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      Engagement in a Diabetes Self-management Website: Usage Patterns and Generalizability of Program Use

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          Abstract

          Background

          Increased access to the Internet and the availability of efficacious eHealth interventions offer great promise for assisting adults with diabetes to change and maintain health behaviors. A key concern is whether levels of engagement in Internet programs are sufficient to promote and sustain behavior change.

          Objective

          This paper used automated data from an ongoing Internet-based diabetes self-management intervention study to calculate various indices of website engagement. The multimedia website involved goal setting, action planning, and self-monitoring as well as offering features such as “Ask an Expert” to enhance healthy eating, physical activity, and medication adherence. We also investigated participant characteristics associated with website engagement and the relationship between website use and 4-month behavioral and health outcomes.

          Methods

          We report on participants in a randomized controlled trial (RCT) who were randomized to receive (1) the website alone (n = 137) or (2) the website plus human support (n = 133) that included additional phone calls and group meetings. The website was available in English and Spanish and included features to enhance engagement and user experience. A number of engagement variables were calculated for each participant including number of log-ins, number of website components visited at least twice, number of days entering self-monitoring data, number of visits to the “Action Plan” section, and time on the website. Key outcomes included exercise, healthy eating, and medication adherence as well as body mass index (BMI) and biological variables related to cardiovascular disease risk.

          Results

          Of the 270 intervention participants, the average age was 60, the average BMI was 34.9 kg/m 2, 130 (48%) were female, and 62 (23%) self-reported Latino ethnicity. The number of participant visits to the website over 4 months ranged from 1 to 119 (mean 28 visits, median 18). Usage decreased from 70% of participants visiting at least weekly during the first 6 weeks to 47% during weeks 7 to 16. There were no significant differences between website only and website plus support conditions on most of the engagement variables. In total, 75% of participants entered self-monitoring data at least once per week. Exercise action plan pages were visited more often than medication taking and healthy eating pages (mean of 4.3 visits vs 2.8 and 2.0 respectively, P < .001). Spearman nonparametric correlations indicated few significant associations between patient characteristics and summary website engagement variables, and key factors such as ethnicity, baseline computer use, age, health literacy, and education were not related to use. Partial correlations indicated that engagement, especially in self-monitoring, was most consistently related to improvement in healthy eating ( r = .20, P = .04) and reduction of dietary fat ( r = -.31, P = .001). There was also a significant correlation between self-monitoring and improvement in exercise ( r = .20, P = .033) but not with medication taking.

          Conclusions

          Participants visited the website fairly often and used all of the theoretically important sections, but engagement decreased over 4 months. Usage rates and patterns were similar for a wide range of participants, which has encouraging implications for the potential reach of online interventions.

          Trial Registration

          NCT00987285; http://clinicaltrials.gov/show/NCT00987285 (Archived by WebCite at http://www.webcitation.org/5vpe4RHTV)

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          Most cited references34

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          The UKPDS risk engine: a model for the risk of coronary heart disease in Type II diabetes (UKPDS 56).

          A definitive model for predicting absolute risk of coronary heart disease (CHD) in male and female people with Type II diabetes is not yet available. This paper provides an equation for estimating the risk of new CHD events in people with Type II diabetes, based on data from 4540 U.K. Prospective Diabetes Study male and female patients. Unlike previously published risk equations, the model is diabetes-specific and incorporates glycaemia, systolic blood pressure and lipid levels as risk factors, in addition to age, sex, ethnic group, smoking status and time since diagnosis of diabetes. All variables included in the final model were statistically significant (P<0.001, except smoking for which P=0.0013) in likelihood ratio testing. This model provides the estimates of CHD risk required by current guidelines for the primary prevention of CHD in Type II diabetes.
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            Effects of Internet behavioral counseling on weight loss in adults at risk for type 2 diabetes: a randomized trial.

