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OBJECTIVEStructured patient education programs can reduce the risk of diabetes-related complications. However, people appear to have difficulties attending face-to-face education and alternatives are needed. This review looked at the impact of computerbased diabetes self-management interventions on health status, cardiovascular risk factors, and quality of life of adults with type 2 diabetes. RESEARCH DESIGN AND METHODSWe searched The Cochrane Library, Medline, Embase, PsycINFO, Web of Science, and CINAHL for relevant trials from inception to November 2011. Reference lists from relevant published studies were screened and authors contacted for further information when required. Two authors independently extracted relevant data using standard data extraction templates. RESULTSSixteen randomized controlled trials with 3,578 participants met the inclusion criteria. Interventions were delivered via clinics, the Internet, and mobile phones. Computerbased diabetes self-management interventions appear to have small benefits on glycemic control: the pooled effect on HbA 1c was 20.2% (22.3 mmol/mol [95% CI 20.4 to 20.1%]). A subgroup analysis on mobile phone-based interventions showed a larger effect: the pooled effect on HbA 1c from three studies was 20.50% (25.46 mmol/mol [95% CI 20.7 to 20.3%]). There was no evidence of improvement in depression, quality of life, blood pressure, serum lipids, or weight. There was no evidence of significant adverse effects. CONCLUSIONSComputer-based diabetes self-management interventions to manage type 2 diabetes appear to have a small beneficial effect on blood glucose control, and this effect was larger in the mobile phone subgroup. There was no evidence of benefit for other biological, cognitive, behavioral, or emotional outcomes.The burden of diabetes is growing, with 347 million people currently affected worldwide (1) and numbers projected to increase to 552 million by 2030 (2). The International Diabetes Federation suggests that in the developed world, the cost of caring for patients with diabetes is double that of the background population, and

BackgroundThe prevalence of type 2 diabetes is increasing globally, and health services in many countries are struggling with the morbidity, mortality, and costs associated with the complications of this long-term condition. Diabetes self-management education (DSME) and behavioral support can reduce the risks of developing diabetes-related complications and improve glycemic control. However, their uptake is low. Digital health interventions (DHI) can provide sustained support and may overcome challenges associated with attending diabetes self-management sessions. They have the potential for delivery at multiple locations at convenient times, anonymity, and presentation of content in attractive and tailored formats. This study investigates the needs and wants of patients with type 2 diabetes to inform the development of digital self-management education and support.ObjectiveThe objective of this study was to explore patient perspectives on unmet needs for self-management and support and the role of DHI in adults living with type 2 diabetes.MethodsThis study used a qualitative approach based on data generated from 4 focus groups with 20 patients.ResultsThe data generated by the focus groups illustrated the significant burden that the diagnosis of diabetes places on many patients and the negative impacts on their emotional well-being, work, social life, and physical health. Although patients’ experiences of the health care services varied, there was agreement that even the best services were unable to meet all users’ needs to support the emotional regulation, psychological adjustment, and behavioral changes needed for successful self-management.ConclusionsBy focusing on medical management and information provision, existing health care services and education programs may not be adequately meeting all the needs of patients with type 2 diabetes. DHIs have the potential to improve access to DSME and behavioral support and extend the range of content offered by health services to fit with a wider range of patient needs. Features that could help DHIs address some of the unmet needs described by participants in this study included placing an emphasis on emotional and role management, being available at all times, having up-to-date evidence-based guidance for patients, and providing access to peer-generated and professional advice.

PurposeWe aimed to quantify the relative risk of progression from mild cognitive impairment (MCI) to dementia in people with and without diabetes, and with and without the MetS (MetS); and to identify potential modifiers of the risk of progression from MCI to dementia in people with diabetes or MetS.MethodsWe searched Medline, Embase, PsycINFO, PsycArticles and Web of Science from inception through to 20th March 2018. Where possible, the results from three or more studies were pooled in a meta-analysis, while other findings have been described narratively.ResultsWe included 15 articles reporting 12 studies (6865 participants). The overall unadjusted pooled odds ratio for the progression of MCI to dementia in people with diabetes/MetS was 1.67 (95% CI 1.27–2.19); the pooled odds ratio for progression in diabetes + MCI was 1.53 (95% CI 1.20–1.97) and in people with MetS + MCI was 2.95 (95% CI 1.23–7.05). There was moderate heterogeneity in the included studies (I2 < 60%). In diabetes, a longer duration of diabetes and the presence of retinopathy were associated with an increased risk of progression, while the use of statins and oral hypoglycaemic agents reduced the risk. Having multiple cardiovascular risk factors was a significant risk factor for progression from MCI to dementia in people with MetS.ConclusionsDiabetes and MetS were both associated with an increased incidence of dementia when co-existing with MCI. Intensive cardiovascular risk reduction and lifestyle changes for patients presenting with MCI and diabetes, prediabetes or MetS may be important in reducing incidence of dementia in this high risk population.Electronic supplementary materialThe online version of this article (10.1007/s00127-018-1581-3) contains supplementary material, which is available to authorized users.

