Effectiveness Of eHealth Interventions Research Articles

Effectiveness of eHealth Interventions in Improving Medication Adherence Among Patients With Cardiovascular Disease: Systematic Review and Meta-Analysis.

Nonadherence to medication among patients with cardiovascular diseases undermines the desired therapeutic outcomes. eHealth interventions emerge as promising strategies to effectively tackle this issue. The aim of this study was to conduct a network meta-analysis (NMA) to compare and rank the efficacy of various eHealth interventions in improving medication adherence among patients with cardiovascular diseases (CVDs). A systematic search strategy was conducted in PubMed, Embase, Web of Science, Cochrane, China National Knowledge Infrastructure Library (CNKI), China Science and Technology Journal Database (Weipu), and WanFang databases to search for randomized controlled trials (RCTs) published from their inception on January 15, 2024. We carried out a frequentist NMA to compare the efficacy of various eHealth interventions. The quality of the literature was assessed using the risk of bias tool from the Cochrane Handbook (version 2.0), and extracted data were analyzed using Stata16.0 (StataCorp LLC) and RevMan5.4 software (Cochrane Collaboration). The certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach. A total of 21 RCTs involving 3904 patients were enrolled. The NMA revealed that combined interventions (standardized mean difference [SMD] 0.89, 95% CI 0.22-1.57), telephone support (SMD 0.68, 95% CI 0.02-1.33), telemonitoring interventions (SMD 0.70, 95% CI 0.02-1.39), and mobile phone app interventions (SMD 0.65, 95% CI 0.01-1.30) were statistically superior to usual care. However, SMS compared to usual care showed no statistical difference. Notably, the combined intervention, with a surface under the cumulative ranking curve of 79.3%, appeared to be the most effective option for patients with CVDs. Regarding systolic blood pressure and diastolic blood pressure outcomes, the combined intervention also had the highest probability of being the best intervention. The research indicates that the combined intervention (SMS text messaging and telephone support) has the greatest likelihood of being the most effective eHealth intervention to improve medication adherence in patients with CVDs, followed by telemonitoring, telephone support, and app interventions. The results of these network meta-analyses can provide crucial evidence-based support for health care providers to enhance patients' medication adherence. Given the differences in the design and implementation of eHealth interventions, further large-scale, well-designed multicenter trials are needed. INPLASY 2023120063; https://inplasy.com/inplasy-2023-12-0063/.

Effects of eHealth Interventions on 24-Hour Movement Behaviors Among Preschoolers: Systematic Review and Meta-Analysis.

The high prevalence of unhealthy movement behaviors among young children remains a global public health issue. eHealth is considered a cost-effective approach that holds great promise for enhancing health and related behaviors. However, previous research on eHealth interventions aimed at promoting behavior change has primarily focused on adolescents and adults, leaving a limited body of evidence specifically pertaining to preschoolers. This review aims to examine the effectiveness of eHealth interventions in promoting 24-hour movement behaviors, specifically focusing on improving physical activity (PA) and sleep duration and reducing sedentary behavior among preschoolers. In addition, we assessed the moderating effects of various study characteristics on intervention effectiveness. We searched 6 electronic databases (PubMed, Ovid, SPORTDiscus, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials) for experimental studies with a randomization procedure that examined the effectiveness of eHealth interventions on 24-hour movement behaviors among preschoolers aged 2 to 6 years in February 2023. The study outcomes included PA, sleep duration, and sedentary time. A meta-analysis was conducted to assess the pooled effect using a random-effects model, and subgroup analyses were conducted to explore the potential effects of moderating factors such as intervention duration, intervention type, and risk of bias (ROB). The included studies underwent a rigorous ROB assessment using the Cochrane ROB tool. Moreover, the certainty of evidence was evaluated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) assessment. Of the 7191 identified records, 19 (0.26%) were included in the systematic review. The meta-analysis comprised a sample of 2971 preschoolers, which was derived from 13 included studies. Compared with the control group, eHealth interventions significantly increased moderate to vigorous PA (Hedges g=0.16, 95% CI 0.03-0.30; P=.02) and total PA (Hedges g=0.37, 95% CI 0.02-0.72; P=.04). In addition, eHealth interventions significantly reduced sedentary time (Hedges g=-0.15, 95% CI -0.27 to -0.02; P=.02) and increased sleep duration (Hedges g=0.47, 95% CI 0.18-0.75; P=.002) immediately after the intervention. However, no significant moderating effects were observed for any of the variables assessed (P>.05). The quality of evidence was rated as "moderate" for moderate to vigorous intensity PA and sedentary time outcomes and "low" for sleep outcomes. eHealth interventions may be a promising strategy to increase PA, improve sleep, and reduce sedentary time among preschoolers. To effectively promote healthy behaviors in early childhood, it is imperative for future studies to prioritize the development of rigorous comparative trials with larger sample sizes. In addition, researchers should thoroughly examine the effects of potential moderators. There is also a pressing need to comprehensively explore the long-term effects resulting from these interventions. PROSPERO CRD42022365003; http://tinyurl.com/3nnfdwh3.

