Efficacy of eHealth Interventions for Adults with Diabetes: A Systematic Review and Meta-Analysis.
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ABSTRACT:
SUBMITTER: Bassi G
PROVIDER: S-EPMC8431552 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe risk of development of chronic diseases related to poor nutrition increases with age. In the face of an aging population, it is important for health care sectors to find solutions in delivering health services efficiently and effectively to middle-aged and older adults.ObjectiveThe aim of this systematic review and meta-analysis was to consolidate the literature that reported the effectiveness of eHealth apps in delivering nutritional interventions for middle-aged and older adults.MethodsA literature search from five databases (PubMed, CINAHL, Cochrane, Web of Science, and Global Health) from the past 5 years was performed. Studies were selected for inclusion that used eHealth to deliver nutritional interventions to adults aged 40 years and above, and reported health and behavioral outcomes. Two independent reviewers searched for research articles and assessed the eligibility of studies to be included in the review. A third reviewer resolved disagreements on study inclusion. We also assessed the quality of the included studies using the CONSORT 2010 checklist.ResultsA total of 70 studies were included for analysis. The study quality ranged from 44% to 85%. The most commonly used eHealth intervention type was mobile apps (22/70, 31%). The majority of studies (62/70, 89%) provided multicomponent health interventions, which aimed to improve nutrition and other health behaviors (eg, exercise, smoking cessation, medication adherence). Meta-analysis results indicated high and significant heterogeneity; hence, conclusions based on these results should be considered with caution. Nonetheless, the results generally showed that eHealth interventions improved anthropometric and clinical outcomes, but not behavioral outcomes such as fruit and vegetable consumption.ConclusionsThe use of eHealth apps to deliver health interventions has been increasing in recent years, and these apps have the potential to deliver health services to a larger group of people. Our findings showed that the effectiveness of eHealth apps to deliver health interventions for middle-aged to older adults was supported by the improvement of anthropometric and clinical outcomes. Future work could aim to develop research frameworks in administering eHealth interventions to address heterogeneity in this field of research.
| S-EPMC8167617 | biostudies-literature
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.
| S-EPMC10422176 | biostudies-literature
Project description:The objective was to describe Diabetes Prevention Program (DPP)-based lifestyle interventions delivered via electronic, mobile, and certain types of telehealth (eHealth) and estimate the magnitude of the effect on weight loss. A systematic review was conducted. PubMed and EMBASE were searched for studies published between January 2003 and February 2016 that met inclusion and exclusion criteria. An overall estimate of the effect on mean percentage weight loss across all the interventions was initially conducted. A stratified meta-analysis was also conducted to determine estimates of the effect across the interventions classified according to whether behavioral support by counselors post-baseline was not provided, provided remotely with communication technology, or face-to-face. Twenty-two studies met the inclusion/exclusion criteria, in which 26 interventions were evaluated. Samples were primarily white and college educated. Interventions included Web-based applications, mobile phone applications, text messages, DVDs, interactive voice response telephone calls, telehealth video conferencing, and video on-demand programing. Nine interventions were stand-alone, delivered post-baseline exclusively via eHealth. Seventeen interventions included additional behavioral support provided by counselors post-baseline remotely with communication technology or face-to-face. The estimated overall effect on mean percentage weight loss from baseline to up to 15months of follow-up across all the interventions was -3.98%. The subtotal estimate across the stand-alone eHealth interventions (-3.34%) was less than the estimate across interventions with behavioral support given by a counselor remotely (-4.31%), and the estimate across interventions with behavioral support given by a counselor in-person (-4.65%). There is promising evidence of the efficacy of DPP-based eHealth interventions on weight loss. Further studies are needed particularly in racially and ethnically diverse populations with limited levels of educational attainment. Future research should also focus on ways to optimize behavioral support.
