Effectiveness of mHealth/eHealth interventions on obesity treatment: a protocol for umbrella review of meta-analyses.
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ABSTRACT: Introduction
Mobile health (mHealth)/electronic health (eHealth) have the effect of facilitating weight loss in overweight and obese populations. However, studies have shown varied results and relatively high heterogeneity in the efficacy of mHealth/eHealth interventions. The aim of the paper was to systematically summarise published studies about the weight loss efficacy of mHealth/eHealth.Methods and analysis
A comprehensive review of PubMed, Embase and Cochrane Library databases published from inception to 21 March 2021 will be conducted. The selected articles are meta-analyses that integrated the studies, which evaluated efficacy of mHealth/eHealth. Two people will select eligible articles and extract data independently. Any disputes will be resolved by discussion or the arbitration of a third person. The methodological quality of the included meta-analyses will be assessed with AMSTAR V.2 and the quality of evidence will be obtained with Grade of Recommendations Assessment, Development and Evaluation (GRADE). The study selection process will be presented using a flowchart. We will reanalyse each outcome with random effect methods. If possible, we will use funnel plot and Egger's test to evaluate if publication bias existed.Ethics and dissemination
Ethical approval is not required for the study, as we collected data only from available published materials. This umbrella review will also be submitted to a peer-reviewed journal for publication after completion.Prospero registration number
CRD42021247006.
SUBMITTER: Lei XG
PROVIDER: S-EPMC9171196 | biostudies-literature | 2022 Jun
REPOSITORIES: biostudies-literature
Publications
Effectiveness of mHealth/eHealth interventions on obesity treatment: a protocol for umbrella review of meta-analyses.
Lei Xiang-Guo XG Huang Zhongheng Z Rashi Tamrakar T Yang Xi X
BMJ open 20220606 6
<h4>Introduction</h4>Mobile health (mHealth)/electronic health (eHealth) have the effect of facilitating weight loss in overweight and obese populations. However, studies have shown varied results and relatively high heterogeneity in the efficacy of mHealth/eHealth interventions. The aim of the paper was to systematically summarise published studies about the weight loss efficacy of mHealth/eHealth.<h4>Methods and analysis</h4>A comprehensive review of PubMed, Embase and Cochrane Library databas ...[more]
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Project description:The aim of this meta-meta-analysis was to systematically review randomised controlled trial (RCT) evidence examining the effectiveness of e- and m-Health interventions designed to improve physical activity, sedentary behaviour, healthy eating and sleep. Nine electronic databases were searched for eligible studies published from inception to 1 June 2023. Systematic reviews with meta-analyses of RCTs that evaluate e- and m-Health interventions designed to improve physical activity, sedentary behaviour, sleep and healthy eating in any adult population were included. Forty-seven meta-analyses were included, comprising of 507 RCTs and 206,873 participants. Interventions involved mobile apps, web-based and SMS interventions, with 14 focused on physical activity, 3 for diet, 4 for sleep and 26 evaluating multiple behaviours. Meta-meta-analyses showed that e- and m-Health interventions resulted in improvements in steps/day (mean difference, MD = 1329 [95% CI = 593.9, 2065.7] steps/day), moderate-to-vigorous physical activity (MD = 55.1 [95% CI = 13.8, 96.4] min/week), total physical activity (MD = 44.8 [95% CI = 21.6, 67.9] min/week), sedentary behaviour (MD = -426.3 [95% CI = -850.2, -2.3] min/week), fruit and vegetable consumption (MD = 0.57 [95% CI = 0.11, 1.02] servings/day), energy intake (MD = -102.9 kcals/day), saturated fat consumption (MD = -5.5 grams/day), and bodyweight (MD = -1.89 [95% CI = -2.42, -1.36] kg). Analyses based on standardised mean differences (SMD) showed improvements in sleep quality (SMD = 0.56, 95% CI = 0.40, 0.72) and insomnia severity (SMD = -0.90, 95% CI = -1.14, -0.65). Most subgroup analyses were not significant, suggesting that a variety of e- and m-Health interventions are effective across diverse age and health populations. These interventions offer scalable and accessible approaches to help individuals adopt and sustain healthier behaviours, with implications for broader public health and healthcare challenges.