Efficacy of eHealth Technologies on Medication Adherence in Patients With Acute Coronary Syndrome: Systematic Review and Meta-Analysis.

Suboptimal adherence to cardiac pharmacotherapy, recommended by the guidelines after acute coronary syndrome (ACS) has been recognized and is associated with adverse outcomes. Several randomized controlled trials (RCTs) have shown that eHealth technologies are useful in reducing cardiovascular risk factors. However, little is known about the effect of eHealth interventions on medication adherence in patients following ACS. The aim of this study is to examine the efficacy of the eHealth interventions on medication adherence to selected 5 cardioprotective medication classes in patients with ACS. A systematic literature search of PubMed, Embase, Scopus, and Web of Science was conducted between May and October 2022, with an update in October 2023 to identify RCTs that evaluated the effectiveness of eHealth technologies, including texting, smartphone apps, or web-based apps, to improve medication adherence in patients after ACS. The risk of bias was evaluated using the modified Cochrane risk-of-bias tool for RCTs. A pooled meta-analysis was performed using a fixed-effect Mantel-Haenszel model and assessed the medication adherence to the medications of statins, aspirin, P2Y12 inhibitors, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and β-blockers. We identified 5 RCTs, applicable to 4100 participants (2093 intervention vs 2007 control), for inclusion in the meta-analysis. In patients who recently had an ACS, compared to the control group, the use of eHealth intervention was not associated with improved adherence to statins at different time points (risk difference [RD] -0.01, 95% CI -0.03 to 0.03 at 6 months and RD -0.02, 95% CI -0.05 to 0.02 at 12 months), P2Y12 inhibitors (RD -0.01, 95% CI -0.04 to 0.02 and RD -0.01, 95% CI -0.03 to 0.02), aspirin (RD 0.00, 95% CI -0.06 to 0.07 and RD -0.00, 95% CI -0.07 to 0.06), angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (RD -0.01, 95% CI -0.04 to 0.02 and RD 0.01, 95% CI -0.04 to 0.05), and β-blockers (RD 0.00, 95% CI -0.03 to 0.03 and RD -0.01, 95% CI -0.05 to 0.03). The intervention was also not associated with improved adherence irrespective of the adherence assessment method used (self-report or objective). This review identified limited evidence on the effectiveness of eHealth interventions on adherence to guideline-recommended medications after ACS. While the pooled analyses suggested a lack of effectiveness of such interventions on adherence improvement, further studies are warranted to better understand the role of different eHealth approaches in the post-ACS context.

Perception of eHealth Programs for Cardiovascular Health: Qualitative Systematic Review and Meta-synthesis.

Despite emerging evidence on the effectiveness of eHealth interventions in improving cardiovascular health, little is known about the perception of use and efficacy of these interventions and real-world application. We sought to develop an in-depth understanding of the perceptions of eHealth interventions in improving cardiovascular health. This is a systematic review and meta-synthesis of qualitative studies. A comprehensive search of multiple databases and a manual search of the references list were conducted. Meta-synthesis of qualitative data was performed to review and interpret the findings. The study report followed the ENTREQ checklist. Four themes emerged regarding perceptions of eHealth interventions: preferred eHealth intervention design features, enabling healthcare professionals' support, eHealth engagement for health benefits, and barriers to eHealth engagement. Intervention design features should integrate motivational elements, use an eHealth literacy lens, and enhance cultural relevance. Healthcare professionals appreciated these new working methods but voiced concern about competency building. Real-world usage initiation was driven by perceived needs and usefulness, whereas persistent engagement was inspired by intrinsic motivation in participants. eHealth interventions were appreciated as a valuable opportunity for providing alternative/supplementary cardiac care for health optimization. Participants commented on the need for more explicit and accurate health information presentation, and they appreciated the motivational elements in empowering them with self-determination over daily self-care behaviors. Professionals raised the need for specific guidance to enhance competency and intervention fidelity when delivering eHealth care.

