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 (R2=0.26, P=0.05). When insulin pump and continuous glucose monitor use were added, the model significance improved (R2=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.
Introduction
Our clinical team at Sansum Diabetes Research Institute (SDRI) (Santa Barbara, CA) joined with chemical engineers at the University of California Santa Barbara in 2004 to begin work on an artificial pancreas (AP) for people with type 1 diabetes mellitus (T1DM). Even with intensive insulin treatment administered as multiple daily injections or via a continuous subcutaneous insulin infusion (CSII) pump, people with T1DM may experience significant episodes of hyperglycemia and hypoglycemia. The goal of an AP system is to combine continuous glucose monitors (CGMs) with CSII pumps to control insulin delivery automatically with a mathematical algorithm. This would potentially improve long-term patient health and reduce the burden of daily management for people with T1DM.1
Many preliminary AP studies were done at SDRI to lay the groundwork to develop a working AP/closed-loop system.2–8 Our first closed-loop study at SDRI was done in April 2007; several studies followed this initial closed-loop design with different controller designs but with the common theme of a fully automated closed-loop system.9,10 Additional AP studies are being conducted in many other settings, including across the United States, the United Kingdom, The Netherlands, Israel, France, and Italy.11–15 Knowing the importance of human behavior in diabetes management, investigators are now looking at future acceptance of AP technology as well as behavioral and psychological considerations.16,17 In an interview and then follow-up survey development study by van Bon et al.,16,18 it was concluded that most patients who used CSII pumps (technology), when provided a written description of an AP system, would likely adopt it.
As of 2004, in total, 49 subjects have volunteered in one or more of the SDRI AP studies. The purpose of this study was to investigate whether participants who have directly experienced AP technology expressed similar attitudes toward future acceptance as those examined in previous studies.16,17,19,20 We hypothesized that subjects with T1DM volunteer for AP studies because they believe that the technology will eventually help them achieve better (more stable and within a tighter range of 80–140 mg/dL) blood glucose control and therefore experience improved health and a life more like someone without T1DM. To test our hypothesis we measured current diabetes treatment satisfaction, dimensions of clinical trial participation motivation, and variables of the technology acceptance model (TAM).21,22 We chose to address these because (1) treatment satisfaction is a known barrier toward future adoption of advanced diabetes management technology,20,23 (2) considering the specific patient population relationships between future adoption and clinical trial participation was of interest, and (3) TAM is frequently used in health care as a model to predict the likelihood of a technology's future adoption.20 Specifically, the TAM explains how patients might come to accept, and therefore adopt, novel tools or methodologies. Three key factors of the theory include subjects' perceived usefulness, perceived ease of use, and trust in the technology,19,20 and TAM has been used to assess future acceptance of an AP system previously.14,17,18 The study end points were completion of the questionnaires, compilation of the answers, and summary of the findings.
Subjects and Methods
Survey design
A questionnaire was developed to learn about variables that might associate with intention to use AP technology in a specific patient population, AP clinical trial subjects. Here the assumption was that intention to use, or technology acceptance, is thought to reliably predict actual use.21,22 The 34-item survey contained eight current treatment satisfaction questions,23 11 TAM questions,20 and 15 questions assessing clinical trial patients' motivation.24,25 A 5-point Likert scale was used. Table 1 lists the 34 items. Patient demographics, self-reported anthropometric and biochemical data, and current diabetes treatment questions, including the use of CGM and CSII pumps, were also collected.
Table 1.
Survey Questions, Constructs, and Reliability Analysis
| Construct | Question | Cronbach's α |
|---|---|---|
| Current treatment satisfaction | Prompt: How satisfied are you with your current diabetes medication? | |
| Satisfaction | Time it takes | 0.8636 |
| Convenient it is | ||
| Easy it is to take medication | ||
| Painful it is | ||
| Easy it was to learn to use | ||
| Easy it is to use | ||
| Effective it is at minimizing hypoglycemia | ||
| Effective it is at minimizing hyperglycemia | ||
| Motivation to participate in clinical trials | Prompt: How much do the following motivate you to participate in an AP research study? | |
| Altruism | AP technology will benefit others with T1DM | 0.5232 |
| Improvement of medical knowledge about T1DM | ||
| Improvement in health in order to take care of family | ||
| Participating in research is the right thing to do | ||
| To give back for good medical care received | ||
| Monetary incentive | Financial compensation for participation | NA |
| Personal health benefit | AP technology will increase my quality of life | 0.888 |
| AP technology will increase my lifespan | ||
| Receiving care from an expert medical team | ||
| Access to intensive monitoring | ||
| Convenience | Overall length (days) of study | 0.8261 |
| Amount of discomfort | ||
| Location of study | ||
| Time of day of study | ||
| Total number of study visits | ||
| TAM | ||
| Intention to use | How likely are you to change your current diabetes medical management system? | NA |
| Prompt: Compared with current treatment my expectations of AP technology are: | ||
| Perceived usefulness | Fewer episodes of hyperglycemia | 0.8415 |
| Fewer episodes of hypoglycemia | ||
| Reduced number of doctor visits | ||
| Increased quality of life | ||
| Increased lifespan | ||
| Improved blood glucose control | ||
| My life will be more like someone without T1DM | ||
| Perceived ease of use | Ease of use | 0.7516 |
| Reduced discomfort | ||
| Requires minimal effort |
AP, artificial pancreas; NA, not applicable; T1DM, type 1 diabetes mellitus; TAM, technology acceptance model.