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Project description:BackgroundNumerous studies have explored interventions to reduce digital addiction outcomes, but inconclusive evidence makes it difficult for decision-makers, managers, and clinicians to become familiar with all available literature and find appropriate interventions.ObjectiveThis study aims to summarize and assess the certainty of evidence of interventions proposed to decrease digital addiction from published meta-analyses.MethodsAn umbrella review of published meta-analyses was performed. We searched PubMed, Cochrane Library, Web of Science, and Embase for meta-analyses published up to February 2024. Eligible studies evaluated interventions using randomized controlled trials, nonrandomized controlled trials, or quasi-experimental studies and were assessed for methodological quality using Assessment of Multiple Systematic Reviews version 2. A random effects model was used to analyze data, considering heterogeneity and publication bias. Grading of Recommendations, Assessment, Development, and Evaluations was applied to assess evidence with certainty.ResultsA total of 5 studies assessing 21 associations were included in the umbrella review, of which 4 (80%) were high-quality meta-analyses. Weak evidence was observed in 19 associations, whereas null associations appeared in the remaining 2 associations. These associations pertained to 8 interventions (group counseling, integrated internet addiction [IA] prevention programs, psychosocial interventions, reality therapy, self-control training programs, cognitive behavioral therapy, interventions to reduce screen time in children, and exercise) and 9 outcomes (self-control, self-esteem, internet gaming disorder symptoms, time spent gaming, IA scores, screen use time, interpersonal sensitivity longlines, anxiety, and depression). Cognitive behavioral therapy reduces anxiety (standardized mean difference [SMD] 0.939, 95% CI 0.311 to 1.586), internet gaming disorder symptoms (SMD 1.394, 95% CI 0.664 to 2.214), time spent gaming (SMD 1.259, 95% CI, 0.311 to 2.206), and IA scores (SMD -2.097, 95% CI -2.814 to -1.381). Group counseling had a large effect on improving self-control (SMD 1.296, 95% CI 0.269 to 2.322) and reducing IA levels (SMD -1.417, 95% CI -1.836 to -0.997). Exercise intervention reduced IA scores (SMD -2.322, 95% CI -3.212 to -1.431), depression scores (SMD -1.421, 95% CI -2.046 to -797), and interpersonal sensitivity scores (SMD -1.433, 95% CI -2.239 to -0.627).ConclusionsThe evidence indicates that current interventions to reduce digital addiction are weak. Data from more and better-designed studies with larger sample sizes are needed to establish robust evidence.Trial registrationPROSPERO CRD42024528173; crd.york.ac.uk/PROSPERO/display_record.php?RecordID=528173.
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Project description:HIV is still the leading cause of death in Sub-Saharan Africa (SSA), despite medical advances. eHealth interventions are effective for HIV prevention and management, but it is unclear whether this can be generalised to resource-poor settings. This systematic review aimed to establish the effectiveness of eHealth interventions in SSA. Six electronic databases were screened to identify randomised controlled trials (RCTs) published between 2000 and 2020. Meta-analyses were performed, following Cochrane methodology, to assess the impact of eHealth interventions on HIV-related behaviours and biological outcomes. 25 RCTs were included in the review. Meta-analyses show that eHealth interventions significantly improved HIV management behaviours (OR 1.21; 95% CI 1.05-1.40; Z = 2.67; p = 0.008), but not HIV prevention behaviours (OR 1.02; 95% CI 0.78-1.34; Z = 0.17; p = 0.86) or biological outcomes (OR 1.17; 95% CI 0.89-1.54; Z = 1.10; p = 0.27) compared with minimal intervention control groups. It is a hugely important finding that eHealth interventions can improve HIV management behaviours as this is a low-cost way of improving HIV outcomes and reducing the spread of HIV in SSA. PROSPERO registration number: CRD42020186025.
