Conclusion A tailored, text message based, self management support programme resulted in modest improvements in glycaemic control in adults with poorly controlled diabetes. Although the clinical significance of these results is unclear, the findings support further investigation into the use of SMS4BG and other text message based support for this patient population.
Owing to individual tailoring, participants in the intervention group received varying numbers of messages. Half the participants (92/183) received messages for three months, an additional 18% (33/183) chose to continue the messages for six months, and the remaining 32% (58/183) chose to continue the messages to the maximum nine months. Only three participants chose to stop their messages early. A total number of 76 523 messages were sent by the system to participants (median number of messages per participant 242 (interquartile range 122-511; range 14-2050)), and 16 251 messages of blood glucose results were sent into the system by participants receiving the reminders (68 (1-169; 0-917)).
-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.
There are three forms of the disease. People with Type 1 Diabetes typically make none of their own insulin and therefore require insulin injections for survival. People with Type 2 Diabetes, the form that comprises the majority of all cases, usually produce their own insulin, but not enough or they are unable to use it properly. Then there is Gestational Diabetes; globally, 1 in 7 births is affected by gestational diabetes. While maternal blood glucose levels usually return to normal after the baby is born, there is an increased risk of both mother and child developing Type 2 Diabetes later in life.
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.
Statistical analyses were performed by SAS version 9.4 (SAS Institute). All statistical tests were two sided at a 5% significance level. Analyses were performed on the principle of intention to treat, including all randomised participants who provided at least one valid measure on the primary outcome after randomisation. Demographics and baseline characteristics of all participants were first summarised by treatment group with descriptive statistics. No formal statistical tests were conducted at baseline, because any baseline imbalance observed between two groups could have occurred by chance with randomisation.
Diabetes mellitus (DM) requires tight control of blood glucose to minimize complications and mortality [1,2]. However, many people with DM have suboptimal glycemic control [3,4]. Use of mobile phone apps in diabetes management has been shown to modestly improve glycemic control [5-10]. Despite this promise, health apps remain largely unregulated, and diabetes apps have not always had safety approval [11] or incorporated evidence-based guidelines [12,13].
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.

Interventions The intervention group received a tailored package of text messages for up to nine months in addition to usual care. Text messages provided information, support, motivation, and reminders related to diabetes self management and lifestyle behaviours. The control group received usual care. Messages were delivered by a specifically designed automated content management system.
Strengths of the current study included its sample size, diverse population, very low loss to follow-up, pragmatic design, absence of protocol violations, and objectively measured primary outcome. Although the initial sample size target was not reached, the final sample of 366 participants is larger than previous randomised controlled trials in this area. This study contributes valuable evidence to the literature on the use of text messages in diabetes particularly for individuals with poor control. Considering poorer outcomes are experienced by ethnic minority groups, a strength of this study was its high proportion of participants representing these groups.
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.
Nearly half of American adults have diabetes or prediabetes; more than 30 million adults and children have diabetes; and every 21 seconds, another individual is diagnosed with diabetes in the U.S. Founded in 1940, the American Diabetes Association (ADA) is the nation’s leading voluntary health organization whose mission is to prevent and cure diabetes, and to improve the lives of all people affected by diabetes. The ADA drives discovery by funding research to treat, manage and prevent all types of diabetes, as well as to search for cures; raises voice to the urgency of the diabetes epidemic; and works to safeguard policies and programs that protect people with diabetes. In addition, the ADA supports people living with diabetes, those at risk of developing diabetes, and the health care professionals who serve them through information and programs that can improve health outcomes and quality of life. For more information, please call the ADA at 1-800-DIABETES (1-800-342-2383) or visit diabetes.org. Information from both of these sources is available in English and Spanish. Find us on Facebook (American Diabetes Association), Twitter (@AmDiabetesAssn) and Instagram (@AmDiabetesAssn)
Pedicures may seem like a modern indulgence, but they actually date back more than 4,000 years to the ancient Babylonians. The word pedicure comes from the Latin “pes” for foot and “cura” for care. Originally practiced to prevent foot problems, today, more popular than ever, pedicures combine nail and skin care with a relaxing and self-pampering experience enjoyed not only by women but more and more by men, also.   (more…)
To assess whether changes in incidence were more marked in certain age groups (as observed overseas [3], [4]), patients were also categorised into three bands according to age at diagnosis: 0–4 yr (children less than 5 yr), 5–9 yr (equal or greater than 5 yr but less than 10 yr), and 10–14 yr (equal or greater than 10 yr but less than 15 yr). These age bands also match national census classifications. The incidence of type 1 diabetes was assessed as the number of new diagnoses per 100,000 age-matched inhabitants on a given year, based on the 5-yearly national census data from Statistics New Zealand [12] and interpolated estimates of the population for the intervening years. Incidence was modelled using the Poisson distribution. Point estimates were calculated with exact Poisson confidence limits, and change in incidence over time were analysed using Poisson regression. Changes in patient numbers, age at diagnosis, and anthropometric data over time were assessed by linear regression. Poisson modelling was undertaken using StatsDirect v2.7.8 (StatsDirect Ltd, UK); other analyses were undertaken using JMP v. 5.1 (SAS Inc, USA).
The 1177 people with diabetes attending clinics at Capital and Coast District Health Board (CCDHB), Wellington, New Zealand over a 12-month period (10th September 2014 to 10th September 2015) were the sample population. Out of the total patients, 521 patients with an email address in the hospital management system were invited to participate via email. To include a representation of people without a recorded email address in the sample (n=656), every 5th person was telephoned (up to twice) and invited to provide an email address. Of the 131 patients telephoned, 54 (41.2%) were reached, of whom 49 (91%) agreed to participate. Patients without phone numbers or unable to provide an email address were excluded. This generated a sample population of 570 people.

