Diabetes Prevention Interventions Research Articles

The essential role of exercise in the management of type 2 diabetes.

Exercise is typically one of the first management strategies advised for patients newly diagnosed with type 2 diabetes. Together with diet and behavior modification, exercise is an essential component of all diabetes and obesity prevention and lifestyle intervention programs. Exercise training, whether aerobic or resistance training or a combination, facilitates improved glucose regulation. High-intensity interval training is also effective and has the added benefit of being very time-efficient. While the efficacy, scalability, and affordability of exercise for the prevention and management of type 2 diabetes are well established, sustainability of exercise recommendations for patients remains elusive.

Determinants of lifestyle behavior change to prevent type 2 diabetes in high-risk individuals

BackgroundAlthough there are many effective lifestyle interventions for type 2 diabetes (T2DM) prevention, insight into effective intervention pathways, especially of long-term interventions, is often lacking. This study aims to provide insight into the effective intervention pathways of the SLIMMER diabetes prevention intervention using mediation analyses.MethodsIn total, 240 participants at increased risk of T2DM were included in the analyses over 18 months. The intervention was a combined lifestyle intervention with a dietary and a physical activity (PA) component. The primary and secondary outcomes were change in fasting insulin (pmol/L) and change in body weight (kg) after 18 months, respectively. Firstly, in a multiple mediator model, we investigated whether significant changes in these outcomes were mediated by changes in dietary and PA behavior. Secondly, in multiple single mediator models, we investigated whether changes in dietary and PA behavior were mediated by changes in behavioral determinants and the participants’ psychological profile. The mediation analyses used linear regression models, where significance of indirect effects was calculated with bootstrapping.ResultsThe effect of the intervention on decreased fasting insulin was 40% mediated by change in dietary and PA behavior, where dietary behavior was an independent mediator of the association (34%). The effect of the intervention on decreased body weight was 20% mediated by change in dietary and PA behavior, where PA behavior was an independent mediator (17%). The intervention significantly changed intake of fruit, fat from bread spread, and fiber from bread. Change in fruit intake was mediated by change in action control (combination of consciousness, self-control, and effort), motivation, self-efficacy, intention, and skills. Change in fat intake was mediated by change in action control and psychological profile. No mediators could be identified for change in fiber intake. The change in PA behavior was mediated by change in action control, motivation, and psychological profile.ConclusionThe effect of the SLIMMER intervention on fasting insulin and body weight was mediated by changes in dietary and PA behavior, in distinct ways. These results indicate that changing dietary as well as PA behavior is important in T2DM prevention.

A narrative systematic review of factors affecting diabetes prevention in primary care settings.

BackgroundType 2 diabetes is impacting millions of people globally; however, many future cases can be prevented through lifestyle changes and interventions. Primary care is an important setting for diabetes prevention, for at-risk populations, because it is a patient’s primary point of contact with the health care system and professionals can provide lifestyle counselling and support, as well as monitoring health outcomes. These are all essential elements for diabetes prevention for at-risk adults.AimTo understand the factors related to the delivery and uptake of type 2 diabetes prevention interventions within primary care in higher income countries.MethodsFor this narrative systematic review, we combined qualitative and quantitative studies of diabetes prevention within a primary care setting for patients at-risk of developing the condition. We used an iterative approach for evidence collection, which included using several databases (MEDLINE, Embase, Pysch info, BNI, SSCI, CINAHL, ASSIA), where we combined diabetes terms with primary care terms. Narrative and thematic synthesis were utilised to identify the prominent themes emerging from the data.ResultsA database of 6646 records was screened by the research team, and 18 papers were included. Three major themes were identified in this review. The first theme of context and setting of diabetes progression includes the risk and progression of diabetes, primary care as a setting, and where the responsibility for change is thought to lie. This review also found mixed views on the value of preventative services within primary care. The second theme focused on the various patient factors associated with diabetes prevention such as a patient’s motivation to modify their current lifestyle, perceptions and knowledge (or lack thereof) of the impacts of diabetes, lack of follow-up in healthcare settings, and trust in healthcare professionals. The third theme was centred on professional factors impacting on diabetes prevention which included workload, time constraints, resources, self-efficacy and knowledge as well as professionals’ perception of patient motivations towards change.ConclusionThis review explored the factors influencing diabetes prevention in primary care, and identified the context of prevention, as well as patient and professional factors related to preventative services being offered in primary care. This systematic review complements previous reviews of real-world settings by exploring the significant factors in prevention, and the findings are relevant to academics, policymakers, patients and practitioners interested in understanding the factors associated with the delivery and uptake of diabetes prevention interventions.

Sustaining diabetes prevention and care interventions: A multiple case study of translational research projects.

This study identifies the barriers and enablers for sustainability of interventions in primary and secondary prevention of diabetes. In the context of translational research, sustainability is defined as the continued use of program components and activities for the continued achievement of desirable program and population outcomes. In this study, eleven translational research projects, supported by the BRIDGES program of the International Diabetes Federation, were investigated. By theoretically-informed semi-structured interviews and analyses of project reports, qualitative data was collected on the sustainability outcomes and the barriers and enablers. The sustainability outcomes can be grouped in three main areas: (1) sustainability at the intervention site(s); (2) diffusion to the wider community; and (3) replication of the intervention at other site(s). Each of the outcomes has their own set of enablers and barriers, and thus requires consideration for a different sustainability strategy. This study is the first international study that relates the sustainability outcomes of translational research project to specific barriers and enablers, and develops an evidence-based framework which provides practical advice on how to ensure the sustainability of health interventions.

Is the success of the SLIMMER diabetes prevention intervention modified by socioeconomic status? A randomised controlled trial.

To explore the role of socioeconomic status (SES) in participation, programme attendance, programme acceptability, adherence to lifestyle guidelines, drop-out, and effectiveness in the SLIMMER diabetes prevention intervention. SLIMMER was a randomised controlled intervention, carried out in a real-world setting, targeting 40- to 70-year-old adults at increased risk of developing type 2 diabetes (n=316). The intervention group participated in a 10-month combined dietary and physical activity programme. Measurements were carried out at baseline, 12months, and 18months. Effectiveness was determined for fasting insulin, HbA1c, weight, BMI, waist circumference, and waist-to-height-ratio. Differences between the low SES (no, primary, or lower secondary school) and higher SES group were tested using logistic regression and ANCOVA. Fifty-two percent of the SLIMMER participants had a low SES. No differences in participation were observed between the low and higher SES group. The most important reason for non-participation in the low SES group was 'lack of interest' (32%), whereas in the higher SES group this was 'I already exercise enough' (31%). Attendance, acceptability, adherence, drop-out, and effectiveness after 12months were similar in the low and higher SES group. After 18months, the low SES group seemed to maintain slightly better effects for fasting insulin, HbA1c, and waist circumference. The current study showed that participation, attendance, acceptability, adherence, drop-out, and effectiveness of the SLIMMER intervention were in general not modified by socioeconomic status. The SLIMMER intervention can contribute to health promotion for individuals in both low and higher socioeconomic groups.

