-
ings of current medication management
devices (Hernandez, Sommerich, & Woods,
To better understand motivation in
medication management and adherence,
we turned to the actual work of personal
medication management. We used contex-
tual design (see sidebar), a method detailed
in Contextual Design: Defining Customer-
Centered Systems (Beyer & Holtzblatt, 1998),
to uncover artifacts, strategies, cultural influ-
ences, and intents that influence medication
adherence in older adults. On the basis of
our data, we developed a software proto-
type of a medication management device
that incorporates motivational factors to
encourage and support long-term medica-
tion adherence.
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Our design team comprised five engineers with back-
grounds in industrial engineering, electrical and computer
engineering, computer science, mechanical engineering,
and psychology. This diversity supported the goal to include
multiple perspectives and to have cross-functional repre-
sentation on the team. The entire design process, from data
collection to prototype development, occurred within 4
months. We split into groups of two and three to collect
data and reconvened to complete the subsequent design
To collect the data, we employed contextual inquiry, an
interview-like activity based on the master–apprentice frame-
work; designers approach the interview as apprentices and
watch and learn from the user, who is the “master craftsman”
(see sidebar). This approach enabled the design team to
observe medication management as it occurred within older
adults’ daily routines. More important, participants verbalized
their intents at each step, which provided the research team
Figure 1. Pictures showing medication storage areas in participants’ homes.
with valuable insights into the intent and motivation behind
certain tasks.
For contextual inquiry, it is generally suggested that six to
ten people be interviewed for each role in the work practice
(Beyer & Holtzblatt, 1998). We initially recruited six partici-
pants, but two dropped out because of ill health, and time
constraints prevented our recruiting more. We conducted
contextual inquiries with the remaining four participants (two
male and two female), who were residents of a Midwestern
town in the United States. Participants were between 55
and 80 years old; three of them were retired and one was
employed. The participants were recruited on the basis of
their interest in our project, and given their willingness to
discuss their medications and medication routines with us, we
considered them a sample of an older adult population willing
to talk about their medication regimens.
All participants managed their medications at home, so we
traveled there to conduct the contextual inquiries. We took
notes and photos (see Figure 1), audiotaped the conversa-
Contextual design is a user-centered design method that
focuses on the work practice of people (Beyer & Holtzblatt,
1998, p. 21). The method usually involves a design focus
on the development of information systems. A design team
collects data on the user’s work, such as communications
among user teams, artifacts and tools the users use, the
culture of the organization, and the physical and virtual
layout of the workplace. In the master-apprentice
model of inquiry, the user is the master who teaches the
work structure and details to his or her apprentice, the
interviewer. The interviewer learns how to do the work
and observes the ways in which the work is done. These
user-based data are then used to reveal the inherent work
pattern. Understanding the details of work can help
unravel existing problems and guide the redesign of work
Contextual design begins with contextual inquiry
of the work practice. Data analysis is conducted by
building five work models and an affinity diagram
and is followed by visioning. The user data and final
vision are then used to construct storyboards that
describe likely work scenarios and the user environment
design. These then inform the paper prototypes, which
are iteratively tested with the users. The final outcome is a
digital design of a system that supports an improved work
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tions, and sketched the physical space during the interview
sessions. The participants had complicated medication
routines: One had to coordinate health services between two
cities; all the participants were on medications that required
administration roughly three times a day; and between them,
they were taking at least 10 different generic and brand-name
pills, eye drops, and vitamins and other supplements. Our
focus for the contextual inquiry was to understand the moti-
vational aspects and intents behind medication management
and long-term adherence.
After the contextual inquiry, we occupied a design
space to consolidate and interpret the data. In the design
space – which consisted of a large flat-screen monitor, bare
wall space, and a floor-to-ceiling dry-erase board (see Figure
2) – we could easily display the data and immerse ourselves in
a collaborative data review.
We developed work models for each participant’s
medication management practice using data from the
contextual inquiries. Contextual design outlines five work
models (Beyer & Holtzblatt, 1998), each of which captures
one aspect of the work practice:
The flow model describes the roles, responsibilities, and
communication among stakeholders of the work.
The sequence model exposes the order of tasks and
The artifact model illustrates the tools used or modified
during work.
The cultural model depicts the social influences of the
The physical model outlines the visible layout and move-
ment of work.
