scholarly journals Evaluation of Mobile Health apps for Non-Medical Cannabis Use: A Scoping Review

2022 ◽  
Vol 196 ◽  
pp. 581-589
Author(s):  
Hayat Sedrati ◽  
Zakaria Belrhiti ◽  
Chakib Nejjari ◽  
Hassan Ghazal
Keyword(s):  
Mobile Health ◽  
Scoping Review ◽  
Cannabis Use ◽  
Medical Cannabis ◽  
Health Apps ◽  
Mobile Health Apps

scholarly journals Evaluating evaluation frameworks: a scoping review of frameworks for assessing health apps

BMJ Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. e047001
Author(s):  
Sarah Lagan ◽  
Lev Sandler ◽  
John Torous
Keyword(s):  
Mobile Health ◽  
Scoping Review ◽  
Data Extraction ◽  
Evaluation Framework ◽  
Publication Date ◽  
Evaluation Tool ◽  
Eligibility Criteria ◽  
Health Apps ◽  
Mobile Health Apps ◽  
The Mind

ObjectivesDespite an estimated 300 000 mobile health apps on the market, there remains no consensus around helping patients and clinicians select safe and effective apps. In 2018, our team drew on existing evaluation frameworks to identify salient categories and create a new framework endorsed by the American Psychiatric Association (APA). We have since created a more expanded and operational framework Mhealth Index and Navigation Database (MIND) that aligns with the APA categories but includes objective and auditable questions (105). We sought to survey the existing space, conducting a review of all mobile health app evaluation frameworks published since 2018, and demonstrate the comprehensiveness of this new model by comparing it to existing and emerging frameworks.DesignWe conducted a scoping review of mobile health app evaluation frameworks.Data sourcesReferences were identified through searches of PubMed, EMBASE and PsychINFO with publication date between January 2018 and October 2020.Eligibility criteriaPapers were selected for inclusion if they meet the predetermined eligibility criteria—presenting an evaluation framework for mobile health apps with patient, clinician or end user-facing questions.Data extraction and synthesisTwo reviewers screened the literature separately and applied the inclusion criteria. The data extracted from the papers included: author and dates of publication, source affiliation, country of origin, name of framework, study design, description of framework, intended audience/user and framework scoring system. We then compiled a collection of more than 1701 questions across 79 frameworks. We compared and grouped these questions using the MIND framework as a reference. We sought to identify the most common domains of evaluation while assessing the comprehensiveness and flexibility—as well as any potential gaps—of MIND.ResultsNew app evaluation frameworks continue to emerge and expand. Since our 2019 review of the app evaluation framework space, more frameworks include questions around privacy (43) and clinical foundation (57), reflecting an increased focus on issues of app security and evidence base. The majority of mapped frameworks overlapped with at least half of the MIND categories. The results of this search have informed a database (apps.digitalpsych.org) that users can access today.ConclusionAs the number of app evaluation frameworks continues to rise, it is becoming difficult for users to select both an appropriate evaluation tool and to find an appropriate health app. This review provides a comparison of what different app evaluation frameworks are offering, where the field is converging and new priorities for improving clinical guidance.

scholarly journals PNS187 US NATIONAL TRENDS OF MOBILE HEALTH APPS USE IN 2014 AND 2018

2019 ◽  
Vol 22 ◽  
pp. S317
Author(s):  
X. Feng ◽  
T. Lavelle ◽  
P.J. Lin
Keyword(s):  
Mobile Health ◽  
Health Apps ◽  
Mobile Health Apps ◽  
National Trends

scholarly journals Mobile Health Apps for Medical Emergencies: Systematic Review

10.2196/18513 ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. e18513
Author(s):  
Alejandro Plaza Roncero ◽  
Gonçalo Marques ◽  
Beatriz Sainz-De-Abajo ◽  
Francisco Martín-Rodríguez ◽  
Carlos del Pozo Vegas ◽  
...  
Keyword(s):  
Health Care ◽  
Mobile Health ◽  
Mobile Apps ◽  
Current Status ◽  
Health Technologies ◽  
Health Apps ◽  
App Store ◽  
Mobile Health Apps ◽  
Medical Emergencies ◽  
Google Play

Background Mobile health apps are used to improve the quality of health care. These apps are changing the current scenario in health care, and their numbers are increasing. Objective We wanted to perform an analysis of the current status of mobile health technologies and apps for medical emergencies. We aimed to synthesize the existing body of knowledge to provide relevant insights for this topic. Moreover, we wanted to identify common threads and gaps to support new challenging, interesting, and relevant research directions. Methods We reviewed the main relevant papers and apps available in the literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was used in this review. The search criteria were adopted using systematic methods to select papers and apps. On one hand, a bibliographic review was carried out in different search databases to collect papers related to each application in the health emergency field using defined criteria. On the other hand, a review of mobile apps in two virtual storage platforms (Google Play Store and Apple App Store) was carried out. The Google Play Store and Apple App Store are related to the Android and iOS operating systems, respectively. Results In the literature review, 28 papers in the field of medical emergency were included. These studies were collected and selected according to established criteria. Moreover, we proposed a taxonomy using six groups of applications. In total, 324 mobile apps were found, with 192 identified in the Google Play Store and 132 identified in the Apple App Store. Conclusions We found that all apps in the Google Play Store were free, and 73 apps in the Apple App Store were paid, with the price ranging from US $0.89 to US $5.99. Moreover, 39% (11/28) of the included studies were related to warning systems for emergency services and 21% (6/28) were associated with disaster management apps.