Effect of Long-Term Metformin and Lifestyle in the Diabetes Prevention Program and Its Outcome Study on Coronary Artery Calcium.

Despite the reduced incidence of coronary heart disease with intensive risk factor management, people with diabetes mellitus and prediabetes remain at increased coronary heart disease risk. Diabetes prevention interventions may be needed to reduce coronary heart disease risk. This approach was examined in the DPP (Diabetes Prevention Program) and the DPPOS (Diabetes Prevention Program Outcome Study), a long-term intervention study in 3234 subjects with prediabetes (mean±SD age, 64±10 years) that showed reduced diabetes risk with lifestyle and metformin compared with placebo over 3.2 years. The DPPOS offered periodic group lifestyle sessions to all participants and continued metformin in the originally randomized metformin group. Subclinical atherosclerosis was assessed in 2029 participants with coronary artery calcium (CAC) measurements after an average of 14 years of follow-up. The CAC scores were analyzed continuously as CAC severity and categorically as CAC presence (CAC score >0) and reported separately in men and women. There were no CAC differences between lifestyle and placebo intervention groups in either sex. CAC severity and presence were significantly lower among men in the metformin versus the placebo group (age-adjusted mean CAC severity, 39.5 versus 66.9 Agatston units, P=0.04; CAC presence, 75% versus 84%, P=0.02), but no metformin effect was seen in women. In multivariate analysis, the metformin effect in men was not influenced by demographic, anthropometric, or metabolic factors; by the development of diabetes mellitus; or by use/nonuse of statin therapy. Metformin may protect against coronary atherosclerosis in prediabetes and early diabetes mellitus among men. URL: http://www.clinicaltrials.gov. Unique identifier: NCT00038727.

Variation in Maturity-Onset Diabetes of the Young Genes Influence Response to Interventions for Diabetes Prevention.

Context:Variation in genes that cause maturity-onset diabetes of the young (MODY) has been associated with diabetes incidence and glycemic traits.Objectives:This study aimed to determine whether genetic variation in MODY genes leads to differential responses to insulin-sensitizing interventions.Design and Setting:This was a secondary analysis of a multicenter, randomized clinical trial, the Diabetes Prevention Program (DPP), involving 27 US academic institutions. We genotyped 22 missense and 221 common variants in the MODY-causing genes in the participants in the DPP.Participants and Interventions:The study included 2806 genotyped DPP participants randomized to receive intensive lifestyle intervention (n = 935), metformin (n = 927), or placebo (n = 944).Main Outcome Measures:Association of MODY genetic variants with diabetes incidence at a median of 3 years and measures of 1-year β-cell function, insulinogenic index, and oral disposition index. Analyses were stratified by treatment group for significant single-nucleotide polymorphism × treatment interaction (Pint < 0.05). Sequence kernel association tests examined the association between an aggregate of rare missense variants and insulinogenic traits.Results:After 1 year, the minor allele of rs3212185 (HNF4A) was associated with improved β-cell function in the metformin and lifestyle groups but not the placebo group; the minor allele of rs6719578 (NEUROD1) was associated with an increase in insulin secretion in the metformin group but not in the placebo and lifestyle groups.Conclusions:These results provide evidence that genetic variation among MODY genes may influence response to insulin-sensitizing interventions.

Cost-effectiveness of population-based, community, workplace and individual policies for diabetes prevention in the UK.

AimTo analyse the cost‐effectiveness of different interventions for Type 2 diabetes prevention within a common framework.MethodsA micro‐simulation model was developed to evaluate the cost‐effectiveness of a range of diabetes prevention interventions including: (1) soft drinks taxation; (2) retail policy in socially deprived areas; (3) workplace intervention; (4) community‐based intervention; and (5) screening and intensive lifestyle intervention in individuals with high diabetes risk. Within the model, individuals follow metabolic trajectories (for BMI, cholesterol, systolic blood pressure and glycaemia); individuals may develop diabetes, and some may exhibit complications of diabetes and related disorders, including cardiovascular disease, and eventually die. Lifetime healthcare costs, employment costs and quality‐adjusted life‐years are collected for each person.ResultsAll interventions generate more life‐years and lifetime quality‐adjusted life‐years and reduce healthcare spending compared with doing nothing. Screening and intensive lifestyle intervention generates greatest lifetime net benefit (£37) but is costly to implement. In comparison, soft drinks taxation or retail policy generate lower net benefit (£11 and £11) but are cost‐saving in a shorter time period, preferentially benefit individuals from deprived backgrounds and reduce employer costs.ConclusionThe model enables a wide range of diabetes prevention interventions to be evaluated according to cost‐effectiveness, employment and equity impacts over the short and long term, allowing decision‐makers to prioritize policies that maximize the expected benefits, as well as fulfilling other policy targets, such as addressing social inequalities.

The Effect of Technology-Mediated Diabetes Prevention Interventions on Weight: A Meta-Analysis

BackgroundLifestyle interventions targeting weight loss, such as those delivered through the Diabetes Prevention Program, reduce the risk of developing type 2 diabetes. Technology-mediated interventions may be an option to help overcome barriers to program delivery, and to disseminate diabetes prevention programs on a larger scale.ObjectiveWe conducted a meta-analysis to evaluate the effect of such technology-mediated interventions on weight loss.MethodsIn this meta-analysis, six databases were searched to identify studies reporting weight change that used technology to mediate diet and exercise interventions, and targeted individuals at high risk for developing type 2 diabetes. Studies published between January 1, 2002 and August 4, 2016 were included.ResultsThe search identified 1196 citations. Of those, 15 studies met the inclusion criteria and evaluated 18 technology-mediated intervention arms delivered to a total of 2774 participants. Study duration ranged from 12 weeks to 2 years. A random-effects meta-analysis showed a pooled weight loss effect of 3.76 kilograms (95% CI 2.8-4.7; P<.001) for the interventions. Several studies also reported improved glycemic control following the intervention. The small sample sizes and heterogeneity of the trials precluded an evaluation of which technology-mediated intervention method was most efficacious.ConclusionsTechnology-mediated diabetes prevention programs can result in clinically significant amounts of weight loss, as well as improvements in glycaemia in patients with prediabetes. Due to their potential for large-scale implementation, these interventions will play an important role in the dissemination of diabetes prevention programs.

