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      mActive: A Randomized Clinical Trial of an Automated mHealth Intervention for Physical Activity Promotion

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          Abstract

          Background

          We hypothesized that a fully automated mobile health ( mHealth) intervention with tracking and texting components would increase physical activity.

          Methods and Results

          mActive enrolled smartphone users aged 18 to 69 years at an ambulatory cardiology center in Baltimore, Maryland. We used sequential randomization to evaluate the intervention's 2 core components. After establishing baseline activity during a blinded run‐in (week 1), in phase I (weeks 2 to 3), we randomized 2:1 to unblinded versus blinded tracking. Unblinding allowed continuous access to activity data through a smartphone interface. In phase II (weeks 4 to 5), we randomized unblinded participants 1:1 to smart texts versus no texts. Smart texts provided smartphone‐delivered coaching 3 times/day aimed at individual encouragement and fostering feedback loops by a fully automated, physician‐written, theory‐based algorithm using real‐time activity data and 16 personal factors with a 10 000 steps/day goal. Forty‐eight outpatients (46% women, 21% nonwhite) enrolled with a mean± SD age of 58±8 years, body mass index of 31±6 kg/m 2, and baseline activity of 9670±4350 steps/day. Daily activity data capture was 97.4%. The phase I change in activity was nonsignificantly higher in unblinded participants versus blinded controls by 1024 daily steps (95% confidence interval [ CI], −580 to 2628; P=0.21). In phase II, participants receiving texts increased their daily steps over those not receiving texts by 2534 (95% CI, 1318 to 3750; P<0.001) and over blinded controls by 3376 (95% CI, 1951 to 4801; P<0.001).

          Conclusions

          An automated tracking‐texting intervention increased physical activity with, but not without, the texting component. These results support new mHealth tracking technologies as facilitators in need of behavior change drivers.

          Clinical Trial Registration

          URL: http://ClinicalTrials.gov/. Unique identifier: NCT01917812.

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          Most cited references17

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          Interventions to promote physical activity and dietary lifestyle changes for cardiovascular risk factor reduction in adults: a scientific statement from the American Heart Association.

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            Apps of steel: are exercise apps providing consumers with realistic expectations?: a content analysis of exercise apps for presence of behavior change theory.

            To quantify the presence of health behavior theory constructs in iPhone apps targeting physical activity. This study used a content analysis of 127 apps from Apple's (App Store) Health & Fitness category. Coders downloaded the apps and then used an established theory-based instrument to rate each app's inclusion of theoretical constructs from prominent behavior change theories. Five common items were used to measure 20 theoretical constructs, for a total of 100 items. A theory score was calculated for each app. Multiple regression analysis was used to identify factors associated with higher theory scores. Apps were generally observed to be lacking in theoretical content. Theory scores ranged from 1 to 28 on a 100-point scale. The health belief model was the most prevalent theory, accounting for 32% of all constructs. Regression analyses indicated that higher priced apps and apps that addressed a broader activity spectrum were associated with higher total theory scores. It is not unexpected that apps contained only minimal theoretical content, given that app developers come from a variety of backgrounds and many are not trained in the application of health behavior theory. The relationship between price and theory score corroborates research indicating that higher quality apps are more expensive. There is an opportunity for health and behavior change experts to partner with app developers to incorporate behavior change theories into the development of apps. These future collaborations between health behavior change experts and app developers could foster apps superior in both theory and programming possibly resulting in better health outcomes.
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              Effect of exercise training on depressive symptoms among patients with a chronic illness: a systematic review and meta-analysis of randomized controlled trials.

              Physical inactivity and comorbid depressive symptoms are prevalent among patients with a chronic illness. To our knowledge, randomized controlled trials of the effects of exercise training on depressive symptoms among patients with a chronic illness have not been systematically reviewed. We estimated the population effect of exercise training on depressive symptoms and determined whether the effect varied according to patient characteristics and modifiable features of exercise exposure and clinical settings. Articles published before June 1, 2011, were located using the Physical Activity Guidelines for Americans Scientific Database, Google Scholar, MEDLINE, PsycINFO, PubMed, and Web of Science. Ninety articles involving 10,534 sedentary patients with a chronic illness were selected. Included articles required (1) randomized allocation to an exercise intervention or nonexercise comparison condition and (2) a depression outcome assessed at baseline and at mid- and/or postintervention. Hedges d effect sizes were computed, study quality was evaluated, and random effects models were used to estimate sampling error and population variance of the observed effects. Exercise training significantly reduced depressive symptoms by a heterogeneous mean effect size delta (Δ) of 0.30 (95% CI, 0.25-0.36). Larger antidepressant effects were obtained when (1) baseline depressive symptoms were higher, (2) patients met recommended physical activity levels, and (3) the trial primary outcome, predominantly function related, was significantly improved among patients having baseline depressive symptoms indicative of mild-to-moderate depression. Exercise reduces depressive symptoms among patients with a chronic illness. Patients with depressive symptoms indicative of mild-to-moderate depression and for whom exercise training improves function-related outcomes achieve the largest antidepressant effects.
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                Author and article information

                Journal
                J Am Heart Assoc
                J Am Heart Assoc
                10.1002/(ISSN)2047-9980
                JAH3
                ahaoa
                Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
                John Wiley and Sons Inc. (Hoboken )
                2047-9980
                09 November 2015
                November 2015
                : 4
                : 11 ( doiID: 10.1002/jah3.2015.4.issue-11 )
                : e002239
                Affiliations
                [ 1 ] Ciccarone Center for the Prevention of Heart DiseaseJohns Hopkins University School of Medicine Baltimore MD
                [ 2 ] Welch Center for Prevention, Epidemiology and Clinical ResearchJohns Hopkins Bloomberg School of Public Health Baltimore MD
                Author notes
                [*] [* ] Correspondence to: Seth S. Martin, MD, MHS, Johns Hopkins Hospital, 600 N. Wolfe St, Carnegie 591, Baltimore, MD 21287. E‐mail: smart100@ 123456jhmi.edu
                Article
                JAH31194
                10.1161/JAHA.115.002239
                4845232
                26553211
                624b9c10-e030-45ba-a304-bbd4e1a69adf
                © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

                This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 20 July 2015
                : 30 September 2015
                Page count
                Pages: 9
                Funding
                Funded by: PJ Schafer Cardiovascular Research Fund
                Funded by: National Institutes of Health
                Award ID: T32HL07024
                Funded by: Pollin Cardiovascular Prevention Fellowship
                Funded by: Marie‐Josée and Henry R Kravis Endowed Fellowship
                Funded by: Kenneth Jay Pollin Professorship
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                jah31194
                November 2015
                Converter:WILEY_ML3GV2_TO_NLMPMC version:4.8.4 mode:remove_FC converted:03.03.2016

                Cardiovascular Medicine
                accelerometer,activity tracker,automation,cardiovascular disease,digital health,ehealth,health technology,mhealth,mobile phone,pedometer,physical activity,prevention,smartphone,text messages,texting,wearable device,wearable sensor

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