Effect of e-health interventions on HIV prevention: a protocol of systematic review and meta-analysis

BackgroundGlobal epidemiological data indicates that despite implementation of multiple interventions and significant financial investment, the HIV/AIDS epidemic remained inadequately controlled as of 2020. E-health presents a novel approach in delivering health information and health care and has gained popularity in HIV prevention worldwide. However, evidence on the effectiveness of e-health interventions on HIV prevention among diverse populations remains inadequate. Our study aims to systematically evaluate the effectiveness of varying e-health interventions on HIV prevention, with the objective of providing data support and guidance for the development of future e-health HIV intervention strategies.MethodsA systematic search of electronic English databases, including MEDLINE through PubMed, Embase, Scopus, and Web of Science, along with three Chinese databases, including National Knowledge Infrastructure (CNKI), Chinese Wanfang Digital Periodicals (WANFANG), and Chinese Science and Technology Periodicals (VIP) database, will be conducted for the period of 1 January 1980 to 31 December 2022. Additionally, gray literature and unpublished trials in trial registers will be searched. Studies aimed at HIV prevention through e-health interventions, with full-text publications available in either English or Chinese, will be included. Study types will be limited to RCT, cluster RCT, and quasi-experiment study. The risk of bias in individual studies will be assessed following the guideline highlighted by the Cochrane Handbook for Systematic Reviews of Interventions. The outcomes will cover cognitive, behavioral, psychological, management, and biological measures of individuals involved in e-health interventions. The quality of evidence will be assessed by the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach. Ultimately, a systematic review with meta-analysis will be conducted to compare the effectiveness of e-health interventions among diverse populations.DiscussionThis systematic review seeks to establish novel insights into the effectiveness of e-health interventions in diverse populations worldwide. It will inform the design and use of e-health interventions to optimize HIV-related strategies.Systematic review registrationPROSPERO CRD42022295909.

A Systematic Review of eHealth Interventions Among Adolescents of Low Socioeconomic and Geographically Remote Backgrounds in Preventing Poor Diet, Alcohol Use, Tobacco Smoking and Vaping

AbstractDisadvantaged adolescents such as those of low socioeconomic and geographically remote backgrounds experience disproportionate chronic disease burden and tend to engage in greater risk behaviors including poor diet, alcohol use, tobacco smoking, and vaping. The social, structural, and economical barriers to health that uniquely affect adolescents of low socioeconomic and geographically remote backgrounds, such as stigma, access to and affordability of services, may partially explain their disadvantage in attaining health equity. Universal eHealth interventions can provide effective prevention, however, it is unclear whether they benefit disadvantaged adolescents, including those from low socioeconomic and geographically remote contexts. This study systematically reviewed the effectiveness of eHealth interventions targeting disadvantaged adolescents in preventing poor diet, alcohol use, tobacco smoking and vaping. Of 3278 identified records, 15 publications assessing 14 interventions were included, comprising 7170 youth (aged 9–18 years, 50.1% female, 56% low-mid SES, 33% remote). Nine interventions targeted poor diet, three targeted alcohol, one targeted tobacco, and one targeted alcohol and tobacco. No interventions targeted vaping. eHealth interventions significantly increased fruit and vegetable intake and percentage energy of nutrient-rich food, decreased sugar-sweetened beverage consumption, total energy intake, nutrient-poor food percentage energy consumption, and were associated with reduced binge drinking at 1-month follow-up among intervention completers. The findings of this study highlight that eHealth interventions can be effective in targeting poor diet and alcohol use among disadvantaged adolescents. However, due to the limited number of studies meeting inclusion criteria for this study, it is critical future research focus on developing and evaluating effective eHealth interventions targeting disadvantaged adolescents.

The Effectiveness of eHealth Interventions on Lifestyle Modification in Patients With Nonalcoholic Fatty Liver Disease: Systematic Review and Meta-analysis.