TEEN HEED: Design of a clinical-community youth diabetes prevention intervention

TEEN HEED: Design of a clinical-community youth diabetes prevention intervention

Preventing diabetes in obese Latino youth with prediabetes: a study protocol for a randomized controlled trial

BackgroundObese Latino adolescents are disproportionately impacted by insulin resistance and type 2 diabetes. Prediabetes is an intermediate stage in the pathogenesis of type 2 diabetes and represents a critical opportunity for intervention. However, to date, no diabetes prevention studies have been conducted in obese Latino youth with prediabetes, a highly vulnerable and underserved group. Therefore, we propose a randomized-controlled trial to test the short-term (6-month) and long-term (12-month) efficacy of a culturally-grounded, lifestyle intervention, as compared to usual care, for improving glucose tolerance and reducing diabetes risk in 120 obese Latino adolescents with prediabetes.MethodsParticipants will be randomized to a lifestyle intervention or usual care group. Participants in the intervention group will attend weekly nutrition and wellness sessions and physical activity sessions twice a week for six months, followed by three months of booster sessions. The overall approach of the intervention is framed within a multilevel Ecodevelopmental model that leverages community, family, peer, and individual factors during the critical transition period of adolescence. The intervention is also guided by Social Cognitive Theory and employs key behavioral modification strategies to enhance self-efficacy and foster social support for making and sustaining healthy behavior changes. We will test intervention effects on quality of life, explore the potential mediating effects of changes in body composition, total, regional, and organ fat on improving glucose tolerance and increasing insulin sensitivity, and estimate the initial incremental cost effectiveness of the intervention as compared with usual care for improving glucose tolerance.DiscussionThe proposed trial builds upon extant collaborations of a transdisciplinary team of investigators working in concert with local community agencies to address critical gaps in how diabetes prevention interventions for obese Latino youth are developed, implemented and evaluated. This innovative approach is an essential step in the development of scalable, cost-effective, solution oriented programs to prevent type 2 diabetes in this and other populations of high-risk youth.Trial RegistrationNCT02615353, registered on June 8, 2016.

The impact of Type 2 diabetes prevention programmes based on risk-identification and lifestyle intervention intensity strategies: a cost-effectiveness analysis.

To develop a cost-effectiveness model to compare Type 2 diabetes prevention programmes targeting different at-risk population subgroups with a lifestyle intervention of varying intensity. An individual patient simulation model was constructed to simulate the development of diabetes in a representative sample of adults without diabetes from the UK population. The model incorporates trajectories for HbA1c , 2-h glucose, fasting plasma glucose, BMI, systolic blood pressure, total cholesterol and HDL cholesterol. Patients can be diagnosed with diabetes, cardiovascular disease, microvascular complications of diabetes, cancer, osteoarthritis and depression, or can die. The model collects costs and utilities over a lifetime horizon. The perspective is the UK National Health Service and personal social services. We used the model to evaluate the population-wide impact of targeting a lifestyle intervention of varying intensity to six population subgroups defined as high risk for diabetes. The intervention produces 0.0003 to 0.0009 incremental quality-adjusted life years and saves up to £1.04 per person in the general population, depending upon the subgroup targeted. Cost-effectiveness increases with intervention intensity. The most cost-effective options are to target individuals with HbA1c > 42 mmol/mol (6%) or with a high Finnish Diabetes Risk (FINDRISC) probability score (> 0.1). The model indicates that diabetes prevention interventions are likely to be cost-effective and may be cost-saving over a lifetime. In the model, the criteria for selecting at-risk individuals differentially impact upon diabetes and cardiovascular disease outcomes, and on the timing of benefits. These findings have implications for deciding who should be targeted for diabetes prevention interventions.

The Effectiveness and Cost of Lifestyle Interventions Including Nutrition Education for Diabetes Prevention: A Systematic Review and Meta-Analysis

BackgroundType 2 diabetes is a significant public health concern. With the completion of the Diabetes Prevention Program, there has been a proliferation of studies attempting to translate this evidence base into practice. However, the cost, effectiveness, and cost-effectiveness of these adapted interventions is unknown. ObjectiveThe purpose of this systematic review was to conduct a comprehensive meta-analysis to synthesize the effectiveness, cost, and cost-effectiveness of lifestyle diabetes prevention interventions and compare effects by intervention delivery agent (dietitian vs non-dietitian) and channel (in-person vs technology-delivered). MethodsEnglish and full-text research articles published up to July 2015 were identified using the Cochrane Library, PubMed, Education Resources Information Center, CAB Direct, Science Direct, and Google Scholar. Sixty-nine studies met inclusion criteria. Most employed both dietary and physical activity intervention components (four of 69 were diet-only interventions). Changes in weight, fasting and 2-hour blood glucose concentration, and hemoglobin A1c were extracted from each article. Heterogeneity was measured by the I2 index, and study-specific effect sizes or mean differences were pooled using a random effects model when heterogeneity was confirmed. ResultsParticipants receiving intervention with nutrition education experienced a reduction of 2.07 kg (95% CI 1.52 to 2.62; P<0.001; I2=90.99%, 95% CI 88.61% to 92.87%) in weight at 12 months with effect sizes over time ranging from small (0.17, 95% CI 0.04 to 0.30; P=0.012; I2= 86.83%, 95% CI 80.42% to 91.14%) to medium (0.65, 95% CI 0.49 to 0.82; P<0.001; I2=98.75%, 95% CI 98.52% to 98.94). Effect sizes for 2-hour blood glucose and hemoglobin A1c level changes ranged from small to medium. The meta-regression analysis revealed a larger relative weight loss in dietitian-delivered interventions than in those delivered by nondietitians (full sample: –1.0 kg; US subsample: –2.4 kg), and did not find statistical evidence that the delivery channel was an important predictor of weight loss. The average cost per kilogram weight loss ranged from $34.06 over 6 months to $1,005.36 over 12 months. The cost of intervention per participant delivered by dietitians was lower than interventions delivered by non-dietitians, although few studies reported costs. ConclusionsLifestyle interventions are effective in reducing body weight and glucose-related outcomes. Dietitian-delivered interventions, compared with those delivered by other personnel, achieved greater weight reduction. No consistent trend was identified across different delivery channels.

Using Digital Health Technology to Prevent and Treat Diabetes.

