The message delivery was managed by our content management system, with messages sent and received through a gateway company to allow for participants to be registered with any mobile network. Sending and receiving messages was free for participants. The system maintained logs of all outgoing and incoming messages. Further details of the intervention can be seen in the published pilot study,28 and protocol.30

The Endocrinology Service at Starship Children's Health provides specialist care for all children diagnosed with type 1 diabetes in the Auckland region (New Zealand). Its Paediatric Diabetes Service provides centralised medical care for all diabetic children up to 15 yr who reside in the Auckland region, drawing from the regional population of approximately 1.5 million [12]. All children or adolescents diagnosed with type 1 diabetes who attended the Paediatric Service between 1 January 1990 and 31 December 2009 were eligible for this study. Subjects were captured from a comprehensive database (Starbase) that gathers data on all children with type 1 diabetes in the Auckland region. This information was cross-referenced with hospital admission data and subsequent clinical follow up, leading to a case ascertainment >95% for children with type 1 diabetes [13].
ED is a failure to obtain/maintain penile erection sufficient for intercourse is more prevalent in men with diabetes and increases with age.  It is important to distinguish erectile failure from premature ejaculation, decreased libido and other problems as these have different causes and treatment. ED in diabetes is largely due to failure of vascular smooth muscle relaxation secondary to endothelial dysfunction and/or autonomic neuropathy.

This study found that a tailored, theoretically based, SMS based, diabetes self management support programme led to modest improvements in glycaemic control. The effects of intervention were also seen in four of 21 secondary outcomes, including foot care behaviour and ratings of diabetes support. The programme showed a high level of acceptability with the overwhelming majority of participants finding the intervention useful and willing to recommend it to others.


Only children aged <15 yr were included. Type 1 diabetes was diagnosed based on clinical features. All patients had elevated blood glucose at presentation: either a random measurement of ≥11.1 mmol/l and presence of classical symptoms, or fasting blood glucose ≥7.1 mmol/l. In addition, all patients met at least one of the following criteria: a) diabetic ketoacidosis; b) presence of at least two type 1 diabetes antibodies (to glutamic acid decarboxylase, islet antigen 2, islet cell, or insulin autoantibodies); or c) ongoing requirement for insulin therapy. Clinical and demographic data were prospectively recorded on all patients at each outpatient visit.

Similar to a national American mHealth survey, a large proportion of patients are not using health apps [26]. However, there was a higher rate (20%) of diabetes app use in this patient group compared to the 4% found in a survey of diabetes app use in the USA in 2015 [14] and 7% in Scotland in 2016 [23]. Our findings are consistent with previous surveys showing people using apps are more likely to be younger [26]. It has been suggested that people who are more in need of diabetes care are less likely to use apps [27]; however, we found no significant difference in HbA1c between app users and non-app users. The most favored feature being the blood glucose diary is not surprising given it is the most common feature included in the apps available [5,14]. However some responders are also using health apps that are not specific to diabetes, such as apps for dietary advice.


Strengths of the intervention were that it was theoretically based, the information reinforced messages from standard care, and it was system initiated, personally tailored, and used simple technology. These strengths result in high relevance to diverse individuals, increasing the intervention’s reach and acceptability. Unlike SMS4BG, previous diabetes SMS programmes have largely focused on specific groups—for example, limiting their generalisability. Furthermore, the SMS4BG intervention was tailored and personalised to the individual. Although this specificity results in a more complex intervention in relation to its delivery, it appears to be a worthwhile endeavour with high satisfaction and the majority of participants happy with their message dosage.
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.
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 majority of responders were not using diabetes apps (80.4%, 152/189), although 60.5% (89/147) reported they would be interested in trying one. Of the 118 people who answered the question, the reasons for not using an app was not knowing they existed (66.9%, 79/118), feeling confident without one (16.9%, 20/118), discontinued use after having used an app previously 16.9% (20/118).
Strengths of the intervention were that it was theoretically based, the information reinforced messages from standard care, and it was system initiated, personally tailored, and used simple technology. These strengths result in high relevance to diverse individuals, increasing the intervention’s reach and acceptability. Unlike SMS4BG, previous diabetes SMS programmes have largely focused on specific groups—for example, limiting their generalisability. Furthermore, the SMS4BG intervention was tailored and personalised to the individual. Although this specificity results in a more complex intervention in relation to its delivery, it appears to be a worthwhile endeavour with high satisfaction and the majority of participants happy with their message dosage.
This cross-sectional observational study used two surveys (see Multimedia Appendices 1 and 2), one for people with diabetes attending a secondary care diabetes outpatient clinic and the second for HPs (who treat people with diabetes) attending a national diabetes conference. Both surveys were multi-choice format, collected, and managed using REDCap electronic data capture tools. REDCap (Research Electronic Data Capture) is a secure, Web-based app designed to support data capture for research studies [24]. The survey questions were derived from criteria in the Mobile app rating scale [25] to address attitudes and practices of both the people with diabetes and HPs. The list of apps was compiled by searching Apple and Android App stores and included the first consecutive ten diabetes apps. We eliminated any apps not specific to diabetes by reviewing app store descriptions. We reviewed the main features from these apps to develop the list of app features. The patient survey asked responders to select any useful app features from a list. Responders could select more than one useful app feature. The HP survey listed app features and used a scale to assess usefulness of app features (from 1 [not at all useful] to 5 [extremely useful]) and their confidence in recommending apps (from 1 [not at all confident] to 5 [extremely confident]).
Of the 189 responders (35.0% response rate) to the patient survey, 19.6% (37/189) had used a diabetes app. App users were younger and in comparison to other forms of diabetes mellitus, users prominently had type 1 DM. The most favored feature of the app users was a glucose diary (87%, 32/37), and an insulin calculator was the most desirable function for a future app (46%, 17/37). In non-app users, the most desirable feature for a future app was a glucose diary (64.4%, 98/152). Of the 115 responders (40.2% response rate) to the HPs survey, 60.1% (68/113) had recommended a diabetes app. Diaries for blood glucose levels and carbohydrate counting were considered the most useful app features and the features HPs felt most confident to recommend. HPs were least confident in recommending insulin calculation apps.
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!
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