scholarly journals Mobile Health Apps That Help With COVID-19 Management: Scoping Review

JMIR Nursing ◽  
10.2196/20596 ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. e20596 ◽  
Author(s):  
Hanson John Leon Singh ◽  
Danielle Couch ◽  
Kevin Yap
Keyword(s):  
Mobile Health ◽  
Mobile Apps ◽  
Information Provision ◽  
Evidence Base ◽  
Contact Tracing ◽  
Symptom Monitoring ◽  
Scoping Reviews ◽  
Meta Analyses ◽  
Google Search ◽  
Mhealth Apps

Background Mobile health (mHealth) apps have played an important role in mitigating the coronavirus disease (COVID-19) response. However, there is no resource that provides a holistic picture of the available mHealth apps that have been developed to combat this pandemic. Objective Our aim is to scope the evidence base on apps that were developed in response to COVID-19. Methods Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for scoping reviews, literature searches were conducted on Google Search, Google Scholar, and PubMed using the country’s name as keywords and “coronavirus,” “COVID-19,” “nCOV19,” “contact tracing,” “information providing apps,” “symptom tracking,” “mobile apps,” “mobile applications,” “smartphone,” “mobile phone,” and “mHealth.” Countries most affected by COVID-19 and those that first rolled out COVID-19–related apps were included. Results A total of 46 articles were reviewed from 19 countries, resulting in a total of 29 apps. Among them, 15 (52%) apps were on contact tracing, 7 (24%) apps on quarantine, 7 (24%) on symptom monitoring, and 1 (3%) on information provision. More than half (n=20, 69%) were from governmental sources, only 3 (10%) were from private organizations, and 3 (10%) from universities. There were 6 (21%) apps available on either Android or iOS, and 10 (34%) were available on both platforms. Bluetooth was used in 10 (34%) apps for collecting data, 12 (41%) apps used GPS, and 12 (41%) used other forms of data collection. Conclusions This review identifies that the majority of COVID-19 apps were for contact tracing and symptom monitoring. However, these apps are effective only if taken up by the community. The sharing of good practices across different countries can enable governments to learn from each other and develop effective strategies to combat and manage this pandemic.

scholarly journals Mobile Health Apps That Help With COVID-19 Management: Scoping Review (Preprint)

2020 ◽  
Author(s):  
Hanson John Leon Singh ◽  
Danielle Couch ◽  
Kevin Yap
Keyword(s):  
Mobile Health ◽  
Mobile Apps ◽  
Information Provision ◽  
Evidence Base ◽  
Contact Tracing ◽  
Symptom Monitoring ◽  
Scoping Reviews ◽  
Meta Analyses ◽  
Google Search ◽  
Mhealth Apps

BACKGROUND Mobile health (mHealth) apps have played an important role in mitigating the coronavirus disease (COVID-19) response. However, there is no resource that provides a holistic picture of the available mHealth apps that have been developed to combat this pandemic. OBJECTIVE Our aim is to scope the evidence base on apps that were developed in response to COVID-19. METHODS Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for scoping reviews, literature searches were conducted on Google Search, Google Scholar, and PubMed using the country’s name as keywords and “coronavirus,” “COVID-19,” “nCOV19,” “contact tracing,” “information providing apps,” “symptom tracking,” “mobile apps,” “mobile applications,” “smartphone,” “mobile phone,” and “mHealth.” Countries most affected by COVID-19 and those that first rolled out COVID-19–related apps were included. RESULTS A total of 46 articles were reviewed from 19 countries, resulting in a total of 29 apps. Among them, 15 (52%) apps were on contact tracing, 7 (24%) apps on quarantine, 7 (24%) on symptom monitoring, and 1 (3%) on information provision. More than half (n=20, 69%) were from governmental sources, only 3 (10%) were from private organizations, and 3 (10%) from universities. There were 6 (21%) apps available on either Android or iOS, and 10 (34%) were available on both platforms. Bluetooth was used in 10 (34%) apps for collecting data, 12 (41%) apps used GPS, and 12 (41%) used other forms of data collection. CONCLUSIONS This review identifies that the majority of COVID-19 apps were for contact tracing and symptom monitoring. However, these apps are effective only if taken up by the community. The sharing of good practices across different countries can enable governments to learn from each other and develop effective strategies to combat and manage this pandemic.

scholarly journals Elements of Social Convoy Theory in Mobile Health for Palliative Care: Scoping Review

