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Web Support for Weight-Loss Interventions: PREDIRCAM2 Clinical Trial Baseline Characteristics and Preliminary Results

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Abstract

An ongoing clinical trial is testing the efficacy of web telematic support in a structured program for obesity treatment and diabetes prevention. Participants were recruited from two tertiary-care hospitals and randomized to receive either a telematic intervention (TI) supported by PREDIRCAM2 web platform or a non-telematic intervention (NTI). All receive 1-year follow-up. Both interventions consist of tailored dietary and exercise prescriptions, based on a Mediterranean dietary pattern and general WHO exercise recommendations for adults. At 6 months, both groups have received 7 contacts, 3 exclusively telematic for the TI group. This is a preliminary result intention-to-treat analysis. One hundred eighty-three participants were recruited, with a mean body mass index of 34.75 ± 2.75 kg/m2. General dropout rate at 6 months was 26.8%. Weight changes were statistically significant at months 3 and 6 compared to baseline, -2.915 ± 0.24 kg, -3.29 ± 0.36 kg, respectively (P < 0.001), but not statistically significant between the 3- and 6-month time points -0.37 ± 0.21 kg (P = 0.24). Mean group differences showed that the TI group lost 1.61 ± 1.88 kg more than the NTI group (P = 0.39). Waist, waist/hip ratio, resting heart rate, blood pressure, HbA1c, and low-density lipoprotein cholesterol also showed statistically significant changes at 6 months, with no significant differences between groups. Weight loss in the TI group shows similar results as the usual care NTI group for weight loss and control of obesity comorbidities. At completion of the clinical trial, these results will be reevaluated to assess the potential role of web support in weight-loss maintenance and its cost-effectiveness.