Participants
The study population was subjects with T1DM who participated in SDRI AP studies since 2004. All 49 clinical trial participants were called via phone. If contact was possible, subjects were invited to participate. Participants were explained the nature and purpose of the study, and each subject had the opportunity to ask questions. Those subjects who verbally agreed to take part, via an approved waiver of a formal informed consent process by the Cottage Health System Institutional Review Board, were e-mailed a link to complete the survey online.
Statistical methods
The statistical analysis was performed using the R Statistical and Rcmdr packages (www.r-project.org/). Frequencies or descriptive statistics were run for demographic information, anthropometric plus biochemical data, and current diabetes treatment. To test for gender differences, χ2 tests were conducted. Questionnaire scales with three or more items were checked for reliability using Cronbach's α. When appropriate (Cronbach's α≥0.7 threshold), the relationship of the factors and/or individual items to the likelihood of AP technology adoption was explored using multiple linear regression. Two-tailed values of P≤0.05 were considered statistically significant.
Results
Sample characteristics
Forty-seven of the 49 subjects (two subjects were lost to follow-up) since 2004 were contacted. All 47 agreed to participate and were sent an e-mail link to complete the survey. Thirty-six subjects (76.6%) completed the survey. Table 2 presents study participant characteristics. A χ2 test revealed no significant gender differences, so all subsequent analyses were performed using the complete dataset (data not shown). Of note is that the majority of subjects used a CSII pump (86.4%, n=32), and fewer than half or 40.5% (n=15) used a CGM system as well.
Table 2.
Subject Characteristics
| Variable | n | Mean±SD or frequency count |
|---|---|---|
| Age (years) | 36 | 46.6±12.5 |
| Gender | 36 | 25 females:11 males |
| Education | 36 | 11 some college, 1 AA, 18 BA, 3 MA, 3 Prof/Doc |
| Years with T1DM | 35 | 28.5±15.5 |
| Employment | 36 | 21 FT, 2 FT-H, 5 PT, 3 S/I, 5 R |
| IP use | 36 | 32 yes/4 no |
| CGM use | 36 | 15 yes/21 no |
| HbA1c (%) | 33 | 7.1±1.1 |
| BMI [(lbs/in2)×703] | 35 | 26.0±7.6 |
| PSP | 36 | 29 yes/7 no |
AA, associate's degree any kind; BA, bachelor's degree any kind; BMI, body mass index; FT, full-time; FT-H, full-time in home; HbA1c, glycosylated hemoglobin; IP, insulin pump; MA, master's degree any kind; Prof/Doc, professional or doctorate any kind; PSP, previous study participation other than AP Sansum Diabetes Research Institute clinical trials; PT, part-time; R, retired; S/I, student/intern; T1DM, type 1 diabetes mellitus.
Reliability of questionnaire
The reliability of the majority of scales was good. Table 1 shows Cronbach's α with scores >0.7 for all constructs except altruism (α=0.53) under the motivation model, although the monetary incentive variable could not be tested using Cronbach's α as it was represented by a single question. This was similarly true for the intention to use item; however, for other factors of TAM, perceived ease of use (α=0.75) and perceived usefulness (α=0.84) were tested and reflected good internal consistency. As expected, the scale for current treatment satisfaction was also reliable when all items were included (α=0.86) (Table 1), supporting the previous survey design study.18 Deletion of any item in each of the scales, where possible, did not improve the respective α values, and thus the scales were left unchanged.