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Project description:BackgroundRapid advancements in eHealth and mobile health (mHealth) technologies have driven researchers to design and evaluate numerous technology-based interventions to promote smoking cessation. The evolving nature of cessation interventions emphasizes a strong need for knowledge synthesis.ObjectiveThis systematic review and meta-analysis aimed to summarize recent evidence from randomized controlled trials regarding the effectiveness of eHealth-based smoking cessation interventions in promoting abstinence and assess nonabstinence outcome indicators, such as cigarette consumption and user satisfaction, via narrative synthesis.MethodsWe searched for studies published in English between 2017 and June 30, 2022, in 4 databases: PubMed (including MEDLINE), PsycINFO, Embase, and Cochrane Library. Two independent reviewers performed study screening, data extraction, and quality assessment based on the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework. We pooled comparable studies based on the population, follow-up time, intervention, and control characteristics. Two researchers performed an independent meta-analysis on smoking abstinence using the Sidik-Jonkman random-effects model and log risk ratio (RR) as the effect measurement. For studies not included in the meta-analysis, the outcomes were narratively synthesized.ResultsA total of 464 studies were identified through an initial database search after removing duplicates. Following screening and full-text assessments, we deemed 39 studies (n=37,341 participants) eligible for this review. Of these, 28 studies were shortlisted for meta-analysis. According to the meta-analysis, SMS or app text messaging can significantly increase both short-term (3 months) abstinence (log RR=0.50, 95% CI 0.25-0.75; I2=0.72%) and long-term (6 months) abstinence (log RR=0.77, 95% CI 0.49-1.04; I2=8.65%), relative to minimal cessation support. The frequency of texting did not significantly influence treatment outcomes. mHealth apps may significantly increase abstinence in the short term (log RR=0.76, 95% CI 0.09-1.42; I2=88.02%) but not in the long term (log RR=0.15, 95% CI -0.18 to 0.48; I2=80.06%), in contrast to less intensive cessation support. In addition, personalized or interactive interventions showed a moderate increase in cessation for both the short term (log RR=0.62, 95% CI 0.30-0.94; I2=66.50%) and long term (log RR=0.28, 95% CI 0.04-0.53; I2=73.42%). In contrast, studies without any personalized or interactive features had no significant impact. Finally, the treatment effect was similar between trials that used biochemically verified or self-reported abstinence. Among studies reporting outcomes besides abstinence (n=20), a total of 11 studies reported significantly improved nonabstinence outcomes in cigarette consumption (3/14, 21%) or user satisfaction (8/19, 42%).ConclusionsOur review of 39 randomized controlled trials found that recent eHealth interventions might promote smoking cessation, with mHealth being the dominant approach. Despite their success, the effectiveness of such interventions may diminish with time. The design of more personalized interventions could potentially benefit future studies.Trial registrationPROSPERO CRD42022347104; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=347104.
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Project description:IntroductionThe National Comprehensive Cancer Network guidelines for adult cancer pain indicate that acupuncture and related therapies may be valuable additions to pharmacological interventions for pain management. Of the systematic reviews related to this topic, some concluded that acupuncture was promising for alleviating cancer pain, while others argued that the evidence was insufficient to support its effectiveness.Methods and analysisThis review will consist of three components: (1) synthesis of findings from existing systematic reviews; (2) updated meta-analyses of randomised clinical trials and (3) analyses of results of other types of clinical studies. We will search six English and four Chinese biomedical databases, dissertations and grey literature to identify systematic reviews and primary clinical studies. Two reviewers will screen results of the literature searches independently to identify included reviews and studies. Data from included articles will be abstracted for assessment, analysis and summary. Two assessors will appraise the quality of systematic reviews using Assessment of Multiple Systematic Reviews; assess the randomised controlled trials using the Cochrane Collaboration's risk of bias tool and other types of studies according to the Newcastle-Ottawa Scale. We will use 'summary of evidence' tables to present evidence from existing systematic reviews and meta-analyses. Using the primary clinical studies, we will conduct meta-analysis for each outcome, by grouping studies based on the type of acupuncture, the comparator and the specific type of pain. Sensitivity analyses are planned according to clinical factors, acupuncture method, methodological characteristics and presence of statistical heterogeneity as applicable. For the non-randomised studies, we will tabulate the characteristics, outcome measures and the reported results of each study. Consistencies and inconsistencies in evidence will be investigated and discussed. Finally, we will use the Grading of Recommendations Assessment, Development and Evaluation approach to evaluate the quality of the overall evidence.Ethics and disseminationThere are no ethical considerations associated with this review. The findings will be disseminated in peer-reviewed journals or conference presentations.Prospero registration numberCRD42017064113.
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Project description:BACKGROUND:Poor adherence to continuous positive airway pressure (CPAP) treatment by adults with obstructive sleep apnea (OSA) is a common issue. Strategies delivered by means of information and communication technologies (ie, eHealth) can address treatment adherence through patient education, real-time monitoring of apnea symptoms and CPAP adherence in daily life, self-management, and early identification and subsequent intervention when device or treatment problems arise. However, the effectiveness of available eHealth technologies in improving CPAP adherence has not yet been systematically studied. OBJECTIVE:This meta-analytic review was designed to investigate the effectiveness of a broad range of eHealth interventions in improving CPAP treatment adherence. METHODS:We conducted a systematic literature search of the databases of Cochrane Library, PsycINFO, PubMed, and Embase to identify relevant randomized controlled trials in adult OSA populations. The risk of bias in included studies was examined using seven items of the Cochrane Collaboration risk-of-bias tool. The meta-analysis was conducted with comprehensive meta-analysis software that computed differences in mean postintervention adherence (MD), which was defined as the average number of nightly hours of CPAP use. RESULTS:The meta-analysis ultimately included 18 studies (N=5429 adults with OSA) comprising 22 comparisons between experimental and control conditions. Postintervention data were assessed at 1 to 6 months after baseline, depending on the length of the experimental intervention. eHealth interventions increased the average nightly use of CPAP in hours as compared with care as usual (MD=0.54, 95% CI 0.29-0.79). Subgroup analyses did not reveal significant differences in effects between studies that used eHealth as an add-on or as a replacement to care as usual (P=.95), between studies that assessed stand-alone eHealth and blended strategies combining eHealth with face-to-face care (P=.23), or between studies of fully automated interventions and guided eHealth interventions (P=.83). Evidence for the long-term follow-up effectiveness of eHealth adherence interventions remains undecided owing to a scarcity of available studies and their mixed results. CONCLUSIONS:eHealth interventions for adults with OSA can improve adherence to CPAP in the initial months after the start of treatment, increasing the mean nightly duration of use by about half an hour. Uncertainty still exists regarding the timing, duration, intensity, and specific types of eHealth interventions that could be most effectively implemented by health care providers.