| S-EPMC5699208 | biostudies-literature
Project description:BackgroundThere has been a recent rise in the use of eHealth treatments for a variety of psychological disorders, including eating disorders.ObjectiveThis meta-analysis of randomized controlled trials is the first to evaluate the efficacy of eHealth interventions specifically for the treatment of binge eating disorder (characterized by compulsive overconsumption of food, in a relatively short period, and without compensatory behaviors such as purging or fasting).MethodsA search on the electronic databases PubMed, Web of Science, Embase, MEDLINE, and CINAHL was conducted for randomized controlled trials that compared the efficacy of eHealth treatment interventions with waitlist controls.ResultsFrom the databases searched, 3 studies (298 participants in total) met the inclusion criteria. All interventions were forms of internet-based guided cognitive behavioral therapy. The results of the analysis demonstrated that when compared with waitlist controls, individuals enrolled in eHealth interventions experienced a reduction in objective binge episodes (standardized mean difference [SMD] -0.77, 95% CI -1.38 to -0.16) and eating disorder psychopathology (SMD -0.71, 95% CI -1.20 to -0.22), which included shape (SMD -0.61, 95% CI -1.01 to -0.22) and weight concerns (SMD -0.91, 95% CI -1.33 to -0.48). There was no significant difference in BMI between the eHealth interventions and controls (SMD -0.01, 95% CI -0.40 to 0.39).ConclusionsThese findings provide promising results for the use of internet-based cognitive behavioral therapy for binge eating disorder treatment and support the need for future research to explore the efficacy of these eHealth interventions.
| S-EPMC8335602 | biostudies-literature
Project description:Patient activation interventions (PAIs) engage patients in care by promoting increased knowledge, confidence, and/or skills for disease self-management. However, little is known about the impact of these interventions on a wide range of outcomes for adults with type 2 diabetes (DM2), or which of these interventions, if any, have the greatest impact on glycemic control.Electronic databases were searched from inception through November 2011. Of 16,290 citations, two independent reviewers identified 138 randomized trials comparing PAIs to usual care/control groups in adults with DM2 that reported intermediate or long-term outcomes or harms. For meta-analyses of continuous outcomes, we used a random-effects model to derive pooled weighted mean differences (WMD). For all-cause mortality, we calculated the pooled odds ratio (OR) using Peto's method. We assessed statistical heterogeneity using the I (2) statistic and conducted meta-regression using a random-effects model when I (2)?>?50 %. A priori meta-regression primary variables included: intervention strategies, intervention leader, baseline outcome value, quality, and study duration.PAIs modestly reduced intermediate outcomes [A1c: WMD 0.37 %, CI 0.28-0.45 %, I (2) 83 %; SBP: WMD 2.2 mmHg, CI 1.0-3.5 mmHg, I (2) 72 %; body weight: WMD 2.3 lbs, CI 1.3-3.2 lbs, I (2) 64 %; and LDL-c: WMD 4.2 mg/dL, CI 1.5-6.9 mg/dL, I (2) 64 %]. The evidence was moderate for A1c, low/very low for other intermediate outcomes, low for long-term mortality and very low for complications. Interventions had no effect on hypoglycemia (evidence: low) or short-term mortality (evidence: moderate). Higher baseline A1c, pharmacist-led interventions, and longer follow-up were associated with larger A1c improvements. No intervention strategy outperformed any other in adjusted meta-regression.PAIs modestly improve A1c in adults with DM2 without increasing short-term mortality. These results support integration of these interventions into primary care for adults with uncontrolled glycemia, and provide evidence to insurers who do not yet cover these programs.
| S-EPMC4099447 | biostudies-other
Project description:BackgroundHeart failure (HF) is a common clinical syndrome associated with substantial morbidity, a heavy economic burden, and high risk of readmission. eHealth self-management interventions may be an effective way to improve HF clinical outcomes.ObjectiveThe aim of this study was to systematically review the evidence for the effectiveness of eHealth self-management in patients with HF.MethodsThis study included only randomized controlled trials (RCTs) that compared the effects of eHealth interventions with usual care in adult patients with HF using searches of the EMBASE, PubMed, CENTRAL (Cochrane Central Register of Controlled Trials), and CINAHL databases from January 1, 2011, to July 12, 2022. The Cochrane Risk of Bias tool (RoB 2) was used to assess the risk of bias for each study. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) criteria were used to rate the certainty of the evidence for each outcome of interest. Meta-analyses were performed using Review Manager (RevMan v.5.4) and R (v.4.1.0 x64) software.ResultsIn total, 24 RCTs with 9634 participants met the inclusion criteria. Compared with the usual-care group, eHealth self-management interventions could significantly reduce all-cause mortality (odds ratio [OR] 0.83, 95% CI 0.71-0.98, P=.03; GRADE: low quality) and cardiovascular mortality (OR 0.74, 95% CI 0.59-0.92, P=.008; GRADE: moderate quality), as well as all-cause readmissions (OR 0.82, 95% CI 0.73-0.93, P=.002; GRADE: low quality) and HF-related readmissions (OR 0.77, 95% CI 0.66-0.90, P<.001; GRADE: moderate quality). The meta-analyses also showed that eHealth interventions could increase patients' knowledge of HF and improve their quality of life, but there were no statistically significant effects. However, eHealth interventions could significantly increase medication adherence (OR 1.82, 95% CI 1.42-2.34, P<.001; GRADE: low quality) and improve self-care behaviors (standardized mean difference -1.34, 95% CI -2.46 to -0.22, P=.02; GRADE: very low quality). A subgroup analysis of primary outcomes regarding the enrolled population setting found that eHealth interventions were more effective in patients with HF after discharge compared with those in the ambulatory clinic setting.ConclusionseHealth self-management interventions could benefit the health of patients with HF in various ways. However, the clinical effects of eHealth interventions in patients with HF are affected by multiple aspects, and more high-quality studies are needed to demonstrate effectiveness.