Descriptive statistics of questionnaire items
Table 3 provides the mean±SD values and 25% and 75% interquartile ranges for the three highest scoring scale items. Highest scoring here refers to items that were ranked by patients as the most positive or likely responses. Overall, findings were concordant with other qualitative and quantitative AP intention to use studies that considered different patient populations.16,17,19,20 The majority of AP clinical trial participants (86.1%) indicated they were either highly likely or likely to change their current diabetes treatment to AP technology once available.
Table 3.
Ranked Order of Top Three Scoring Items for Current Treatment Satisfaction and Factors of Both Clinical Trial Participation Motivations and Technology Acceptance Model
| Item | n | Mean±SD | 25% IQR | 75% IQR |
|---|---|---|---|---|
| Current treatment satisfaction | ||||
| Painful it is (satisfaction) | 36 | 4.08±0.81 | 3 | 5 |
| Easy it is to use (satisfaction) | 36 | 4.06±0.71 | 4 | 5 |
| Easy it was to learn to use (satisfaction) | 36 | 4.06±0.71 | 4 | 5 |
| Motivation to participate in clinical trials | ||||
| Benefit others with T1DM (altruism) | 36 | 4.89±0.32 | 4 | 5 |
| Improvement of medical knowledge (altruism) | 36 | 4.72±0.51 | 3 | 5 |
| Improvement in health in order to take care of family (altruism) | 36 | 4.72±0.51 | 3 | 5 |
| Increase lifespan (personal health benefit) | 36 | 4.56±0.61 | 3 | 5 |
| Increase quality of life (personal health benefit) | 36 | 4.56±0.77 | 1 | 5 |
| Receive care from expert (personal health benefit) | 36 | 4.42±0.87 | 1 | 5 |
| Length of study (convenience) | 36 | 4.03±0.84 | 3 | 4 |
| Number of study visits (convenience) | 36 | 3.78±0.80 | 2 | 4 |
| Time of day (convenience) | 36 | 3.75±0.87 | 2 | 4 |
| TAM | ||||
| Improved blood glucose control (useful) | 36 | 4.64±0.54 | 4 | 5 |
| Increased quality of life (useful) | 36 | 4.56±0.61 | 4 | 5 |
| Fewer episodes of hyperglycemia (useful) | 36 | 4.50±0.70 | 4 | 5 |
| Likelihood of changing to AP (intention to use) | 36 | 4.39±0.80 | 4 | 5 |
| Ease of use (ease of use) | 36 | 4.36±0.64 | 4 | 5 |
| Requires minimal effort (ease of use) | 36 | 3.83±0.77 | 3 | 4 |
| Reduced discomfort (ease of use) | 36 | 3.53±0.81 | 3 | 4 |
Answers were given on a 5-point Likert scale where 5=completely satisfied, strongly agree, or highly likely and 1=not at all satisfied, strongly disagree, or highly unlikely.
AP, artificial pancreas; IQR, interquartile range; T1DM, type 1 diabetes mellitus; TAM, technology acceptance model.
Most patients were satisfied with their current diabetes treatment for all questions as summarized in Table 3. Subjects were surprisingly most content with how painful and easy to use their current diabetes management system is; 66.7% reported they were either completely satisfied or very satisfied, and 77.8% reported they were either completely satisfied or very satisfied with how easy their current treatment is to use. The two lowest scoring satisfaction variables related to blood glucose control, with 66.7% subjects responding with neutral input toward the ability of their current system to minimize episodes of both hyper- and hypoglycemia.
Overall, the clinical trial participation motivation items showed the most variance. Motivating variables tended to cluster together, with altruism and personal health benefit ranking the highest, followed by convenience and then monetary incentive (Table 3). These findings align with the literature.24,25 The two highest scoring questions for motivating factors were AP technology could benefit others and improve the T1DM medical knowledge, with 88.9% and 77.7% of subjects reporting they strongly agree, respectively. The lowest scoring motivators of clinical trial participation were measures of convenience. Subjects rated discomfort, with 11.1% responding they strongly agree that it is an influencer, and that time of day of the study impacts willingness to participate, with 16.7% of subjects strongly agreeing. This appears to support the responses from the current treatment satisfaction variables. Here, convenience (like pain) of clinical trial participation was ranked lower than other motivating factors, like personal health benefit. This is similar to the finding that subjects were more satisfied in the amount of pain related to, or difficulty of using, their current diabetes management system when compared with their reported satisfaction with the ability of their respective treatments to control episodes of hyper- and hypoglycemia.