The prevalence of nonalcoholic fatty liver disease (NAFLD) is increasing in parallel with the epidemic of obesity and metabolic syndrome. Lifestyle modification is a crucial strategy for the treatment of NAFLD, which can lead to a reduction in liver fat with concomitant weight loss. The use of eHealth technologies is an effective approach to improve health outcomes in patients as they do not have any time and space limitations. This study aimed to evaluate published eHealth intervention studies for the improvement of lifestyle modifications among patients with NAFLD and to provide recommendations for future studies. We conducted a systematic review and meta-analysis. Five electronic databases (PubMed, Cochrane Central, CINAHL, Embase, and Web of Science) were searched for studies reporting the effect of lifestyle modification intervention using eHealth in patients with NAFLD published from inception to November 3, 2022. Study selection, data extraction, and quality assessment were performed by 3 researchers independently. The quality of included studies was assessed using the Cochrane risk of bias tool and the Risk of Bias Assessment Tool for Nonrandomized Studies. In total, 2688 records were identified, and 41 full-text articles were assessed. Seven studies were included in the systematic review. The participants of all interventions were 1257 individuals with NAFLD, and the mean age ranged from 38.3 to 57.9 years. The duration of the interventions was 3-24 months, and all interventions were categorized into 3 types: internet-based computers, telephones, and mobile apps. Of these, 4 studies were randomized controlled trials and were included in the meta-analysis: 3 studies for body weight and BMI and 4 studies for alanine aminotransferase (ALT) and aspartate aminotransferase (AST). According to the meta-analysis, clear improvements in BMI (P=.02; 95% CI -1.01 to -0.10), AST (P=.02; 95% CI -1.22 to -0.13), and ALT (P=.01; 95% CI -1.28 to -0.15) were observed in the eHealth intervention as compared with the control groups. Lifestyle modification interventions using eHealth technologies are significantly effective for BMI, AST, and ALT in patients with NAFLD. Future research should conduct interventions with larger sample sizes and evaluate whether these interventions have sustained benefits, and how we can make these eHealth methods most effective on a large scale.

Optimization of eHealth interventions for intimate partner violence and abuse: A qualitative study amongst Arabic-speaking migrant women.

This interview study focuses on the needs and wishes of Arabic-speaking migrant women in the Netherlands to culturally adapt and optimize the digital support platform SAFE (safewomen.nl) for intimate partner violence and abuse (IPVA) for their use. This is a qualitative interview-based study. We conducted the study between March 2020 and 2021. The study entailed 16 semi-structured interviews with Arabic-speaking women in the Netherlands with a migration background. Findings suggest that a cultural gap, a lack of knowledge of the Dutch law, and the prevalence of restrictive gender roles amongst the participants and their spouses affected their acknowledgement of the different forms of IPVA. Furthermore, mental health consequences of IPVA were also strongly stigmatized. Clear information in their native language, summarizing infographics and potential interactive features should be main components of any eHealth intervention for this target group. The participants in our study deemed e-help a potentially valuable support option for women experiencing IPVA in their community. The impact of IPVA on mental health is currently overlooked within this target group and should be emphasized in future interventions. Cultural sensitivity proved crucial in understanding the concepts of IPVA amongst women with migrant backgrounds. To ensure effective eHealth interventions for migrant women, they should be involved in the design and delivery of these interventions.

EHealth Interventions Targeting Poor Diet, Alcohol Use, Tobacco Smoking, and Vaping Among Disadvantaged Youth: Protocol for a Systematic Review.

BackgroundChronic disease burden is higher among disadvantaged populations. Preventing lifestyle risk behaviors such as poor diet, alcohol use, tobacco smoking, and vaping in adolescence is critical for reducing the risk of chronic disease and related harms in adolescence and adulthood. Although eHealth interventions are a promising prevention approach among the general population, it is unclear whether they adequately serve adolescents from disadvantaged backgrounds such as those living in geographically remote or lower socioeconomic areas.ObjectiveThis is the first systematic review to identify, evaluate, and synthesize evidence for the effectiveness of eHealth interventions targeting adolescents living in geographically remote or lower socioeconomic areas in preventing poor diet, alcohol use, tobacco smoking, and vaping.MethodsA systematic search will be conducted in 7 electronic databases: the Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, PROSPERO, MEDLINE (Ovid), Embase (Ovid), Scopus, and PsycInfo (Ovid). The search will be limited to eHealth-based experimental studies (ie, randomized controlled trials and quasi-experimental studies) targeting diet, alcohol use, tobacco smoking, and vaping among adolescents (aged 10-19 years). Eligible studies will be those reporting on at least one marker of socioeconomic status (eg, social class, household income, parental occupation status, parental education, and family affluence) or geographical remoteness (eg, living in rural, regional, and remote areas, or living outside major metropolitan centers). One reviewer will screen all studies for eligibility, of which 25% will be double-screened. Data will be extracted and summarized in a narrative synthesis. Risk of bias will be assessed using the Cochrane Revised Risk of Bias Tool.ResultsAs of December 2021, the title and abstract screening of 3216 articles was completed, and the full-text review was underway. The systematic review is expected to be completed in 2022.ConclusionsThis systematic review will provide an in-depth understanding of effective eHealth interventions targeting poor diet, alcohol use, tobacco smoking, and vaping among adolescents living in geographically remote or lower socioeconomic areas and the factors that contribute to their effectiveness. This in turn will provide critical knowledge to improve future interventions delivered to these populations.Trial RegistrationPROSPERO CRD42021294119; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=294119International Registered Report Identifier (IRRID)PRR1-10.2196/35408

Designing Effective eHealth Interventions for Underserved Groups: Five Lessons From a Decade of eHealth Intervention Design and Deployment.