We created five models per case, a total of 20 work models,
that visualized the work of medication management. Each
model type was then consolidated (e.g., the four sequence
models were consolidated into one sequence model), resulting
in five consolidated models representing our interviews.
Next, we constructed an affinity diagram to organize our
insights from the interviews and work models (see Figure 3).
The affinity diagram “shows the scope of the user problem: it
reveals in one place all the issues, worries, and key elements
of work practice relevant to the team’s focus” (Beyer &
Holtzblatt, 1998, p. 154). We gathered insights that emerged
from contextual inquiry and model building. We then
inductively categorized these insights into common findings.
Using the same inductive process, we grouped these categories
into higher-level categories until we had four levels.
We identified the following major constructs of the work:
empowerment in health and lifestyle,
separation of medication,
strategic placement of memory aids,
need for timely medication information,
coordination between self and care network, and
work environment conditions.
These constructs were central to informing the motivational
aspects of our medication management device. More
important, the affinity diagram reinforced the perspective
that empowerment could be a powerful philosophy to guide
device design that is intended to motivate and support long-
term adherence behavior. For example, our participants
used personalized strategies to maintain health, freedom,
and mobility. They also disliked complicated technology
that disrupted their lives and desired easier access to medical
information and services. To highlight these relationships, we
mapped our work model insights to the motivation findings
(see Table 1).
Building on our findings, we decided our device would
need to serve multiple roles: as an information hub, a
medication organization device, and a household object
Figure 2. Snapshots of the design space during collaborative data review.
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meant for display. Although ease of access to information is
important for self-education and long-term adherence, we felt
that if the device were purely an informational tool, people
would be less motivated to use it. Furthermore, our contextual
inquiries revealed how older adults remind themselves to take
medications in ways that would be inconspicuous to guests –
by placing strategic objects in prominent locations but storing
actual medication out of sight. To echo this strategy, the
device would be aesthetically elegant to warrant public display
but commonplace to avoid announcing one’s health status to
The insights gleaned from our data collection and
analysis informed our next step: developing visions of an
ideal workflow. Our final vision describes a medication
management device that facilitates information exchange
as a predominant motivational factor. This vision was
driven by findings from our flow model, artifact model, and
affinity diagram depicting a need for specific information
from multiple sources. We also found that self-education
and information were particularly important for long-term
motivation, which echoes previous findings showing that
barriers to medication adherence include a lack of medication
knowledge and social support (Foo et al., 2011; Vlasnik
et al., 2005).
The cultural model showed that users’ experiences with
the technology, particularly tentative attitudes of older adults
toward “complicated” technology, must guide the vision for
the medication management device. Thus, we also considered
details such as how the device would notify a user when to
take medication. Our vision is as follows:
The device is attractively designed so the user is
encouraged to place it in a prominent location within
the home, such as the living room or kitchen. When
placed in a visually prominent area, the device serves
as a visual reminder for taking medication. The device
also stores the medications and would dispense them
according to the prescription. The device reminds the
user about medication times by visually glowing and
audibly chiming, and offers comprehensive medication
information in a clear and simple way that supports the
user’s information needs. With these basic functions
implemented in unobtrusive ways, the device is a useful
and engaging object.
As an information resource, the device organizes and
aggregates medication information typically dispersed
through different channels and formats, such as prescription
printouts or Web pages. To eliminate barriers to relevant
medication information, the device organizes these resources
in one easy-to-navigate system. The user can select a medicine
Figure 3. The affinity diagram, outlined by groupings, with up to four levels per group.
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Table 1. Main Insights From Our Consolidated Work Models and Affinity Diagram
Related Motivation
Flow Outlined critical information users would need to achieve their work, such as
pharmacy instructions, dose adjustments (titration), and refill information.
Indicated a complex network of information in prescribing and titrating medi-
cation; to facilitate this process, the device should support information flow
between users and care providers.
Supported the idea that users should have access to medication and therapy
information at any time, which is considered important for building knowl-
edge and understanding and which have been identified as key motivational
factors (Vlasnik, Aliotta, & DeLor, 2005).
Ease of access to
Sequence Captured intents of steps taken in the medication regimen process and
measures that prevent forgetting a dose; potential breakdowns in daily
regimen were mostly attributable to travel or special situations.
