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

Background. The established interventions for weight loss are resource intensive which can create barriers for full participation and ultimate translation. The major goal of this pilot study was to evaluate the feasibility, acceptability, and preliminary efficacy of theoretically based behavioral interventions delivered by smartphone technology. Methods. The study randomized 68 obese adults to receive one of four interventions for six months: (1) intensive counseling intervention, (2) intensive counseling plus smartphone intervention, (3) a less intensive counseling plus smartphone intervention, and (4) smartphone intervention only. The outcome measures of weight, BMI, waist circumference, and self-reported dietary intake and physical activity were assessed at baseline and six months. Results. The sample was 78% female and 49% African American, with an average age of 45 years, and average BMI of 34.3 kg/m2. There were trends for differences in weight loss among the four intervention groups. Participants in the intensive counseling plus self-monitoring smartphone group and less intensive counseling plus self-monitoring smartphone group tended to lose more weight than other groups (5.4 kg and 3.3 kg, resp.). Conclusions. The results of this pilot trial of a weight loss intervention provide preliminary support for using a smartphone application for self-monitoring as an adjunct to behavioral counseling.

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Objective This systematic review was conducted to determine user satisfaction and effectiveness of smartphone applications and text messaging interventions to promote weight reduction and physical activity. Methods Studies of smartphone applications and text messaging interventions related to the cardiovascular risk factors of physical inactivity and overweight/obesity published between January 2005 and August 2010 were eligible. Studies related to disease management were excluded. Study characteristics and results were gathered and synthesized. Results A total of 36 citations from CINAHL, EMBASE, MEDLINE, PsyclNFO, and PubMed were identified; 7 articles were eligible for inclusion. The most frequent outcome measured in the studies was change in the weight of participants (57%). More than half of the studies (71%) reported statistically significant results in at least 1 outcome of weight loss, physical activity, dietary intake, decreased body mass index, decreased waist circumference, sugar-sweetened beverage intake, screen time, and satisfaction or acceptability outcomes. Conclusions All of the technology interventions that were supported by education or an additional intervention demonstrated a beneficial impact of text messaging or smartphone application for reduction of physical inactivity and/or overweight/obesity. More rigorous trials that determine what parts of the technology or intervention are effective as well as establishment of cost-effectiveness are necessary for further evaluation of smartphone and text messaging interventions.

Objective: This systematic review focused on randomized controlled trials (RCTs) with physicians and nurses that tested interventions designed to improve their mental health, well-being, physical health, and lifestyle behaviors. Data Source: A systematic search of electronic databases from 2008 to May 2018 included PubMed, CINAHL, PsycINFO, SPORTDiscus, and the Cochrane Library. Study Inclusion and Exclusion Criteria: Inclusion criteria included an RCT design, samples of physicians and/or nurses, and publication year 2008 or later with outcomes targeting mental health, well-being/resiliency, healthy lifestyle behaviors, and/or physical health. Exclusion criteria included studies with a focus on burnout without measures of mood, resiliency, mindfulness, or stress; primary focus on an area other than health promotion; and non-English papers. Data Extraction: Quantitative and qualitative data were extracted from each study by 2 independent researchers using a standardized template created in Covidence. Data Synthesis: Although meta-analytic pooling across all studies was desired, a wide array of outcome measures made quantitative pooling unsuitable. Therefore, effect sizes were calculated and a mini meta-analysis was completed. Results: Twenty-nine studies (N = 2708 participants) met the inclusion criteria. Results indicated that mindfulness and cognitive-behavioral therapy-based interventions are effective in reducing stress, anxiety, and depression. Brief interventions that incorporate deep breathing and gratitude may be beneficial. Visual triggers, pedometers, and health coaching with texting increased physical activity. Conclusion: Healthcare systems must promote the health and well-being of physicians and nurses with evidence-based interventions to improve population health and enhance the quality and safety of the care that is delivered.