            Weight loss programs on the Internet appear promising for short-term weight loss but have not been studied for weight loss in individuals at risk of type 2 diabetes; thus, the longer-term efficacy is unknown. To compare the effects of an Internet weight loss program alone vs with the addition of behavioral counseling via e-mail provided for 1 year to individuals at risk of type 2 diabetes. A single-center randomized controlled trial conducted from September 2001 to September 2002 in Providence, RI, of 92 overweight adults whose mean (SD) age was 48.5 (9.4) years and body mass index, 33.1 (3.8). Participants were randomized to a basic Internet (n = 46) or to an Internet plus behavioral e-counseling program (n = 46). Both groups received 1 face-to-face counseling session and the same core Internet programs and were instructed to submit weekly weights. Participants in e-counseling submitted calorie and exercise information and received weekly e-mail behavioral counseling and feedback from a counselor. Measured weight and waist circumference at 0 and 12 months. Intent-to-treat analyses showed the behavioral e-counseling group lost more mean (SD) weight at 12 months than the basic Internet group (-4.4 [6.2] vs -2.0 [5.7] kg; P =.04), and had greater decreases in percentage of initial body weight (4.8% vs 2.2%; P =.03), body mass index (-1.6 [2.2] vs -0.8 [2.1]; P =.03), and waist circumference (-7.2 [7.5] vs -4.4 [5.7] cm; P =.05). Adding e-mail counseling to a basic Internet weight loss intervention program significantly improved weight loss in adults at risk of diabetes.
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              Multiple behavioral risk factor interventions in primary care. Summary of research evidence.

              An important barrier to the delivery of health behavior change interventions in primary care settings is the lack of an integrated screening and intervention approach that can cut across multiple risk factors and help clinicians and patients to address these risks in an efficient and productive manner. We review the evidence for interventions that separately address lack of physical activity, an unhealthy diet, obesity, cigarette smoking, and risky/harmful alcohol use, and evidence for interventions that address multiple behavioral risks drawn primarily from the cardiovascular and diabetes literature. There is evidence for the efficacy of interventions to reduce smoking and risky/harmful alcohol use in unselected patients, and evidence for the efficacy of medium- to high-intensity dietary counseling by specially trained clinicians in high-risk patients. There is fair to good evidence for moderate, sustained weight loss in obese patients receiving high-intensity counseling, but insufficient evidence regarding weight loss interventions in nonobese adults. Evidence for the efficacy of physical activity interventions is limited. Large gaps remain in our knowledge about the efficacy of interventions to address multiple behavioral risk factors in primary care. We derive several principles and strategies for delivering behavioral risk factor interventions in primary care from the research literature. These principles can be linked to the "5A's" construct (assess, advise, agree, assist, and arrange-follow up) to provide a unifying conceptual framework for describing, delivering, and evaluating health behavioral counseling interventions in primary healthcare settings. We also provide recommendations for future research.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                JMIR
                Journal of Medical Internet Research
                Gunther Eysenbach (Centre for Global eHealth Innovation, Toronto, Canada )
                1438-8871
                Jan-Mar 2011
                25 January 2011
                : 13
                : 1
                : e9
                Affiliations
                [4] 4simpleOregon Research Institute Eugene, ORUnited States
                [3] 3simpleVirginia Polytechnic Institute and State University Blacksburg, VAUnited States
                [2] 2simpleIntervision Media Eugene, ORUnited States
                [1] 1simpleInstitute for Health Research simpleKaiser Permanente Denver, COUnited States
                Article
                v13i1e9
                10.2196/jmir.1391
                3221359
                21371992
                1669366e-030e-4d8d-aa2d-b54a087ee26e
                ©Russell E Glasgow, Steven M Christiansen, Deanna Kurz, Diane K King, Tim Woolley, Andrew J Faber, Paul A Estabrooks, Lisa Strycker, Deborah Toobert, Jennifer Dickman. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 25.01.2011.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 28 October 2009
                : 02 March 2010
                : 08 July 2010
                : 14 July 2010
                Categories
                Original Paper

                Medicine
                engagement,internet,diabetes self-management,research methods,health disparities
                Medicine
                engagement, internet, diabetes self-management, research methods, health disparities

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