Closed-Loop Glucose Control: Psychological and Behavioral Considerations

Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, Virginia 22908 , USA.
Journal of diabetes science and technology 11/2011; 5(6):1387-95. DOI: 10.1177/193229681100500610
Source: PubMed


Since 2000, the diabetes community has witnessed tremendous technological advances that have revolutionized diabetes management. Currently, closed-loop glucose control (CLC) systems, which link continuous subcutaneous insulin infusion and continuous glucose monitoring, are the newest, cutting edge technology aimed at reducing glycemic variability and improving daily management of diabetes. Although advances in knowledge and technology in the treatment of diabetes have improved exponentially, adherence to diabetes regimens remains complex and often difficult to predict. Human factors, such as patient perceptions and behavioral self-regulation, are central to adherence to prescribed regimens, as well as to adoption and utilization of diabetes technology, and they will continue to be crucial as diabetes management evolves. Thus, the aims of this article are three-fold: (1) to review psychological and behavioral factors that have influenced adoption and utilization of past technologies, (2) to examine three theoretical frameworks that may help in conceptualizing relevant patient factors in diabetes management, and (3) to propose patient-selection factors that will likely affect future CLC systems.


Available from: Jaclyn A. Shepard, Sep 07, 2015
Closed-Loop Glucose Control:
Psychological and Behavioral Considerations
Linda Gonder-Frederick, Ph.D.,
Jaclyn Shepard, Psy.D.,
and Ninoska Peterson, Ph.D.
Author Aliation:
Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, Virginia
Abbreviations: (AADE) American Association of Diabetes Educators, (BG) blood glucose, (CGM) continuous glucose monitoring,
(CLC) closed-loop control, (CSII) continuous subcutaneous insulin infusion, (DIT) diusion of technology theory, (HbA1c) hemoglobin A1c,
(HBM) Health Belief Model, (JDRF) Juvenile Diabetes Research Foundation, (MDI) multiple daily injections, (SAP) sensor-augmented pump,
(STAR) Sensor-Augmented Pump Therapy for A1c Reduction, (T1DM) type 1 diabetes mellitus, T2DM) type 2 diabetes mellitus, (TPB) theory of
planned behavior
Keywords: adoption and utilization, articial pancreas, behavioral factors, closed loop glucose control, diabetes technology
Corresponding Author: Linda Gonder-Frederick, Ph.D., PO Box 800223, Behavioral Medicine Center, University of Virginia, Charlottesville,
Virginia 22908; email address
Journal of Diabetes Science and Technology
Volume 5, Issue 6, November 2011
© Diabetes Technology Society
Since 2000, the diabetes community has witnessed tremendous technological advances that have revolutionized
diabetes management. Currently, closed-loop glucose control (CLC) systems, which link continuous
subcutaneous insulin infusion and continuous glucose monitoring, are the newest, cutting edge technology
aimed at reducing glycemic variability and improving daily management of diabetes. Although advances in
knowledge and technology in the treatment of diabetes have improved exponentially, adherence to diabetes
regimens remains complex and often dicult to predict. Human factors, such as patient perceptions and
behavioral self-regulation, are central to adherence to prescribed regimens, as well as to adoption and
utilization of diabetes technology, and they will continue to be crucial as diabetes management evolves. Thus,
the aims of this article are three-fold: (1) to review psychological and behavioral factors that have inuenced
adoption and utilization of past technologies, (2) to examine three theoretical frameworks that may help in
conceptualizing relevant patient factors in diabetes management, and (3) to propose patient-selection factors
that will likely aect future CLC systems.
J Diabetes Sci Technol 2011;5(6):1387-1395
Since 2000, technological advances in continuous
subcutaneous insulin infusion (CSII) and continuous
glucose monitoring (CGM) devices have produced a
dramatic paradigm shift for future diabetes management.
Development of closed-loop glucose control (CLC) systems,
or the articial pancreas, is now considered a feasible goal.
Currently, development of CLC systems is the focus of
several research projects around the globe, and several
prototypes have undergone successful initial testing.
