This study showed that a tailored and automated SMS self management support programme has potential for improving glycaemic control in adults with poorly controlled diabetes. Although the clinical significance of these results is unclear, and the full duration of these effects is yet to be determined, exploration of SMS4BG to supplement current practice is warranted.
We saw no significant interaction between the treatment group and any of the prespecified subgroups: type 1 versus type 2 diabetes (P=0.82), non-Māori/non-Pacific versus Māori/Pacific ethnicity (P=0.60), high urban versus high rural/remote region (P=0.38). Adjusted mean differences on change in HbA1c from baseline to nine months for patients with type 1 and type 2 diabetes were −5.75 mmol/mol (95% confidence interval −10.08 to −1.43, P=0.009) and −3.64 mmol/mol (−7.72 to 0.44, P=0.08), respectively. Adjusted mean differences for non-Māori/non-Pacific and Māori/Pacific people were −4.97 mmol/mol (−8.51 to −1.43, P=0.006) and −3.21 mmol/mol (−9.11 to 2.70, P=0.28), respectively. Adjusted mean differences for participants living in high urban and high rural/remote areas were −4.54 mmol/mol (−8.40 to −0.68, P=0.02) and −3.94 mmol/mol (−9.00 to 1.12, P=0.13), respectively (table 3).
Diabetes Depot carries a full line insulin pump supplies, including all major insulin infusions sets, insulin reservoirs and cartridges available in Canada, all at significant discounts below the manufacturer's list price. Our product line of diabetic supplies, required daily by people living with diabetes, include blood glucose meters, glucose test strips, lancets, insulin pen needles, insulin products, Dex-4 glucose tablets and Emla anesthetic cream. We also carry accessories such as pump clips, pump cases & pouches, prep pads, battery caps, diabetic socks, and helpful books on diabetes… everything an insulin pump user would require. Plus, because the Diabetes Depot is located within Stutt's Pharmacy, we also offer a complete prescription service.
Main outcome measures Primary outcome measure was change in glycaemic control (HbA1c) from baseline to nine months. Secondary outcomes included change in HbA1c at three and six months, and self efficacy, diabetes self care behaviours, diabetes distress, perceptions and beliefs about diabetes, health related quality of life, perceived support for diabetes management, and intervention engagement and satisfaction at nine months. Regression models adjusted for baseline outcome, health district category, diabetes type, and ethnicity.

We’ll also teach you what to do with everything you’re learning. Using the latest research and stories from people with diabetes, we’ll help you make small changes through short videos and simple action items. Soon, you’ll be seeing results, feeling better and having more energy. Many people with diabetes say that they’re healthier NOW than they were before they were diagnosed– you can be one of them!


This study contributes to the evidence around the use of SMS to support diabetes management.131415 The improvements in HbA1c seen in this study are similar to those reported in meta-analyses of SMS interventions in diabetes not limited to those with poor control.141641 Unlike previous studies that typically focus on a particular population defined by diabetes type, age, or treatment, the current study provided an intervention for all adults with either type 1 or type 2 diabetes under any treatment regimen, enhancing potential reach and generalisability. The only limit on the population was the requirement that participants had to have poor diabetes control. This criterion was particularly important given associated costs and debilitating complications of poorly controlled diabetes. Although few trials so far have examined the effectiveness of mHealth interventions in this population,42 this study provides evidence to support the use of this modality to provide diabetes education and support to individuals with poor control.
In Type 1 Diabetes, symptoms are often sudden and can be life-threatening; therefore it is usually diagnosed quite quickly. In Type 2 Diabetes, many people have no symptoms at all, while other signs can go unnoticed, being seen as part of ‘getting older’. Therefore, by the time symptoms are noticed, complications of diabetes may already be present.
The reasons underpinning the considerable increase in incidence over the study period are unclear. This may reflect an actual change in the type 1 diabetes incidence in patients <15 yr. Alternatively, it may reflect an earlier age of onset without change in incidence over all ages, so that greater numbers of people are being diagnosed with type 1 diabetes in adolescence rather than in young adulthood. This would be consistent with the ‘accelerator hypothesis’, which suggests that an increasing rate of obesity is a primary driver for an earlier age of diabetes onset [6]. Studies have shown an association between higher BMI and younger age at diagnosis [9], [10], [11], indicating greater adiposity in childhood may hasten the onset of diabetes mellitus. The ‘accelerator hypothesis’ predicts an early onset rather than increased risk [11], and a Swedish study examining type 1 diabetes incidence on a nation-wide cohort 0–34 yr showed a shift in age of onset towards younger ages, rather than an increase in incidence per se across the whole population [20]. Although we cannot rule out a similar phenomenon in Auckland, we did not observe an increase in BMI SDS among children recently diagnosed with type 1 diabetes, or an association between BMI SDS and age at diagnosis. In fact, we observed an actual increase in age at diagnosis which is inconsistent with the ‘accelerator hypothesis’. Thus, our data suggest a true increase in the incidence of type 1 diabetes in the Auckland region, and not changes driven by increasing adiposity.
The survey was piloted with the first 30 patients with an email addresses (chronological order of clinic visits). Responses were reviewed after response rate reached 50%. As 4 questions were unanswered by some participants, a “none of the above” option was added. The invitations were sent out to the remaining 540 participants. A further 31 participants were excluded (4 email address errors, 13 gestational diabetes, 10 deceased, 4 did not have diabetes) resulting in a final total of 539 participants. This survey remained open for 3 weeks, with reminders sent to non-responders at one week and two weeks.
Almost two-thirds of HPs responding had recommended a diabetes app to patients. Dieticians were more likely to recommend an app than others. Blood glucose and carbohydrate diaries were considered the most useful feature and HPs were most confident to recommend blood glucose diaries. HPs are the least confident recommending insulin dose calculation functions. Over one-third of HPs desire guidance with app recommendations.
Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: support from Waitemata District Health Board for the development of SMS4BG, and support from the Health Research Council of New Zealand in partnership with the Waitemata District Health Board and Auckland District Health Board, and the New Zealand Ministry of Health for the randomised controlled trial; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.
There are a variety of mobile apps for people with diabetes. They can be a useful way to learn about and take control of your diabetes. Many apps have features that enable you to record your blood glucose levels, food, medication and physical activity. By looking for patterns or trends in your results and discussing them with your healthcare team, you can learn how to make changes to your diabetes management plan and better manage your diabetes. The Health Navigator team have reviewed some diabetes apps that you might to consider.   

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