Diabetes Technology & TherapeuticsVol. 19, No. S1 Original ArticlesFree AccessUsing Digital Health Technology to Prevent and Treat DiabetesNeal Kaufman and Ayten SalahiNeal KaufmanFielding School of Public Health, Geffen School of Medicine, UCLA, Los Angeles, CA.Canary Health, Los Angeles, CA.Search for more papers by this author and Ayten SalahiIndependent Consultant to Canary Health, Los Angeles, CA.Search for more papers by this authorPublished Online:1 Feb 2017https://doi.org/10.1089/dia.2017.2506AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail IntroductionAs anyone reading this yearbook knows, diabetes mellitus is a chronic disease that requires long-term medical attention both to limit the development of severe complications and to manage them when they do occur. It is one of the leading causes of morbidity and mortality worldwide because of its role in the development of cardiovascular, renal, neuropathic, and retinal disease.The prognosis in patients with diabetes mellitus is strongly influenced by the degree of control of their disease. Patients with diabetes have a lifelong challenge to achieve and maintain blood glucose levels as close to the targeted range as possible. Attention must also be paid to achieving normal blood pressure and lipids. With appropriate control, the risk of microvascular and neuropathic complications is decreased markedly.People with diabetes face a myriad of barriers to better health. Managing diabetes, often along with other comorbidities, can be a daunting task. Depressive symptoms and major depressive disorders are common in people with diabetes and pose a major challenge for clinical practice. People need to be able to confidently interact with their physicians and an increasingly complex medical system, administer the right medicines and therapies at the right time, eat properly, exercise appropriately, and (often) lose weight. While most people know what they should do, they often find themselves unable to actually take the steps necessary to achieve better health. Many complications of diabetes are preventable if patients take greater responsibility for the management of their condition.Self-management support is one approach to help people attain the knowledge, attitudes, skills, and behaviors they need to better manage chronic disease symptoms and improve their health outcomes. It addresses how to recognize and act on symptoms, use medication appropriately, maintain nutrition and exercise programs, interact effectively with health-care providers, and manage psychological responses to illness.Self-management support, coupled with diabetes education, leads to the best outcomes over time. Diabetes education has traditionally been, and in many places still is, primarily taught by health professionals in clinical settings with professionals assessing patients' needs and instructing them how to control blood glucose and other key parameters and avoid diabetes complications. Patients and professionals work collaboratively toward an individualized self-management plan. Unfortunately, the combination of the large number of people living with diabetes, cultural and socio-economic factors, as well as a limited number of skilled diabetes educators, means that most patients receive little or no diabetes education or self-management support.The articles reviewed in this article are all related to the central theme that activated and empowered patients, when given the information, wisdom, and tools they need to self-manage their conditions and their lives, can improve their disease trajectories and lower the rate of getting complications and adding additional comorbidities. The papers address a variety of ways that information technology is leading the way in transforming health-care delivery to put the patient back in the center of his or her health journey.Articles are divided into 4 themes: 1. Intervention design.2. Prevention of type 2 diabetes.3. Interventions to impact overall diabetes self-management.4. Useful tools/interventions addressing one element of diabetes self-management.Key Articles Reviewed for the ArticleUser-centered design for psychosocial intervention development and implementationAaron R. Lyon, Kelly KoernerClin Psychol Sci Pract 2016; 23: 180–200The systematic design of a behavioural mobile health application for the self-management of type 2 diabetesGoyal S, Morita P, Lewis GF, Yu C, Seto E, Cafazzo JACan J Diabetes 2016; 40: 95–104Evidence-based mHealth chronic disease mobile app intervention design: development of a frameworkWilhide Iii CC, Peeples MM, Anthony Kouyaté RCJMIR Res Protoc 2016; 5: e25Designing, implementing, and evaluating mobile health technologies for managing chronic conditions in older adults: a scoping reviewMatthew-Maich N, Harris L, Ploeg J, Markle-Reid M, Valaitis R, Ibrahim S, Gafni A, Isaacs SJMIR Mhealth Uhealth 2016; 4: e29A systematic review on incentive-driven mobile health technology: as used in diabetes managementde Ridder M, Kim J, Jing Y, Khadra M Nanan RJ Telemed Telecare 2017; 23:26-35 [epub 2016 Jul9]Do weight management interventions delivered by online social networks effectively improve body weight, body composition, and chronic disease risk factors? A systematic reviewWillis EA, Szabo-Reed AN, Ptomey LT, Steger FL, Honas JJ, Washburn RA, Donnelly JEJ Telemed Telecare 2016. [Epub ahead of print] pii: 1357633X16630846Diabetes prevention and weight loss with a fully automated behavioral intervention by email, web, and mobile phone: a randomized controlled trial among persons with prediabetesBlock G, Azar KMJ, Romanelli RJ, Block TJ, Hopkins Ds, Carpenter HA, Dolginsky MS, Hudes ML, Palaniappan LP, Block CHJ Med Internet Res 2015; 17: e240Use of m-Health technology for preventive interventions to tackle cardiometabolic conditions and other non-communicable diseases in Latin America – challenges and opportunitiesBeratarrechea A, Diez-Canseco F, Irazola V, Miranda J, Ramirez-Zea M, Rubinstein AProgress in Cardiovascular Diseases 2016; 58: 661–673Return on investment for digital behavioral counseling in patients with prediabetes and cardiovascular diseaseSu W, Chen F, Dall TM, Iacobucci W, Perreault LPrev Chronic Dis 2016; 13: 150357.Cost effectiveness of an internet-delivered lifestyle intervention in primary care patients with high cardiovascular riskSmith KJ, Kuo S, Zgibor JC, McTigue KM, Hess R, Bhargava T, Bryce CLPreventive Medicine 2016; 87: 103–109Mobile technology and the digitization of healthcareBhavnani SP, Narula J, Sengupta PPEuropean Heart Journal 2016; 37: 1428–1438Personalized telehealth in the future: a global research agendaDinesen B, Nonnecke B, Lindeman D, Toft E, Kidholm K, Jethwani K, Young HM, Spindler H, Oestergaard CU, Southard JA, Gutierrez M, Anderson N, Albert NM, Han JJ, Nesbitt TJ Med Internet Res 2016; 18: e53A systematic review of randomized controlled trials of mHealth interventions against non-communicable diseases in developing countriesStephani V, Opoku D, Quentin WBMC Public Health 2016; 16: 572The effectiveness of self-management mobile phone and tablet apps in long-term condition management: a systematic reviewWhitehead L, Philippa Seaton PJ Med Internet Res 2016; 18: e97The use of videogames, gamification, and virtual environments in the self-management of diabetes: a systematic review of evidenceTheng YL, Lee JW, Patinadan PV, Foo SSGames Health J 2015; 4: 352–361A review of nutritional tracking mobile applications for diabetes patient useDarby A, Strum MW, Holmes E, Gatwood JDiabetes Technology and Therapeutics 2016; 18: 200–212The effectiveness of prompts to promote engagement with digital interventions: a systematic reviewAlkhaldi G, Hamilton FL, Lau R, Webster R, Michie S, Murray EJ Med Internet Res 2016; 18: e6.User-centered design for psychosocial intervention development and implementationLyon Aaron R.1, Koerner Kelly21Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA2Kelly Koerner, Evidence-Based Practice Institute, LLC, University of Washington. Seattle, WAClin Psychol Sci Pract 2016; 23: 180–200BackgroundUser-centered design (UCD) principles can be leveraged to improve the implementation and scalability of various evidence-based treatments (EBTs) in psychosocial intervention. This paper presents particularly salient points for improvement in the research, design, implementation, and scaling-up of behavioral EBTs by describing UCD as a cornerstone for effective innovation.MethodsA description of studies pertaining to EBT design and implementation protocols was completed, alongside a discussion of studies related to psychosocial findings with potential to improve the usability, packaging, and dissemination of such therapies. The authors synthesized this information into a UCD-focused design agenda composed of four primary design concepts.ResultsEBT success is inherently diminished by design and development weaknesses related to flexibility, complexity, and sustainability of treatment. These factors are exacerbated in the growing field of digital EBTs. There are previously described design goals for the development of EBTs in behavioral health that aim to address these. The authors present 4 salient design methods therein: (1) deliberate identification of both end user populations and their needs; (2) design of clear protocols for rapid replication; (3) streamlining pre-existing procedures; and (4) leveraging natural design constraints of the product or service's destination context.ConclusionsThere are gaps to EBT design that undermine its potential for effectiveness, scalability, and replicability in psychosocial interventions. EBT researchers and developers must adopt a user-centered design approach to maximize the potential for EBTs in behavioral therapies of any kind.CommentThe hallmarks of user-centered design put the participant in a digital intervention in the center of