As diabetes management moves toward the development
and integration of these new technologies, it is important
to begin to consider the psychological and behavioral
factors likely to play a signicant role in the use of CLC
systems. With the advent of technological advances, it
is often easy to underestimate the central role human
factors will continue to play in diabetes management.
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Closed-Loop Glucose Control: Psychological and Behavioral Considerations Gonder-Frederick
J Diabetes Sci Technol Vol 5, Issue 6, November 2011
The purpose of this article is to review and explore some
of the psychological and behavioral factors that are likely
to signicantly inuence patient adoption and utilization
of future CLC systems.
Most research into CLC systems has been aimed at system
development and renement and demonstration of safety
and ecacy. Only a few studies have considered patient
reactions, or expected reactions, to the use of these
emerging systems. However, there is existing research on
patient adoption and use of CSII and CGM, two essential
components of any CLC system, which may provide
insight into human factors likely to be important for
upcoming diabetes technology. There is also a small but
growing literature on patient use of the newly-developed
sensor-augmented pump (SAP) therapy, the rst step
toward integrated use of CSII and CGM, which may
also provide useful information. The review of studies
of these existing technologies will focus on ndings that
have relevance to patient selection and training for CLC
use, predicting barriers likely to interfere with optimal
use and therapeutic benets from this technology, and
developing the type of patient support systems needed
for long-term success. In addition, this article will review
several theoretical frameworks for exploring those
psychological and behavioral processes that are likely
to inuence patient adoption and use of CLC systems.
These include the Health Belief Model, theory of planned
behavior, and diusion of innovation theory, each of
which can serve as a useful guide to identifying and
understanding human and social factors important to
diabetes technology dissemination and utilization.
Before this scientic and theoretical review, however, we
begin by looking at two recent surveys of patient attitudes
about CLC systems.
Patient Interest in and Acceptance of CLC
Two studies investigating interest in and acceptance of
CLC have yielded encouraging ndings, demonstrating
a very high level of enthusiasm on the part of patients
and family members. In the rst study,
parents of children
with type 1 diabetes mellitus (T1DM) using CSII were
surveyed concerning their attitudes toward overnight
CLC systems. The overwhelming majority believed that
they could use these systems with condence, with
most parents reporting that they would trust the system
to deliver the correct insulin dose and would not be
worried about their childs overnight insulin being
controlled by a computer. However, only 19 parents
participated in this survey and none of the families had
used CGM before. The second study
surveyed 132 adults
with T1DM who used CSII on their attitudes toward the
articial pancreas. Patients completed a questionnaire
based on the Technology Acceptance Model that denes
acceptance as the individual’s perceptions of a new
technology in terms of usefulness and ease of use as
well as trust. The majority (75%) reported that they
intended to use the articial pancreas and gave high
ratings to the articial pancreas on perceived usefulness,
ease of use, and trust (administering correct insulin dose/
accurately measuring glucose). However, these patients
also had limited exposure to the actual components of
an articial pancreas. Patients based their ratings on a
detailed written description of the system rather than
the presentation of a prototype, and only ~33% had any
experience with CGM, and that was with short-term use.
These studies point out that a key factor when predicting
patient adoption of CLC technology may be the extent to
which patients expectations about the device will match
their actual experience when using it. These surveys
show that patients and family members have very high
expectations regarding the positive impact of CLC on
diabetes control (usefulness), the low level of eort
needed on their part (ease of use), and the accuracy of
the system (trust). While this can be viewed as positive,
expectations that are unrealistically high are likely to be
problematic and contribute to discontinued or reduced
use of these systems. Evidence for this type of eect
was reported during the Juvenile Diabetes Research
Foundation (JDRF) randomized CGM trial.
Youth who
used CGM less than 6 days per week, which resulted
in less improvement in diabetes control, reported that
using the device was more dicult than as expected.
It may be important to assess patient expectations early
in the process of exposure to CLC or other technological
innovation in diabetes management in order to
identify individuals who have unrealistic expectations
and intervene to improve the match between patient
expectations and actual experience.
Patient Adoption and Use of CSII Therapy
To put patient adoption and use of CSII into perspective,
it is helpful to begin with some statistics. Since 2000,
estimates of worldwide CSII use in T1DM patients range
from 300,000 to 700,000, with the majority of users living
in the United States.
