Dataset Information

Mobile Health for Pediatric Weight Management: Systematic Scoping Review.

ABSTRACT: BACKGROUND:The prevalence and consequences of obesity among children and adolescents remain a leading global public health concern, and evidence-based, multidisciplinary lifestyle interventions are the cornerstone of treatment. Mobile electronic devices are widely used across socioeconomic categories and may provide a means of extending the reach and efficiency of health care interventions. OBJECTIVE:We aimed to synthesize the evidence regarding mobile health (mHealth) for the treatment of childhood overweight and obesity to map the breadth and nature of the literature in this field and describe the characteristics of published studies. METHODS:We conducted a systematic scoping review in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews, by searching nine academic databases in addition to gray literature for studies describing acceptability, usability, feasibility, effectiveness, adherence, or cost-effectiveness of interventions assessing mHealth for childhood obesity treatment. We also hand searched the reference lists of relevant articles. Studies aimed at the prevention of overweight or obesity were excluded, as were studies in which mHealth was not the primary mode of treatment delivery for at least one study arm or was not independently assessed. A random portion of all abstracts and full texts was double screened by a second reviewer to ensure consistency. Data were charted according to study characteristics, including design, participants, intervention content, behavior change theory (BCT) underpinning the study, mode of delivery, and outcomes measured. RESULTS:We identified 42 eligible studies assessing acceptability (n=7), usability (n=2), feasibility or pilot studies (n=15), treatment effect (n=17), and fidelity (n=1). Change in BMI z-scores or percentiles was most commonly measured, among a variety of dietary, physical activity, psychological, and usability or acceptability measures. SMS, mobile apps, and wearable devices made up the majority of mobile interventions, and 69% (29/42) of the studies specified a BCT used. CONCLUSIONS:Pediatric weight management using mHealth is an emerging field, with most work to date aimed at developing and piloting such interventions. Few large trials are published, and these are heterogeneous in nature and rarely reported according to the Consolidated Standards of Reporting Trials for eHealth guidelines. There is an evidence gap in the cost-effectiveness analyses of such studies.

SUBMITTER: Tully L

PROVIDER: S-EPMC7301268 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Mobile Health for Pediatric Weight Management: Systematic Scoping Review.

Tully Louise L Burls Amanda A Sorensen Jan J El-Moslemany Riyad R O'Malley Grace G

JMIR mHealth and uHealth 20200603 6

<h4>Background</h4>The prevalence and consequences of obesity among children and adolescents remain a leading global public health concern, and evidence-based, multidisciplinary lifestyle interventions are the cornerstone of treatment. Mobile electronic devices are widely used across socioeconomic categories and may provide a means of extending the reach and efficiency of health care interventions.<h4>Objective</h4>We aimed to synthesize the evidence regarding mobile health (mHealth) for the tre ...[more]

PMID: 32490849

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Project description:IntroductionAn estimated one billion people globally are currently suffering from hypertension. Prevention and management of hypertension are suboptimal especially in low- and middle-income countries leading to increased complications and deaths. With increased mobile phone coverage globally, this study aims to review mobile health technologies used for the prevention and management of hypertension.MethodsWe conducted a literature search on electronic databases using identified keywords involving "hypertension", "mobile health technology" and their synonyms. Snowballing technique was also used. Papers were screened at two levels by independent reviewers. The targets were studies published in peer-reviewed journals reporting mobile health interventions for hypertension prevention and management. Only primary research studies published in English from January 2017 to April 2024 were included. Google Forms were used to extract the data along with other characteristics, and selected articles were categorised into: mobile application, web-based solutions, and Short Message Service (SMS) and other offline solutions.ResultThe search yielded 184 articles, and 44 studies were included in the review. Most (n = 26) were randomised control trials. Twenty-two studies (22) focused only on mobile applications solutions, 12 on SMS and other offline mHealth, 5 web-based solutions, and 5 combined more than one type of mobile health technology. The United States of America had the majority of studies (n = 17), with 6 studies from other American countries, 11 from Asia and nine from Europe, while only one from Africa. A total of 36 studies reported that mobile health technology significantly improved hypertension care through reduced blood pressure, improved adherence to follow-up visits and medications, and lifestyle changes. SMS and offline mHealth strategies have also demonstrated effectiveness in promoting self-management and reducing racial disparities in hypertension care.ConclusionMobile health technology has the potential to play a significant role in the prevention and management of hypertension. However, there is a need for mobile health solutions for hypertension prevention and management in African countries and other developing countries. Integrating mHealth into primary healthcare delivery would also go a long way in strengthening patient care and reducing the burden on healthcare systems.