his or her own health journey. The accomplishment this goal requires a multidisciplinary team in which developers work with clinicians and end-users to iterate approaches which are most likely to get a sustained impact. The more the team understands the unique characteristics of the target population, the more appropriate and impactful the intervention will be. Modern website and intervention design takes into account these principles and when coupled with foundational work demonstrating what approaches work for what behaviors with which individuals, effective and efficient interventions can be created. These interventions need to be able to be modified over time as information on outcomes and user input is obtained.The systematic design of a behavioural mobile health application for the self-management of type 2 diabetesGoyal S1,2, Morita P1, Lewis GF4, Yu C5,6, Seto E1,3, Cafazzo JA1,2,31Centre for Global eHealth Innovation, Techna Institute, University Health Network, Toronto, ON, Canada2Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada3Institute of Health Policy, Management and Evaluation, Faculty of Medicine, University of Toronto, Toronto, ON, Canada4Departments of Medicine and Physiology, Division of Endocrinology and the Banting and Best Diabetes Centre, University of Toronto, Toronto, ON, Canada5Division of Endocrinology & Metabolism and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada6Faculty of Medicine and Dalla Lana School of Public Health, University of Toronto, Toronto, ON, CanadaCan J Diabetes 2016; 40: 95–104BackgroundThe significance of self-monitoring of blood glucose (SMBG) has been unclear for noninsulin requiring patients with type 2 diabetes (T2). By effectively improving self-management skills like clinical decision-making and self-awareness, structured SMBG has now been shown to demonstrate significant benefit for this subset of patients. The authors conjecture that successful self-management for noninsulin requiring patients with T2 requires behavioral intervention that elucidates the relationship between glycemic control and lifestyle. Few mHealth apps attempt to bring about positive behavioral adjustments for the purpose of cultivating self-care skills. The purpose of this paper is to describe a model for the design and development of a diabetes self-management mHealth app that elicits behavioral change through social cognitive theory and patient incentives.MethodsA comprehensive literature review examining the state of mHealth for diabetes self-management was completed. The authors described a theoretical model for the development and validation of diabetes self-management applications through user-centered design following the Knowledge to Action (KTA) and Medical Research Council's (MRC) blended framework for complex interventions. This framework incorporates elements of social cognitive theory (SCT) to incite and sustain positive behavioral changes known to improve patient compliance and clinical outcomes.ResultsThe result was KTA-MRC Phase 1 development of bant II, a user-centered mHealth app for self-management of diabetes with four primary functions: tracking SMBG and wellness-related lifestyle choices (e.g., diet, exercise), highlighting patterns between glycemic control and lifestyle choices, providing remedial direction to improve clinical decision-making, and guiding eventual mastery of diabetes self-management through incentivized, gamified positive behavioral change.ConclusionsBant II shows promise in guiding the development of sustainable self-management, improved quality of life, and prevention of diabetes-related complications through incentivized positive behavioral change for patients with T2. Phase 2 and 3 of app development will involve a patient usability evaluation and a randomized control trial to measure the effectiveness of the app, with a primary clinical outcome of HbA1c.Evidence-based mHealth chronic disease mobile app intervention design: development of a frameworkWilhide CCIII, Peeples MM, Anthony Kouyaté RCWellDoc Inc, Baltimore, MDJMIR Res Protoc 2016; 5: e25BackgroundChronic disease management through mHealth innovation offers promising new possibilities for real-time, remote health-care interventions. Such innovations require a framework for development and evaluation that is evidence-based, replicable, scalable, and adaptable across chronic disease states, and effective in the achievement of specific health outcomes. The purpose of this review is to describe the process required to identify, develop, and enhance such an app-based intervention design framework in the context of chronic disease management.MethodsA three-phased approach was used over the span of two years (June 2012 to June 2014) to develop, apply, refine, and finalize a framework for the evolution of an evidence-based mHealth app design. The framework was developed iteratively across three chronic disease management app types and seven chronic disease states. The preliminary model was applied to type 2 diabetes (T2) and incorporated data from clinical and behavioral evidence-based research, clinical practice subject matter experts, standards of care, clinical procedures, and best practices.ResultsThe final outcome was the development of the Chronic Disease mHealth App Intervention Design Framework. This iterative design model sequentially uses seven key decision-making and content domains to guide the development of mHealth app features, and is based on both clinical and behavioral evidence known to improve health outcomes in chronic disease. The model concurrently evaluates the effectiveness of particular design features towards a specific outcome, and feeds the output of a preceding iteration into the subsequent domain in a process that is referred to as a waterfall process. The effect of the waterfall process across multiple chronic disease states and app types was to evolve each iteration of the mHealth app design framework across multivariate disease management strata.ConclusionsThe Chronic Disease mHealth App Intervention Design Framework offers a scalable, replicable, and iterative model upon which mHealth innovation developers can expand to enhance the usability, applicability, and evidence-based effectiveness of mHealth technologies across chronic disease states and real-life settings.CommentThe authors have done a terrific job in having summarized a very complex software development process, providing a coherent approach to building a technology platform which can be used to power a variety of chronic disease self-management approaches. This paper is made all the more interesting and important since it comes from a for-profit company willing to share some of its “secret sauce” serving as the foundation of its business model. They have also highlighted some of the challenges inherent in using evidence-based practices proven effective in-person and transforming them for digital delivery. There is a need to balance often competing principles of behavior change, application and user-centered design, and condition or behavior specific protocols and curriculum. This paper demonstrates one successful approach.Designing, implementing, and evaluating mobile health technologies for managing chronic conditions in older adults: a scoping reviewMatthew-Maich N1,2, Harris L3, Ploeg J2, Markle-Reid M2, Valaitis R2, Ibrahim S4, Gafni A5, Isaacs S21Aging, Community & Health Research Unit, McMaster University, Mohawk College/McMaster University School of Nursing, Hamilton, ON, Canada2Aging, Community & Health Research Unit, School of Nursing, McMaster University, Hamilton, ON, Canada3SickKids Hospital, mHealth Innovation, Toronto, ON, Canada4Arthur Labatt Family School of Nursing, Department of Nursing, Western University, London, ON, Canada5Aging, Community & Health Research Unit, Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, CanadaJMIR Mhealth Uhealth 2016; 4: e29BackgroundAging patients managing multiple chronic conditions present a particularly complex challenge for health-care providers and caregivers. While mHealth technologies have demonstrated the potential to support this demographic, insufficient evidence-based research has been conducted to inform the development of such technologies. This review describes the current landscape of mHealth support in the management of chronic conditions in aging, community-living adults, and provides recommendations for enhanced usability, feasibility, and user acceptance.MethodsThe authors completed a comprehensive, five-stage scoping literature review, ranging from January 2005 through March 2015, to identify mHealth innovations designed for use by aging, community-living adults managing a minimum of one chronic condition. They also included information on both formal and informal health-care services offered in the home and community setting for this population.ResultsIn total, the authors identified 42 papers that met the abovementioned search criteria. Seventeen of the 42 articles (40.4%) specifically described mHealth technologies developed for aging adults with a particular chronic condition or set of conditions, while 6 (14.3%) described such innovations for chronic conditions in general and 18 (42.9%) did so for those receiving home and/or community care. They identified three prominent themes among these publications: evaluation methods of mHealth innovation; factors that detract from mHealth usability, feasibility, and user acceptance; and considerations specific to the development of mHealth technologies.ConclusionsUser acceptance for mHealth technologies in aging adults is limited but increasing. To improve user acceptance, feasibility, and usability of mHealth home health-care in older adults, developers must adopt an integrative, user-centric, and collaborative approach to design and development of mHealth innovations.CommentThis