Specific to the TAM, subjects ranked the perceived usefulness of AP higher than perceived ease of use (Table 3). This aligns with the survey study of van Bon et al.,18 as well as the findings from the motivation and current treatment satisfaction variables. Table 3 shows that 66.6% strongly agree that an AP system will improve their blood glucose control and that 63.9% strongly agree that an AP system will improve their quality of life.
Linear modeling
Multiple linear regression was conducted using combined scale scores for all but the altruism construct. This was due to its calculated reliability of <0.7. Individual altruism items were included in the model. Analysis showed that AP adoption is best fit by the TAM constructs of ease of use and usefulness plus and, surprisingly, the motivation construct of convenience plus the individual item benefit to others (R2=0.26, P=0.05). By adding in CSII and CGM use, the model significance improved (R2=0.37, P=0.02). The scales of personal health benefit and current diabetes satisfaction did not improve the R2 value, nor did any additional altruism questions.
Discussion
In this pilot study we developed a questionnaire to assess potential predictors of likelihood of AP technology adoption among a motivated patient population that had directly experienced an AP system. Specifically, the AP Motivation and Satisfaction Survey (APMSS) was partially developed using theory presented by van Bon et al.16,18 These researchers detailed adapting the TAM21,22 to investigate attitudes about perceived usefulness and perceived ease of use regarding AP technology, as well as trust in the system. APMSS also uses current treatment satisfaction questions from the Diabetes Medication System Rating Questionnaire survey developed by Peyrot et al.23 For the AMPSS motivation questions, factors favoring participation in clinical trials were identified.24,25 Factors shown to influence participation in clinical trials were grouped into four themes: altruism, personal health benefit, monetary reimbursement, and convenience.
We found that subjects ranked items associated with altruism, including volunteering in order to benefit others, potential for improvement of personal health in order to take care of family, and advancing medical knowledge, as the highest ranked motivators for participation in AP clinical trials. Monetary incentives and convenience were not ranked as important, although convenience was a key aspect of linear modeling. These findings support other motivation research that demonstrate monetary incentive and overall convenience of research study participation are not perceived by subjects as important influencers.22,23 Although the altruism scale was not found to be reliable, the question of benefit to others was significant in linear modeling. This suggests that future directions of patient-based research regarding adoption of an AP system include specific altruism items. Another interesting finding was that satisfaction with current diabetes treatment was not predictive of AP technology adoption by any measure.
Subjects ranked perceived usefulness of an AP higher than perceived ease of use. This has implications for acceptance of an AP system and long-term use. Users will need to be educated about the system and its limitations; expectations will need to be realistic, especially as the system is being developed. If subjects perceive that the system will be of use for blood glucose control and improved health, they may be willing to be more engaged and trained on the system rather than having a system, which is simply “easy to use.” If patients can be shown the effectiveness of an AP system, then acceptance of the technology may be easier. It will be important to assess the effect of an AP system on the quality of life and the degree of trust in the AP. Relinquishing of diabetes management control to an automated system will be a significant hurdle to adoption of an AP.20
The best predictors of AP adoption were variables of TAM. No current diabetes treatment satisfaction items and many motivations to participate in clinical trials questions were significant in our linear model. In summary, a combination of scales, or groupings of questions, was the best predictors of AP adoption, and these included questions related to the TAM items of ease of use and usefulness plus motivation questions related to convenience, as well as the individual item of benefit to others. Insulin pump and CGM use improved the model prediction. This is not an unexpected finding because subjects were a motivated group of individuals, with the majority having other direct technology experience of using CSII and CGMs. Identifying patient populations most likely to benefit from an AP system will be an important consideration; previous studies have demonstrated that correct technology implementation is a barrier to use of technology and thus achievement of improved blood glucose control.26 Aligning with this observation includes findings specific to the convenience scale. Although not ranked as a strong motivator for clinical trial participation, it was significant in linear modeling. Thus, the convenience of an AP system should be addressed for both development of the technology and as an important point of discussion with potential users.
A strength of our study was that almost all of our subjects are familiar with the components of an AP system, such as CSII and CGM, and during the in-clinic closed-loop trials they were able to experience aspects of what an AP would look and feel like. The main limitations of this pilot study were small sample size and nonvalidated operational constructs. In addition, our subjects tend to be highly motivated and to have fairly well controlled diabetes. It will be useful and beneficial to recruit subjects who are not as highly motivated, or as well controlled, and more representative of the general T1DM population to gain their perspective on an AP system. Another limitation of our study is that subjects who chose not to participate in AP studies were not included, and these subjects may help us to understand why people with T1DM would not adopt an AP system. These limitations will be addressed in the future. We also plan to validate and refine our questionnaire for use in future AP trials. For example, questions related to current diabetes treatment satisfaction will be removed. It is encouraging that more closed-loop AP studies are considering the impact of psychology and behavior on the success of an AP system.