Project description:BACKGROUND:The use of apps to tackle overweight and obesity by tracking physical and dietary patterns and providing recommendations and motivation strategies to achieve personalized goals has increased over recent years. However, evidence of the efficacy, effectiveness, and safety of these apps is severely lacking. OBJECTIVE:The aim of this study was to identify efficacy, safety, and effectiveness criteria used to assess weight control, overweight, and obesity management in mobile health (mHealth) interventions through a systematic review. METHODS:PubMed, PsycINFO, Scopus, UK Trial Database, ClinicalTrials.gov, and the Cochrane Library were surveyed up to May 2018. All types of clinical studies were considered. A total of 2 independent reviewers assessed quality using Scottish Intercollegiate Guidelines Network (SIGN) criteria. Ratings were used to provide an overall score for each study (low, moderate, or high). Data were synthesized in evidence tables. RESULTS:From 233 potentially relevant publications, only 28 studies were included. Of these, 13 (46%) were randomized control trials, 11 were single-arm studies (39%), 3 were nonrandomized controlled trials (11%), and 1 study was a cluster randomized trial (4%). The studies were classified as low (15), high (7), and moderate (6) quality according to SIGN criteria. All studies focused on efficacy, with only 1 trial mentioning safety and another 1 effectiveness. In 11 studies, the apps were used as stand-alone interventions, the others were multicomponent studies that included other tools for support such as sensors or websites. The main management tool included in the apps was feedback messaging (24), followed by goal-setting mechanisms (20) and self-monitoring (19). The majority of studies took weight or body mass index loss as the main outcome (22) followed by changes in physical activity (14) and diet (12). Regarding outputs, usability, adherence, and engagement (17) were the most reported, followed by satisfaction (7) and acceptability (4). CONCLUSIONS:There is a remarkable heterogeneity among these studies and the majority have methodological limitations that leave considerable room for improvement. Further research is required to identify all relevant criteria for assessing the efficacy of mHealth interventions in the management of overweight and obesity. TRIAL REGISTRATION:PROSPERO CRD42017056761; https://tinyurl.com/y2zhxtjx.

Project description:BackgroundA total of 75% of people with mental health disorders have an onset of illness between the ages of 12 and 24 years. Many in this age group report substantial obstacles to receiving quality youth-centered mental health care services. With the rapid development of technology and the recent COVID-19 pandemic, mobile health (mHealth) has presented new opportunities for youth mental health research, practice, and policy.ObjectiveThe research objectives were to (1) synthesize the current evidence supporting mHealth interventions for youths who experience mental health challenges and (2) identify current gaps in the mHealth field related to youth's access to mental health services and health outcomes.MethodsGuided by the methods of Arksey and O'Malley, we conducted a scoping review of peer-reviewed studies that used mHealth tools to improve youth mental health (January 2016-February 2022). We searched MEDLINE, PubMed, PsycINFO, and Embase databases using the following key terms: (1) mHealth; (2) youth and young adults; and (3) mental health. The current gaps were analyzed using content analysis.ResultsThe search produced 4270 records, of which 151 met inclusion criteria. Included articles highlight the comprehensive aspects of youth mHealth intervention resource allocation for targeted conditions, mHealth delivery methods, measurement tools, evaluation of mHealth intervention, and youth engagement. The median age for participants in all studies is 17 (IQR 14-21) years. Only 3 (2%) studies involved participants who reported their sex or gender outside of the binary option. Many studies (68/151, 45%) were published after the onset of the COVID-19 outbreak. Study types and designs varied, with 60 (40%) identified as randomized controlled trials. Notably, 143 out of 151 (95%) studies came from developed countries, suggesting an evidence shortfall on the feasibility of implementing mHealth services in lower-resourced settings. Additionally, the results highlight concerns related to inadequate resources devoted to self-harm and substance uses, weak study design, expert engagement, and the variety of outcome measures selected to capture impact or changes over time. There is also a lack of standardized regulations and guidelines for researching mHealth technologies for youths and the use of non-youth-centered approaches to implementing results.ConclusionsThis study may be used to inform future work as well as the development of youth-centered mHealth tools that can be implemented and sustained over time for diverse types of youths. Implementation science research that prioritizes youths' engagement is needed to advance the current understanding of mHealth implementation. Moreover, core outcome sets may support a youth-centered measurement strategy to capture outcomes in a systematic way that prioritizes equity, diversity, inclusion, and robust measurement science. Finally, this study suggests that future practice and policy research are needed to ensure the risk of mHealth is minimized and that this innovative health care service is meeting the emerging needs of youths over time.

