Diabetes and Technology for Increased Activity (DaTA) Study: Results of a Remote Monitoring Intervention for Prevention of Metabolic Syndrome

Stuckey, Melanie I.; Russell-Minda, Elizabeth; Read, Emily; Munoz, Claudio; Shoemaker, J. Kevin; Kleinstiver, Peter; Petrella, Robert J.

doi:10.1177/193229681100500416

Cited by 43 publications

(74 citation statements)

References 26 publications

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“…237 Supplying patients with smartphones with Bluetooth-enabled BP monitors, glucometers, and a Web site for tracking resulted in decreases in total cholesterol; however, these studies did not include a control group. 228,230 Research has shown that education of consumers and self-management interventions can be beneficial for patients. Advances in information technology and consumer health-related mHealth are emerging as promising tools for facilitating the management of dyslipidemia, for example, home lipid testing with a smartphone, educational smartphone apps, and Web portals for patients and providers.…”

Section: Use Of Mhealth In Management Of Dyslipidemiamentioning

confidence: 99%

“…223,[240][241][242] Others were focused on small studies with inconclusive results 226,236,243 or were pilot feasibility studies that did not provide adequate results. 228,230 Only 1 peerreviewed publication 244 addressed the topic of consumer use of technology as stand-alone tools specifically for lipid disorders ( Table 7). The vast majority of publications did not meet the criteria for inclusion in the tables because of the absence of a control group or because they did not include lipids as a primary outcome.…”

Section: Use Of Mhealth In Management Of Dyslipidemiamentioning

confidence: 99%

“…202,[222][223][224][225][226][227][228][229][230][231] Some of these materials provide the basis for the development of CVD risk scores and Web-based score calculators that are available for patients and providers. For example, the Framingham Risk Score was developed from predictive equations based on >5000 men and women who were 30 to 74 years old at baseline and were followed up for cardiovascular events for 12 years.…”

Section: Use Of Mhealth In Management Of Dyslipidemiamentioning

confidence: 99%

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Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention

Burke¹,

Ma²,

Azar³

et al. 2015

Circulation

476

389

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A lthough mortality for cardiovascular disease (CVD) has declined for several decades, heart disease and stroke continue to be the leading causes of death, disability, and high healthcare costs. Unhealthy behaviors related to CVD risk (eg, smoking, sedentary lifestyle, and unhealthful eating habits) remain highly prevalent. The high rates of overweight, obesity, and type 2 diabetes mellitus (T2DM); the persistent presence of uncontrolled hypertension; lipid levels not at target; and the ≈18% of adults who continue to smoke cigarettes pose formidable challenges for achieving improved cardiovascular health.1,2 It is apparent that the performance of healthful behaviors related to the management of CVD risk factors has become an increasingly important facet of the prevention and management of CVD. 3In 2010, the American Heart Association (AHA) made a transformative shift in its strategic plan and added the concept of cardiovascular health.2 To operationalize this concept, the AHA targeted 4 health behaviors in the 2020 Strategic Impact Goals: reduction in smoking and weight, healthful eating, and promotion of regular physical activity. Three health indicators also were included: glucose, blood pressure (BP), and cholesterol. On the basis of the AHA Life's Simple 7 metrics for improved cardiovascular health, <1% of adults in the United States follow a healthful eating plan, only 32% have a normal body mass index, and > 30% have not reached the target levels for lipids or BP. National Health and Nutrition Examination Survey (NHANES) data revealed that people who met ≥6 of the cardiovascular health metrics had a significantly better risk profile (hazard ratio for all-cause mortality, 0.49) compared with individuals who had achieved only 1 metric or none.2 The studies reviewed in this statement targeted these behaviors (ie, smoking, physical activity, healthful eating, and maintaining a healthful weight) and cardiovascular health indicators (ie, blood glucose, lipids, BP, body mass index) as the primary outcomes in the clinical trials testing mobile health (mHealth) interventions.eHealth, or digital health, is the use of emerging communication and information technologies, especially the Internet, to improve health and health care 4 (Table 1). mHealth, a subsegment of eHealth, is the use of mobile computing and communication technologies (eg, mobile phones, wearable sensors) for health services and information.4,5 mHealth technology uses techniques and advanced concepts from an array of disciplines, for example, computer science, electrical and

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Section: Use Of Mhealth In Management Of Dyslipidemiamentioning

confidence: 99%

Section: Use Of Mhealth In Management Of Dyslipidemiamentioning

confidence: 99%

Section: Use Of Mhealth In Management Of Dyslipidemiamentioning

confidence: 99%

See 1 more Smart Citation

Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention

Burke¹,

Ma²,

Azar³

et al. 2015

Circulation

476

389

View full text Add to dashboard Cite

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“…Of these, 19 were relevant, of which full text was available for 14. One of these studies, by Stuckey et al, 268 discussed a meta-analysis undertaken by Bravata et al, 269 which is discussed below.…”

