| Title |
Quality of Life and Technology: Impact on Children and Families With Diabetes
|
|---|---|
| Published in |
Current Diabetes Reports, August 2012
|
| DOI | 10.1007/s11892-012-0313-4 |
| Pubmed ID | |
| Authors |
Masakazu Hirose, Elizabeth A. Beverly, Katie Weinger |
| Abstract |
Ensuring quality of life (QOL) while maintaining glycemic control within targets is an important challenge in type 1 and type 2 diabetes treatment. For children with diabetes, QOL includes enjoying meals, feeling safe in school, and perceiving positive, supportive relationships with parents, siblings, and friends. Yet many treatment-related and psychosocial barriers can interfere with a child's QOL and their ability to manage diabetes effectively. Diabetes management also imposes considerable lifestyle demands that are difficult and often frustrating for children to negotiate at a young age. Recent advances in diabetes medications and technologies have improved glycemic control in children with diabetes. Two widely used technologies are the insulin pump and continuous glucose monitoring (CGM) system. These technologies provide patients with more flexibility in their daily life and information about glucose fluctuations. Several studies report improvements in glycemic control in children with type 1 diabetes using the insulin pump or sensor-augmented pump therapy. Importantly, these technologies may impact QOL for children and families with diabetes, although they are rarely used or studied in the treatment of children with type 2 diabetes. Further, emerging closed loop and web- and phone-based technologies have great potential for supporting diabetes self-management and perhaps QOL. A deeper understanding and appreciation of the impact of diabetes technology on children's and parents' QOL is critical for both the medical and psychological care of diabetes. Thus, the purpose of this review is to discuss the impact of new diabetes technologies on QOL in children, adolescents and families with type 1 diabetes. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 201 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 2 | <1% |
| Mexico | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 197 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 28 | 14% |
| Researcher | 25 | 12% |
| Student > Master | 23 | 11% |
| Student > Ph. D. Student | 16 | 8% |
| Student > Postgraduate | 16 | 8% |
| Other | 44 | 22% |
| Unknown | 49 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 54 | 27% |
| Nursing and Health Professions | 30 | 15% |
| Psychology | 22 | 11% |
| Computer Science | 7 | 3% |
| Engineering | 6 | 3% |
| Other | 30 | 15% |
| Unknown | 52 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 August 2012.
All research outputs
#18,534,624
of 22,955,959 outputs
Outputs from Current Diabetes Reports
#783
of 1,015 outputs
Outputs of similar age
#130,189
of 169,585 outputs
Outputs of similar age from Current Diabetes Reports
#21
of 32 outputs
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