study emphasizes a fundamental tenant of all patient education and support. To maximize effectiveness, they need to follow a number of principles one of which is being designed for a specific target population. Ideally the target population is involved with the development, testing, and refinement of the approach during all phases of planning, implementing, and evaluating a program. No surprise, interventions created for “older” adults…don't know what that age is, but I assume always older than I am at the time…need to be different than those designed for younger people.A systematic review on incentive-driven mobile health technology: as used in diabetes managementde Ridder M1,2, Kim J1,2,3, Jing Y1,2, Khadra M4, Nanan R5,61Personal Digital Assistant, Biomedical and Multimedia Information Technology Research Group, The University of Sydney, Australia2Personal Digital Assistant, Institute of Biomedical Engineering and Technology, The University of Sydney, Australia3Personal Digital Assistant, Nepean Telehealth Technology Centre, Nepean Hospital, Australia4Personal Digital Assistant, Sydney Medical School, The University of Sydney, Australia5Personal Digital Assistant, Nepean Clinical School, The University of Sydney, Australia6Personal Digital Assistant, Charles Perkins Centre Nepean, The University of Sydney, AustraliaJ Telemed Telecare 2017; 23:26-35 [epub 2016 Jul9]BackgroundBenefits of mHealth intervention towards the management of chronic diseases are undermined by difficulty in retaining and engaging the patients who use them. These difficulties are commonly addressed by utilizing incentive-driven technology (IDT) design to maintain and empower mHealth app users. This review catalogues various methods of IDT implementation in diabetes-related mHealth technologies, as well as impediments to user engagement with IDTs.MethodsA systematic literature review across seven major databases was completed to analyze mHealth solutions for diabetes management, as well as mHealth solutions for diabetes management using IDTs. Publications ranged from 2008 to 2014. The search rendered a total of 42 papers.ResultsWhile automation and personalization components of IDTs have advanced over the course of the last five years in mHealth design, the predominating IDT categories have remained largely unchanged. Of the 42 search results, 34 described mHealth innovations that leveraged IDTs. More than half of these studies used ≥1 IDT method (n=19). The remaining eight articles were used to qualitatively assess impediments to user engagement with IDTs. Authors characterized IDT methods in the following categories: (1) financial (n=2); (2) reminder (n=11); (3) social (n=8); (4) alert (n=5); (5) gamification (n=3); (6) feedback (n=10); and (7) education (n=21).ConclusionsIDTs are used to improve rates of retention in mobile telehealth technologies. mHealth innovations for diabetes management currently employ seven primary categories of IDTs to incentivize retention and empowerment of end users. There methods are characterized here based upon a review of literature dating to 2014.CommentIncentives are a tried and true approach to increasing engagement and retention. The problems is that they do not necessarily work with many people and under many circumstances. Which incentives work and under what circumstances are they most effective is an important research question. This study helps to catalog the approach to incentives and could help others as they design studies regarding incentives.Do weight management interventions delivered by online social networks effectively improve body weight, body composition, and chronic disease risk factors? A systematic reviewWillis EA, Szabo-Reed AN, Ptomey LT, Steger FL, Honas JJ, Washburn RA, Donnelly JECardiovascular Research Institute, Division of Internal Medicine, Kansas City, MOJ Telemed Telecare 2016. [Epub ahead of print] pii: 1357633X16630846BackgroundThe role of online social networks (OSNs) as a primary intervention delivery method remains largely unexamined. This report constitutes the first systematic review and meta-analysis evaluating the effectiveness of OSN-delivered weight management interventions on weight loss outcomes.MethodsStudies ranging from December 1990 through November 2015 were included within the initial scope of candidate articles. A systematic literature review across five pertinent databases was completed to identify data describing the influence of OSNs on weight loss outcomes. Among other requirements, inclusion criteria required the use of peer-reviewed, primary source publications that collected weight loss data specifically related to the use of OSN-delivered body weight management and lifestyle interventions. A total of five papers met inclusion criteria for final review.ResultsOf the five studies selected for analysis, three reported significant reductions to body weight. In these instances, significant weight loss was observed when OSN-delivered weight management interventions were utilized alongside individualized health educator support for program participants. One of the five studies indicated clinically significant total weight loss of ≥5%.ConclusionsThe findings described here are promising and suggest potential for OSN-delivered interventions to be effective for weight management; however, further research is needed to recapitulate and build upon these findings, in order to clarify which components of OSN-delivered interventions are most critical to weight management or other health benefits.CommentOnline social networks certainly should be effective as a way to decrease social isolation and improve health outcomes. This review, with only five studies, did not demonstrate very significant results but that is not surprising. Social networks by themselves, without specific protocols and content to help participants overcome barriers, will probably not be robust enough to help patients change often lifelong behaviors.Diabetes prevention and weight loss with a fully automated behavioral intervention by email, web, and mobile phone: a randomized controlled trial among persons with prediabetesBlock G1,2, Azar KMJ3, Romanelli RJ3, Block TJ1, Hopkins Ds1, Carpenter HA1, Dolginsky MS3, Hudes ML4, Palaniappan LP3, Block CH11Turnaround Health, a division of NutritionQuest, Berkeley, CA2Division of Community Health and Human Development, School of Public Health, University of California, Berkeley, CA3Palo Alto Medical Foundation Research Institute, Palo Alto, CA4Center for Weight and Health, University of California, Berkeley, CAJ Med Internet Res 2015; 17: e240BackgroundOne in three U.S. adults has prediabetes. About 70% of those living with prediabetes are expected to advance to type 2 (T2), and about one in 10 U.S. health-care dollars were spent in the associated costs of prediabetes and diabetes in 2012. Lifestyle adjustments like increased physical activity, weight loss, and dietary modifications can reduce risk of progression to diabetes by 40% to 70%. This study assesses the efficacy of Alive-PD, a fully-automated, remote behavioral intervention for diabetes prevention that uses a combined mobile phone, e-mail, and the Internet delivery methods to reduce the biomarkers that constitute the benchmarks for diabetes (e.g., HbA1c, fasting blood glucose(BG)).MethodsThis study was a wait-list controlled RCT, with primary outcome measures of HbA1c and fasting BG at baseline and at six months. Secondary outcome measures included body mass index (BMI), weight, waist circumference, metabolic syndrome, Framingham diabetes score, and triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio. Analysis was completed by intention-to-treat. Participants were required to meet inclusion criteria for clinical evidence of prediabetes. Patients were randomized to either the Alive-PD intervention group (n=339) or the wait-list usual-care control group (n=176). Subjects in the Alive-PD group received personalized behavioral support for lifestyle modifications, including dietary habits, exercise, sleep, stress, and weight loss, in addition to a mobile phone app, and automated phone calls. Subjects also received weekly e-mails outlining suggestions for incremental goals and providing access to a separate website that could be used for data tracking, social support, competitions, coaching, and health material.ResultsParticipants in the Alive-PD group had reduced their Framingham eight year diabetes risk significantly more than the control group (P<0.001), from 16% to 11%. When compared to controls, the Alive-PD group also showed significantly greater reductions in HbA1c (mean −0.26%, 95% confidence interval (CI) −0.27 to −0.24 vs. mean −0.18%, 95% CI −0.19 to −0.16, P<0.001), fasting glucose (mean −7.36 mg/dL, 95% CI −7.85 to −6.87 vs. mean −2.19, 95% CI −2.64 to −1.73, P<0.001), body weight, waist circumference, TG/HDL, and BMI. Of the total subjects in the Alive-PD group who had metabolic syndrome at baseline, 46.5% (40/86) no longer had metabolic syndrome at six months, compared to 20.0% (20/110) in the control group. Participant engagement with the program began and remained high through the course of the study, with 70.6% (115/163) of the intervention group still engaging with the program in the final month of the study.ConclusionsAlive-PD was proven effective in reducing the biomarkers that constitute diabetes, as well as risk of progressing from prediabetes to diabetes. Further research is required to elucidate which features of the intervention were salient to its success. Fully automated, evidence-based behavioral interventions such as Alive-PD have potential for large-scale implementation as a preventative option for at-risk populations and people with prediabetes.CommentThis study is promising because not only did it get positive results (at six months), it did so using technology w

