Eligible participants were randomised to either an intervention or control group in a 1:1 ratio. Randomisation was stratified by health district category (high urban or high rural/remote), diabetes type (1 or 2), and ethnicity (Māori and Pacific, or non-Māori/non-Pacific). The randomisation sequence was generated by computer programme using variable block sizes of two or four, and overseen by the study statistician. Following participant consent and completion of the baseline interview, the research assistant then randomised the participant to intervention or control, using the REDCap randomisation module. The REDCap randomisation module ensured that treatment allocation was concealed until the point of randomisation. Due to the nature of the intervention, participants were aware of their treatment allocation. Research assistants conducting the phone interviews were also aware of the treatment allocation. However, the objective primary outcome was measured by blinded assessors throughout the study period.
-Keep your blood pressure under control. The same lifestyle changes that control blood glucose levels (dietary modifications and exercise) may also help you keep your blood pressure at safe levels. The American Diabetes Association recommends that people with diabetes keep their blood pressure below 140/80, but check with your health care professional about what target is best for you.
Mobile phone ownership rates are increasing. Similar to trends seen in the United States and Canada, where mobile phone ownership is 72% and 67%, respectively [20], 70% of New Zealanders own a mobile phone, making diabetes apps potentially available to most people [21]. Limited research exists into the use of diabetes apps in New Zealand. However with increasing rates of both diabetes prevalence and mobile phone ownership, access to safe apps is essential for both HPs as potential app prescribers and patients as app users [21,22]. In Scotland, a survey of people with diabetes found high mobile phone ownership (67%) with over half reporting an interest in using apps for self-management of diabetes, but app usage in only 7% of responders [23]. The objectives of this study were (1) To establish whether people with diabetes use apps to assist with diabetes self-management and which features are useful or desirable, and (2) To establish whether HPs treating people with diabetes recommend diabetes apps, which features were thought to be useful, and which features were they confident to recommend.
SMS4BG was delivered in the English language (with the exception of some Māori, Samoan, and Tongan words). With high rates of diabetes in ethnic minority groups, delivery of this type of intervention in languages native to these groups could provide greater benefit. It is likely that some people were not referred to the study, or were unable to take part, due to the criteria that they must be able to read English. SMS health programmes have been translated into other languages such as Te Reo;44 thus, further research needs to look at whether such translations would be of benefit in SMS4BG.
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!

The SMS4BG (self management support for blood glucose) intervention was developed to address the need for innovative solutions to support self management in adults with poorly controlled diabetes.28 The individually tailored intervention provides information and support designed to motivate a person to engage in the behaviours required to manage their diabetes effectively for long term health improvement. The development of SMS4BG followed the mHealth Development and Evaluation Framework29 (including extensive formative work and end user engagement to ensure that it met the needs of the population it was designed to reach) is evidence based and theoretically grounded. A previous pilot study found SMS4BG to be acceptable and perceived it as useful.28 This study aimed to determine the effectiveness of the mHealth diabetes self management support programme—SMS4BG in adults with poorly controlled type 1 or type 2 diabetes, in addition to their usual diabetes care.
Data were imported into SPSS version 24 (IBM). Incomplete responses were included in the analysis. In the patient survey, independent sample t tests were conducted to compare mean clinical variables (age, BP, C:HDL, LDL, HbA1c) by type of diabetes, method of recruitment, and whether the responder used a diabetes mobile phone app. Adjustment was made for unequal variances. Normal distribution was assumed for all variables, apart from urinary microalbumin to creatinine for which a Wilcoxin test was used. No statistically significant differences in these variables or in mobile phone app use were found between patients with recorded email addresses and patients phoned for their email address. Therefore, all 189 responses were combined for further analysis. Chi-square tests were used to compare medications and survey responses by type of diabetes. Statistical significance was determined by exact 2-sided P values less than .05. In the HP survey, mean values on the usefulness and confidence Likert scales were calculated to compare app features.
It is well documented that any reduction in HbA1c is likely to be associated with a decrease in the risk of diabetic complications.38 Reductions in HbA1c are much more clinically important at higher levels, given that the association between vascular complications and HbA1c is non-linear and that similar reductions at lower HbA1c levels have much less effect.383940 In a less ethnically diverse population of people with type 2 diabetes who had levels of HbA1c higher than 6.5% (53 mmol/mol), a decrease of 1% (11 mmol/mol) has been found to result in reduced microvascular complications by 37%, myocardial infarction by 14%, and risk of death by 21%.38 A total of 75% of participants in the intervention group experienced a decrease in HbA1c at nine months, with a mean reduction in HbA1c of 8.9 mmol/mol (0.8%) from baseline, and a significant group difference of 4.2 mmol/mol (0.4%) in favour of the intervention. Therefore, the results in this study have potential to be clinically relevant in reducing the risk of vascular complications and death, although further investigation is needed.
The control group also experienced a decrease in HbA1c from baseline to the nine month follow-up, and experienced improvements in secondary outcomes, which could indicate trial effects. Previous research has shown that recruitment to a clinical trial alone can result in improvements in HbA1c,43 but it is not expected that these improvements would be sustainable past the initial few months without intervention.