Approximately 37,000 patients in
the United States with type 2 diabetes mellitus (T2DM)
also use insulin pump therapy.
Given that approximately
3 million people and more than 20 million people in the
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Closed-Loop Glucose Control: Psychological and Behavioral Considerations Gonder-Frederick
J Diabetes Sci Technol Vol 5, Issue 6, November 2011
United States have T1DM and T2DM, respectively, one
obvious challenge to the widespread dissemination of
CLC will be in increasing the willingness of patients to
use insulin pumps. From the patients perspective, CSII
may have both benets and barriers. Potential clinical
advantages can include tighter glycemic control, more
precise insulin dosing, increased therapeutic exibility,
better management of the dawn phenomenon,
reductions of exercise-related
and other hypoglycemic
episodes. In spite of the many possible clinical benets,
studies and meta-analyses
comparing glycemic
control in patients using multiple daily injections (MDI)
versus CSII have produced equivocal results. Thus, there
is no guarantee that an individual patient will achieve
improved diabetes control with CSII. However, these
inconsistent results may occur because some patient
populations are more likely to experience improvements
in glucose parameters than others. For example, a meta-
found that improvements in metabolic control
with CSII were more likely in patients with the highest
hemoglobin A1c (HbA1c) levels when using MDI and the
greatest reductions in severe hypoglycemia occurred in
those with the most frequent severe hypoglycemia on MDI.
There are also potential psychological and behavioral
barriers to insulin pump use. Across studies,
of rates of CSII discontinuation in children and adults
range from 064%. From a behavioral perspective, CSII
is in some ways the most demanding insulin regimen,
requiring constant engagement on the part of patients
and/or family members. However, research has not
found this demand to be a major factor when CSII is
discontinued. Some patients report discontinuing because
of failure to achieve improved glycemic control with
CSII, but the majority cite skin discomfort, irritation, or
infection at the infusion site as the primary reason.
19, 20
This nding points out the critical role played by
characteristics of the technology itself, which can reduce
likelihood of adoption.
A psychological issue of special importance for adolescents
is body image concern, assumed to be the reason
females aged 10 years and older are repeatedly found
to be at high risk for discontinuing CSII.
pump use may also be associated with the undesired
side-eect of weight gain.
Older pump users can face
other age–related psychosocial and behavioral barriers,
including cognitive and visual impairment, impaired
dexterity, lack of caregiver assistance, and anxiety about
Feelings of vulnerability and fear of device
failure may also preclude optimal pump use and lead to
eventual discontinuation.
Because of the wide range of potential clinical outcomes
and possible barriers to long-term use, appropriate patient
selection for CSII is critical. Although there are standards
for patient selection, albeit dicult to dene objectively,
and there are no standardized clinical, psychological or
behavioral guidelines for the process of patient selection.
The American Diabetes Associations standards
that candidates should demonstrate (1) strong motivation
for improved glucose control, (2) willingness to work
with their health care provider in assuming substantial
responsibility for diabetes management, (3) an ability
to understand and demonstrate the use of CSII, and
(4) adherence to self-monitoring of blood glucose (BG)
and the ability to translate BG data into pump use.
The American Association of Diabetes Educators
further recommend that a number of psychological and
behavioral factors be considered in the assessment of
patients for pump therapy, including eective coping
patterns, adequate social support, and ability to solve
diabetes management issues. Unfortunately, systematic
implementation of these recommendations is greatly
limited by the lack of consensus and concrete criteria for
measuring these characteristics.
Surprisingly little research has tested patient charac-
teristics that are associated with long-term maintenance
of CSII therapy and positive clinical outcomes. One easily
identied behavioral variable, found to be highly predictive
of CSII success, is a history of vigilant BG self-monitoring,
which likely serves as a proxy measure of behavioral
engagement in diabetes management.
Other patient
characteristics have been recommended as important
to patient success, including maturity, acceptance of
diabetes, realistic expectations about pump therapy,
and adequate knowledge about numerous aspects of
diabetes management.