Culturally Targeted Strategies for Diabetes Prevention in Minority Population.

Purpose The purpose of this study is to (a) assess the effectiveness of culturally tailored diabetes prevention interventions in minority populations and (b) develop a novel framework to characterize 4 key domains of culturally tailored interventions. Prevention strategies specifically tailored to the culture of ethnic minority patients may help reduce the incidence of diabetes. Methods We searched PubMed, EMBASE, and CINAHL for English-language, randomized controlled trials (RCTs) or quasi-experimental (QE) trials testing culturally tailored interventions to prevent diabetes in minority populations. Two reviewers independently extracted data and assessed risk of bias. Inductive thematic analysis was used to develop a framework with 4 domains (FiLLM: Facilitating [ie, delivering] Interventions Through Language, Location, and Message). The framework was used to assess the overall effectiveness of culturally tailored interventions. Results Thirty-four trials met eligibility criteria. Twelve studies were RCTs, and 22 were QE trials. Twenty-five out of 34 studies (74%) that used cultural tailoring demonstrated significantly improved A1C, fasting glucose, and/or weight loss. Of the 25 successful interventions, 21 (84%) incorporated at least 3 culturally targeted domains. Seven studies used all 4 domains and were all successful. The least utilized domain was delivery (4/34) of the intervention's key educational message. Conclusions Culturally tailoring interventions across the 4 domains of facilitators, language, location, and messaging can be effective in improving risk factors for progression to diabetes among ethnic minority groups. Future studies should evaluate how specific tailoring approaches work compared to usual care as well as comparative effectiveness of each tailoring domain.