The flexibility of mobile phones and their adoption into everyday life mean that they are an ideal tool in supporting people with diabetes whose condition needs constant management. Mobile phones, which have been used effectively to support diabetes management,13141516 offer an ideal avenue for providing care at the patient’s desired intensity. Additionally, they can provide effective methods of support to patients in rural and remote locations where access to healthcare providers can be limited.1718 Although there is growing support for the use of mobile health (mHealth) in diabetes, there is increasing evidence of a digital divide, with lower use of some technologies in specific population groups.1920 These groups include people who have low health literacy,21 have low income,222324 and are members of ethnic minorities.2526 Contributing factors include low technology literacy, mismatch between individual needs and the available tools, lack of local information, cost, literacy and language barriers, and lack of cultural appropriateness.27 For mHealth tools to be used to manage poor diabetes control, they need to be designed to the needs and preferences of those people who need the greatest support by considering these factors.
The A1C is a common blood test that measures the amount of glucose that is attached to the hemoglobin in our red blood cells. It has a variety of other names, including glycated hemoglobin, glycosylated hemoglobin, hemoglobin A1C and HbA1 and is used in the diagnosis and monitoring of diabetes. Unlike the traditional blood glucose test, the A1C does not require fasting, and blood can be drawn at any time of day. It is hoped that this will result in more people getting tested and decreasing the number of people with undiagnosed diabetes, which is currently estimated to be more than 7 million adults in the U.S. (more…)

Data were imported into SPSS version 24 (IBM). Incomplete responses were included in the analysis. In the patient survey, independent sample t tests were conducted to compare mean clinical variables (age, BP, C:HDL, LDL, HbA1c) by type of diabetes, method of recruitment, and whether the responder used a diabetes mobile phone app. Adjustment was made for unequal variances. Normal distribution was assumed for all variables, apart from urinary microalbumin to creatinine for which a Wilcoxin test was used. No statistically significant differences in these variables or in mobile phone app use were found between patients with recorded email addresses and patients phoned for their email address. Therefore, all 189 responses were combined for further analysis. Chi-square tests were used to compare medications and survey responses by type of diabetes. Statistical significance was determined by exact 2-sided P values less than .05. In the HP survey, mean values on the usefulness and confidence Likert scales were calculated to compare app features.
The features most frequently used by current app users were blood glucose diaries (87%, 32/37), followed by carbohydrate/meal diaries (38%, 14/37) with 22% (8/37) reporting insulin dose calculation devices to be useful (Table 3). Table 3 demonstrates the features app users found useful in their current apps. App users reported the most desired feature for future use in an app was an insulin dose calculator (46%, 17/37; Table 4). Table 5 shows that non-app users reported insulin dose calculators to be the third most desired feature (54.6%, n=83/152). Blood glucose diaries were the most desired app feature amongst non-app users (64.4%, 98/152; Table 5). Non app users with T1DM were more likely to desire an insulin dose calculation device, than non-app users with T2DM, P=.01).
Participants could choose to receive blood glucose monitoring reminders to which they could reply by sending in their result by text message. They could then view their results graphically over time on a password protected website. If they were identified as not having access to the internet at baseline they were mailed their graphs once a month. All messages were delivered in English although the Māori version included keywords in Te Reo Māori and the Pacific version had keywords in either Samoan or Tongan dependent on ethnicity. Examples of SMS4BG messages can be seen in the box. Participants were able to select the timing of messages and reminders, and identify the names of their support people and motivations for incorporation into the messages. The duration of the programme was also tailored to individual preferences. At three and six months, participants received a message asking if they would like to continue the programme for an additional three months, and had the opportunity to reselect their modules receiving up to a maximum nine months of messages. Participants could stop their messages by texting the word “STOP” or put messages on hold by texting “HOLIDAY.”