Good candidates for CSII have
also been described as those who have the ability to
problem-solve, troubleshoot, engage in sophisticated self-
care behaviors, and master the technology.
most of these recommendations are based on clinical
experience, not empirical evidence. In fact, there is
evidence that the relationship between these positive
patient characteristics and likelihood of success using
intensive therapies may be more complex. A study
investigated the impact of self-management competence
in pediatric patients and their families on their response
to intensied insulin therapy with MDI or CSII. Contrary
to predictions, families with the lowest levels of self-
management competence beneted just as much from
intensied treatment, in terms of HbA1c improvements,
as those with moderate and high levels. These results
challenge some of the most common assumptions about
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Closed-Loop Glucose Control: Psychological and Behavioral Considerations Gonder-Frederick
J Diabetes Sci Technol Vol 5, Issue 6, November 2011
patient-selection factors for more complex regimens, and
suggest that it may be benecial to implement such
treatments in individuals and families who struggle with
diabetes management and control.
Continuous subcutaneous insulin infusion use requires
comprehensive training for the patient and members
of the family/support system involved in diabetes care,
and this will also certainly be the case for CLC systems.
There are existing programs that serve as models, such
as the one at Children’s National Medical Center in
Washington D.C., that require pediatric candidates and
their families to follow a complex CSII regimen with
intensive record keeping for 3–6 months in preparation
for pump initiation.
The diabetes clinic at the Royal
Children’s Hospital in Melbourne, Australia, employs
regular progress review and practical integrative workshops
to help maintain optimal management behaviors in their
pediatric pump program.
The AADE has recommended
education and training that includes comprehensive
instruction in numerous aspects of diabetes management.
Despite these models and recommendations, there are no
standardized requirements for CSII training or methods
for measuring patient competence to begin pump use.
More research will be needed to establish the require-
ments of training and support programs for patients
using CLC.
Continuous Glucose Monitoring
Because CGM technology has only recently been made
available to the larger public, there is limited data on
its adoption and use in diabetes management. Use of
CGM has rapidly expanded, increasing from 7,000 users
in 2006 to 15,000 users in 2007.
Reports from 2007
projected more than 140,000 users in 2009, but user
data for 2011 is unclear.
Unlike CSII, reimbursement
for the cost of CGM devices and supplies varies greatly
across insurance providers, so nances can also pose
a signicant barrier for many patients who might
otherwise want to use this technology.
It has been demonstrated that real-time CGM has
the ability to improve metabolic control, including
lowering HbA1c without increasing the time spent in
hypoglycemia, for some individuals with T1DM.
A recent meta-analysis
of six randomized, controlled
trials of two or more months’ duration yielded positive
results, with signicant reductions in HbA1c with CGM
use, especially in those patients with the highest baseline
HbA1c levels, as well as those who used the device more.
This same study also found some evidence, although
weaker, for a reduction in time spent in hypoglycemia.
Despite the expected advantages of CGM, more research
is needed to determine which patients will reap the
most benets from this technology. In addition, few
studies to date have examined the psychological impact
of CGM use, including issues related to quality of life
and reductions in fear of hypoglycemia. Early results
indicate that CGM use has neither adverse nor benecial
eects on psychological functioning in youth, but clearly
more research is needed. Actual data on level of interest
in CGM in the T1DM community is scarce. In one
, 90% of parents endorsed a high level of interest
in having their children with T1DM use CGM but only
if the cost was covered by insurance. Without insurance
coverage, only 50% of parents believed they would
use CGM.
It is important for potential users and their families to have
realistic expectations about CGM, such as understanding
that this technology is not a cure for diabetes, nor is
it the articial pancreas.
Additionally, users should
understand that with novelty comes imperfection, including
discrepancies between interstitial glucose and BG meter
readings, frequent false alarms, and a potentially
overwhelming amount of glucose data.
A common
unrealistic expectation is that CGM will prevent all
episodes of hypoglycemia and hyperglycemia, which,
unfortunately, is not accurate. Ideally, a structured assess-
ment of patient knowledge of intensive diabetes self-
management, as well as patient expectations, would
be conducted prior to CGM initiation, to identify those
individuals who can most successfully use this technology,
as well as those who might need more preparation.
