Is mobile health all peer pressure? The influence of mass media exposure on the motivation to use mobile health apps

2016 ◽  
Vol 23 (6) ◽  
pp. 565-586 ◽  
Author(s):  
Min-Woo Kwon ◽  
Kwansik Mun ◽  
Jin Kyun Lee ◽  
Douglas M McLeod ◽  
Jonathan D’Angelo
Keyword(s):  
Interpersonal Communication ◽  
Mobile Health ◽  
Media Exposure ◽  
Peer Pressure ◽  
Motivational Factors ◽  
Future Research ◽  
Health Apps ◽  
Communication Devices ◽  
Mobile Health Apps ◽  
Effects Of Media

In recent years, the spread of mobile communication devices such as smartphones has been markedly rapid. With this technological diffusion, mobile health (mHealth) has become an increasingly important issue. In particular, there is an increasing interest in smartphone apps improving public health. Although there is increased availability of mobile devices and health apps, little is known about motivational factors predicting health app adoption and use. The aim of this study was to identify motivational factors that predict the adoption and use of health apps (i.e. health app engagement). To identify the motivational factors, 391 college students were surveyed and survey questions considered the effects of media exposure to health information, interpersonal communication on health issues, and psychological factors (e.g. attitude, usefulness, peer norm, and self-efficacy) on health app engagement. Our results confirm the effect of attitude ( β = 0.36) and usefulness are ( β = 0.33) on mHealth App usage. Furthermore, we found that age ( β = 0.11) and reading news articles about health ( β = 0.13) predict mHealth App usage. Theoretical and practical implications and suggestions for future research are discussed.

scholarly journals Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis

10.2196/18212 ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. e18212
Author(s):  
Cheng Peng ◽  
Miao He ◽  
Sarah L Cutrona ◽  
Catarina I Kiefe ◽  
Feifan Liu ◽  
...  
Keyword(s):  
Bibliometric Analysis ◽  
San Francisco ◽  
Mobile Health ◽  
System Development ◽  
Descriptive Analysis ◽  
The United States ◽  
Future Research ◽  
Health Apps ◽  
Mobile Health Apps ◽  
The University

Background Due to the widespread and unprecedented popularity of mobile phones, the use of digital medicine and mobile health apps has seen significant growth. Mobile health apps have tremendous potential for monitoring and treating diseases, improving patient care, and promoting health. Objective This paper aims to explore research trends, coauthorship networks, and the research hot spots of mobile health app research. Methods Publications related to mobile health apps were retrieved and extracted from the Web of Science database with no language restrictions. Bibliographic Item Co-Occurrence Matrix Builder was employed to extract bibliographic information (publication year and journal source) and perform a descriptive analysis. We then used the VOSviewer (Leiden University) tool to construct and visualize the co-occurrence networks of researchers, research institutions, countries/regions, citations, and keywords. Results We retrieved 2802 research papers on mobile health apps published from 2000 to 2019. The number of annual publications increased over the past 19 years. JMIR mHealth and uHealth (323/2802, 11.53%), Journal of Medical Internet Research (106/2802, 3.78%), and JMIR Research Protocols (82/2802, 2.93%) were the most common journals for these publications. The United States (1186/2802, 42.33%), England (235/2802, 8.39%), Australia (215/2802, 7.67%), and Canada (112/2802, 4.00%) were the most productive countries of origin. The University of California San Francisco, the University of Washington, and the University of Toronto were the most productive institutions. As for the authors’ contributions, Schnall R, Kuhn E, Lopez-Coronado M, and Kim J were the most active researchers. The co-occurrence cluster analysis of the top 100 keywords forms 5 clusters: (1) the technology and system development of mobile health apps; (2) mobile health apps for mental health; (3) mobile health apps in telemedicine, chronic disease, and medication adherence management; (4) mobile health apps in health behavior and health promotion; and (5) mobile health apps in disease prevention via the internet. Conclusions We summarize the recent advances in mobile health app research and shed light on their research frontier, trends, and hot topics through bibliometric analysis and network visualization. These findings may provide valuable guidance on future research directions and perspectives in this rapidly developing field.

scholarly journals Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis (Preprint)

2020 ◽  
Author(s):  
Cheng Peng ◽  
Miao He ◽  
Sarah L Cutrona ◽  
Catarina I Kiefe ◽  
Feifan Liu ◽  
...  
Keyword(s):  
Bibliometric Analysis ◽  
San Francisco ◽  
Mobile Health ◽  
System Development ◽  
Descriptive Analysis ◽  
The United States ◽  
Future Research ◽  
Health Apps ◽  
Mobile Health Apps ◽  
The University

BACKGROUND Due to the widespread and unprecedented popularity of mobile phones, the use of digital medicine and mobile health apps has seen significant growth. Mobile health apps have tremendous potential for monitoring and treating diseases, improving patient care, and promoting health. OBJECTIVE This paper aims to explore research trends, coauthorship networks, and the research hot spots of mobile health app research. METHODS Publications related to mobile health apps were retrieved and extracted from the Web of Science database with no language restrictions. Bibliographic Item Co-Occurrence Matrix Builder was employed to extract bibliographic information (publication year and journal source) and perform a descriptive analysis. We then used the VOSviewer (Leiden University) tool to construct and visualize the co-occurrence networks of researchers, research institutions, countries/regions, citations, and keywords. RESULTS We retrieved 2802 research papers on mobile health apps published from 2000 to 2019. The number of annual publications increased over the past 19 years. <i>JMIR mHealth and uHealth</i> (323/2802, 11.53%), <i>Journal of Medical Internet Research</i> (106/2802, 3.78%), and <i>JMIR Research Protocols</i> (82/2802, 2.93%) were the most common journals for these publications. The United States (1186/2802, 42.33%), England (235/2802, 8.39%), Australia (215/2802, 7.67%), and Canada (112/2802, 4.00%) were the most productive countries of origin. The University of California San Francisco, the University of Washington, and the University of Toronto were the most productive institutions. As for the authors’ contributions, Schnall R, Kuhn E, Lopez-Coronado M, and Kim J were the most active researchers. The co-occurrence cluster analysis of the top 100 keywords forms 5 clusters: (1) the technology and system development of mobile health apps; (2) mobile health apps for mental health; (3) mobile health apps in telemedicine, chronic disease, and medication adherence management; (4) mobile health apps in health behavior and health promotion; and (5) mobile health apps in disease prevention via the internet. CONCLUSIONS We summarize the recent advances in mobile health app research and shed light on their research frontier, trends, and hot topics through bibliometric analysis and network visualization. These findings may provide valuable guidance on future research directions and perspectives in this rapidly developing field.

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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