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.

Like my customers, I use an insulin pump to control my diabetes because it allows me to be spontaneous and flexible in managing my diabetes while reducing hypoglycemia. Reaching target blood glucose levels is not always easy, but being a Pharmacist, as well as a Certified Diabetes Educator and Certified Pump Trainer, I know the importance of managing my blood glucose to reduce long-term complications. You are welcome to contact me about any aspect of insulin pump therapy or with any questions about specific insulin pump supplies.
New Zealand has a population of approximately 4.4 million people, the majority being of European descent. Auckland, the largest city in New Zealand, is the most ethnically diverse, with approximately 11% of people identifying themselves as indigenous Maori, 14% as Pacific, and 19% as Asian [12]. By international standards, the incidence of type 1 diabetes in young New Zealanders was assessed as moderate at 17.9 per 100,000 [13]. However, this figure was obtained from a 2-year snapshot, and did not provide information on possible time trends on type 1 diabetes incidence. In addition, previous studies on type 1 diabetes incidence in New Zealand are out of date or refer to a specific geographical region [14], [15], [16].

Height and weight were recorded for 660 patients at their required first post-diagnostic clinic (on average 15 weeks from diagnosis) from 1994 onwards. Annual mean BMI SDS of newly diagnosed type 1 diabetes did not alter (average non-significant change smaller than ±0.02 SDS/year) over the period for the entire population, or for any gender, age, or ethnicity sub-group. There was no association between BMI SDS and age at diagnosis.
In contrast with the extensive app problems presented in the literature, over half of the responders with an app reported no problems [5,11-13,15]. This discrepancy may be due to false self-report or responders may have tried multiple apps before finding the one they like. Our study is unable to add significantly to literature about insulin dose calculation problems [15], as only 7 responders reported using their app for insulin calculation. However it is notable that this feature is desired by users and reinforces the importance of having a regulated environment to ensure safety.
Data were imported into SPSS version 24 (IBM). Incomplete responses were included in the analysis. In the patient survey, independent sample t tests were conducted to compare mean clinical variables (age, BP, C:HDL, LDL, HbA1c) by type of diabetes, method of recruitment, and whether the responder used a diabetes mobile phone app. Adjustment was made for unequal variances. Normal distribution was assumed for all variables, apart from urinary microalbumin to creatinine for which a Wilcoxin test was used. No statistically significant differences in these variables or in mobile phone app use were found between patients with recorded email addresses and patients phoned for their email address. Therefore, all 189 responses were combined for further analysis. Chi-square tests were used to compare medications and survey responses by type of diabetes. Statistical significance was determined by exact 2-sided P values less than .05. In the HP survey, mean values on the usefulness and confidence Likert scales were calculated to compare app features.

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 control group also experienced a decrease in HbA1c from baseline to the nine month follow-up, and experienced improvements in secondary outcomes, which could indicate trial effects. Previous research has shown that recruitment to a clinical trial alone can result in improvements in HbA1c,43 but it is not expected that these improvements would be sustainable past the initial few months without intervention.


Hi neighbours! Make the perfect pet bed for your furry friend that works with your décor. It's easy to make a handmade rope basket using touches of your favourite Resene colours with Resene testpots. Choose colours to suit your room’s colour scheme and match with your furry best friend! Make the most of your weekend with this easy step by step project idea from Resene. Find out how to create this quick and easy project yourself.
×