As research into patient acceptance and long-term use
of CGM continues, it can serve as an essential guide
for the development of patient selection, training, and
support needed for CLC systems.
Research is just beginning to investigate potential psycho-
logical and behavioral barriers to CGM use, and initial
ndings indicate that patients will need to have the
motivation, willingness, and ability to use CGM extremely
consistently in terms of the number of hours/days per
week that the device is worn. As noted above, a meta-
of CGM studies indicates that improvements in
glycemic control most likely occur in patients who use
the device more consistently. In the JDRF CGM trial
which was included in that study, use of CGM was more
consistent among adults age 25 years or older than in
the younger age groups, with 83% of adults averaging
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Closed-Loop Glucose Control: Psychological and Behavioral Considerations Gonder-Frederick
J Diabetes Sci Technol Vol 5, Issue 6, November 2011
at least 6 days of usage per week. Adults 25 years
and older also demonstrated a signicant reduction
in HbA1c levels compared to the younger age groups.
Those aged 15–24 years showed the least HbA1c improve-
ment, and only 30% of these participants used the device
at least six days per week. The fact that CGM may be
benecial in improving metabolic control only for those
individuals who will use the technology almost all of
the time has important implications for patient selection
and education. One factor has been identied that
appears to predict greater CGM use, which is pre-CGM
frequency of BG monitoring.
Because this behavioral
variable also predicts success with CSII, it should be
considered as an important patient selection characteristic
for CLC trials.
Psychological factors, such as coping skills and perceived
support, have also been identied as predictors of CGM
A recent study comparing adult responders
to CGM (improved HbA1c) to non-responders (no
improvement) demonstrated the importance of type of
coping strategy and perceived social support in reaping
glycemic benets from the device. Although participants
in both groups experienced frustrations related to CGM
use, responders tended to engage in self-controlled
coping strategies (i.e., taking a neutral problem-solving
approach), and they reported receiving more support
from their signicant others. Given the hassle factor
that comes with CGM use, which can include frequent
false alarms, physical discomfort of the sensor, sensor
calibration failures, and discrepancies between CGM
interstitial glucose and BG meter readings,
patients ability
to cope with these stressors, as well as their willingness
to use CGM consistently and make changes in diabetes
management behaviors, appear to be predictors of
individuals who will fare best with this technology.
The abundance of glucose data that CGM provides
may also render feelings of anxiety.
It is critical that
patients know how to interpret and apply the data that
they receive from the system, but there are no published
guidelines for outpatient use at this time.
In response to
this problem, the DirectNet Study Group developed the
DirecNet Applied Treatment Algorithm, which utilizes
algorithms to help patients make diabetes management
decisions (i.e., insulin dosing) based on real-time glucose
values and downloaded sensor data.
Promising results
of a pilot pediatric study found that, after 13 weeks, all
participants and their parents believed the algorithms
provided clear instructions and improved postprandial
BG excursions.
Not surprisingly, adoption and utilization of CGM requires
ample patient education not only on the specic features
and functions of the device, but also on how to utilize
glucose feedback to improve diabetes self-management.
Graded, gradual, systematic training is recommended,
similar to the education protocols currently in place for
initiating CSII.
An education and training model has
been proposed for health care professionals to enhance
their eciency with CGM technology and better train
patients in its use.
Such comprehensive education and
close follow-up are likely to be necessary for many patients
to achieve optimal glycemic control from CGM.
Sensor-Augmented Insulin Pump Therapy
Sensor-augmented pump therapy, which integrates CSII
and CGM, is considered the rst step toward development
of a CLC system. An increasing number of studies,
including two prominent randomized controlled trials
(Sensor-Augmented Pump Therapy for A1c Reduction
[STAR] 3; Sensing with Insulin Pump Therapy to Control
HbA1c), are evaluating clinical ecacy.
In both adults
and children, SAP therapy has been shown to have
benecial eects on metabolic control
and decreased
though results are inconsistent regarding
whether these improvements are signicantly greater than
when CGM is paired with MDI.