Christian 2008 {published data only} Christian JG, Bessesen DH, Byers TE, Christian KK, Goldstein MG, Bock BC. Clinic-based support to help overweight patients with type 2 diabetes increase physical activity and lose weight. Archives of Internal Medicine 2008; 168(2):141-6. Glasgow 1997 {published data only} Glasgow RE, La Chance PA, Toobert DJ, Brown J, Hampson SE, Riddle MC. Long-term effects and costs of brief behavioural dietary intervention for patients with diabetes delivered from the medical office. Patient Education and Counselling 1997;32(3):175-84. Glasgow 2003 {published data only} Glasgow RE, Boles SM, Mckay HG, Feil EG, Barrera M. The D-Net diabetes self-management program: longterm implementation, outcomes and generalization results.

BackgroundEvidence on how to implement new interventions into complex healthcare environments is often poorly reported and indexed, reducing its potential to inform initiatives to improve healthcare services. Using the implementation of a digital intervention within routine National Health Service (NHS) practice, we provide an example of how to develop a theoretically based implementation plan and how to report it transparently. In doing so we also highlight some of the challenges to implementation in routine healthcare.MethodsThe implemented intervention was HeLP-Diabetes, a digital self-management programme for people with Type 2 Diabetes, which was effective in improving diabetes control. The target setting for the implementation was an inner city London Clinical Commissioning Group in the NHS comprised of 34 general practices. HeLP-Diabetes was designed to be offered to patients as part of routine diabetes care across England. Evidence synthesis, engagement of local stakeholders, a theory of implementation (Normalization Process Theory), feedback, qualitative interviews and usage data were used to develop an implementation plan.ResultsA new implementation plan was developed to implement HeLP-Diabetes within routine practice. Individual component strategies were selected and developed informed by Normalization Process Theory. These strategies included: engagement of local opinion leaders, provision of educational materials, educational visits, educational meetings, audit and feedback and reminders. Additional strategies were introduced iteratively to address barriers that arose during the implementation. Barriers largely related to difficulties in allocating resources to implement the intervention within routine care.ConclusionThis paper provides a worked example of implementing a digital health intervention. The learning from this work can inform others undertaking the work of planning and executing implementation activities in routine healthcare. Of particular importance is: the selection of appropriate theory to guide the implementation process and selection of strategies; ensuring that enough attention is paid to planning implementation; and a flexible approach that allows response to emerging barriers.Electronic supplementary materialThe online version of this article (10.1186/s12913-018-3615-7) contains supplementary material, which is available to authorized users.

ObjectiveTo determine the effectiveness of a web-based self-management programme for people with type 2 diabetes in improving glycaemic control and reducing diabetes-related distress.Methods and designIndividually randomised two-arm controlled trial.Setting21 general practices in England.ParticipantsAdults aged 18 or over with a diagnosis of type 2 diabetes registered with participating general practices.Intervention and comparatorUsual care plus either Healthy Living for People with Diabetes (HeLP-Diabetes), an interactive, theoretically informed, web-based self-management programme or a simple, text-based website containing basic information only.Outcomes and data collectionJoint primary outcomes were glycated haemoglobin (HbA1c) and diabetes-related distress, measured by the Problem Areas in Diabetes (PAID) scale, collected at 3 and 12 months after randomisation, with 12 months the primary outcome point. Research nurses, blind to allocation collected clinical data; participants completed self-report questionnaires online.AnalysisThe analysis compared groups as randomised (intention to treat) using a linear mixed effects model, adjusted for baseline data with multiple imputation of missing values.ResultsOf the 374 participants randomised between September 2013 and December 2014, 185 were allocated to the intervention and 189 to the control. Final (12 month) follow-up data for HbA1c were available for 318 (85%) and for PAID 337 (90%) of participants. Of these, 291 (78%) and 321 (86%) responses were recorded within the predefined window of 10–14 months. Participants in the intervention group had lower HbA1c than those in the control (mean difference −0.24%; 95% CI −0.44 to −0.049; p=0.014). There was no significant overall difference between groups in the mean PAID score (p=0.21), but prespecified subgroup analysis of participants who had been more recently diagnosed with diabetes showed a beneficial impact of the intervention in this group (p = 0.004). There were no reported harms.ConclusionsAccess to HeLP-Diabetes improved glycaemic control over 12 months.Trial registration numberISRCTN02123133.

Background Digital health interventions have potential to contribute to better health outcomes, better healthcare and lower costs. However, evidence for their effectiveness is variable. The development and content of digital health interventions are often not described in enough detail to enable others to replicate the research or improve on previous interventions. This has led to a call for transparent reporting of intervention content and development. Purpose To describe the development process and content of a digital self-management intervention for people with type 2 diabetes (HeLP-Diabetes) that has been found to achieve its target clinical outcome, the reduction of HbA1c, a measure of glycaemic control. Method We synthesised theory, data from existing research evidence and international guidelines, and new qualitative data from target users to identify the determinants of self-management and the content to be included in HeLP-Diabetes. Using an ongoing iterative participatory design approach the content of the intervention was written, produced, reviewed and changed. Conclusion It is possible to develop and transparently report self-management programmes for long-term conditions, which reflect current best evidence, theoretical underpinning and user involvement. We intend that reporting the development process and content will inform future digital intervention development.