Despite the proliferation of eHealth interventions, such as web portals, for health information dissemination or the use of mobile apps and wearables for health monitoring, research has shown that underserved groups do not benefit proportionately from these eHealth interventions. This is largely because of usability issues and the lack of attention to the broader structural, physical, and psychosocial barriers to technology adoption and use. The objective of this paper is to draw lessons from a decade of experience in designing different user-centered eHealth interventions (eg, web portals and health apps) to inform future work in leveraging technology to address health disparities. We draw these lessons from a series of interventions from the work we have done over 15 years in the Viswanath laboratory at the Dana-Farber Cancer Institute and Harvard TH Chan School of Public Health, focusing on three projects that used web portals and health apps targeted toward underserved groups. The projects were the following: Click to Connect, which was a community-based eHealth intervention that aimed to improve internet skills and health literacy among underserved groups by providing home access to high-speed internet, computer, and internet training classes, as well as a dedicated health web portal with ongoing technical support; PLANET MassCONECT, which was a knowledge translation project that built capacity among community-based organizations in Boston, Lawrence, and Worcester in Massachusetts to adopt evidence-based health promotion programs; and Smartphone App for Public Health, which was a mobile health research that facilitated both participatory (eg, surveys) and passive data (eg, geolocations and web-browsing behaviors) collection for the purpose of understanding tobacco message exposure in individuals’ built environment. Through our work, we distilled five key principles for researchers aiming to design eHealth interventions for underserved groups. They are as follows: develop a strategic road map to address communication inequalities (ie, a concrete action plan to identify the barriers faced by underserved groups and customize specific solutions to each of them), engage multiple stakeholders from the beginning for the long haul, design with usability—readability and navigability—in mind, build privacy safeguards into eHealth interventions and communicate privacy–utility tradeoffs in simplicity, and strive for an optimal balance between open science aspirations and protection of underserved groups.

Evidence Synthesis of Digital Interventions to Mitigate the Negative Impact of the COVID-19 Pandemic on Public Mental Health: Rapid Meta-review.

BackgroundAccumulating evidence suggests the COVID-19 pandemic has negative effects on public mental health. Digital interventions that have been developed and evaluated in recent years may be used to mitigate the negative consequences of the pandemic. However, evidence-based recommendations on the use of existing telemedicine and internet-based (eHealth) and app-based mobile health (mHealth) interventions are lacking.ObjectiveThe aim of this study was to investigate the theoretical and empirical base, user perspective, safety, effectiveness, and cost-effectiveness of digital interventions related to public mental health provision (ie, mental health promotion, prevention, and treatment of mental disorders) that may help to reduce the consequences of the COVID-19 pandemic.MethodsA rapid meta-review was conducted. The MEDLINE, PsycINFO, and CENTRAL databases were searched on May 11, 2020. Study inclusion criteria were broad and considered systematic reviews and meta-analyses that investigated digital tools for health promotion, prevention, or treatment of mental health conditions and determinants likely affected by the COVID-19 pandemic.ResultsOverall, 815 peer-reviewed systematic reviews and meta-analyses were identified, of which 83 met the inclusion criteria. Our findings suggest that there is good evidence on the usability, safety, acceptance/satisfaction, and effectiveness of eHealth interventions. Evidence on mHealth apps is promising, especially if social components (eg, blended care) and strategies to promote adherence are incorporated. Although most digital interventions focus on the prevention or treatment of mental disorders, there is some evidence on mental health promotion. However, evidence on process quality, cost-effectiveness, and long-term effects is very limited.ConclusionsThere is evidence that digital interventions are particularly suited to mitigating psychosocial consequences at the population level. In times of physical distancing, quarantine, and restrictions on social contacts, decision makers should develop digital strategies for continued mental health care and invest time and efforts in the development and implementation of mental health promotion and prevention programs.

Exchanges in a Virtual Environment for Diabetes Self-Management Education and Support: Social Network Analysis.

