Dataset Information

Mindful Eating Mobile Health Apps: Review and Appraisal.

ABSTRACT:

Background

Mindful eating is an emerging area of research for managing unhealthy eating and weight-related behaviors such as binge eating and emotional eating. Although there are numerous commercial mindful eating apps available, their quality, effectiveness, and whether they are accurately based on mindfulness-based eating awareness are unknown.

Objective

This review aimed to appraise the quality of the mindful eating apps and to appraise the quality of content on mindful eating apps.

Methods

A review of mindful eating apps available on Apple iTunes was undertaken from March to April 2018. Relevant apps meeting the inclusion criteria were subjectively appraised for general app quality using the Mobile App Rating Scale (MARS) guidelines and for the quality of content on mindful eating. A total of 22 apps met the inclusion criteria and were appraised.

Results

Many of the reviewed apps were assessed as functional and had moderate scores in aesthetics based on the criteria in the MARS assessment. However, some received lower scores in the domains of information and engagement. The majority of the apps did not teach users how to eat mindfully using all five senses. Hence, they were scored as incomplete in accurately providing mindfulness-based eating awareness. Instead, most apps were either eating timers, hunger rating apps, or diaries. Areas of potential improvement were in comprehensiveness and diversity of media, in the quantity and quality of information, and in the inclusion of privacy and security policies. To truly teach mindful eating, the apps need to provide guided examples involving the five senses beyond simply timing eating or writing in a diary. They also need to include eating meditations to assist people with their disordered eating such as binge eating, fullness, satiety, and craving meditations that may help them with coping when experiencing difficulties. They should also have engaging and entertaining features delivered through diverse media to ensure sustained use and interest by consumers.

Conclusions

Future mindful eating apps could be improved by accurate adherence to mindful eating. Further improvement could be achieved by ameliorating the domains of information, engagement, and aesthetics and having adequate privacy policies.

SUBMITTER: Lyzwinski LN

PROVIDER: S-EPMC6727629 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Mindful Eating Mobile Health Apps: Review and Appraisal.

Lyzwinski Lynnette Nathalie LN Edirippulige Sisira S Caffery Liam L Bambling Matthew M

JMIR mental health 20190822 8

<h4>Background</h4>Mindful eating is an emerging area of research for managing unhealthy eating and weight-related behaviors such as binge eating and emotional eating. Although there are numerous commercial mindful eating apps available, their quality, effectiveness, and whether they are accurately based on mindfulness-based eating awareness are unknown.<h4>Objective</h4>This review aimed to appraise the quality of the mindful eating apps and to appraise the quality of content on mindful eating ...[more]

PMID: 31441431

Similar Datasets

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) is a rapidly emerging market, which has been implemented in a variety of different disease areas. Tuberculosis remains one of the most common causes of death from an infectious disease worldwide, and mHealth apps offer an important contribution to the improvement of tuberculosis treatment. In particular, apps facilitating dose individualization, adherence monitoring, or provision of information and education about the disease can be powerful tools to prevent the development of drug-resistant tuberculosis or disease relapse.ObjectiveThe aim of this review was to identify, describe, and categorize mobile and Web-based apps related to tuberculosis that are currently available.MethodsPubMed, Google Play Store, Apple Store, Amazon, and Google were searched between February and July 2019 using a combination of 20 keywords. Apps were included in the analysis if they focused on tuberculosis, and were excluded if they were related to other disease areas or if they were games unrelated to tuberculosis. All apps matching the inclusion criteria were classified into the following five categories: adherence monitoring, individualized dosing, eLearning/information, diagnosis, and others. The included apps were then summarized and described based on publicly available information using 12 characteristics.ResultsFifty-five mHealth apps met the inclusion criteria and were included in this analysis. Of the 55 apps, 8 (15%) were intended to monitor patients' adherence, 6 (11%) were designed for dosage adjustment, 29 (53%) were designed for eLearning/information, 3 (6%) were focused on tuberculosis diagnosis, and 9 (16%) were related to other purposes.ConclusionsThe number of mHealth apps related to tuberculosis has increased during the past 3 years. Although some of the discovered apps seem promising, many were found to contain errors or provided harmful or wrong information. Moreover, the majority of mHealth apps currently on the market are focused on making information about tuberculosis available (29/55, 53%). Thus, this review highlights a need for new, high-quality mHealth apps supporting tuberculosis treatment, especially those supporting individualized optimized treatment through model-informed precision dosing and video observed treatment.