Project description:BackgroundFoodborne disease outbreaks are common and notifiable in South Africa; however, they are rarely reported and poorly investigated. Surveillance data from the notification system is suboptimal and limited, and does not provide adequate information to guide public health action and inform policy. We performed a systematic review of published literature to identify mobile application-based outbreak response systems for managing foodborne disease outbreaks and to determine the elements that the system requires to generate foodborne disease data needed for public action.MethodsStudies were identified through literature searches using online databases on PubMed/Medline, CINAHL, Academic Search Complete, Greenfile, Library, Information Science & Technology. Search was limited to studies published in English during the period January 1990 to November 2020. Search strategy included various terms in varying combinations with Boolean phrases "OR" and "AND". Data were collected following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement. A standardised data collection tool was used to extract and summarise information from identified studies. We assessed qualities of mobile applications by looking at the operating system, system type, basic features and functionalities they offer for foodborne disease outbreak management.ResultsFive hundred and twenty-eight (528) publications were identified, of which 48 were duplicates. Of the remaining 480 studies, 2.9% (14/480) were assessed for eligibility. Only one of the 14 studies met the inclusion criteria and reported on one mobile health application named MyMAFI (My Mobile Apps for Field Investigation). There was lack of detailed information on the application characteristics. However, based on minimal information available, MyMAFI demonstrated the ability to generate line lists, reports and offered functionalities for outbreak verification and epidemiological investigation. Availability of other key components such as environmental and laboratory investigations were unknown.ConclusionsThere is limited use of mobile applications on management of foodborne disease outbreaks. Efforts should be made to set up systems and develop applications that can improve data collection and quality of foodborne disease outbreak investigations.

Project description:Addressing health workforce cultural competence is a common approach to improving health service quality for culturally and ethnically diverse groups. Research evidence in this area is primarily focused on cultural competency training and its effects on practitioners' knowledge, attitudes, skills and behaviour. While improvements in measures of healthcare practitioner cultural competency and other healthcare outcomes have been reported, there are concerns around evidence strength and quality. This scoping review reports on the intervention strategies, outcomes, and measures of included studies with the purpose of informing the implementation and evaluation of future interventions to improve health workforce cultural competence.This systematic scoping review was completed as part of a larger systematic literature search conducted on cultural competence intervention evaluations in health care in Canada, the United States, Australia and New Zealand published from 2006 to 2015. Overall, 64 studies on cultural competency interventions were found, with 16 aimed directly at the health workforce.There was significant heterogeneity in workforce intervention strategies, measures and outcomes reported across studies making comparisons of intervention effects difficult. The two main workforce intervention strategies identified were cultural competency training and other professional development interventions including other training and mentoring. Positive outcomes were commonly reported for improved practitioner knowledge (9/16), skills (7/16), and attitudes/beliefs (5/16). Although health care (6/16) and health (2/16) outcomes were reported in some studies there was very limited evidence of positive intervention impacts. Only four studies utilised existing validated measurement tools to assess intervention outcomes.Training and development of the health workforce remain a principle strategy towards the goal of improved cultural competence in health services and systems. Diverse approaches are available to increase health workforce cultural competence. However, the effects of interventions beyond practitioner knowledge and attitudes remains unclear. Assessment of practitioner behavioural outcomes as well as measures of intervention impact on healthcare and health outcomes are needed to build a stronger evidence base.

Project description:BackgroundPrivacy has always been a concern, especially in the health domain. The proliferation of mobile health (mHealth) apps has led to a large amount of sensitive data being generated. Some authors have performed privacy assessments of mHealth apps. They have evaluated diverse privacy components; however, different authors have used different criteria for their assessments.ObjectiveThis scoping review aims to understand how privacy is assessed for mHealth apps, focusing on the components, scales, criteria, and scoring methods used. A simple taxonomy to categorize the privacy assessments of mHealth apps based on component evaluation is also proposed.MethodsWe followed the methodology defined by Arksey and O'Malley to conduct a scoping review. Included studies were categorized based on the privacy component, which was assessed using the proposed taxonomy.ResultsThe database searches retrieved a total of 710 citations-24 of them met the defined selection criteria, and data were extracted from them. Even though the inclusion criteria considered articles published since 2009, all the studies that were ultimately included were published from 2014 onward. Although 12 papers out of 24 (50%) analyzed only privacy, 8 (33%) analyzed both privacy and security. Moreover, 4 papers (17%) analyzed full apps, with privacy being just part of the assessment. The evaluation criteria used by authors were heterogeneous and were based on their experience, the literature, and/or existing legal frameworks. Regarding the set of items used for the assessments, each article defined a different one. Items included app permissions, analysis of the destination, analysis of the content of communications, study of the privacy policy, use of remote storage, and existence of a password to access the app, among many others. Most of the included studies provided a scoring method that enables the comparison of privacy among apps.ConclusionsThe privacy assessment of mHealth apps is a complex task, as the criteria used by different authors for their evaluations are very heterogeneous. Although some studies about privacy assessment have been conducted, a very large set of items to evaluate privacy has been used up until now. In-app information and privacy policies are primarily utilized by the scientific community to extract privacy information from mHealth apps. The creation of a scale based on more objective criteria is a desirable step forward for privacy assessment in the future.