BackgroundDiabetes remains a major health problem in the United States, affecting an estimated 10.5% of the population. Diabetes self-management interventions improve diabetes knowledge, self-management behaviors, and clinical outcomes. Widespread internet connectivity facilitates the use of eHealth interventions, which positively impacts knowledge, social support, and clinical and behavioral outcomes. In particular, diabetes interventions based on virtual environments have the potential to improve diabetes self-efficacy and support, while being highly feasible and usable. However, little is known about the patterns of social interactions and support taking place within type 2 diabetes–specific virtual communities.ObjectiveThe objective of this study was to examine social support exchanges from a type 2 diabetes self-management education and support intervention that was delivered via a virtual environment.MethodsData comprised virtual environment–mediated synchronous interactions among participants and between participants and providers from an intervention for type 2 diabetes self-management education and support. Network data derived from such social interactions were used to create networks to analyze patterns of social support exchange with the lens of social network analysis. Additionally, network correlations were used to explore associations between social support networks.ResultsThe findings revealed structural differences between support networks, as well as key network characteristics of supportive interactions facilitated by the intervention. Emotional and appraisal support networks are the larger, most centralized, and most active networks, suggesting that virtual communities can be good sources for these types of support. In addition, appraisal and instrumental support networks are more connected, suggesting that members of virtual communities are more likely to engage in larger group interactions where these types of support can be exchanged. Lastly, network correlations suggest that participants who exchange emotional support are likely to exchange appraisal or instrumental support, and participants who exchange appraisal support are likely to exchange instrumental support.ConclusionsSocial interaction patterns from disease-specific virtual environments can be studied using a social network analysis approach to better understand the exchange of social support. Network data can provide valuable insights into the design of novel and effective eHealth interventions given the unique opportunity virtual environments have facilitating realistic environments that are effective and sustainable, where social interactions can be leveraged to achieve diverse health goals.

Identifying Persuasive Design Principles and Behavior Change Techniques Supporting End User Values and Needs in eHealth Interventions for Long-Term Weight Loss Maintenance: Qualitative Study.

BackgroundAn increasing number of eHealth interventions aim to support healthy behaviors that facilitate weight loss. However, there is limited evidence of the effectiveness of the interventions and little focus on weight loss maintenance. Knowledge about end user values and needs is essential to create meaningful and effective eHealth interventions, and to identify persuasive system design (PSD) principles and behavior change techniques (BCTs) that may contribute to the behavior change required for successful long-term weight loss maintenance.ObjectiveThis study aimed to provide insight into the design of eHealth interventions supporting behavior change for long-term weight maintenance. The study sought to identify the values and needs of people with obesity aiming to maintain weight after weight loss, and to identify PSD principles, BCTs, and design requirements that potentially enable an eHealth intervention to meet end user values and needs.MethodsThis study presents the concept of integrating PSD principles and BCTs into the design process of eHealth interventions to meet user values and needs. In this study, individual interviews and focus groups were conducted with people with obesity (n=23) and other key stakeholders (n=27) to explore end user values and needs related to weight loss maintenance. Design thinking methods were applied during the focus group sessions to identify design elements and to explore how eHealth solutions can support the needs to achieve sustainable weight loss maintenance. The PSD model and behavior change taxonomy by Michie were used to identify PSD principles and BCT clusters to meet end user values and needs.ResultsA total of 8 key end user values were identified, reflecting user needs for weight loss maintenance support: self-management, personalized care, autonomy, feel supported, positive self-image, motivation, happiness, and health. Goals and planning, feedback and monitoring, repetition and substitution, shaping knowledge, social support, identity, and self-belief were some of the BCT clusters identified to address these concepts, together with PSD principles such as personalization, tailoring, self-monitoring, praise, and suggestions.ConclusionsThe process of translating end user values and needs into design elements or features of eHealth technologies is an important part of the design process. To our knowledge, this is the first study to explore how PSD principles and BCTs can be integrated when designing eHealth self-management interventions for long-term weight loss maintenance. End users and other key stakeholders highlighted important factors to be considered in the design of eHealth interventions supporting sustained behavior change. The PSD principles and BCTs identified provide insights and suggestions about design elements and features to include for supporting weight loss maintenance. The findings indicate that a combination of BCTs and PSD principles may be needed in evidence-based eHealth interventions to stimulate motivation and adherence to support healthy behaviors and sustained weight loss maintenance.Trial RegistrationClinicalTrials.gov NCT04537988; https://clinicaltrials.gov/ct2/show/NCT04537988

Effects of eHealth interventions on physical activity and weight among pregnant and postpartum women and the sociodemographic characteristics of study populations: a systematic review protocol.