Section: Economic Analysismentioning

confidence: 99%

Screening for glucose intolerance and development of a lifestyle education programme for prevention of type 2 diabetes in a population with intellectual disabilities: the STOP Diabetes research project

Dunkley

Tyrer

Spong

et al. 2017

Programme Grants Appl Res

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BackgroundThe prevalence of type 2 diabetes mellitus (T2DM) and of cardiovascular disease (CVD) is believed to be higher among people with intellectual disability (ID) than in the general population. However, research on prevalence and prevention in this population is limited.ObjectivesThe objectives of this programme of work were to establish a programme of research that would significantly enhance the knowledge and understanding of impaired glucose regulation (IGR) and T2DM in people with ID; to test strategies for the early identification of IGR and T2DM in people with ID; and to develop a lifestyle education programme and educator training protocol to promote behaviour change in a population with ID and IGR (or at a high risk of T2DM/CVD).SettingLeicestershire, UK.ParticipantsAdults with ID were recruited from community settings, including residential homes and family homes. Adults with mild to moderate ID who had an elevated body mass index (BMI) of ≥ 25 kg/m2and/or IGR were invited to take part in the education programme.Main outcome measuresThe primary outcome of the screening programme was the prevalence of screen-detected T2DM and IGR. The uptake, feasibility and acceptability of the intervention were assessed.Data sourcesParticipants were recruited from general practices, specialist ID services and clinics, and through direct contact.ResultsA total of 930 people with ID were recruited to the screening programme: 58% were male, 80% were white and 68% were overweight or obese. The mean age of participants was 43.3 years (standard deviation 14.2 years). Bloods were obtained for 675 participants (73%). The prevalence of previously undiagnosed T2DM was 1.3% [95% confidence interval (CI) 0.5% to 2%] and of IGR was 5% (95% CI 4% to 7%). Abnormal IGR was more common in those of non-white ethnicity; those with a first-degree family history of diabetes; those with increasing weight, waist circumference, BMI, diastolic blood pressure or triglycerides; and those with lower high-density lipoprotein cholesterol. We developed a lifestyle educational programme for people with ID, informed by findings from qualitative stakeholder interviews (health-care professionals,n = 14; people with ID,n = 7) and evidence reviews. Subsequently, 11 people with ID (and carers) participated in pilot education sessions (two groups) and five people attended education for the feasibility stage (one group). We found that it was feasible to collect primary outcome measures on physical activity and sedentary behaviour using wrist-worn accelerometers. We found that the programme was relatively costly, meaning that large changes in activity or diet (or a reduction in programme costs) would be necessary for the programme to be cost-effective. We also developed a quality development process for assessing intervention fidelity.LimitationsWe were able to screen only around 30% of the population and involved only a small number in the piloting and feasibility work.ConclusionsThe results from this programme of work have significantly enhanced the existing knowledge and understanding of T2DM and IGR in people with ID. We have developed a lifestyle education programme and educator training protocol to promote behaviour change in this population.Future workFurther work is needed to evaluate the STOP Diabetes intervention to identify cost-effective strategies for its implementation.Trial registrationClinicalTrials.gov NCT02513277.FundingThe National Institute for Health Research Programme Grants for Applied Research programme and will be published in full inHealth Research Programme Grants for Applied Research; Vol. 5, No. 11. See the NIHR Journals Library website for further project information.

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“…Clinical outcomes are reported elsewhere. 15 During this 8-week study, two alarms were generated by two participants determined to have previously undiagnosed conditions. On day 10 of the study, a participant submitted an elevated BG of 20.9 mmol/liter, and on day 13, another participant submitted a systolic BP of 195 mm Hg, which was lower than the alarm threshold but detected by the CT when monitoring the database.…”

Section: Resultsmentioning

confidence: 99%

Remote Monitoring Technologies for the Prevention of Metabolic Syndrome: The Diabetes and Technology for Increased Activity (DaTA) Study

Stuckey

Fulkerson²,

Read

et al. 2011

J Diabetes Sci Technol

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Diabetes and Technology for Increased Activity (DaTA) Study: Results of a Remote Monitoring Intervention for Prevention of Metabolic Syndrome

Cited by 43 publications

References 26 publications

Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention

Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention

Screening for glucose intolerance and development of a lifestyle education programme for prevention of type 2 diabetes in a population with intellectual disabilities: the STOP Diabetes research project

Remote Monitoring Technologies for the Prevention of Metabolic Syndrome: The Diabetes and Technology for Increased Activity (DaTA) Study

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