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      Using an electronic activity monitor system as an intervention modality: A systematic review

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          Abstract

          Background

          Obesity is a growing global health concern that may lead to cardiovascular disease, type II diabetes, and cancer. Several systematic reviews have shown that technology is successful in combating obesity through increased physical activity, but there is no known review on interventions that use an electronic activity monitor system (EAMS). EAMSs are defined as a wearable device that objectively measures lifestyle physical activity and can provide feedback, beyond the display of basic activity count information, via the monitor display or through a partnering application to elicit continual self-monitoring of activity behavior. These devices improve upon standard pedometers because they have the ability to provide visual feedback on activity progression, verbal encouragement, and social comparison. This systematic review aimed to synthesize the efficacy and feasibility results of EAMSs within published physical activity interventions.

          Methods

          Electronic databases and journal references were searched for relevant articles. Data sources included CINAHL, Cochrane CENTRAL, Medline Ovid, PsycINFO, and clinicaltrials.gov. Out of the 1,574 retrieved, 11 articles met the inclusion criteria. These articles were reviewed for quality and content based on a risk of bias tool and intervention components.

          Results

          Most articles were determined to be of medium quality while two were of low quality, and one of high quality. Significant pre-post improvements in the EAMS group were found in five of nine studies for physical activity and in four of five studies for weight. One found a significant increase in physical activity and two studies found significant weight loss in the intervention group compared with the comparator group. The EAMS interventions appear to be feasible with most studies reporting continual wear of the device during waking hours and a higher retention rate of participants in the EAMS groups.

          Conclusion

          These studies provide preliminary evidence suggesting that EAMS can increase physical activity and decrease weight significantly, but their efficacy compared to other interventions has not yet been demonstrated. More high-quality randomized controlled trials are needed to evaluate the overall effect of EAMS, examine which EAMS features are most effective, and determine which populations are most receptive to an EAMS.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12889-015-1947-3) contains supplementary material, which is available to authorized users.

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          Most cited references27

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          Physical Activity and Public Health: Updated Recommendation for Adults From the American College of Sports Medicine and the American Heart Association

          In 1995 the American College of Sports Medicine and the Centers for Disease Control and Prevention published national guidelines on Physical Activity and Public Health. The Committee on Exercise and Cardiac Rehabilitation of the American Heart Association endorsed and supported these recommendations. The purpose of the present report is to update and clarify the 1995 recommendations on the types and amounts of physical activity needed by healthy adults to improve and maintain health. Development of this document was by an expert panel of scientists, including physicians, epidemiologists, exercise scientists, and public health specialists. This panel reviewed advances in pertinent physiologic, epidemiologic, and clinical scientific data, including primary research articles and reviews published since the original recommendation was issued in 1995. Issues considered by the panel included new scientific evidence relating physical activity to health, physical activity recommendations by various organizations in the interim, and communications issues. Key points related to updating the physical activity recommendation were outlined and writing groups were formed. A draft manuscript was prepared and circulated for review to the expert panel as well as to outside experts. Comments were integrated into the final recommendation. To promote and maintain health, all healthy adults aged 18 to 65 yr need moderate-intensity aerobic (endurance) physical activity for a minimum of 30 min on five days each week or vigorous-intensity aerobic physical activity for a minimum of 20 min on three days each week. [I (A)] Combinations of moderate- and vigorous-intensity activity can be performed to meet this recommendation. [IIa (B)] For example, a person can meet the recommendation by walking briskly for 30 min twice during the week and then jogging for 20 min on two other days. Moderate-intensity aerobic activity, which is generally equivalent to a brisk walk and noticeably accelerates the heart rate, can be accumulated toward the 30-min minimum by performing bouts each lasting 10 or more minutes. [I (B)] Vigorous-intensity activity is exemplified by jogging, and causes rapid breathing and a substantial increase in heart rate. In addition, every adult should perform activities that maintain or increase muscular strength and endurance a minimum of two days each week. [IIa (A)] Because of the dose-response relation between physical activity and health, persons who wish to further improve their personal fitness, reduce their risk for chronic diseases and disabilities or prevent unhealthy weight gain may benefit by exceeding the minimum recommended amounts of physical activity. [I (A)]
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            Behavior Change Techniques Implemented in Electronic Lifestyle Activity Monitors: A Systematic Content Analysis