The objective of this review is to evaluate the impact of electronic health (eHealth) interventions on physical activity and weight changes among pregnant and/or postpartum populations and to describe the sociodemographic characteristics of the study populations. The American College of Obstetricians and Gynecologists recommends 20 minutes of daily physical activity during pregnancy and postpartum. Few pregnant women are physically active and among those who are, physical activity levels decline as pregnancy progresses and during postpartum. Behavioral eHealth interventions offer convenient and frequent accessibility at low cost and high reach. A search of the extant literature including PROSPERO, MEDLINE (PubMed), the Cochrane Database of Systematic Reviews and the JBI Database of Systematic Reviews and Implementation Reports revealed no published or in-progress reviews examining eHealth physical activity interventions among pregnant and/or postpartum populations. Studies of eHealth interventions including pregnant and/or within one-year postpartum populations will be included. This review will be conducted in accordance with JBI methodology for systematic reviews of effectiveness. The search strategy will aim to locate studies from the inception of each database. Citations will be collated, and duplicates removed. Titles and abstracts will be screened for eligibility against the inclusion criteria and relevant studies retrieved. Included studies will be appraised for methodological quality using JBI standardized critical appraisal instruments. Extracted data will include study methods, intervention design and outcomes (physical activity, weight, participant sociodemographic characteristics). The Grading of Recommendations, Assessment, Development and Evaluation approach for grading the certainty of evidence will be followed. PROSPERO CRD42020124611.

Applying the Electronic Health Literacy Lens: Systematic Review of Electronic Health Interventions Targeted at Socially Disadvantaged Groups.

BackgroundElectronic health (eHealth) has the potential to improve health outcomes. However, eHealth systems need to match the eHealth literacy needs of users to be equitably adopted. Socially disadvantaged groups have lower access and skills to use technologies and are at risk of being digitally marginalized, leading to the potential widening of health disparities.ObjectiveThis systematic review aims to explore the role of eHealth literacy and user involvement in developing eHealth interventions targeted at socially disadvantaged groups.MethodsA systematic search was conducted across 10 databases for eHealth interventions targeted at older adults, ethnic minority groups, low-income groups, low-literacy groups, and rural communities. The eHealth Literacy Framework was used to examine the eHealth literacy components of reviewed interventions. The results were analyzed using narrative synthesis.ResultsA total of 51 studies reporting on the results of 48 interventions were evaluated. Most studies were targeted at older adults and ethnic minorities, with only 2 studies focusing on low-literacy groups. eHealth literacy was not considered in the development of any of the studies, and no eHealth literacy assessment was conducted. User involvement in designing interventions was limited, and eHealth intervention developmental frameworks were rarely used. Strategies to assist users in engaging with technical systems were seldom included in the interventions, and accessibility features were limited. The results of the included studies also provided inconclusive evidence on the effectiveness of eHealth interventions.ConclusionsThe findings highlight that eHealth literacy is generally overlooked in developing eHealth interventions targeted at socially disadvantaged groups, whereas evidence about the effectiveness of such interventions is limited. To ensure equal access and inclusiveness in the age of eHealth, eHealth literacy of disadvantaged groups needs to be addressed to help avoid a digital divide. This will assist the realization of recent technological advancements and, importantly, improve health equity.

What are the effects of eHealth interventions for people with chronic kidney disease?

What are the effects of eHealth interventions for people with chronic kidney disease?

Mental Health Therapy Protocols and eHealth Design: Focus Group Study.

BackgroundElectronic health (eHealth) programs are often based on protocols developed for the original face-to-face therapies. However, in practice, therapists and patients may not always follow the original therapy protocols. This form of personalization may also interfere with the intended implementation and effects of eHealth interventions if designers do not take these practices into account.ObjectiveThe aim of this explorative study was to gain insights into the personalization practices of therapists and patients using cognitive behavioral therapy, one of the most commonly applied types of psychotherapy, in a youth addiction care center as a case context.MethodsFocus group discussions were conducted asking therapists and patients to estimate the extent to which a therapy protocol was followed and about the type and reasons for personalization of a given therapy protocol. A total of 7 focus group sessions were organized involving therapists and patients. We used a commonly applied protocol for cognitive behavioral therapy as a therapy protocol example in youth mental health care. The first focus group discussions aimed at assessing the extent to which patients (N=5) or therapists (N=6) adapted the protocol. The second focus group discussions aimed at estimating the extent to which the therapy protocol is applied and personalized based on findings from the first focus groups to gain further qualitative insight into the reasons for personalization with groups of therapists and patients together (N=7). Qualitative data were analyzed using thematic analysis.ResultsTherapists used the protocol as a “toolbox” comprising different therapy tools, and personalized the protocol to enhance the therapeutic alliance and based on their therapy-provision experiences. Therapists estimated that they strictly follow 48% of the protocol, adapt 30%, and replace 22% by other nonprotocol therapeutic components. Patients personalized their own therapy to conform the assignments to their daily lives and routines, and to reduce their levels of stress and worry. Patients estimated that 29% of the provided therapy had been strictly followed by the therapist, 48% had been adjusted, and 23% had been replaced by other nonprotocol therapeutic components.ConclusionsA standard cognitive behavioral therapy protocol is not strictly and fully applied but is mainly personalized. Based on these results, the following recommendations for eHealth designers are proposed to enhance alignment of eHealth to therapeutic practice and implementation: (1) study and copy at least the applied parts of a protocol, (2) co-design eHealth with therapists and patients so they can allocate the components that should be open for user customization, and (3) investigate if components of the therapy protocol that are not applied should remain part of the eHealth applied. To best generate this information, we suggest that eHealth designers should collaborate with therapists, patients, protocol developers, and mental health care managers during the development process.

