A randomized controlled trial on a nurse-led smartphone-based self-management programme for people with poorly controlled type 2 diabetes: A study protocol.

AIM: To develop and compare a nurse-led smartphone-based self-management programme with an existing nurse-led diabetes service on health-related outcomes for people with poorly controlled type 2 diabetes in Singapore. BACKGROUND: Over the past decades, Asia has emerged as the "diabetes epicentre" in the world due to rapid economic development, urbanization and nutrition transition. There is an urgent need to develop more effective care management strategies in response to this rising diabetes epidemic. DESIGN: A randomized controlled trial with pre- and repeated posttests control group design. METHODOLOGY: A total of 128 adults with poorly controlled type 2 diabetes will be recruited from the diabetes clinic of a public acute hospital in Singapore through convenience sampling. Study participants will be randomly allocated either to the experimental group or the control group. Outcome measures will include the 10-item General Self-Efficacy Scale, 11-item Revised Summary of Diabetes Self-care Activities and 19-item Diabetes-Dependent Quality of Life. Data will be collected at three time points: baseline, 3 and 6 months from the baseline. DISCUSSION: It is expected that this programme will be an alternative offered to diabetes patients to master their self-care management skills, in addition to the existing diabetes service provided in diabetes clinics in Singapore hospitals. Furthermore, the self-supporting and less resource-intensive nature of this programme, using a smartphone application as the mode of intervention delivery, will greatly reduce nurses' direct contact time with patients and allow more time to be allocated to those who require more attention. The study has been registered with ClinicalTrials.gov. The trial registration number is NCT03088475.

Shape Sensing Techniques for Continuum Robots in Minimally Invasive Surgery: A Survey.

Continuum robots provide inherent structural compliance with high dexterity to access the surgical target sites along tortuous anatomical paths under constrained environments and enable to perform complex and delicate operations through small incisions in minimally invasive surgery. These advantages enable their broad applications with minimal trauma and make challenging clinical procedures possible with miniaturized instrumentation and high curvilinear access capabilities. However, their inherent deformable designs make it difficult to realize 3-D intraoperative real-time shape sensing to accurately model their shape. Solutions to this limitation can lead themselves to further develop closely associated techniques of closed-loop control, path planning, human-robot interaction, and surgical manipulation safety concerns in minimally invasive surgery. Although extensive model-based research that relies on kinematics and mechanics has been performed, accurate shape sensing of continuum robots remains challenging, particularly in cases of unknown and dynamic payloads. This survey investigates the recent advances in alternative emerging techniques for 3-D shape sensing in this field and focuses on the following categories: fiber-optic-sensor-based, electromagnetic-tracking-based, and intraoperative imaging modality-based shape-reconstruction methods. The limitations of existing technologies and prospects of new technologies are also discussed.