scholarly journals Patient-Centric Structural Determinants of Adherence Rates Among Asthma Populations: Exploring the Potential of Patient Activation and Encouragement Tool TRUSTR to Improve Adherence

2020 ◽  
Vol 7 (2) ◽  
Author(s):  
Asim Zia ◽  
Arthur Brassart ◽  
Sheila Thomas ◽  
Fen Ye ◽  
Judith Stephenson ◽  
...  
Keyword(s):  
Clinical Data ◽  
Mobile Health ◽  
Medical Condition ◽  
Total Effect ◽  
Adherence Rate ◽  
Administrative Claims ◽  
Structural Determinants ◽  
Health Apps ◽  
Mobile Health Apps ◽  
Patient Centric

Background: Lack of adherence with prescribed medications among the asthma populations exacerbates health outcomes and increases social and economic costs. Objectives: The proposed study aims to model patient-centric structural determinants of adherence rates among asthma patients and explore the potential of mobile health apps such as the TRUSTR platform to improve adherence using its power of monetary and non-monetary chatbotting and non-monetary nudges. Following specific hypotheses are tested: (1) Patient attributes, such as their age and medical condition, have significant effect on their adherence with the prescribed treatment plans. (2) Behavioral nudging with rewards and engagement via mobile health apps will increase adherence rates. Methods: The patient population (N= 37 359) consists of commercially insured patients with asthma who have been identified from administrative claims in the HealthCore Integrated Research Database (HIRD) between April 1, 2018 and March 31, 2019. Two Structural Equation Models (SEMs) are estimated to quantify direct, indirect and total effect sizes of age and medical condition on proportion of days covered (PDC) and medical possession ratio (MPR), mediated by patient medical and pharmacy visits. Fourteen additional SEMs were estimated to lateralize TRUSTR findings and conduct sensitivity analysis. Results: HIRD data reveal mean adherence rate of 59% (standard deviation (SD) 29%) for PDC and 58% for MPR (SD 36%). Key structural findings from SEMs derived from the HIRD dataset indicate that each additional year in the age of the patient has a positive total effect on the adherence rate. Patients with poor medical condition are likely to have lower adherence rate, but this direct effect is countered by mediating variables. Further, each additional reward and higher engagement with a mobile app is likely to have a positive total effect on increasing the adherence rate. Conclusions: HIRD data reveal mean adherence rate of 59% (SD 29%), providing the evidence for the opportunity to increase adherence rate by around 40%. Statistical modeling results reveal structural determinants, such as the opportunity to nudge, are higher among younger patients, as they have higher probability of being non-adherent. Methodologically, lateralization approach demonstrates the potential to capture real-world evidence beyond clinical data and merge it with clinical data.

Abstract 13206: Blood Pressure Apps: Do They Educate the Lay Public About Risk Factors?

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Arunima Vijay ◽  
Gloria Wu
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Mobile Health ◽  
Health Apps ◽  
Hypertension Risk ◽  
Apple Ios ◽  
Mobile Health Apps ◽  
Google Play ◽  
Lay Public ◽  
Mood Depression

Introduction: Hypertension affects 108 million Americans. To help track and manage hypertension, there are many free and popular mobile health apps that track BP. Hypothesis: BP tracking mobile health apps have many downloads but do not fully educate the public about hypertension risk factors. Methods: “Blood Pressure” as a search term was used in the Google Play and Apple iOS stores to identify the most popular, free BP tracking apps aimed at the lay public. The top 10 most popular, free apps on each store were evaluated for educating the lay public on hypertension risk factors. Inclusion criteria: top 10 free blood pressure (BP) apps, by highest number of downloads on Google Play and highest rating (out of five stars) on Apple iOS Store (no available data on iOS downloads). Exclusion criteria: non-English, requiring a wearable device, primary purpose other BP tracking. Results: Of top 20 apps: BP log: 19/20, BP ranges: 13/20, height: 5/20, weight: 8/20, BMI: 3/20, race: 1/20, gender: 4/20, age: 6/20, diet: 1/20, exercise: 1/20, medication: 4/20, diabetes: 1/20, FBS: 1/20, goals: 3/20, mood/depression: 1/20. 2 apps mentioned the American Heart Association (AHA). None of the apps had information on cvriskcalculator.com, family history, cholesterol, LDL, triglycerides, HbA1c, and alcohol use. Conclusion: Most free and popular BP apps monitor BP but largely ignore hypertension risk factors such as cholesterol, LDL, triglycerides, alcohol intake, mood/depression, race, and gender. Furthermore, 7/20 apps do not uniformly educate patients that a normal BP is <120/<80, in accordance with the AHA and ACC guidelines. More collaboration may be needed between physicians and software developers to educate and meet the needs of our hypertensive patients in America.

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