Conclusions
Patient decisions about adopting and using new technologies are rarely based solely on objective benefits, and this has led to a limited understanding of important psychological and behavioral factors that are related to successful use of new technology, such as an AP. Questionnaire studies are useful for the identification of people who will be most compliant and successful with new technology, those who will benefit most from this technology (such as people with hypoglycemia unawareness), which factors are most important, and how to develop training and support tools.
Acknowledgments
We also acknowledge and thank all of our artificial pancreas clinical trials participants for their patience, support, time, dedication, and “sense of humor.” This work has been supported by grants from the National Institutes of Health, the JDRF, and the Otis Williams Fund at the Santa Barbara Foundation. The studies have been conducted with generous product support from LifeScan, Inc., a Johnson & Johnson Company; DexCom, Inc.; Animas Corporation, a Johnson & Johnson Company; Insulet Corporation; Abbott; Eli Lilly; Novo Nordisk; Roche; and Sanofi.
Author Disclosure Statement
W.C.B., S.M.F., R.P.F., and R.R.R. have no conflicts of interest and no disclosures. H.C.Z. received honoraria for scientific lectures and travel reimbursement from Animas, Cellnovo, Insulet, MannKind, and Roche, has received research grants and product support from Animas, Abbott, Dexcom, Eli Lilly, GluMetrics, Insulet, LifeScan, Medtronic, Novo Nordisk, Roche, and Sanofi, and is a board member of Artificial Pancreas Technologies. E.D. received honoraria for scientific lectures from Animas and is a board member of Artificial Pancreas Technologies. L.J. received honoraria for scientific lectures and travel reimbursement from Animas, Eli Lilly, Insulet, MannKind, Novo Nordisk, and Roche. F.J.D. III received honoraria for scientific lectures from Animas and is a board member of Artificial Pancreas Technologies.
References
- 1.Mehta SN, Wolfsdorf JI: Contemporary management of patients with type 1 diabetes. Endocrinol Metab Clin North Am 2010;39:573–593 [DOI] [PubMed] [Google Scholar]
- 2.Zisser H, Jovanovic L, Doyle F, III, Ospina P, Owens C: Run-to-run control of meal-related insulin dosing. Diabetes Technol Ther 2005;7:48–57 [DOI] [PubMed] [Google Scholar]
- 3.Palerm CC, Rodriguez-Fernandez M, Bevier WC, Zisser H, Banga JR, Jovanovič L, Doyle FJ, III: Robust parameter estimation in a model for glucose kinetics in type 1 diabetes subjects. Conf Proc IEEE Eng Med Biol Soc 2006;1:319–322 [DOI] [PubMed] [Google Scholar]
- 4.Zisser HC, Bevier WC, Jovanovič L: Restoring euglycemia in the basal state using continuous glucose monitoring in subjects with type 1 diabetes mellitus. Diabetes Technol Ther 2007;9:509–515 [DOI] [PubMed] [Google Scholar]
- 5.Bevier WC, Zisser HC, Jovanovič L, Finan DA, Palerm CC, Seborg DE, Doyle FJ, III: Use of continuous glucose monitoring to estimate insulin requirements in patients with type 1 diabetes mellitus during a short course of prednisone. J Diabetes Sci Technol 2008;2:578–583 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Finan DA, Doyle FJ, III, Palerm CC, Bevier WC, Zisser HC, Jovanovič L, Seborg DE: Experimental evaluation of a recursive model identification technique for type 1 diabetes. J Diabetes Sci Technol 2009;3:1192–1202 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Harvey RA, Wang Y, Grosman B, Percival MW, Bevier W, Finan DA, Zisser H, Seborg DE, Jovanovič L, Doyle FJ, III, Dassau E: Quest for the artificial pancreas: combining technology with treatment. IEEE Eng Med Biol Mag 2010;29:53–62 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Zisser H, Breton M, Dassau E, Markova K, Bevier W, Seborg D, Kovatchev B: Novel methodology to determine the accuracy of the OmniPod insulin pump: a key component of the artificial pancreas system. J Diabetes Sci Technol 2011;5:1509–1518 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Harvey RA, Dassau E, Bevier WC, Seborg DE, Jovanovič L, Doyle FJ, III, Zisser HC: Clinical evaluation of an automated artificial pancreas using zone-model predictive control and health monitoring system. Diabetes Technol Ther 2014;16:348–357 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Dassau E, Zisser H, Harvey RA, Percival MW, Grosman B, Bevier W, Atlas E, Miller S, Nimri R, Jovanovič L, Doyle FJ, III: Clinical evaluation of a personalized artificial pancreas. Diabetes Care 2013;36:801–809 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Bruttomesso D, Farret A, Costa S, Marescotti MC, Vettore M, Avogaro A, Tiengo A, Dalla Man C, Place J, Facchinetti A, Guerra S, Magni L, De Nicolao G, Cobelli C, Renard E, Maran A: Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: preliminary studies in Padova and Montpellier. J Diabetes Sci Technol 2009;3:1014–1021 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Hovorka R, Kumareswaran K, Harris J, Allen JM, Elleri D, Xing D, Kollman C, Nodale M, Murphy HR, Dunger DB, Amiel SA, Heller SR, Wilinska ME, Evans ML: Overnight closed loop insulin delivery (artificial pancreas) in adults with type 1 diabetes: crossover randomised controlled studies. BMJ 2011;342:d1855. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Atlas E, Nimri R, Miller S, Grunberg EA, Phillip M: MD-Logic artificial pancreas system: a pilot study in adults with type 1 diabetes. Diabetes Care 2010;33:1072–1076 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Renard E, Place J, Cantwell M, Chevassus H, Palerm CC: Closed-loop insulin delivery using a subcutaneous glucose sensor and intraperitoneal insulin delivery: feasibility study testing a new model for the artificial pancreas. Diabetes Care 2010;33:121–127 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Clarke WL, Anderson S, Breton M, Patek S, Kashmer L, Kovatchev B: Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: the Virginia experience. J Diabetes Sci Technol 2009;3:1031–1038 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.van Bon AC, Kohinor MJ, Hoekstra JB, von Basum G, deVries JH: Patients' perception and future acceptance of an artificial pancreas. J Diabetes Sci Technol 2010;4:596–602 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Gonder-Frederick L, Shepard J, Peterson N: Closed-loop glucose control: psychological and behavioral considerations. J Diabetes Sci Technol 2011;5:1387–1395 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.van Bon AC, Brouwer TB, von Basum G, Hoekstra JB, DeVries JH: Future acceptance of an artificial pancreas in adults with type 1 diabetes. Diabetes Technol Ther 2011;13:731–736 [DOI] [PubMed] [Google Scholar]
- 19.Elleri D AC, Allen JM, Hayes J, Pesterfield C, Wilinska ME, Dunger DB, Hovorka R: Parental attitudes towards overnight closed-loop glucose control in children with type 1 diabetes. Diabetes Technol Ther 2010;12:35–39 [DOI] [PubMed] [Google Scholar]
- 20.Shepard JA, Gonder-Frederick L, Vajda K, Kovatchev B: Patient perspectives on personalized glucose advisory systems for type 1 diabetes management. Diabetes Technol Ther 2012;14:858–861 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Davis FD: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MISQ 1989;13:319–40 [Google Scholar]
- 22.Holden RJ, Karsh BT: The technology acceptance model: its past and its future in health care. J Biomed Inform 2010;43:159–172 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Peyrot M, Harshaw Q, Shillington AC, Xu Y, Rubin RR: Validation of a tool to assess medication treatment satisfaction in patients with type 2 diabetes: the Diabetes Medication System Rating Questionnaire (DMSRQ). Diabet Med 2012;29:1060–1066 [DOI] [PubMed] [Google Scholar]
- 24.Jones JM, Nyhof-Young J, Moric J, Friedman A, Wells W, Catton P: Identifying motivations and barriers to patient participation in clinical trials. J Cancer Educ 2006;21:237–242 [DOI] [PubMed] [Google Scholar]
- 25.Locock L, Smith L: Personal benefit, or benefiting others? Deciding whether to take part in clinical trials. Clin Trials 2011;8:85–93 [DOI] [PubMed] [Google Scholar]
- 26.Chase HP, Beck RW, Xing D, Tamborlane WV, Coffey J, Fox LA, Ives B, Keady J, Kollman C, Laffel L, Ruedy KJ: Continuous glucose monitoring in youth with type 1 diabetes: 12-month follow-up of the Juvenile Diabetes Research Foundation continuous glucose monitoring randomized trial. Diabetes Technol Ther 2010;12:507–515 [DOI] [PubMed] [Google Scholar]