| S-EPMC9555330 | biostudies-literature
Project description:BACKGROUND:Dyadic psychosocial interventions have been found beneficial both for people coping with mental or physical health conditions as well as their family members and friends who provide them with support. Delivering these interventions via electronic health (eHealth) may help increase their scalability. OBJECTIVE:This scoping review aimed to provide the first comprehensive overview of dyadic eHealth interventions for individuals of all ages affected by mental or physical illness and their family members or friends who support them. The goal was to understand how dyadic eHealth interventions have been used and to highlight areas of research needed to advance dyadic eHealth intervention development and dissemination. METHODS:A comprehensive electronic literature search of PubMed, EMBASE, Cochrane, Cumulative Index to Nursing and Allied Health Literature, and PsycINFO was conducted for articles published in the English language through March 2019. Eligible records described a psychosocial eHealth intervention that intervened with both care recipients and their support person. RESULTS:A total of 7113 records were reviewed of which 101 met eligibility criteria. There were 52 unique dyadic eHealth interventions identified, which were tested across 73 different trials. Of the unique interventions, 33 were conducted among dyads of children and their supporting parent, 1 was conducted with an adolescent-young adult care recipient population, and the remaining 18 were conducted among adult dyads. Interventions targeting pediatric dyads most commonly addressed a mental health condition (n=10); interventions targeting adult dyads most commonly addressed cancer (n=9). More than three-fourths of interventions (n=40) required some human support from research staff or clinicians. Most studies (n=64) specified one or more primary outcomes for care recipients, whereas less than one-fourth (n=22) specified primary outcomes for support persons. Where specified, primary outcomes were most commonly self-reported psychosocial or health factors for both care recipients (n=43) and support persons (n=18). Results of the dyadic eHealth intervention tended to be positive for care recipients, but evidence of effects for support persons was limited because of few studies specifying primary outcomes for supporters. Trials of dyadic eHealth interventions were most commonly randomized controlled trials (RCTs; n=44), and RCTs most commonly compared the dyadic eHealth intervention to usual care alone (n=22). CONCLUSIONS:This first comprehensive review of dyadic eHealth interventions demonstrates that there is substantial, diverse, and growing literature supporting this interventional approach. However, several significant gaps were identified. Few studies were designed to evaluate the unique effects of dyadic interventions relative to individual interventions. There was also limited assessment and reporting of outcomes for support persons, and there were no interventions meeting our eligibility criteria specifically targeting the needs of older adult dyads. Findings highlight areas of research opportunities for developing dyadic eHealth interventions for novel populations and for increasing access to dyadic care.
| S-EPMC7081137 | biostudies-literature
Project description:Many organisations promote eHealth applications as a feasible, low-cost method of addressing mental ill-health and stress amongst their employees. However, there are good reasons why the efficacy identified in clinical or other samples may not generalize to employees, and many Apps are being developed specifically for this group. The aim of this paper is to conduct the first comprehensive systematic review and meta-analysis evaluating the evidence for the effectiveness and examine the relative efficacy of different types of eHealth interventions for employees.Systematic searches were conducted for relevant articles published from 1975 until November 17, 2016, of trials of eHealth mental health interventions (App or web-based) focused on the mental health of employees. The quality and bias of all identified studies was assessed. We extracted means and standard deviations from published reports, comparing the difference in effect sizes (Hedge's g) in standardized mental health outcomes. We meta-analysed these using a random effects model, stratified by length of follow up, intervention type, and whether the intervention was universal (unselected) or targeted to selected groups e.g. "stressed".23 controlled trials of eHealth interventions were identified which overall suggested a small positive effect at both post intervention (g = 0.24, 95% CI 0.13 to 0.35) and follow up (g = 0.23, 95% CI 0.03 to 0.42). There were differential short term effects seen between the intervention types whereby Mindfulness based interventions (g = 0.60, 95% CI 0.34 to 0.85, n = 6) showed larger effects than the Cognitive Behaviour Therapy (CBT) based (g = 0.15, 95% CI 0.02 to 0.29, n = 11) and Stress Management based (g = 0.17, 95%CI -0.01 to 0.34, n = 6) interventions. The Stress Management interventions however differed by whether delivered to universal or targeted groups with a moderately large effect size at both post-intervention (g = 0.64, 95% CI 0.54 to 0.85) and follow-up (g = 0.69, 95% CI 0.06 to 1.33) in targeted groups, but no effect in unselected groups.There is reasonable evidence that eHealth interventions delivered to employees may reduce mental health and stress symptoms post intervention and still have a benefit, although reduced at follow-up. Despite the enthusiasm in the corporate world for such approaches, employers and other organisations should be aware not all such interventions are equal, many lack evidence, and achieving the best outcomes depends upon providing the right type of intervention to the correct population.