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Project description:IntroductionNon-pharmacological approaches have shown promising results in improving symptoms and quality of life of patients with fibromyalgia. However, these approaches may not be easily accessible or feasible for everyone. eHealth interventions may offer a more convenient and cost-effective approach to reach a wider range of patients with fibromyalgia and improve their outcomes. As eHealth tools become more prevalent in clinical practice, it is crucial to understand their effectiveness, limitations and how they can be integrated into standard care to optimise clinical outcomes. This systematic review aims to evaluate the effectiveness of eHealth therapeutic education interventions in managing fibromyalgia.Methods and analysisRandomised controlled trials including eHealth therapeutic education interventions for individuals ≥18 years old with fibromyalgia, published in English or Spanish, will be retrieved by searching the databases PubMed, CINAHL Plus, EMBASE, Scopus, ISI Web of Science, PsycINFO and the Cochrane Central Register of Controlled Trials. Covidence software will be used for the selection of studies and data extraction. The risk of bias and the certainty of evidence will be assessed using the Cochrane Risk of Bias Assessment tool. We plan to perform a meta-analysis contingent on the number of studies retrieved and the interstudy heterogeneity, which will be explored with I2 statistics.Ethics and disseminationThis protocol and the subsequent systematic review will not collect individual-level data and do not require approval by an ethical committee. We intend to disseminate the study results via peer-reviewed scientific journals and relevant (inter)national conferences.Prospero registration numberCRD42022343373.
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Project description:BackgroundElectronic (eHealth) and mobile (mHealth) health interventions can provide a large coverage, and are promising tools to change health behavior (i.e. physical activity, sedentary behavior and healthy eating). However, the determinants of intervention effectiveness in primary prevention has not been explored yet. Therefore, the objectives of this umbrella review were to evaluate intervention effectiveness, to explore the impact of pre-defined determinants of effectiveness (i.e. theoretical foundations, behavior change techniques, social contexts or just-in-time adaptive interventions), and to provide recommendations for future research and practice in the field of primary prevention delivered via e/mHealth technology.MethodsPubMed, Scopus, Web of Science and the Cochrane Library were searched for systematic reviews and meta-analyses (reviews) published between January 1990 and May 2020. Reviews reporting on e/mHealth behavior change interventions in physical activity, sedentary behavior and/or healthy eating for healthy subjects (i.e. subjects without physical or physiological morbidities which would influence the realization of behaviors targeted by the respective interventions) were included if they also investigated respective theoretical foundations, behavior change techniques, social contexts or just-in-time adaptive interventions. Included studies were ranked concerning their methodological quality and qualitatively synthesized.ResultsThe systematic search revealed 11 systematic reviews and meta-analyses of moderate quality. The majority of original research studies within the reviews found e/mHealth interventions to be effective, but the results showed a high heterogeneity concerning assessment methods and outcomes, making them difficult to compare. Whereas theoretical foundation and behavior change techniques were suggested to be potential positive determinants of effective interventions, the impact of social context remains unclear. None of the reviews included just-in-time adaptive interventions.ConclusionFindings of this umbrella review support the use of e/mHealth to enhance physical activity and healthy eating and reduce sedentary behavior. The general lack of precise reporting and comparison of confounding variables in reviews and original research studies as well as the limited number of reviews for each health behavior constrains the generalization and interpretation of results. Further research is needed on study-level to investigate effects of versatile determinants of e/mHealth efficiency, using a theoretical foundation and additionally explore the impact of social contexts and more sophisticated approaches like just-in-time adaptive interventions.Trial registrationThe protocol for this umbrella review was a priori registered with PROSPERO: CRD42020147902 .
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