Similar to ndings
in CGM trials, consistent SAP therapy use (at least 60%
of the time) appears to be necessary for improvements
in HbA1c,
again highlighting the importance of
patient motivation and behavior. In terms of patient
training and support for use of SAP, the STAR 3 study
group has proposed a model utilizing a stepwise, systematic
protocol to introduce CSII and CGM sequentially, along
with web-based diabetes management modules and
therapy-management software for patient support.
Theoretical Frameworks
Successful implementation of CLC systems will depend
on a number of complex processes that determine
patient willingness to adopt, utilize, and continue using
this type of technology. As one author has noted,
the ecacy of technological devices themselves often
depends on patient adherence, and this certainly appears to
be the case with CGM. Past studies have revealed a few
of the important psychological and behavioral variables
that may inuence adequate utilization of CSII and CGM.
However, clearly much more eort is needed in order to
prepare for patient transition to CLC systems. To advance
research in this area, we need to begin to consider
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Closed-Loop Glucose Control: Psychological and Behavioral Considerations Gonder-Frederick
J Diabetes Sci Technol Vol 5, Issue 6, November 2011
theoretical frameworks that can explain the critical
processes involved in patient adoption, utilization, and
continued use of technology in diabetes self-management.
There are a number of health care-related theories that
can serve as guides in understanding these processes and
identifying those psychological and behavioral variables
most likely to be relevant to CLC technology. Here we
will focus on three of these theories: Health Belief Model
(HBM), theory of planned behavior (TPB), and diusion
of innovation theory (DIT). There is strong empirical
evidence that each of these theories predicts health and
diabetes management behaviors.
However, it should
also be noted that there are other theories of health care
behavior, not included in this review, which may also
provide valuable insight and deserve consideration.
The HBM is the oldest of the theories discussed here,
and it emphasizes the role of patient perceptions,
attitudes, and beliefs in health care decision-making
and behaviors.
Critical patient constructs include
perceptions of personal vulnerability and seriousness
of a health problem, perceived cost versus benet ratios,
perceived locus of internal or external personal control,
and self-ecacy. Other important constructs in the HBM
include coping styles, environmental cues to action, and
perceived barriers to goal achievement. Diabetes-specic
constructs such as fear of hypoglycemia and hyper-
glycemia, as well as tendency to have negative emotional
reactions to glucose readings, will also likely inuence
use of diabetes technology.
Numerous studies support
the relationship between the HBM and a wide range
of diabetes self-care behaviors in both adolescents and
adults, including foot care
and adherence to insulin,
diet, and exercise.
The TPB is another behavior change model that predicts
diabetes management behaviors, including a healthy diet
and engaging in physical activity.
In TPB, the process
of behavior change is a product of patient attitudes,
subjective norms, and perceived behavioral control, which
determine intention to engage in a new behavior.
Patient attitudes relevant to successful adoption and use
of CLC systems might include patient perceptions and
beliefs about the positive versus negative eects of using
the system, perceived social pressure and network support
for use, perceived control over the behaviors involved
in use of the technology, and personal condence in
the ability to use it eectively. The TPB places a unique
emphasis on the importance of existing social support
systems to facilitate not only changes in behavior, but
also maintenance of new behaviors. These systems
include family members and friends, but also education,
training, and other support programs to optimize
patient success.
Finally, the DIT provides a model of how innovations (i.e.,
new ideas, products, or practices) are adopted by groups,
and what factors inhibit or facilitate the speed at which
innovations are accepted and implemented.
Diusion is
conceptualized as a ve-step process moving from an
individual’s or group’s knowledge (rst information and
exposure to the innovation) persuasion (formation of
favorable or unfavorable attitudes) decision (to adopt
or reject) implementation (procurement, training
and use) conrmation (evaluation of reinforcement).
This process is not necessarily sequential and linear, but
rather contains feedback loops; for example, evaluation
can trigger a new decision to continue or discontinue
innovation use. As with the HBM and TPB, this theoretical
perspective recognizes that more than just objective
evidence and benets are necessary for rapid diusion
of innovations. In all of these theoretical models, adoption,
successful implementation, and maintenance of new
health care behaviors are highly dependent on the
subjective perceptions of the potential user. For this reason,
it is critical to keep in mind that achieving widespread
adoption and utilization of CLC systems will require
more than studies showing evidence for its objective
benets on glucose control.