            Background Electronic activity monitors (such as those manufactured by Fitbit, Jawbone, and Nike) improve on standard pedometers by providing automated feedback and interactive behavior change tools via mobile device or personal computer. These monitors are commercially popular and show promise for use in public health interventions. However, little is known about the content of their feedback applications and how individual monitors may differ from one another. Objective The purpose of this study was to describe the behavior change techniques implemented in commercially available electronic activity monitors. Methods Electronic activity monitors (N=13) were systematically identified and tested by 3 trained coders for at least 1 week each. All monitors measured lifestyle physical activity and provided feedback via an app (computer or mobile). Coding was based on a hierarchical list of 93 behavior change techniques. Further coding of potentially effective techniques and adherence to theory-based recommendations were based on findings from meta-analyses and meta-regressions in the research literature. Results All monitors provided tools for self-monitoring, feedback, and environmental change by definition. The next most prevalent techniques (13 out of 13 monitors) were goal-setting and emphasizing discrepancy between current and goal behavior. Review of behavioral goals, social support, social comparison, prompts/cues, rewards, and a focus on past success were found in more than half of the systems. The monitors included a range of 5-10 of 14 total techniques identified from the research literature as potentially effective. Most of the monitors included goal-setting, self-monitoring, and feedback content that closely matched recommendations from social cognitive theory. Conclusions Electronic activity monitors contain a wide range of behavior change techniques typically used in clinical behavioral interventions. Thus, the monitors may represent a medium by which these interventions could be translated for widespread use. This technology has broad applications for use in clinical, public health, and rehabilitation settings.
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              Validity of consumer-based physical activity monitors.

              Many consumer-based monitors are marketed to provide personal information on the levels of physical activity and daily energy expenditure (EE), but little or no information is available to substantiate their validity. This study aimed to examine the validity of EE estimates from a variety of consumer-based, physical activity monitors under free-living conditions. Sixty (26.4 ± 5.7 yr) healthy males (n = 30) and females (n = 30) wore eight different types of activity monitors simultaneously while completing a 69-min protocol. The monitors included the BodyMedia FIT armband worn on the left arm, the DirectLife monitor around the neck, the Fitbit One, the Fitbit Zip, and the ActiGraph worn on the belt, as well as the Jawbone Up and Basis B1 Band monitor on the wrist. The validity of the EE estimates from each monitor was evaluated relative to criterion values concurrently obtained from a portable metabolic system (i.e., Oxycon Mobile). Differences from criterion measures were expressed as a mean absolute percent error and were evaluated using 95% equivalence testing. For overall group comparisons, the mean absolute percent error values (computed as the average absolute value of the group-level errors) were 9.3%, 10.1%, 10.4%, 12.2%, 12.6%, 12.8%, 13.0%, and 23.5% for the BodyMedia FIT, Fitbit Zip, Fitbit One, Jawbone Up, ActiGraph, DirectLife, NikeFuel Band, and Basis B1 Band, respectively. The results from the equivalence testing showed that the estimates from the BodyMedia FIT, Fitbit Zip, and NikeFuel Band (90% confidence interval = 341.1-359.4) were each within the 10% equivalence zone around the indirect calorimetry estimate. The indicators of the agreement clearly favored the BodyMedia FIT armband, but promising preliminary findings were also observed with the Fitbit Zip.
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                Author and article information

                Contributors
                zalewisp@utmb.edu
                ellyons@utmb.edu
                jmjarvis@utmb.edu
                jbaillar@utmb.edu
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                24 June 2015
                24 June 2015
                2015
                : 15
                : 585
                Affiliations
                [ ]Division of Rehabilitation Sciences, University of Texas Medical Branch (UTMB), 301 University Blvd, Galveston, TX USA
                [ ]Department of Preventive Medicine & Community Health, UTMB, Galveston, TX USA
                [ ]Department of Nutrition and Metabolism, UTMB, Galveston, TX USA
                [ ]Center for Interdisciplinary Research in Women’s Health, UTMB, Galveston, TX USA
                [ ]Division of Epidemiology and Outcomes, Correctional Managed Care, UTMB, Galveston, TX USA
                Article
                1947
                10.1186/s12889-015-1947-3
                4479243
                26104189
                8cae70f8-5551-4cb5-896d-936d54f41d45
                © Lewis et al. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 29 January 2015
                : 17 June 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Public health
                activity monitor,wearable technology,activity tracker,physical activity,weight,obesity,technology,self-monitoring,systematic review

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