10.2196/16060 ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. e16060 ◽  
Author(s):  
Jennifer D Portz ◽  
Kira Elsbernd ◽  
Evan Plys ◽  
Kelsey Lynett Ford ◽  
Xuhong Zhang ◽  
...  
Keyword(s):  
Palliative Care ◽  
Family Support ◽  
Mobile Health ◽  
Scoping Review ◽  
Family Caregiving ◽  
Mobile Apps ◽  
Team Approach ◽  
Diverse Backgrounds ◽  
Meta Analyses ◽  
Patient Use

Background Mobile health (mHealth) provides a unique modality for improving access to and awareness of palliative care among patients, families, and caregivers from diverse backgrounds. Some mHealth palliative care apps exist, both commercially available and established by academic researchers. However, the elements of family support and family caregiving tools offered by these early apps is unknown. Objective The objective of this scoping review was to use social convoy theory to describe the inclusion and functionality of family, social relationships, and caregivers in palliative care mobile apps. Methods Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Review guidelines, a systematic search of palliative care mHealth included (1) research-based mobile apps identified from academic searches published between January 1, 2010, and March 31, 2019 and (2) commercially available apps for app stores in April 2019. Two reviewers independently assessed abstracts, app titles, and descriptions against the inclusion and exclusion criteria. Abstracted data covered app name, research team or developer, palliative care element, target audience, and features for family support and caregiving functionality as defined by social convoy theory. Results Overall, 10 articles describing 9 individual research-based apps and 22 commercially available apps were identified. Commercially available apps were most commonly designed for both patients and social convoys, whereas the majority of research apps were designed for patient use only. Conclusions Results suggest there is an emerging presence of apps for patients and social convoys receiving palliative care; however, there are many needs for developers and researchers to address in the future. Although palliative care mHealth is a growing field, additional research is needed for apps that embrace a team approach to information sharing, target family- and caregiver-specific issues, promote access to palliative care, and are comprehensive of palliative needs.

Traumatic Brain Injury in Young Children: A Scoping Review

2020 ◽  
Vol 41 (02) ◽  
pp. 125-142
Author(s):  
Jessica Salley ◽  
Libby Crook ◽  
Angela Ciccia ◽  
Juliet Haarbauer-Krupa ◽  
Jennifer P. Lundine
Keyword(s):  
Traumatic Brain Injury ◽  
Early Childhood ◽  
Brain Injury ◽  
Young Children ◽  
Scoping Review ◽  
Evidence Base ◽  
Contributing Factors ◽  
Rigorous Research ◽  
Scoping Reviews ◽  
Meta Analyses

AbstractTo review the evidence available on early childhood (i.e., 0–5 years 11 months) traumatic brain injury (TBI) and identify clinical implications and future directions for speech-language pathology (SLP) practice and research, a scoping review of the literature was conducted following the 2018 Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRSIMA-ScR) guidelines. A total of 44 peer-reviewed articles were included for review. Included studies were assigned one or more of the following thematic labels related to early childhood TBI: etiology, assessment, treatment, outcomes, contributing factors. Most of the studies were nonexperimental studies and addressed outcomes following early childhood TBI. We conclude, based on this scoping review, that children who experience a TBI before 6 years of age are at risk for persistent long-term difficulties in academic and social functioning. SLPs are among the group of clinicians most appropriate to assess and treat these children; yet, the evidence for assessment, treatment, and identification of factors contributing to the recovery of young children with TBI is particularly lacking. Rigorous research is needed to improve the evidence base for SLPs.

Mobile health (mHealth) for headache disorders: A review of the evidence base

2016 ◽  
Vol 22 (8) ◽  
pp. 472-477 ◽  
Author(s):  
Mahsa Mosadeghi-Nik ◽  
Marzyeh S Askari ◽  
Farhad Fatehi
Keyword(s):  
Mobile Health ◽  
Mobile Apps ◽  
Evidence Base ◽  
Headache Disorders ◽  
Trigger Factors ◽  
Clinical Safety ◽  
Hierarchy Of Evidence ◽  
Mobile Health Applications ◽  
Conference Papers