Showed that users adapted their medication regimen to their daily routine.
Users visually checked the number or color of pills just before administra-
tion. They also occasionally checked the amount of medication left in the
bottle when they predicted refills were imminent.
Fit to daily routines
Artifact Revealed a persistent medication management tool, the pillbox. These pill-
boxes were used to store and organize pills by time of day, for a week. One
user preferred to store pills in her pillbox by emptying all the pills of one type
into a slot, not by day or time.
Communication from the health system (e.g., the Veterans Health Adminis-
tration) prompted the user to schedule a checkup or order the next shipment
of medication.
Half pills were stored in pill splitters, to be taken in the next dose.
Simple technology, no
Ease of access to
Cultural Users relied more on memory and habits, not technologies, such as
computers or smartphones.
Users did not see themselves as sick and enjoyed living active lives. They felt
empowered by managing their therapies themselves, leading us to follow the
“motivation through empowerment” perspective for the design.
Fit to daily routines
Simple technology,
no disruption
Physical Described where users store and administer medications.
Medications are mostly stored out of sight (e.g., in cupboards), and a week’s
supply is typically transferred to pillboxes.
Medications were also placed near a water source or everyday objects
(e.g., coffee pots) to serve as reminders for taking night or early-morning
medications. These objects were part of an everyday routine, without being
prominent or obvious to outsiders.
Fit to daily routines
by name or image to obtain information on the treatment,
dose, side effects, and specifics of the therapy when taking
that medication. Ease of use helps to maintain the user’s posi-
tive perception of the technology, and usefulness motivates
sustained use.
A prominent feature of the design connects the user to
social support mechanisms while reflecting personal goals
of living an active and independent life. Like a digital photo
frame, the device displays the user’s personal photos on the
home screen to augment the emotional connection between
users and family members separated by distance and to asso-
ciate medication adherence with living a healthier life. Digital
photos have been identified as a means to leverage emotional
connections in older adults and the role photographs play in
people’s lives (Mynatt, Rowan, Jacobs, & Craighill, 2001). In
addition to being a pleasant but commonplace display in the
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home, this feature has the goal of serving to remind the user
of reasons to maintain good health and to motivate the user to
adhere to his or her medication regimen.
When the user is not actively interacting with the device,
the screen loops through a stored set of photos from the
user’s life. When it is time for the user to take medication,
the screen space around the picture glows green. As time
progresses and the user has not dispensed the pills, the lights
turn to yellow and then to red. In such a case, the photo
fades away and reappears when the user resumes the medi-
cation regimen. Audio chimes can also act as reminders,
based on the user’s preference. By connecting the work of
medication management to meaningful goals and relation-
ships, the user receives motivational support for maintaining
good health and associates the device with positive past and
future experiences.
Equipped with a vision, we constructed 10 storyboards
of different medication management work scenarios to
hypothetically test our design. The storyboards, consolidated
models, and affinity diagram were then used to inform our
user environment design (UED). The UED, akin to the user
interface designer’s specification sheet, showed each aspect of
the redesigned work practice and how the work flows from
one function to another. The UED focused on grounding
personal medication management in the intrinsic motivation
of users to lead empowered and healthy lives.
Aspects of medication management span multiple roles
and systems, including different health-care providers, system
developers, and patients. When building our prototype, we
singled out focus areas most relevant to user motivation:
1. Reporting medication storage content and information to
empower the user to self-manage complicated prescription
refill and dosage information.
2. Informing the user of his or her health records and trends.
3. Providing personal, visual medication reminders to subtly
encourage an active, healthy lifestyle.
We excluded some important aspects of medication
management work from our prototype design, including
titration, communication with family or caregivers,
information exchange with providers, and travel. Notably,
all users we interviewed discussed travel or changes to daily
routine as part of their medication management process.
We decided these were special work cases tangential to our
primary goal of designing for fundamental motivation factors
in a daily medication regimen, and that they would be best
addressed in subsequent iterations of the design.
Table 2. Feedback From Prototype Testers Regarding Motivational Features
Feedback Description Integration Rationale
Illuminate the outer portion of the device,
remove explicit warning symbols to prevent
anxiety, and keep photo on screen even during
Yes In line with goal to support a pleasant user experience
and avoid anxiety or alarm fatigue. Facilitates a
positive reinforcement approach to motivation.