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... The 2-year follow-up rate of this study was 70.5%, i.e. similar to other lifestyle interventions [26,34]. As previous ICT interventions for obesity or MetS had shorter follow-up periods and the follow-up rates have varied from 73.1% to 79.1% during the 6 months intervention [17,33,35], this study is fully feasible and generalizable, and long-term applicable. ...
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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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Healthy diet and regular physical activity are powerful tools in reducing diabetes and cardiometabolic risk. Various international scientific and health organizations have advocated the use of new technologies to solve these problems. The PREDIRCAM project explores the contribution that a technological system could offer for the continuous monitoring of lifestyle habits and individualized treatment of obesity as well as cardiometabolic risk prevention. PREDIRCAM is a technological platform for patients and professionals designed to improve the effectiveness of lifestyle behavior modifications through the intensive use of the latest information and communication technologies. The platform consists of a web-based application providing communication interface with monitoring devices of physiological variables, application for monitoring dietary intake, ad hoc electronic medical records, different communication channels, and an intelligent notification system. A 2-week feasibility study was conducted in 15 volunteers to assess the viability of the platform. The website received 244 visits (average time/session: 17 min 45 s). A total of 435 dietary intakes were recorded (average time for each intake registration, 4 min 42 s ± 2 min 30 s), 59 exercises were recorded in 20 heart rate monitor downloads, 43 topics were discussed through a forum, and 11 of the 15 volunteers expressed a favorable opinion toward the platform. Food intake recording was reported as the most laborious task. Ten of the volunteers considered long-term use of the platform to be feasible. The PREDIRCAM platform is technically ready for clinical evaluation. Training is required to use the platform and, in particular, for registration of dietary food intake.
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Obesity is a public health crisis that has reached epidemic proportions. Although intensive behavioral interventions can produce clinically significant weight loss, their cost to implement, coupled with resource limitations, pose significant barriers to scalability. To overcome these challenges, researchers have made attempts to shift intervention content to the Internet and other mobile devices. This article systematically reviews the recent literature examining technology-supported interventions for weight loss and maintenance among overweight and obese adults. Thirteen studies were identified that satisfied our inclusion criteria (12 weight loss trials, 1 weight maintenance trial). Our findings suggest that technology interventions may be efficacious at producing weight loss. However, several studies are limited by methodologic shortcomings. There are insufficient data to evaluate their efficacy for weight maintenance. Further research is needed that employs state-of-the-art methodology, with careful attention being paid to adherence and fidelity to intervention protocols.
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Objective: The aim of this study was to test the efficacy of technology-based weight loss interventions for endometrial cancer (EC) survivors with obesity. Methods: EC survivors with obesity (n = 196) from three medical centers completed assessments for knowledge of obesity as a risk for EC and interest in weight management. Forty-one women were randomized to a 6-month intervention: telemedicine with Wi-Fi scales, text messaging (texting), or enhanced usual care (EUC). Changes in anthropometrics and psychosocial measures were analyzed. Results: One-third of survey participants lacked awareness that obesity increased the risk of EC, and 40% misclassified their body mass. There were no significant differences in weight loss across interventions (mean = -4.4 kg, SD = 6.5 kg). Telemedicine showed improvements in physical health and cancer-related body image (Ps = 0.04) compared to texting and in sexual functioning compared to EUC (P = 0.03). Total physical activity was increased in EUC compared with telemedicine (P = 0.01), and vigorous physical activity was increased in EUC compared with both interventions (P = 0.01-0.03); walking significantly increased in texting compared with telemedicine (P = 0.02). Conclusions: Technology-based lifestyle interventions in EC survivors with obesity were accessible and resulted in weight loss and improved quality of life. EUC also produced weight loss, demonstrating a potential for beginning weight management with information on specific diet and exercise goals.
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Background: The chronicity status of breast cancer survivors suggests a growing need for cancer rehabilitation. Currently, the use of technology is a promising strategy for providing support, as reflected in the emergence of research interest in Web-based interventions in cancer survivorship. Methods: A randomized controlled trial was conducted that included a total of 81 participants who had completed adjuvant therapy (except hormone treatment) for stage I to IIIA breast cancer. Participants were randomly assigned to an 8-week Internet-based, tailored exercise program (n = 40) or to a control group (n = 41).The instruments used at baseline, 8 weeks, and 6-month follow-up were the European Organization for Research and Treatment of Cancer Quality-of-Life Questionnaire Core 30 and its breast cancer module, the Brief Pain Inventory, the handgrip dynamometer, the isometric abdominal test, the back dynamometer, the multiple sit-to-stand test, and the Piper Fatigue Scale. Results: After the intervention, the telerehabilitation group had significantly improved scores for global health status, physical, role, cognitive functioning, and arm symptoms (all P < .01) as well as pain severity (P = .001) and pain interference (P = .045) compared with the control group. Significant improvements also were observed favoring the telerehabilitation group for affected and nonaffected side handgrip (both P = .006), abdominal, back and lower body strength (all P < .01), and total fatigue (P < .001). These findings were maintained after 6 months of follow-up, except for role functioning, pain severity, and nonaffected side handgrip. Analysis was based on an intention-to-treat principle. Conclusions: This program may improve adverse effects and maintain benefits in breast cancer survivors. The results of this study have encouraging implications for cancer care. Cancer 2016. © 2016 American Cancer Society.
Article
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Article
A systematic review of randomized controlled trials was conducted to evaluate the effectiveness of eHealth interventions for the prevention and treatment of overweight and obesity in adults. Eight databases were searched for studies published in English from 1995 to 17 September 2014. Eighty-four studies were included, with 183 intervention arms, of which 76% (n = 139) included an eHealth component. Sixty-one studies had the primary aim of weight loss, 10 weight loss maintenance, eight weight gain prevention, and five weight loss and maintenance. eHealth interventions were predominantly delivered using the Internet, but also email, text messages, monitoring devices, mobile applications, computer programs, podcasts and personal digital assistants. Forty percent (n = 55) of interventions used more than one type of technology, and 43.2% (n = 60) were delivered solely using eHealth technologies. Meta-analyses demonstrated significantly greater weight loss (kg) in eHealth weight loss interventions compared with control (MD -2.70 [-3.33,-2.08], P < 0.001) or minimal interventions (MD -1.40 [-1.98,-0.82], P < 0.001), and in eHealth weight loss interventions with extra components or technologies (MD 1.46 [0.80, 2.13], P < 0.001) compared with standard eHealth programmes. The findings support the use of eHealth interventions as a treatment option for obesity, but there is insufficient evidence for the effectiveness of eHealth interventions for weight loss maintenance or weight gain prevention. © 2015 World Obesity.