The aim of this review was to explore and summarise the evidence base for using mobile apps for the management of headache disorders. PubMed, Web of Science, Embase and Scopus were searched for studies reporting the use of mobile health applications (apps) for managing headache disorders. Different combinations of keywords for mobile health, smartphone and headache were used for electronic search. Six studies (two journal papers and four conference papers) met the inclusion criteria and were reviewed. All of the reviewed studies were categorised as the lowest level (level IV) of evidence according to the National Health and Medical Research Council (NHMRC) hierarchy of evidence. The results of the studies demonstrated the feasibility and acceptability of a few mobile apps for headache in very limited settings, and indicated that these apps can be effective tools for identifying trigger factors of migraine, improving self-management of headache disorders, and mediating the interactions between headache sufferers and their treating doctors. The role of participatory research and involvement of patients and clinicians in the development of such apps was also highlighted. Despite the availability of numerous mobile apps for headache disorders, the evidence base to support their effectiveness and clinical safety is very weak. The current literature indicates that mobile apps have the potential for improving the care of headache sufferers, but this is yet to be proven by adequately designed studies.

scholarly journals Usability of Mobile Health Apps for Postoperative Care: Systematic Review

10.2196/19099 ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. e19099
Author(s):  
Ben Patel ◽  
Arron Thind
Keyword(s):  
Systematic Review ◽  
Systematic Reviews ◽  
Mobile Health ◽  
Conflicts Of Interest ◽  
Data Extraction ◽  
Measurement Tool ◽  
Validated Questionnaire ◽  
System Usability Scale ◽  
Meta Analyses ◽  
Mhealth Apps

Background Mobile health (mHealth) apps are increasingly used postoperatively to monitor, educate, and rehabilitate. The usability of mHealth apps is critical to their implementation. Objective This systematic review evaluates the (1) methodology of usability analyses, (2) domains of usability being assessed, and (3) results of usability analyses. Methods The A Measurement Tool to Assess Systematic Reviews checklist was consulted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guideline was adhered to. Screening was undertaken by 2 independent reviewers. All included studies were assessed for risk of bias. Domains of usability were compared with the gold-standard mHealth App Usability Questionnaire (MAUQ). Results A total of 33 of 720 identified studies were included for data extraction. Of the 5 included randomized controlled trials (RCTs), usability was never the primary end point. Methodology of usability analyses included interview (10/33), self-created questionnaire (18/33), and validated questionnaire (9/33). Of the 3 domains of usability proposed in the MAUQ, satisfaction was assessed in 28 of the 33 studies, system information arrangement was assessed in 11 of the 33 studies, and usefulness was assessed in 18 of the 33 studies. Usability of mHealth apps was above industry average, with median System Usability Scale scores ranging from 76 to 95 out of 100. Conclusions Current analyses of mHealth app usability are substandard. RCTs are rare, and validated questionnaires are infrequently consulted. Of the 3 domains of usability, only satisfaction is regularly assessed. There is significant bias throughout the literature, particularly with regards to conflicts of interest. Future studies should adhere to the MAUQ to assess usability and improve the utility of mHealth apps.

scholarly journals Usability of Mobile Health Apps for Postoperative Care: Systematic Review (Preprint)

2020 ◽  
Author(s):  
Ben Patel ◽  
Arron Thind
Keyword(s):  
Systematic Review ◽  
Systematic Reviews ◽  
Mobile Health ◽  
Conflicts Of Interest ◽  
Data Extraction ◽  
Measurement Tool ◽  
Validated Questionnaire ◽  
System Usability Scale ◽  
Meta Analyses ◽  
Mhealth Apps

BACKGROUND Mobile health (mHealth) apps are increasingly used postoperatively to monitor, educate, and rehabilitate. The usability of mHealth apps is critical to their implementation. OBJECTIVE This systematic review evaluates the (1) methodology of usability analyses, (2) domains of usability being assessed, and (3) results of usability analyses. METHODS The A Measurement Tool to Assess Systematic Reviews checklist was consulted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guideline was adhered to. Screening was undertaken by 2 independent reviewers. All included studies were assessed for risk of bias. Domains of usability were compared with the gold-standard mHealth App Usability Questionnaire (MAUQ). RESULTS A total of 33 of 720 identified studies were included for data extraction. Of the 5 included randomized controlled trials (RCTs), usability was never the primary end point. Methodology of usability analyses included interview (10/33), self-created questionnaire (18/33), and validated questionnaire (9/33). Of the 3 domains of usability proposed in the MAUQ, satisfaction was assessed in 28 of the 33 studies, system information arrangement was assessed in 11 of the 33 studies, and usefulness was assessed in 18 of the 33 studies. Usability of mHealth apps was above industry average, with median System Usability Scale scores ranging from 76 to 95 out of 100. CONCLUSIONS Current analyses of mHealth app usability are substandard. RCTs are rare, and validated questionnaires are infrequently consulted. Of the 3 domains of usability, only satisfaction is regularly assessed. There is significant bias throughout the literature, particularly with regards to conflicts of interest. Future studies should adhere to the MAUQ to assess usability and improve the utility of mHealth apps.

