Patients' Perception and Future Acceptance of an Artificial Pancreas

Bon, Arianne C. van; Kohinor, Miriam J. E.; Hoekstra, J. B. L.; Basum, Golo von; DeVries, J. Hans

doi:10.1177/193229681000400313

Cited by 41 publications

(57 citation statements)

References 16 publications

(12 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[11][12][13][14][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.…”

mentioning

confidence: 99%

“…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).…”

mentioning

confidence: 99%

See 1 more Smart Citation

Artificial Pancreas (AP) Clinical Trial Participants' Acceptance of Future AP Technology

Bevier

Fuller

et al. 2014

Diabetes Technology & Therapeutics

View full text Add to dashboard Cite

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 a. 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.

show abstract

mentioning

confidence: 99%

mentioning

confidence: 99%

Artificial Pancreas (AP) Clinical Trial Participants' Acceptance of Future AP Technology

Bevier

Fuller

et al. 2014

Diabetes Technology & Therapeutics

View full text Add to dashboard Cite

show abstract

“…1 At present, the optimum approach appears to be a combination of insulin pump therapy and real-time continuous glucose monitoring. 2 However, despite patient acceptance of this technological approach to glucose control, 3 the majority of people still continue to use multiple daily injections (MDIs) of insulin. Whatever the method of insulin delivery, a fundamental component of training in intensive insulin therapy requires participants to be adept at handling numbers in order for them to understand the nuances of glucose monitoring and to calculate appropriate and safe insulin doses ( Table 1).…”

Section: Introductionmentioning

confidence: 99%

Poor Numeracy: The Elephant in the Diabetes Technology Room

Kerr

2010

J Diabetes Sci Technol

View full text Add to dashboard Cite

show abstract

“…3 Recent behavioral studies have also shown that people with T1DM are interested in an automated system but are concerned with relinquishing full control. 4,5 Therefore, an automatic AP that is safe and robust to daily living conditions and is trusted by the users is critical.The AP is a multilayered device that will contain several features, including a core glucose controller, devices for monitoring of glucose and possibly other biologically relevant compounds or signals, software to interface with the user, safety systems to monitor the status of the system, and telemedicine to convey information about the system to the user and family and/or medical personnel. The core of the AP is the controller, the design of which has been explored by several research teams, with promising results.…”

mentioning

confidence: 99%

mentioning

confidence: 99%

Design of the Glucose Rate Increase Detector

Harvey

Dassau

Zisser

et al. 2014

J Diabetes Sci Technol

View full text Add to dashboard Cite

The primary goal of the artificial pancreas (AP) is to eliminate the occurrence of severe hypoglycemia and reduce the time spent in hyperglycemia (>180 mg/dL) in an effort to improve quality of life and reduce long-term complications. 1 Safe and effective control of type 1 diabetes mellitus (T1DM) using an AP has been researched widely for several decades, with many advances, but several challenges remain. These challenges include overcoming large meal disturbances, the effects of exercise, and the delays associated with subcutaneous glucose sensing and insulin delivery. 2 One of the most difficult aspects of the diabetes therapy routine is dealing with meals, and it has been shown that inaccurate estimation of meal sizes occurs frequently, resulting in additional glucose fluctuations. 3 Recent behavioral studies have also shown that people with T1DM are interested in an automated system but are concerned with relinquishing full control. 4,5 Therefore, an automatic AP that is safe and robust to daily living conditions and is trusted by the users is critical.The AP is a multilayered device that will contain several features, including a core glucose controller, devices for monitoring of glucose and possibly other biologically relevant compounds or signals, software to interface with the user, safety systems to monitor the status of the system, and telemedicine to convey information about the system to the user and family and/or medical personnel. The core of the AP is the controller, the design of which has been explored by several research teams, with promising results. [6][7][8][9][10][11] Continuous glucose monitoring (CGM) devices and insulin pumps are continually being improved, and are at a performance level that enables automatic control. 12,13 Currently, longer clinical trials with several meals and exercise are being performed with good results. 6,14 Generally, the trials with meals larger than 50 g of carbohydrate (CHO) use a feed-forward approach, announcing meals and giving a full AbstractThe Glucose Rate Increase Detector (GRID), a module of the Health Monitoring System (HMS), has been designed to operate in parallel to the glucose controller to detect meal events and safely trigger a meal bolus. The GRID algorithm was tuned on clinical data with 40-70 g CHO meals and tested on simulation data with 50-100 g CHO meals. Active closed-and open-loop protocols were executed in silico with various treatments, including automatic boluses based on a 75 g CHO meal and boluses based on simulated user input of meal size. An optional function was used to reduce the recommended bolus using recent insulin and glucose history. For closed-loop control of a 3-meal scenario (50, 75, and 100 g CHO), the GRID improved median time in the 80-180 mg/dL range by 17% and in the >180 range by 14% over unannounced meals, using an automatic bolus for a 75 g CHO meal at detection. Under open-loop control of a 75 g CHO meal, the GRID shifted the median glucose peak down by 73 mg/dL and earlier by 120 min and reduced the time >...

show abstract

Patients' Perception and Future Acceptance of an Artificial Pancreas

Cited by 41 publications

References 16 publications

Artificial Pancreas (AP) Clinical Trial Participants' Acceptance of Future AP Technology

Artificial Pancreas (AP) Clinical Trial Participants' Acceptance of Future AP Technology

Poor Numeracy: The Elephant in the Diabetes Technology Room

Design of the Glucose Rate Increase Detector

Contact Info

Product

Resources

About