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.
In relation to perceptions and beliefs about diabetes, a significant reduction in illness identity (how much patients experience diabetes related symptoms) on the BIPQ was observed in favour of the intervention (adjusted mean difference −0.54 (95% confidence interval −1.04 to −0.03), P=0.04). However, we saw no significant group differences for perceptions of consequences, timeline, control, concern, emotions, and illness comprehensibility. A significant improvement in health status on the EQ-5D VAS was observed in favour of the intervention (4.38 (0.44 to 8.33), P=0.03) but no significant differences were observed between groups for the quality of life index score. Finally, the measure of perceived support for diabetes management showed a significant improvement between the groups in how supported the participants felt in relation to their diabetes management overall (0.26 (0.03 to 0.50), P=0.03) but no significant group differences on appraisal, emotional, and informational support.
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 use of apps to record blood glucose was the most favored function in apps used by people with diabetes, with interest in insulin dose calculating function. HPs do not feel confident in recommending insulin dose calculators. There is an urgent need for an app assessment process to give confidence in the quality and safety of diabetes management apps to people with diabetes (potential app users) and HPs (potential app prescribers).
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.
This study shows app usage is relatively low among people with diabetes, while 60.2% of HPs have recommended an app to patients. There is, however, interest amongst people with diabetes and HPs to use diabetes apps, with strong interest in an insulin dose calculator. Apps with this feature have the potential to improve diabetes control. However, the critical problem of app safety remains a barrier to the prescription and use of insulin dose calculators. Further work is needed to ensure apps are safe and provided in a regulated environment. An app assessment process would provide HPs with confidence in the apps they recommend and would ultimately ensure app quality and safety for app users. At present, however, app users and HPs must remain cautious with diabetes apps, especially those in the insulin dose calculator category.

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).
In conclusion, there has been a steady increase in type 1 diabetes incidence in children <15 yr in Auckland over a 20-year span. However, in contrast to observations elsewhere, age at diagnosis in Auckland has increased over the study period. Our data do not support the ‘accelerator hypothesis’, and factors other than simply increasing adiposity are likely to be at play.
“It was fantastic for me to have all this information on the screen so I didn’t need to look it up. It means that I can see the latest results and any patterns that emerge on screen, without having to look them up, and yet I can interact with Ellen and the patient as I have a really good picture and good sound. At first, I was worried that the telehealth clinic would be too impersonal but it isn’t and the patients get quickly familiar with the setup and seeing and talking to me onscreen.”
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