scholarly journals Goldilocks and the Three Bears: A Just-Right Hybrid Model to Synthesize the Growing Landscape of Publicly Available Health-Related Mobile Apps (Preprint)

2021 ◽  
Author(s):  
Nancy Lau ◽  
Alison O'Daffer ◽  
Joyce Yi-Frazier ◽  
Abby R Rosenberg
Keyword(s):  
Hybrid Model ◽  
Mobile Apps ◽  
Evidence Base ◽  
Mobile App ◽  
Essential Question ◽  
Health Related ◽  
Rapid Pace ◽  
Research Standards ◽  
State Of The Science ◽  
Mhealth Apps

UNSTRUCTURED Mobile health (mHealth) technologies have provided an innovative platform for the deployment of health care diagnostics, symptom monitoring, and prevention and intervention programs. Such health-related smartphone apps are universally accepted by patients and providers with over 50 million users worldwide. Despite the rise in popularity and accessibility among consumers, the evidence base in support of health-related apps has fallen well behind the rapid pace of industry development. To bridge this evidence gap, researchers are beginning to consider how to best apply evidence-based research standards to the systematic synthesis of the mHealth consumer market. In this viewpoint, we argue for the adoption of a “hybrid model” that combines a traditional systematic review with a systematic search of mobile app download platforms for health sciences researchers interested in synthesizing the state of the science of consumer apps. This approach, which we have successfully executed in a recent review, maximizes the benefits of traditional and novel approaches to address the essential question of whether popular consumer mHealth apps work.

Systematic Review of Mobile Applications to Monitor Symptoms of COVID-19 Using the Mobile Application Rating Scale (Preprint)

2022 ◽  
Author(s):  
Suzanna Schmeelk ◽  
Alison Davis ◽  
Qiaozheng Li ◽  
Caroline Shippey ◽  
Michelle Utah ◽  
...  
Keyword(s):  
Systematic Review ◽  
Mobile Application ◽  
Rating Scale ◽  
Mobile Apps ◽  
World Health ◽  
Symptom Monitoring ◽  
Difficulty Breathing ◽  
Health Organization ◽  
Mhealth Apps

BACKGROUND Monitoring acute and long-term symptoms of COVID-19 is critical for personal and public health. Mobile health (mHealth) applications (apps) can be used to support symptom monitoring at the point of need for patients with COVID-19. OBJECTIVE To systematically review and evaluate mHealth apps for quality, functionality, and consistency with guidelines for monitoring symptoms of COVID-19. METHODS We conducted a systematic review of apps for COVID-19 symptom monitoring by searching in two major app stores. The final apps were independently assessed using the Mobile Application Rating Scale (MARS), IMS Institute for Healthcare Informatics functionality score, and guidelines from the Center for Disease Control and World Health Organization. Interrater reliability between the reviewers was calculated. RESULTS A total of 1,017 mobile apps were reviewed and 20 met the inclusion criteria. The majority of the apps (90%, n=18) were designed to track acute COVID-19 symptoms, and only two addressed long-term symptoms. Overall, the apps scored high on quality, with an overall MARS rating of 3.94. The most common functionality among all apps was the instruct function (95%, n=19). The most common symptoms included in the apps for tracking were: fever and dry cough (n=18), aches and pains (n=17), difficulty breathing (n=17), tiredness, sore throat, headache, loss of taste, or smell (n=16), and diarrhea (n=15). CONCLUSIONS mHealth apps designed to monitor symptoms of COVID-19 had high quality, but the majority of apps focused almost exclusively on acute symptoms. Future apps should also incorporate monitoring long-term symptoms of COVID-19. CLINICALTRIAL N/A

scholarly journals Assessment of the Fairness of Privacy Policies of Mobile Health Apps: Scale Development and Evaluation in Cancer Apps (Preprint)

2019 ◽  
Author(s):  
Jaime Benjumea ◽  
Jorge Ropero ◽  
Octavio Rivera-Romero ◽  
Enrique Dorronzoro-Zubiete ◽  
Alejandro Carrasco
Keyword(s):  
Mobile Health ◽  
Mobile Apps ◽  
Privacy Policies ◽  
Sensitive Data ◽  
General Data Protection Regulation ◽  
Android Apps ◽  
Mobile Health Apps ◽  
General Data ◽  
Adjusted Scores ◽  
Mhealth Apps

