With technology advancing rapidly, there is a call for mHealth to move towards more complex technology. However, this study has shown that text messaging—available on any mobile phone—although simple, is still potentially effective for improving glycaemic control. Equally, this study had very few technical difficulties, which probably contributed to the high satisfaction with the intervention. The individual tailoring of the intervention, and ability for participants to choose varying components and dosages, means that questions remain around the ideal duration for implementation as well as the components most important for effectiveness. Further research is needed to understand the components of this intervention that are most effective and the ideal intervention dosage to further refine this intervention and inform the development of future interventions. With participants highly satisfied with the intervention and largely happy with their intervention dosage, but great variance in the modules, durations, and dosages, SMS4BG may need to remain individually tailored in this way, resulting in a more complex intervention for delivery until further investigation on this can be made.
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.
Patients were involved in all stages of the study, including the initial conceptualisation and formative work leading to the development of SMS4BG (for more information, see the development paper28). Patient feedback informed the intervention modality, purpose, and structure, and patients reviewed intervention content before it was finalised. Patient feedback on the acceptability of SMS4BG through the pilot study28 led to improvements to the intervention including additional modules, the option for feedback graphs to be posted, additional tailoring variables, and a longer duration of intervention. Patient feedback also informed the design of this trial—specifically its duration, the inclusion criteria, and recruitment methods. Additionally, patients contributed to workshops of key stakeholders held to discuss interpretation, dissemination of the findings, and potential implementation. We have thanked all participants for their involvement and they will be given access to all published results when these are made publicly available.

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].
Among the intervention participants, 169 (92%) completed questions at follow-up about satisfaction and acceptability of the intervention (table 5). Participants reported high levels of satisfaction with SMS4BG, and all but two participants thought that text messaging was a good way to deliver this type of support. Ten participants reported technical issues while receiving the intervention, most commonly issues replying to the messages (n=4), issues accessing graphs (n=2), and mobile reception issues (n=2).
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