Change shape of the popup screen for “Side
Effects” and “More Information.”
Yes Turned into dialogue boxes for clarity. Enhances
usability for older adults, avoiding interface ambiguity
that could lead to frustration and barriers to motivated
Use an avatar (computer agent) to communi-
cate with the user.
No More research would be needed to determine the
effects of avatar features (gender, age, etc.) on user
behavior and motivated use.
Turn the list of medications into individual
Yes Made it clearer to the user that the medication names
could be clicked on for more information. Enhances
usability for older adults, avoiding interface ambiguity
that could lead to frustration and barriers to motivated
Add brief drug, dosage, and timing information
to the time settings screen.
Yes Reduces the number of clicks and avoids reliance on
memory. Enhances usability for older adults, avoiding
navigational ambiguity that could lead to frustration
and barriers to motivated use.
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To test whether our UED described an improved work
process, we used paper prototypes. The paper prototypes
were hand drawn on sheets of paper or “sticky” notes using
colored markers and pencils. They were deliberately “rough”
sketches to communicate to testers that the design is an
unfinished product and to invite feedback and discussion
without overwhelming them with design details. Because the
paper prototypes were pieced together with easy-to-assemble
materials, the design team was able to respond quickly to
impromptu ideas and suggestions.
To broaden the participant pool, we recruited two
prototype testers. The testers differed from the original users
in location (different city), age (at least 10 years younger),
and technology literacy (more exposure to computerized
technology). Both were familiar with the work of medication
management, in that they self-manage their medication
regimens. One of these testers was a nurse who provided a
clinical perspective on the design, and the other tester had
expert experience in human factors/ergonomics design.
Several key features of our resulting digital prototype came
directly from our testers’ feedback on motivational features.
Table 2 shows how their feedback was integrated into the final
The resulting prototype (Figure 4) relied heavily on our
user data. In addition, to support use among older adults
who may have limited dexterity and limited patience with
technology, we avoided swipe actions, kept button design
as unambiguous as possible (e.g., arrow buttons to indicate
direction), and minimized navigation in any direction to
roughly three clicks or less. Each sheet of paper from the
paper prototype represented a page in Adobe Catalyst® CS5.5,
which made translating the paper prototype into digital
format straightforward. Sticky notes translated to popup
Contextual design is an effective method for guiding the
design of a work system centered on information transfer
among multiple parties, such as helping those in information
technology departments to recognize the work practice of the
business and to support cross-department system consistency
in a company (Beyer & Holtzblatt, 1998, pp. 144–145). As
demonstrated in our case, it can also be useful for driving the
discovery of less tangible aspects of work, such as aesthetic,
affective, and motivational features. The features described in
our prototype have not been field tested, but initial feedback
from medical professionals and potential users uninvolved
with the study has been promising.
We attribute some limitations of our study to the small
sample size and our narrowed focus in the UED. We extracted
three focus areas from our UED, which limited aspects of
our prototype. Prior to further development, we recommend
closer analysis of information transfer among pharmacists,
physicians, caregivers, and developers – important aspects of
medication management we set aside in this version of the
In this study of medication management, contextual design
helped us untangle some of the complexity surrounding
personal medication management, appreciate the multiple
parts of the care process, and visualize the difficulties device
designers face given the distributed elements of the U.S.
health-care system. For example, pharmacies may have
electronic information systems for storing patient information
that cannot communicate with other pharmacies’ electronic
information systems. This lack of communication may cause
gaps in information or record keeping, especially if patients
go to more than one pharmacy because of cost, location, or
other incentives. The issues we came across would need to
be addressed by health-care policy or other issues that would
be outside the control of the designer. Success of a device
Figure 4. Paper prototype (left) showing sticky notes as buttons and a popup screen, and the translated digital prototype (right) of the
medication information screen.
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such as ours would need top management support (Beyer
& Holtzblatt, 1998), which in this case may extend beyond
project managers to health-care providers and policy makers.
Beyer, H., & Holtzblatt, K. (1998). Contextual design: Defining customer-
centered systems. San Francisco, CA: Morgan Kaufmann.
Carter, K. F., & Kulbok, P. A. (2002). Motivation for health behaviours: A
systematic review of the nursing literature. Journal of Advanced Nursing,
40, 316–330.