BACKGROUND Cancer patients are increasingly using mobile health (mHealth) apps to take control of their health. Many studies have explored their efficiency, content, usability, and adherence; however, these apps have created a new set of privacy challenges, as they store personal and sensitive data. OBJECTIVE The purpose of this study was to refine and evaluate a scale based on the General Data Protection Regulation and assess the fairness of privacy policies of mHealth apps. METHODS Based on the experience gained from our previous work, we redefined some of the items and scores of our privacy scale. Using the new version of our scale, we conducted a case study in which we analyzed the privacy policies of cancer Android apps. A systematic search of cancer mobile apps was performed in the Spanish version of the Google Play website. RESULTS The redefinition of certain items reduced discrepancies between reviewers. Thus, use of the scale was made easier, not only for the reviewers but also for any other potential users of our scale. Assessment of the privacy policies revealed that 29% (9/31) of the apps included in the study did not have a privacy policy, 32% (10/31) had a score over 50 out of a maximum of 100 points, and 39% (12/31) scored fewer than 50 points. CONCLUSIONS In this paper, we present a scale for the assessment of mHealth apps that is an improved version of our previous scale with adjusted scores. The results showed a lack of fairness in the mHealth app privacy policies that we examined, and the scale provides developers with a tool to evaluate their privacy policies.

scholarly journals Evaluation of Two Mobile Health Apps in the Context of Smoking Cessation: Qualitative Study of Cognitive Behavioral Therapy (CBT) Versus Non-CBT-Based Digital Solutions (Preprint)

2017 ◽  
Author(s):  
Carina Tudor-Sfetea ◽  
Riham Rabee ◽  
Muhammad Najim ◽  
Nima Amin ◽  
Mehak Chadha ◽  
...  
Keyword(s):  
Mental Health ◽  
Smoking Cessation ◽  
Health Behavior ◽  
Mobile Health ◽  
Thematic Analysis ◽  
Behavioral Change ◽  
Behavioral Therapy ◽  
Health Behavior Change ◽  
Evidence Base ◽  
Mhealth Apps

BACKGROUND Mobile health (mHealth) apps can offer users numerous benefits, representing a feasible and acceptable means of administering health interventions such as cognitive behavioral therapy (CBT). CBT is commonly used in the treatment of mental health conditions, where it has a strong evidence base, suggesting that it represents an effective method to elicit health behavior change. More importantly, CBT has proved to be effective in smoking cessation, in the context of smoking-related costs to the National Health Service (NHS) having been estimated to be as high as £2.6bn in 2015. Although the evidence base for computerized CBT in mental health is strong, there is limited literature on its use in smoking cessation. This, combined with the cost-effectiveness of mHealth interventions, advocates a need for research into the effectiveness of CBT-based smoking cessation apps. OBJECTIVE The objective of this study was, first, to explore participants’ perceptions of 2 mHealth apps, a CBT-based app, Quit Genius, and a non-CBT-based app, NHS Smokefree, over a variety of themes. Second, the study aimed to investigate the perceptions and health behavior of users of each app with respect to smoking cessation. METHODS A qualitative short-term longitudinal study was conducted, using a sample of 29 smokers allocated to one of the 2 apps, Quit Genius or Smokefree. Each user underwent 2 one-to-one semistructured interviews, 1 week apart. Thematic analysis was carried out, and important themes were identified. Descriptive statistics regarding participants’ perceptions and health behavior in relation to smoking cessation are also provided. RESULTS The thematic analysis resulted in five higher themes and several subthemes. Participants were generally more positive about Quit Genius’s features, as well as about its design and information engagement and quality. Quit Genius users reported increased motivation to quit smoking, as well as greater willingness to continue using their allocated app after 1 week. Moreover, these participants demonstrated preliminary changes in their smoking behavior, although this was in the context of our limited sample, not yet allowing for the finding to be generalizable. CONCLUSIONS Our findings underscore the use of CBT in the context of mHealth apps as a feasible and potentially effective smoking cessation tool. mHealth apps must be well developed, preferably with an underlying behavioral change mechanism, to promote positive health behavior change. Digital CBT has the potential to become a powerful tool in overcoming current health care challenges. The present results should be replicated in a wider sample using the apps for a longer period so as to allow for generalizability. Further research is also needed to focus on the effect of greater personalization on behavioral change and on understanding the psychological barriers to the adoption of new mHealth solutions.

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