| S-EPMC5739441 | biostudies-literature
Project description:Parent stress and mental health problems negatively impact early child development. This study aimed to systematically review and meta-analyze the effect of eHealth interventions on parent stress and mental health outcomes, and identify family- and program-level factors that may moderate treatment effects. A search of PsycINFO, Medline, CINAHL, Cochrane and Embase databases was conducted from their inception dates to July 2020. English-language controlled and open trials were included if they reported: (a) administration of an eHealth intervention, and (b) stress or mental health outcomes such as self-report or clinical diagnosis of anxiety and depression, among (c) parents of children who were aged 1-5 years old. Non-human studies, case reports, reviews, editorials, letters, dissertations, and books were excluded. Risk of bias was assessed using the National Institutes of Health (NIH) Study Quality Assessment Tools. Random-effects meta-analyses of standardized mean differences (SMD) were conducted and meta-regressions tested potential moderators. 38 studies were included (N = 4360 parents), from 13 countries (47.4% USA). Meta-analyses indicated eHealth interventions were associated with better self-reported mental health among parents (overall SMD = .368, 95% CI 0.228, 0.509), regardless of study design (k = 30 controlled, k = 8 pre-post) and across most outcomes (k = 17 anxiety, k = 19 depression, k = 12 parenting stress), with small to medium effect sizes. No significant family- or program-level moderators emerged. Despite different types and targets, eHealth interventions offer a promising and accessible option to promote mental health among parents of young children. Further research is needed on moderators and the long-term outcomes of eHealth interventions. Prospero Registration: CRD42020190719.
| S-EPMC8858396 | biostudies-literature
Project description:BackgroundMental health conditions are considered the leading cause of disability, sickness absence, and long-term work incapacity. eHealth interventions provide employees with access to psychological assistance. There has been widespread implementation and provision of eHealth interventions in the workplace as an inexpensive and anonymous way of addressing common mental disorders.ObjectiveThis updated review aimed to synthesize the literature on the efficacy of eHealth interventions for anxiety, depression, and stress outcomes in employee samples in organizational settings and evaluate whether their effectiveness has improved over time.MethodsSystematic searches of relevant articles published from 2004 to July 2020 of eHealth intervention trials (app- or web-based) focusing on the mental health of employees were conducted. The quality and bias of all studies were assessed. We extracted means and SDs from publications by comparing the differences in effect sizes (Hedge g) in standardized mental health outcomes. We meta-analyzed these data using a random-effects model.ResultsWe identified a tripling of the body of evidence, with 75 trials available for meta-analysis from a combined sample of 14,747 articles. eHealth interventions showed small positive effects for anxiety (Hedges g=0.26, 95% CI 0.13-0.39; P<.001), depression (Hedges g=0.26, 95% CI 0.19-0.34; P<.001), and stress (Hedges g=0.25, 95% CI 0.17-0.34; P<.001) in employees' after intervention, with similar effects seen at the medium-term follow-up. However, there was evidence of no increase in the effectiveness of these interventions over the past decade.ConclusionsThis review and meta-analysis confirmed that eHealth interventions have a small positive impact on reducing mental health symptoms in employees. Disappointingly, we found no evidence that, despite the advances in technology and the enormous resources in time, research, and finance devoted to this area for over a decade, better interventions are being produced. Hopefully, these small effect sizes do not represent optimum outcomes in organizational settings.Trial registrationPROSPERO CRD42020185859; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=185859.
| S-EPMC9555335 | biostudies-literature