Research into patient use of CSII and CGM has focused
primarily on the objective clinical benets of these
technologies, with much less emphasis on systematically
studying and understanding patients’ subjective reactions
to these technologies. This empirical approach ignores
the evidence that patient decisions about adopting
and using new technologies are rarely based solely on
objective benets, and, therefore, has led to a limited
understanding of important psychological and behavioral
factors. For example, the CSII literature has relatively
little to oer on questions of patient selection and those
patient characteristics that are positive (or negative)
prognostic indicators for pump therapy. However, there
are encouraging signs that future investigations into
diabetes technology will be more inclusive of psycho-
logical and behavioral processes, with recent CGM
studies addressing the impact of constructs such as
patient satisfaction
and coping styles.
More studies
such as these are critical for a more comprehensive
understanding of the human factors likely to play a
pivotal role in the successful adoption and use of CLC
systems, and to begin to build an empirical foundation
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Closed-Loop Glucose Control: Psychological and Behavioral Considerations Gonder-Frederick
J Diabetes Sci Technol Vol 5, Issue 6, November 2011
for the development of patient selection, training, and
support tools.
NIH/NIDDK R01DK085623 and R21DK080896.
Linda Gonder-Frederick has received research funding from Abbott
Laboratories, consulting fees from Merck & Co., Inc., and serves on an
advisory committee for AstraZeneca Pharmaceuticals LP.
The authors thank Karen Vajda, B.A., for her editorial assistance.
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  • Source
    [Show abstract] [Hide abstract] ABSTRACT: Background: Artificial pancreas (AP) systems are currently an active field of diabetes research. This pilot study examined the attitudes of AP clinical trial participants toward future acceptance of the technology, having gained firsthand experience. Subjects and methods: After possible influencers of AP technology adoption were considered, a 34-question questionnaire was developed. The survey assessed current treatment satisfaction, dimensions of clinical trial participant motivation, and variables of the technology acceptance model (TAM). Forty-seven subjects were contacted to complete the survey. The reliability of the survey scales was tested using Cronbach's α. The relationship of the factors to the likelihood of AP technology adoption was explored using regression analysis. Results: Thirty-six subjects (76.6%) completed the survey. Of the respondents, 86.1% were either highly likely or likely to adopt the technology once available. Reliability analysis of the survey dimensions revealed good internal consistency, with scores of >0.7 for current treatment satisfaction, convenience (motivation), personal health benefit (motivation), perceived ease of use (TAM), and perceived usefulness (TAM). Linear modeling showed that future acceptance of the AP was significantly associated with TAM and the motivation variables of convenience plus the individual item benefit to others (R(2)=0.26, P=0.05). When insulin pump and continuous glucose monitor use were added, the model significance improved (R(2)=0.37, P=0.02). Conclusions: This pilot study demonstrated that individuals with direct AP technology experience expressed high likelihood of future acceptance. Results support the factors of personal benefit, convenience, perceived usefulness, and perceived ease of use as reliable scales that suggest system adoption in this highly motivated patient population.
    Preview · Article · May 2014 · Diabetes Technology & Therapeutics
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    [Show abstract] [Hide abstract] ABSTRACT: Aim: This study aimed to systematically review the evidence base for the use of existing psychological and psychosocial measures suitable for use in artificial pancreas (AP) research. Materials and methods: This systematic review of published literature, gray literature, previous systematic reviews, and qualitative and economic studies was conducted using terms and abbreviations synonymous with diabetes, AP, and quality of life (QoL). Results: Two hundred ninety-two abstracts were identified that reported psychosocial assessment of diabetes-related technologies. Of these, nine met the inclusion criteria and were included. Only four of 103 ongoing trials evaluated psychosocial aspects as an outcome in the trial. Of these, treatment satisfaction, acceptance and use intention of AP, fear of hypoglycemia episodes, satisfaction with AP, and an unspecified QoL measure were used. Conclusions: A better understanding of the psychosocial side of AP systems and the extent to which human factors play a role in the uptake and efficient use of these systems will ultimately lead to the most benefit for people with diabetes.
    Full-text · Article · Dec 2014 · Diabetes Technology & Therapeutics
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