Filling the gaps of patient information and comprehension.

This review describes the gaps in cancer patient information and comprehension and provides examples of interventions aimed at filling the gaps. Despite the technologically advanced era, unmet information needs remain a challenge in current cancer care, even though the beneficial effects of adequate information provision are well described.It starts with the basics of patient-physician communication and information exchange. Barriers are described both patient and physician-specific. For patients to comprehend and recall information correctly, information provision should be tailored to the specific patient in content, as well as in readability level. Tailored content based on bidirectional and iterative information exchange (i.e., patients reported outcomes, followed by specific/personalized feedback) is of focus in the current development of interventions aimed at meeting the gaps. However, the effects of such interventions are not overwhelming and the explanation could be multifactorial. Unmet informational needs are still a gap in current cancer care. The effect of eHealth interventions is not yet well established. Key is to educate patients and (future) healthcare professionals in eHealth. Future research should focus on identifying what kind of interventions are able to fill the gaps.

The Effect of eHealth Interventions on Physical Activity in Patients with Chronic Obstructive Pulmonary Disease: A Mini Review

The Effect of eHealth Interventions on Physical Activity in Patients with Chronic Obstructive Pulmonary Disease: A Mini Review

A Self-Regulation-Based eHealth Intervention to Promote a Healthy Lifestyle: Investigating User and Website Characteristics Related to Attrition.

BackgroundeHealth interventions can reach large populations and are effective in increasing physical activity (PA) and fruit and vegetable intake. Nevertheless, the effects of eHealth interventions are overshadowed by high attrition rates. Examining more closely when users decide to leave the intervention can help eHealth developers to make informed decisions about which intervention components should be reshaped or simply removed. Investigating which users are more likely to quit an intervention can inform developers about whether and how their intervention should be adapted to specific subgroups of users.ObjectiveThis study investigated the pattern of attrition in a Web-based intervention to increase PA, fruit, and vegetable intake. The first aim was to describe attrition rates according to different self-regulation components. A second aim was to investigate whether certain user characteristics are predictors for start session completion, returning to a follow-up session and intervention completion.MethodsThe sample consisted of 549 adults who participated in an online intervention, based on self-regulation theory, to promote PA and fruit and vegetable intake, called “MyPlan 1.0.” Using descriptive analysis, attrition was explored per self-regulation component (eg, action planning and coping planning). To identify which user characteristics predict completion, logistic regression analyses were conducted.ResultsAt the end of the intervention program, there was an attrition rate of 78.2% (330/422). Attrition rates were very similar for the different self-regulation components. However, attrition levels were higher for the fulfillment of questionnaires (eg, to generate tailored feedback) than for the more interactive components. The highest amount of attrition could be observed when people were asked to make their own action plan. There were no significant predictors for first session completion. Yet, two subgroups had a lower chance to complete the intervention, namely male users (OR: 2.24, 95% CI=1.23-4.08) and younger adults (OR: 1.02, 95% CI=1.00-1.04). Furthermore, younger adults were less likely to return to the website for the first follow-up after one week (OR: 1.03, 95% CI=1.01-1.04).ConclusionsThis study informs us that eHealth interventions should avoid the use of extensive questionnaires and that users should be provided with a rationale for several components (eg, making an action plan and completing questions). Furthermore, future interventions should focus first on motivating users for the behavior change before guiding them through action planning. Though, this study provides no evidence for removal of one of the self-regulation techniques based on attrition rates. Finally, strong efforts are needed to motivate male users and younger adults to complete eHealth interventions.