Project description:BackgroundMobile health (mHealth) interventions are increasingly being designed to facilitate health-related behavior change. Integrating insights from behavioral science and design science can help support the development of more effective mHealth interventions. Behavioral Design (BD) and Design Thinking (DT) have emerged as best practice approaches in their respective fields. Until now, little work has been done to examine how BD and DT can be integrated throughout the mHealth design process.ObjectiveThe aim of this scoping review was to map the evidence on how insights from BD and DT can be integrated to guide the design of mHealth interventions. The following questions were addressed: (1) what are the main characteristics of studies that integrate BD and DT during the mHealth design process? (2) what theories, models, and frameworks do design teams use during the mHealth design process? (3) what methods do design teams use to integrate BD and DT during the mHealth design process? and (4) what are key design challenges, implementation considerations, and future directions for integrating BD and DT during mHealth design?MethodsThis review followed the Joanna Briggs Institute reviewer manual and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. Studies were identified from MEDLINE, PsycINFO, Embase, CINAHL, and JMIR by using search terms related to mHealth, BD, and DT. Included studies had to clearly describe their mHealth design process and how behavior change theories, models, frameworks, or techniques were incorporated. Two independent reviewers screened the studies for inclusion and completed the data extraction. A descriptive analysis was conducted.ResultsA total of 75 papers met the inclusion criteria. All studies were published between 2012 and 2021. Studies integrated BD and DT in notable ways, which can be referred to as "Behavioral Design Thinking." Five steps were followed in Behavioral Design Thinking: (1) empathize with users and their behavior change needs, (2) define user and behavior change requirements, (3) ideate user-centered features and behavior change content, (4) prototype a user-centered solution that supports behavior change, and (5) test the solution against users' needs and for its behavior change potential. The key challenges experienced during mHealth design included meaningfully engaging patient and public partners in the design process, translating evidence-based behavior change techniques into actual mHealth features, and planning for how to integrate the mHealth intervention into existing clinical systems.ConclusionsBest practices from BD and DT can be integrated throughout the mHealth design process to ensure that mHealth interventions are purposefully developed to effectively engage users. Although this scoping review clarified how insights from BD and DT can be integrated during mHealth design, future research is needed to identify the most effective design approaches.

Project description:BACKGROUND:Cardiovascular disease (CVD) has grown to become one of the leading causes of mortality worldwide. The advancements of CVD-related treatments have led to a decline in CVD prevalence among individuals in high-income countries (HICs). However, these improvements do not reflect the state of individuals in low- and middle-income countries (LMICs) and vulnerable subgroup populations in HICs, such as the Indigenous. To help minimize the health disparities in these populations, technology-based interventions have been offered as a potential solution, but there is concern regarding if they will be effective, or even needed, as these tools have been designed for use in HICs. OBJECTIVE:The objective of this study was to explore how mobile health (mHealth) interventions currently assist individuals in Indigenous communities and LMICs with CVD management. METHODS:A scoping review guided by the methods outlined by Arksey and O'Malley was conducted. A comprehensive search was completed by 2 reviewers in 5 electronic databases using keywords related to mobile health, cardiovascular disease, self-care, Indigenous communities, and LMICs. Studies were screened over 2 rounds and critically reviewed using a descriptive-analytical narrative method. Descriptive data were categorized into thematic groups reflecting the major findings related to the study objective. RESULTS:We identified a total of 11 original articles and 11 review papers that met the criteria for this scoping review. The majority of the studies included a telemonitoring- and text messaging (short message service, SMS)-related feature associated with the intervention. The use of SMS was the most common approach to effectively promote disease management among individuals in both LMICs and Indigenous communities. However, customizing for cultural considerations within the design of the intervention was highlighted as a pivotal component to encourage CVD management. Specifically, individuals emphasized that the inclusion of collaborative partnerships with community members would strengthen the effectiveness of the intervention by ensuring it was designed with the appropriate context. CONCLUSIONS:Technology-based interventions used within Indigenous communities and LMICs have shown their potential to assist individuals with managing their condition. Although the literature available regarding this topic is limited, this review outlines key components to promote the effective use of these tools in the context of these vulnerable populations.

Dataset Information

Mobile Health for Pediatric Weight Management: Systematic Scoping Review.

Publications

Mobile Health for Pediatric Weight Management: Systematic Scoping Review.

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