Project description:BackgroundThere are an increasing number of mobile apps available for adolescents with mental health problems and an increasing interest in assimilating mobile health (mHealth) into mental health services. Despite the growing number of apps available, the evidence base for their efficacy is unclear.ObjectiveThis review aimed to systematically appraise the available research evidence on the efficacy and acceptability of mobile apps for mental health in children and adolescents younger than 18 years.MethodsThe following were systematically searched for relevant publications between January 2008 and July 2016: APA PsychNet, ACM Digital Library, Cochrane Library, Community Care Inform-Children, EMBASE, Google Scholar, PubMed, Scopus, Social Policy and Practice, Web of Science, Journal of Medical Internet Research, Cyberpsychology, Behavior and Social Networking, and OpenGrey. Abstracts were included if they described mental health apps (targeting depression, bipolar disorder, anxiety disorders, self-harm, suicide prevention, conduct disorder, eating disorders and body image issues, schizophrenia, psychosis, and insomnia) for mobile devices and for use by adolescents younger than 18 years.ResultsA total of 24 publications met the inclusion criteria. These described 15 apps, two of which were available to download. Two small randomized trials and one case study failed to demonstrate a significant effect of three apps on intended mental health outcomes. Articles that analyzed the content of six apps for children and adolescents that were available to download established that none had undergone any research evaluation. Feasibility outcomes suggest acceptability of apps was good and app usage was moderate.ConclusionsOverall, there is currently insufficient research evidence to support the effectiveness of apps for children, preadolescents, and adolescents with mental health problems. Given the number and pace at which mHealth apps are being released on app stores, methodologically robust research studies evaluating their safety, efficacy, and effectiveness is promptly needed.

Project description:BackgroundMobile health (mHealth) apps are revolutionizing the way clinicians and researchers monitor and manage the health of their participants. However, many studies using mHealth apps are hampered by substantial participant dropout or attrition, which may impact the representativeness of the sample and the effectiveness of the study. Therefore, it is imperative for researchers to understand what makes participants stay with mHealth apps or studies using mHealth apps.ObjectiveThis study aimed to review the current peer-reviewed research literature to identify the notable factors and strategies used in adult participant engagement and retention.MethodsWe conducted a systematic search of PubMed, MEDLINE, and PsycINFO databases for mHealth studies that evaluated and assessed issues or strategies to improve the engagement and retention of adults from 2015 to 2020. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Notable themes were identified and narratively compared among different studies. A binomial regression model was generated to examine the factors affecting retention.ResultsOf the 389 identified studies, 62 (15.9%) were included in this review. Overall, most studies were partially successful in maintaining participant engagement. Factors related to particular elements of the app (eg, feedback, appropriate reminders, and in-app support from peers or coaches) and research strategies (eg, compensation and niche samples) that promote retention were identified. Factors that obstructed retention were also identified (eg, lack of support features, technical difficulties, and usefulness of the app). The regression model results showed that a participant is more likely to drop out than to be retained.ConclusionsRetaining participants is an omnipresent challenge in mHealth studies. The insights from this review can help inform future studies about the factors and strategies to improve participant retention.

Project description:BackgroundGlobally, mobile phones have achieved wide reach at an unprecedented rate, and mobile phone apps have become increasingly prevalent among users. The number of health-related apps that were published on the two leading platforms (iOS and Android) reached more than 100,000 in 2014. However, there is a lack of synthesized evidence regarding the effectiveness of mobile phone apps in changing people's health-related behaviors.ObjectiveThe aim was to examine the effectiveness of mobile phone apps in achieving health-related behavior change in a broader range of interventions and the quality of the reported studies.MethodsWe conducted a comprehensive bibliographic search of articles on health behavior change using mobile phone apps in peer-reviewed journals published between January 1, 2010 and June 1, 2015. Databases searched included Medline, PreMedline, PsycINFO, Embase, Health Technology Assessment, Education Resource Information Center (ERIC), and Cumulative Index to Nursing and Allied Health Literature (CINAHL). Articles published in the Journal of Medical Internet Research during that same period were hand-searched on the journal's website. Behavior change mechanisms were coded and analyzed. The quality of each included study was assessed by the Cochrane Risk of Bias Assessment Tool.ResultsA total of 23 articles met the inclusion criteria, arranged under 11 themes according to their target behaviors. All studies were conducted in high-income countries. Of these, 17 studies reported statistically significant effects in the direction of targeted behavior change; 19 studies included in this analysis had a 65% or greater retention rate in the intervention group (range 60%-100%); 6 studies reported using behavior change theories with the theory of planned behavior being the most commonly used (in 3 studies). Self-monitoring was the most common behavior change technique applied (in 12 studies). The studies suggest that some features improve the effectiveness of apps, such as less time consumption, user-friendly design, real-time feedback, individualized elements, detailed information, and health professional involvement. All studies were assessed as having some risk of bias.ConclusionsOur results provide a snapshot of the current evidence of effectiveness for a range of health-related apps. Large sample, high-quality, adequately powered, randomized controlled trials are required. In light of the bias evident in the included studies, better reporting of health-related app interventions is also required. The widespread adoption of mobile phones highlights a significant opportunity to impact health behaviors globally, particularly in low- and middle-income countries.

