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Mobile health technologies supporting colonoscopy preparation: A systematic review and meta-analysis of randomized controlled trials.
El Bizri, M, El Sheikh, M, Lee, GE, Sewitch, MJ
PloS one. 2021;(3):e0248679
Abstract
BACKGROUND Mobile health (mHealth) technologies are innovative solutions for delivering instructions to patients preparing for colonoscopy. OBJECTIVE To systematically review the literature evaluating the effectiveness of mHealth technologies supporting colonoscopy preparation on patient and clinical outcomes. METHODS MEDLINE, EMBASE, CINAHL and CENTRAL were searched for randomized controlled trials (RCTs) that evaluated the effectiveness of mHealth technologies for colonoscopy preparation on patient and clinical outcomes. Two reviewers independently assessed study eligibility, extracted data, and appraised methodological quality using the Cochrane Risk-of-Bias tool. Data were pooled using random effects models and when heterogeneity, assessed using I2, was statistically significant, a qualitative synthesis of the data was performed. Publication bias was assessed using a funnel plot. RESULTS Ten RCTs (3,383 participants) met inclusion criteria. MHealth interventions included smartphone apps, SMS text messages, videos, camera apps, and a social media app. Outcomes were bowel cleanliness quality, user satisfaction, colonoscopy quality indicators (cecal intubation time, withdrawal time, adenoma detection rate), adherence to diet, and cancellation/no-show rates. MHealth interventions were associated with better bowel cleanliness scores on the Boston Bowel Preparation Scale [standardized mean difference (SMD) 0.57, 95%CI 0.37-0.77, I2 = 60%, p = 0.08] and the Ottawa Bowel Preparation Scale [SMD -0.39, 95%CI -0.59-0.19, I2 = 45%, p = 0.16], but they were not associated with rates of willingness to repeat the colonoscopy using the same regimen [odds ratio (OR) 1.88, 95%CI 0.85-4.15, I2 = 48%, p = 0.12] or cancellations/no-shows [OR 0.96, 95%CI 0.68-1.35, I2 = 0%]. Most studies showed that adequate bowel preparation, user satisfaction and adherence to diet were better in the intervention groups compared to the control groups, while inconsistent findings were observed for the colonoscopy quality indicators. All trials were at high risk of bias for lack of participant blinding. Visual inspection of a funnel plot revealed publication bias. CONCLUSIONS MHealth technologies show promise as a way to improve bowel cleanliness, but trials to date were of low methodological quality. High-quality research is required to understand the effectiveness of mHealth technologies on colonoscopy outcomes.
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E-health education interventions on HbA1c in patients with type 1 diabetes on intensive insulin therapy: A systematic review and meta-analysis of randomized controlled trials.
Feigerlová, E, Oussalah, A, Zuily, S, Sordet, S, Braun, M, Guéant, JL, Guerci, B
Diabetes/metabolism research and reviews. 2020;(6):e3313
Abstract
AIMS: Patient-centered education improves glycemic control in subjects with type 1 diabetes (T1D). E-health technologies are widely used to support medical decision-making, patient advising or teleconsultations; however, the active participation of a patient is missing. Challenges remain whether e-health education can be effectively incorporated into clinical pathways. The purpose of the study was to examine the effects of e-health education, compared to standard care, on HbA1c. MATERIAL AND METHODS We conducted a literature search (EMBASE, MEDLINE, The Cochrane Library and Web of Science) up to February 2018 for randomized controlled trials (RCTs) of Internet-/ mobile application-based educational interventions, with the active involvement of patients, provided in addition to, or substituting usual care in patients with T1D on intensive insulin therapy. The primary outcome was the standardized difference in means (SDM) of HbA1c change from baseline between intervention and comparator groups. RESULTS Eight RCTs involving 757 subjects were included on 6335 screened citations. After excluding two trials with a high risk of bias from the meta-analysis, the HbA1c change from baseline did not significantly differ between intervention and comparator groups (SDM = -0.154, 95% CI: -0.335 to 0.025; P = 0.01, random-effect model). The number of studies is limited with a relatively short duration. Reporting of educational outcomes was not rigorous. CONCLUSIONS The effect of e-health educational interventions on HbA1c in patients with T1D is comparable to the standard care. This review highlights the need for further well-designed RCTs that will investigate the opportunities of incorporating e-health education into clinical pathways.
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Effect of Behavioral Weight Management Interventions Using Lifestyle mHealth Self-Monitoring on Weight Loss: A Systematic Review and Meta-Analysis.
Cavero-Redondo, I, Martinez-Vizcaino, V, Fernandez-Rodriguez, R, Saz-Lara, A, Pascual-Morena, C, Álvarez-Bueno, C
Nutrients. 2020;(7)
Abstract
Alongside an increase in obesity, society is experiencing the development of substantial technological advances. Interventions that are easily scalable, such as lifestyle (including diet and physical activity) mobile health (mHealth) self-monitoring, may be highly valuable in the prevention and treatment of excess weight. Thus, the aims of this systematic review and meta-analysis were to estimate the following: (i) the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss and (ii) the adherence to behavioral weight management interventions using lifestyle mHealth self-monitoring. MEDLINE via PubMed, EMBASE, the Cochrane Central Register of Controlled Trials and the Web of Science databases were systematically searched. The DerSimonian and Laird method was used to estimate the effect of and adherence to behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss. Twenty studies were included in the systematic review and meta-analysis, yielding a moderate decrease in weight and higher adherence to intervention of behavioral weight management interventions using lifestyle mHealth self-monitoring, which was greater than other interventions. Subgroup analyses showed that smartphones were the most effective mHealth approach to achieve weight management and the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring was more pronounced when compared to usual care and in the short-term (less than six months). Furthermore, behavioral weight management interventions using lifestyle mHealth self-monitoring showed a higher adherence than: (i) recording on paper at any time and (ii) any other intervention at six and twelve months.
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Cost-effectiveness and diagnostic accuracy of telemedicine in macular disease and diabetic retinopathy: A systematic review and meta-analysis.
Ullah, W, Pathan, SK, Panchal, A, Anandan, S, Saleem, K, Sattar, Y, Ahmad, E, Mukhtar, M, Nawaz, H
Medicine. 2020;(25):e20306
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Abstract
OBJECTIVE To determine cost-effectiveness and the diagnostic accuracy of teleophthalmology (TO) in the detection of macular edema (ME) and various grades of diabetic retinopathy (DR). METHODS MEDLINE, EMBASE, and Cochrane databases were searched for TO, ME, and DR on May 25, 2016. The search was updated on April 2, 2019. Pooled sensitivity and specificity for ME and various grades of DR were determined using Meta-Disc software. A systematic review of the articles discussing the cost-effectiveness of TO screening was also performed. RESULTS Thirty-three articles on the diagnostic accuracy and 28 articles on the cost-effectiveness were selected. CONCLUSIONS Telescreening is moderately sensitive but very specific for the diagnosis of diabetic retinopathy. Non-mydriatic Teleretinal screening services are cost-effective, decrease clinics workload, and increase patient compliance if provided free of cost in remote low socioeconomic regions.
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Mobile health in the management of type 1 diabetes: a systematic review and meta-analysis.
Wang, X, Shu, W, Du, J, Du, M, Wang, P, Xue, M, Zheng, H, Jiang, Y, Yin, S, Liang, D, et al
BMC endocrine disorders. 2019;(1):21
Abstract
BACKGROUND As an insulin-dependent disease, type 1 diabetes requires paying close attention to the glycemic control. Studies have shown that mobile health (mHealth) can improve the management of chronic diseases. However, the effectiveness of mHealth in controlling the glycemic control remains uncertain. The objective of this study was to carry out a systematic review and meta-analysis using the available literature reporting findings on mHealth interventions, which may improve the management of type 1 diabetes. METHODS We performed a systematic literature review of all studies in the PubMed, Web of Science, and EMbase databases that used mHealth (including mobile phones) in diabetes care and reported glycated hemoglobin (HbA1c) values as a measure of glycemic control. The fixed effects model was used for this meta-analysis. RESULTS This study analyzed eight studies, which involved a total of 602 participants. In the meta-analysis, the fixed effects model showed a statistically significant decrease in the mean of HbA1c in the intervention group: - 0.25 (95% confidence interval: - 0.41, - 0.09; P = 0.003, I2 = 12%). Subgroup analyses indicated that the patient's age, the type of intervention, and the duration of the intervention influenced blood glucose control. Funnel plots showed no publication bias. CONCLUSIONS Mobile health interventions may be effective among patients with type 1 diabetes. A significant reduction in HbA1c levels was associated with adult age, the use of a mobile application, and the long-term duration of the intervention.