Study Protocol: The Norfolk Diabetes Prevention Study [NDPS]: a 46\xa0month multi - centre, randomised, controlled parallel group trial of a lifestyle intervention [with or without additional support from lay lifestyle mentors with Type 2 diabetes] to prevent transition to Type 2 diabetes in high risk groups with non - diabetic hyperglycaemia, or impaired fasting glucose

BackgroundThis 7 year NIHR programme [2011–2018] tests the primary hypothesis that the NDPS diet and physical activity intervention will reduce the risk of transition to type 2 diabetes (T2DM) in groups at high risk of Type 2 diabetes. The NDPS programme recognizes the need to reduce intervention costs through group delivery and the use of lay mentors with T2DM, the realities of normal primary care, and the complexity of the current glycaemic categorisation of T2DM risk.MethodsNDPS identifies people at highest risk of T2DM on the databases of 135 general practices in the East of England for further screening with ab fasting plasma glucose and glycosylated haemoglobin [HbA1c]. Those with an elevated fasting plasma glucose [impaired fasting glucose or IFG] with or without an elevated HbA1c [non -diabetic hyperglycaemia; NDH] are randomised into three treatment arms: a control arm receiving no trial intervention, an arm receiving an intensive bespoke group-based diet and physical activity intervention, and an arm receiving the same intervention with enhanced support from people with T2DM trained as diabetes prevention mentors [DPM]. The primary end point is cumulative transition rates to T2DM between the two intervention groups, and between each intervention group and the control group at 46 months. Participants with screen detected T2DM are randomized into an equivalent prospective controlled trial with the same intervention and control arms with glycaemic control [HbA1c] at 46 months as the primary end point. Participants with NDH and a normal fasting plasma glucose are randomised into an equivalent prospective controlled intervention trial with follow up for 40 months. The intervention comprises six education sessions for the first 12 weeks and then up to 15 maintenance sessions until intervention end, all delivered in groups, with additional support from a DPM in one treatment arm.DiscussionThe NDPS programme reports in 2018 and will provide trial outcome data for a group delivered diabetes prevention intervention, supported by lay mentors with T2DM, with intervention in multiple at risk glycaemic categories, and that takes into account the realities of normal clinical practice.Trial registrationISRCTN34805606 (Retrospectively registered 16.3.16)

Combined Diabetes Prevention and Disease Self-Management Intervention for Nicaraguan Ethnic Minorities: A Pilot Study.

Informed by formative community-based participatory research (CBPR), we developed a combined model of diabetes prevention and self-management. To assess the feasibility, acceptability, and preliminary efficacy of our CBPR-inspired model. A mixed methods study was conducted using a pre-experimental design. The setting was a church-based clinic located on Nicaragua's rural Atlantic coast. Miskitos and Creoles with or at risk for diabetes were sampled. Preliminary efficacy was assessed with A1C, weight, and quality of life (QOL) measures at baseline, 3 months, and 6 months. An open-ended survey assessed intervention satisfaction. The 8-week, registered nurse (RN)-led intervention emphasized knowledge acquisition and behavioral strategies for dietary, physical activity, and medication regimen adherence. Paired t tests were computed to assess preliminary efficacy. Content analysis was conducted to assess intervention acceptability. A total of 42 participants were enrolled. For participants completing follow-up data collection (n = 33), mean A1C improved from 8.8% to 8.3% (t = -2.19; p = .04) from baseline to 3 months. Among participants with a baseline A1C of greater than 7.5% (n = 24), the mean A1C decreased from 9.7% to 9.0% from baseline to 3 months (t = -2.86; p = .01), and to 8.7% at 6 months (t = -3.00; p = .01). Nonsignificant weight changes were observed. Mental health QOL improved, on average from baseline to 3 months (t = 2.20; p = .04) and 6 months (t = 4.7; p &lt; .01) for the sample. An increase in mean physical health QOL was observed from baseline to 3 months (t = 2.91; p &lt; .01). The intervention was found to be acceptable. Study feasibility was good, with successful research capacitation and achievement of sampling goals. Findings suggest our novel intervention holds promise for wider application to reduce diabetes burden among Nicaraguan ethnic minorities.

Diabetes Prevention in U.S. Hispanic Adults: A Systematic Review of Culturally Tailored Interventions.

Type 2 diabetes, prediabetes, and metabolic syndrome are highly prevalent in Hispanic individuals in the U.S. Cultural adaptations of traditional lifestyle interventions have been recommended to better reach this high-risk population. This systematic review examined the effectiveness of diabetes prevention programs for Hispanics in lowering risk for Type 2 diabetes, as evidenced by a reduction in weight or improvement in glucose regulation. PubMed/MEDLINE, Cochrane Central Register of Controlled Trials, Web of Science, and PsycINFO were searched from database inception to June 2016 for studies that evaluated diabetes prevention trials targeting U.S. Hispanic populations. Twelve publications met criteria for inclusion. Interventions varied substantially in length, rigor, and tailoring strategies. Five of 12 studies were RCTs. Eight studies included entirely or largely (>70%) female samples. All studies were delivered in Spanish and took place in community settings. Nine studies reported significant reductions in weight, and two in glucose regulation, post-intervention or when compared with controls. Effect sizes were small to moderate, study quality was moderate, and attrition was high in most trials. Interventions with the largest effect sizes included one or more of the following adaptations: literacy modification, Hispanic foods/recipes, cultural diabetes beliefs, family/friend participation, structured community input, and innovative experiential learning. Culturally tailored lifestyle interventions for diabetes prevention appear to be modestly effective in reducing risk for diabetes in Hispanics in the U.S. More studies are needed that utilize randomized controlled designs, recruit Hispanic men, report intervention content and tailoring strategies systematically, and publish participant evaluation and feedback.

Clinical impact of lifestyle interventions for the prevention of diabetes: an overview of systematic reviews

ObjectivesTo review the clinical outcomes of combined diet and physical activity interventions for populations at high risk of type 2 diabetes.DesignOverview of systematic reviews (search dates April–December 2015).SettingAny level of...

Use of Mobile Health Technology in the Prevention and Management of Diabetes Mellitus.

Cardiovascular disease is the leading cause of morbidity and mortality globally, with diabetes being an independent risk factor. Adequate diabetes management has proven to be resource-intensive, requiring frequent lab work, primary care and specialist visits, and time-consuming record-keeping by the patient and care team. New mobile health (mHealth) technologies have enhanced how diabetes is managed and care is delivered. While more recent work has investigated mHealth devices as complementary tools in behavioral interventions for diabetes prevention and management, little is still known about the effectiveness of mHealth technology as stand-alone intervention tools for reducing diabetes risk. In addition, more work is needed to identify the role of mHealth technology in treating vulnerable populations to ameliorate cardiovascular health disparities. With advances in mobile health technology development for diabetes prevention and management, these modalities will likely play an increasingly prominent role in reducing cardiometabolic risk for the US population.