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Web-Based Interventions Targeting Cardiovascular Risk Factors in Middle-Aged and Older People: A Systematic Review and Meta-Analysis.
Beishuizen, CR, Stephan, BC, van Gool, WA, Brayne, C, Peters, RJ, Andrieu, S, Kivipelto, M, Soininen, H, Busschers, WB, Moll van Charante, EP, et al
Journal of medical Internet research. 2016;(3):e55
Abstract
BACKGROUND Web-based interventions can improve single cardiovascular risk factors in adult populations. In view of global aging and the associated increasing burden of cardiovascular disease, older people form an important target population as well. OBJECTIVE In this systematic review and meta-analysis, we evaluated whether Web-based interventions for cardiovascular risk factor management reduce the risk of cardiovascular disease in older people. METHODS Embase, Medline, Cochrane and CINAHL were systematically searched from January 1995 to November 2014. Search terms included cardiovascular risk factors and diseases (specified), Web-based interventions (and synonyms) and randomized controlled trial. Two authors independently performed study selection, data-extraction and risk of bias assessment. In a meta-analysis, outcomes regarding treatment effects on cardiovascular risk factors (blood pressure, glycated hemoglobin A1c (HbA1C), low-density lipoprotein (LDL) cholesterol, smoking status, weight and physical inactivity) and incident cardiovascular disease were pooled with random effects models. RESULTS A total of 57 studies (N=19,862) fulfilled eligibility criteria and 47 studies contributed to the meta-analysis. A significant reduction in systolic blood pressure (mean difference -2.66 mmHg, 95% CI -3.81 to -1.52), diastolic blood pressure (mean difference -1.26 mmHg, 95% CI -1.92 to -0.60), HbA1c level (mean difference -0.13%, 95% CI -0.22 to -0.05), LDL cholesterol level (mean difference -2.18 mg/dL, 95% CI -3.96 to -0.41), weight (mean difference -1.34 kg, 95% CI -1.91 to -0.77), and an increase of physical activity (standardized mean difference 0.25, 95% CI 0.10-0.39) in the Web-based intervention group was found. The observed effects were more pronounced in studies with short (<12 months) follow-up and studies that combined the Internet application with human support (blended care). No difference in incident cardiovascular disease was found between groups (6 studies). CONCLUSIONS Web-based interventions have the potential to improve the cardiovascular risk profile of older people, but the effects are modest and decline with time. Currently, there is insufficient evidence for an effect on incident cardiovascular disease. A focus on long-term effects, clinical endpoints, and strategies to increase sustainability of treatment effects is recommended for future studies.
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Interactive computer-based interventions for weight loss or weight maintenance in overweight or obese people.
Wieland, LS, Falzon, L, Sciamanna, CN, Trudeau, KJ, Brodney, S, Schwartz, JE, Davidson, KW
The Cochrane database of systematic reviews. 2012;(8):CD007675
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Abstract
BACKGROUND The World Health Organization (WHO) estimates that the number of obese or overweight individuals worldwide will increase to 1.5 billion by 2015. Chronic diseases associated with overweight or obesity include diabetes, heart disease, hypertension and stroke. OBJECTIVES To assess the effects of interactive computer-based interventions for weight loss or weight maintenance in overweight or obese people. SEARCH METHODS We searched several electronic databases, including CENTRAL, MEDLINE, EMBASE, CINAHL, LILACS and PsycINFO, through 25 May 2011. We also searched clinical trials registries to identify studies. We scanned reference lists of included studies and relevant systematic reviews. SELECTION CRITERIA Studies were included if they were randomized controlled trials or quasi-randomized controlled trials that evaluated interactive computer-based weight loss or weight maintenance programs in adults with overweight or obesity. We excluded trials if the duration of the intervention was less than four weeks or the loss to follow-up was greater than 20% overall. DATA COLLECTION AND ANALYSIS Two authors independently extracted study data and assessed risk of bias. Where interventions, control conditions, outcomes and time frames were similar between studies, we combined study data using meta-analysis. MAIN RESULTS We included 14 weight loss studies with a total of 2537 participants, and four weight maintenance studies with a total of 1603 participants. Treatment duration was between four weeks and 30 months. At six months, computer-based interventions led to greater weight loss than minimal interventions (mean difference (MD) -1.5 kg; 95% confidence interval (CI) -2.1 to -0.9; two trials) but less weight loss than in-person treatment (MD 2.1 kg; 95% CI 0.8 to 3.4; one trial). At six months, computer-based interventions were superior to a minimal control intervention in limiting weight regain (MD -0.7 kg; 95% CI -1.2 to -0.2; two trials), but not superior to infrequent in-person treatment (MD 0.5 kg; 95% -0.5 to 1.6; two trials). We did not observe consistent differences in dietary or physical activity behaviors between intervention and control groups in either weight loss or weight maintenance trials. Three weight loss studies estimated the costs of computer-based interventions compared to usual care, however two of the studies were 11 and 28 years old, and recent advances in technology render these estimates unlikely to be applicable to current or future interventions, while the third study was conducted in active duty military personnel, and it is unclear whether the costs are relevant to other settings. One weight loss study reported the cost-effectiveness ratio for a weekly in-person weight loss intervention relative to a computer-based intervention as USD 7177 (EUR 5678) per life year gained (80% CI USD 3055 to USD 60,291 (EUR 2417 to EUR 47,702)). It is unclear whether this could be extrapolated to other studies. No data were identified on adverse events, morbidity, complications or health-related quality of life. AUTHORS' CONCLUSIONS Compared to no intervention or minimal interventions (pamphlets, usual care), interactive computer-based interventions are an effective intervention for weight loss and weight maintenance. Compared to in-person interventions, interactive computer-based interventions result in smaller weight losses and lower levels of weight maintenance. The amount of additional weight loss, however, is relatively small and of brief duration, making the clinical significance of these differences unclear.
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Computerized knowledge management in diabetes care.
Balas, EA, Krishna, S, Kretschmer, RA, Cheek, TR, Lobach, DF, Boren, SA
Medical care. 2004;(6):610-21
Abstract
INTRODUCTION Many scientific achievements become part of usual diabetes care only after long delays. The purpose of this article is to identify the impact of automated information interventions on diabetes care and patient outcomes and to enable this knowledge to be incorporated into diabetes care practice. METHODS We conducted systematic electronic and manual searches and identified reports of randomized clinical trials of computer-assisted interventions in diabetes care. Studies were grouped into 3 categories: computerized prompting of diabetes care, utilization of home glucose records in computer-assisted insulin dose adjustment, and computer-assisted diabetes patient education. RESULTS Among 40 eligible studies, glycated hemoglobin and blood glucose levels were significantly improved in 7 and 6 trials, respectively. Significantly improved guideline compliance was reported in 6 of 8 computerized prompting studies. Three of 4 pocket-sized insulin dosage computers reduced hypoglycemic events and insulin doses. Metaanalysis of studies using home glucose records in insulin dose adjustment documented a mean decrease in glycated hemoglobin of.14 mmol/L (95% confidence interval [CI], 0.11-0.16) and a decrease in blood glucose of.33 mmol/L (95% CI, 0.28-0.39). Several computerized educational programs improved diet and metabolic indicators. DISCUSSION Computerized knowledge management is becoming a vital component of quality diabetes care. Prompting follow-up procedures, computerized insulin therapy adjustment using home glucose records, remote feedback, and counseling have documented benefits in improving diabetes-related outcomes.