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The effects of mobile health interventions on lipid profiles among patients with metabolic syndrome and related disorders: A systematic review and meta-analysis of randomized controlled trials.
Akbari, M, Lankarani, KB, Naghibzadeh-Tahami, A, Tabrizi, R, Honarvar, B, Kolahdooz, F, Borhaninejad, V, Asemi, Z
Diabetes & metabolic syndrome. 2019;(3):1949-1955
Abstract
OBJECTIVE The current systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to summarize the effect of mobile health (m-health) interventions on lipid profiles among patients with metabolic syndrome and related disorders. METHODS Cochrane Library, EMBASE, PubMed, and Web of Science databases were searched to indentify the relevant randomized clinical trials published up April 30th, 2018. Two reviewers examined study eligibility, extracted data, and assessed risk of bias of included clinical trials, individually. Heterogeneity was measured using I-square (I2) statistic and Cochran's Q test. Data were pooled the standardized mean difference (SMD) effect size by the random-effect model. RESULTS 18 trials of 1681 citations were identified to be appropriate for the current meta-analysis. Findings random-effects model indicated that m-health interventions significantly decreased total- (SMD -0.54; 95% CI, -1.05, -0.03) and LDL-cholesterol levels (SMD -0.66; 95% CI, -1.18, -0.15). M-health interventions had no significant effect on triglycerides (SMD -0.14; 95% CI, -0.56, 0.28) and HDL-cholesterol levels (SMD -0.35; 95% CI, -0.81, 0.11). CONCLUSION Overall, the current meta-analysis demonstrated that m-health interventions resulted in an improvement in total- and LDL-cholesterol, but did not affect triglycerides and HDL-cholesterol levels.
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Tele-Ophthalmology for Age-Related Macular Degeneration and Diabetic Retinopathy Screening: A Systematic Review and Meta-Analysis.
Kawaguchi, A, Sharafeldin, N, Sundaram, A, Campbell, S, Tennant, M, Rudnisky, C, Weis, E, Damji, KF
Telemedicine journal and e-health : the official journal of the American Telemedicine Association. 2018;(4):301-308
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Abstract
BACKGROUND To synthesize high-quality evidence to compare traditional in-person screening and tele-ophthalmology screening. METHODS Only randomized controlled trials (RCTs) were included in this systematic review and meta-analysis. The intervention of interest was any type of tele-ophthalmology, including screening of diseases using remote devices. Studies involved patients receiving care from any trained provider via tele-ophthalmology, compared with those receiving equivalent face-to-face care. A search was executed on the following databases: Medline, EMBASE, EBM Reviews, Global Health, EBSCO-CINAHL, SCOPUS, ProQuest Dissertations and Theses Global, OCLC Papers First, and Web of Science Core Collection. Six outcomes of care for age-related macular degeneration (AMD), diabetic retinopathy (DR), or glaucoma were measured and analyzed. RESULTS Two hundred thirty-seven records were assessed at the full-text level; six RCTs fulfilled inclusion criteria and were included in this review. Four studies involved participants with diabetes mellitus, and two studies examined choroidal neovascularization in AMD. Only data of detection of disease and participation in the screening program were used for the meta-analysis. Tele-ophthalmology had a 14% higher odds to detect disease than traditional examination; however, the result was not statistically significant (n = 2,012, odds ratio: 1.14, 95% confidence interval (CI): 0.52-2.53, p = 0.74). Meta-analysis results show that odds of having DR screening in the tele-ophthalmology group was 13.15 (95% CI: 8.01-21.61; p < 0.001) compared to the traditional screening program. CONCLUSIONS The current evidence suggests that tele-ophthalmology for DR and age-related macular degeneration is as effective as in-person examination and potentially increases patient participation in screening.