Centers for Disease Control and Prevention. (2003). Public health and aging:
Trends in aging–US and worldwide. Retrieved from
Elliott, R. A., Ross-Degnan, D., Adams, A. S., Safran, D. G., & Soumerai,
S. B. (2007). Strategies for coping in a complex world: Adherence
behavior among older adults with chronic illness. Journal of General
Internal Medicine, 22, 805–810.
E-Pill Medication Reminders. (2011). E-Pill automatic pill dispensers.
Retrieved from
Federal Interagency Forum on Aging-Related Statistics. (2012). Older
Americans 2012: Key indicators of well-being. Washington, DC:
Government Printing Office.
Foo, M., Chua, J. C., & Ng, J. (2011). Enhancing medicine adherence through
multifaceted personalized medicine management. In 2011 IEEE 13th
International Conference on e-Health Networking, Applications and Services
(pp. 262–265). New York, NY: IEEE.
Hernandez, O. K., Sommerich, C. M., & Woods, D. D. (2011). Telepresence as
an aid for medication self-management. Ergonomics in Design, 19(3), 15–23.
Murray, M., & Morrow, D. (2004). A conceptual framework to study
medication adherence in older adults. American Journal of Geriatric
Pharmacotherapy, 2(1), 36–43.
Mynatt, E. D., Rowan, J., Jacobs, A., & Craighill, S. (2001). Digital family
portraits: Supporting peace of mind for extended family members. In CHI
’01 Proceedings of the SIGCHI Conference on Human Factors in Computing
Systems (pp. 333–340). New York, NY: ACM Press.
Vlasnik, J. J., Aliotta, S. L., & Delor, B. (2005). Medication adherence: Factors
influencing compliance with prescribed medication plans. Case Manager,
16(2), 47–51.
Erin Chiou is a PhD student in the Industrial
and Systems Engineering Human Factors
and Ergonomics Program at the University
of Wisconsin-Madison. She received her BS
(psychology, philosophy) from the University
of Illinois at Urbana-Champaign. Her research
interests include trust in technology, health systems,
cooperation, and device design. She may be reached at
Vindhya Venkatraman is a PhD student in the
Cognitive Systems Laboratory, Department of
Industrial and Systems Engineering at the University
of Wisconsin-Madison. She received a BE in 2009
(mechanical engineering) from Anna University-
Madras (India) and an MS in 2011 (mechanical engi-
neering) from the University of Wisconsin-Madison. Her research
centers on information exchange and facilitation between human
users and systems using human–computer collaboration models.
Kathleen Larson is a master’s student in the
Department of Industrial and Systems Engineering
at the University of Wisconsin-Madison, where
she received a BS (electrical engineering). She
is a senior software engineer at ThermoFisher
Scientific in Madison, Wisconsin.
Yaqiong Li is a PhD student in the Department of
Industrial and Systems Engineering and a research
assistant in the Center for Quality and Productivity
Improvement at the University of Wisconsin-
Madison. Her primary research interests are
in human factors and ergonomics, health-care
systems engineering, health-care information technology, and
mixed methods in field research.
Madeleine Gibson is an undergraduate senior
in the Department of Industrial and Systems
Engineering at the University of Wisconsin-
Madison. She works in the Cognitive Systems
Laboratory on research that uses the contextual
design method to understand older adults’ driving
behavior for technology design.
John D. Lee is the Emerson Electric Professor
in the Department of Industrial and Systems
Engineering at the University of Wisconsin-
Madison and director of the Cognitive Systems
Laboratory. He received a BS (mechanical
engineering) and BA (psychology) from Lehigh
University and his MS and PhD (mechanical engineering) from the
University of Illinois at Urbana-Champaign. His research focuses
on safety and acceptance of complex human-machine systems by
considering how technology mediates attention.
This project was partially supported by the Agency for Healthcare
Research and Quality (P50 HS019917) and would not have been
possible without the Center for Health Enhancement Systems
Studies, especially Andrew Isham, Brett Iverson, Fiona McTavish,
and Pat Batemon. We also thank the reviewers for their helpful
Copyright 2013 by Human Factors and Ergonomics Society. All rights reserved.
DOI: 10.1177/1064804613508950
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