Project description:Aim: This brief report provides an overview of the development and structure of the Health App Review Tool. Methods: The Health App Review Tool has been designed to assess smart phone health apps according to their compatibility to individuals within the Alzheimer's disease community. Specifically, app features and functions are characterized according to their appropriateness to the needs, abilities, and preferences of potential users. The Health App Review Tool is comprised of two components, the App and User Assessment; each component includes four complementary domains. Items in these domains can be compared between App and User assessments using a scoring key that will produce a match score. The score indicates the level of appropriateness in reference to the app's ability to meet the user's needs. Discussion: The Health App Review Tool was designed using available evidence and stakeholder preference data to ensure a user-centered design. The result was the development of a tool built on evidence and informed by the perceptions and preferences of those within and working with the Alzheimer's disease population. App and User domains include usefulness, complexity, accessibility, and external variables. This unique matching approach is anticipated to significantly impact individualized, client-centered care. We anticipate that this study will serve as a model for future development of technology matching tools for other diagnostic populations. Discussion: The Health App Review Tool was designed using available evidence and stakeholder preference data to ensure a user-centered design. The result was the development of a tool built on evidence and informed by the perceptions and preferences of those within and working with the Alzheimer's disease population. App and User domains include usefulness, complexity, accessibility, and external variables. This unique matching approach is anticipated to significantly impact individualized, client-centered care. We anticipate that this study will serve as a model for future development of technology matching tools for other diagnostic populations.

Project description:BackgroundIn recent years, the considerable increase in the number of mobile health (mHealth) apps has made health care more accessible and affordable for all. However, the exponential growth in mHealth solutions has occurred with almost no control or regulation of any kind. Despite some recent initiatives, there is still no specific regulation procedure, accreditation system, or standards to help the development of the apps, mitigate risks, or guarantee quality.ObjectiveThe main aim of this study was to propose a set of criteria for mHealth-related apps on the basis of what is available from published studies, guidelines, and standards in the various areas that are related to health app development.MethodsWe used three sources of information to identify the most important criteria. First, we conducted a systematic review of all the studies published on pain-related apps. Second, we searched for health app recommendations on the websites of professional organizations. Third, we looked for standards governing the development of software for medical devices on the specialized websites of regulatory organizations. Then, we grouped and subsumed the criteria we had identified on the basis of their shared characteristics. Finally, the comprehensibility and perceived importance of the resulting criteria were evaluated for face validity with a group of 18 stakeholders.ResultsWe identified a total of 503 criteria from all sources, which, after close analysis, were grouped into eight different categories, including 36 important criteria for health apps. The resulting categories were usability, privacy, security, appropriateness and suitability, transparency and content, safety, technical support and updates, and technology. The results of the preliminary analysis showed that the criteria were mostly understood by the group of stakeholders. In addition, they perceived all of them as important.ConclusionsThis set of criteria can help health care providers, developers, patients, and other stakeholders to guide the development of mHealth-related apps and, potentially, to measure the quality of an mHealth app.

Project description:BackgroundThe United States is currently facing a maternal morbidity and mortality crisis, with the highest rates of any resource-rich nation. In efforts to address this, new guidelines for postpartum care suggest that mobile health (mHealth) apps can help provide complementary clinical support for new mothers during the postpartum period. However, to date no study has evaluated the quality of existing mHealth tools targeted to this time period in terms of sufficiency of maternal health information, inclusivity of people of color, and app usability.MethodsPreferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards were used to review the peripartum apps from the Apple and Google Play stores in either the Health/Fitness, Medical, or Education categories. Apps were evaluated for extent and quality of maternal health information and inclusivity of people of color using an a priori coding scheme. App usability was evaluated using the Mobile Application Rating Scale (MARS) score.ResultsOf the 301 apps from the Apple and Google Play stores, 25 met criteria for final evaluation. Of the 30 maternal health topics coded for, the median number addressed by apps was 19.5 (65%). Peripartum behaviors were more frequently addressed than peripartum outpatient care topics and peripartum acute health risks. The coverage of maternal health information and inclusivity of people of color in app imagery both correlated positively with the MARS usability score of the app. Only 8 apps (32%) portrayed greater than 24% images of people of color- the percent of non-white Americans according to 2019 census estimates. There was no correlation between MARS usability score and number of app users, as estimated by number of ratings for the app available on the app store. In addition, apps with evidence-based maternal health information had greater MARS engagement, information, and aesthetics scores. However, presence of evidence-based information did not correlate with greater numbers of app users.ConclusionsCurrent commercially available peripartum apps range widely in quality. Overall current app offerings generally do not provide adequate maternal health information and are not optimally accessible to the target users in terms of inclusivity of women of color or app usability. Apps delivering evidence-based information and more usable design are more likely to meet these standards but are not more likely to be downloaded by users.

Dataset Information

Mindful Eating Mobile Health Apps: Review and Appraisal.

Background

Objective

Methods

Results

Conclusions

Publications

Mindful Eating Mobile Health Apps: Review and Appraisal.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets