Mobile applications and patient education: Are currently available GERD mobile apps sufficient?

2016 ◽  
Vol 127 (8) ◽  
pp. 1775-1779 ◽  
Author(s):  
Michael Bobian ◽  
Aron Kandinov ◽  
Nour El-Kashlan ◽  
Peter F. Svider ◽  
Adam J. Folbe ◽  
...  
Keyword(s):  
Patient Education ◽  
Mobile Applications ◽  
Mobile Apps

Mobile Applications for Health Management of Older Adults: A Scoping Review (Preprint)

2020 ◽  
Author(s):  
Nurul Asilah Ahmad ◽  
Shahrul Azman Mohd Noah ◽  
Arimi Fitri Mat Ludin ◽  
Suzana Shahar ◽  
Noorlaili Mohd Tohit
Keyword(s):  
Older Adults ◽  
Goal Setting ◽  
Mobile Applications ◽  
Health Management ◽  
Mobile Apps ◽  
Personalized Feedback ◽  
Self Monitoring ◽  
App Store ◽  
Evidenced Based ◽  
Google Play

BACKGROUND Currently, the use of smartphones to deliver health-related content has experienced a rapid growth, with more than 165,000 mobile health (mHealth) applications currently available in the digital marketplace such as iOS store and Google Play. Among these, there are several mobile applications (mobile apps) that offer tools for disease prevention and management among older generations. These mobile apps could potentially promote health behaviors which will reduce or delay the onset of disease. However, no review to date that has focused on the app marketplace specific for older adults and little is known regarding its evidence-based quality towards the health of older adults. OBJECTIVE The aim of this review was to characterize and critically appraise the content and functionality of mobile apps that focuses on health management and/or healthy lifestyle among older adults. METHODS An electronic search was conducted between May 2019 to December 2019 of the official app store for two major smartphone operating systems: iPhone operating system (iTunes App Store) and Android (Google Play Store). Stores were searched separately using predetermined search terms. Two authors screened apps based on information provided in the app description. Metadata from all included apps were abstracted into a standard assessment criteria form. Evidenced based strategies and health care expert involvement of included apps was assessed. Evidenced based strategies included: self-monitoring, goal setting, physical activity support, healthy eating support, weight and/or health assessment, personalized feedback, motivational strategies, cognitive training and social support. Two authors verified the data with reference to the apps and downloaded app themselves. RESULTS A total of 16 apps met the inclusion criteria. Six out of 16 (37.5%) apps were designed exclusively for the iOS platform while ten out of 16 (62.5%) were designed for Android platform exclusively. Physical activity component was the most common feature offered in all the apps (9/16, 56.3%) and followed by cognitive training (8/16, 50.0%). Diet/nutrition (0/16, 0%) feature, however, was not offered on all reviewed mobile apps. Of reviewed apps, 56.3% (9/16) provide education, 37.5% (6/16) provide self-monitoring features, 18.8% (3/16) provide goal setting features, 18.5% (3/16) provide personalized feedback, 6.3% (1/16) provide social support and none of the reviewed apps offers heart rate monitoring and reminder features to the users. CONCLUSIONS All reviewed mobile apps for older adults in managing health did not focused on diet/nutrition component, lack of functional components and lack of health care professional involvement in their development process. There is also a need to carry out scientific testing prior to the development of the app to ensure cost effective and its health benefits to older adults. Collaborative efforts between developers, researchers, health professionals and patients are needed in developing evidence-based, high quality mobile apps in managing health prior they are made available in the app store.

Assessment and Prediction of Privacy Concerns on Health Apps (Preprint)

2020 ◽  
Author(s):  
Reham AlTamime ◽  
Vincent Marmion ◽  
Wendy Hall
Keyword(s):  
Data Sharing ◽  
Mobile Applications ◽  
Retention Rate ◽  
Mobile Apps ◽  
Third Party ◽  
Privacy Concerns ◽  
Health Apps ◽  
Mobile Health Apps ◽  
Specific Factors ◽  
And Control

BACKGROUND Mobile apps and IoT-enabled smartphones technologies facilitate collecting, sharing, and inferring from a vast amount of data about individuals’ location, health conditions, mobility status, and other factors. The use of such technology highlights the importance of understanding individuals’ privacy concerns to design applications that integrate their privacy expectations and requirements. OBJECTIVE This paper explores, assesses, and predicts individuals’ privacy concerns in relation to collecting and disclosing data on mobile health apps. METHODS We designed a questionnaire to identify participants’ privacy concerns pertaining to a set of 432 mobile apps’ data collection and sharing scenarios. Participants were presented with 27 scenarios that varied across three categorical factors: (1) type of data collected (e.g. health, demographic, behavioral, and location); (2) data sharing (e.g., whether it is shared, and for what purpose); and, (3) retention rate (e.g., forever, until the purpose is satisfied, unspecified, week, or year). RESULTS Our findings show that type of data, data sharing, and retention rate are all factors that affect individuals’ privacy concerns. However, specific factors such as collecting and disclosing health data to a third-party tracker play a larger role than other factors in triggering privacy concerns. CONCLUSIONS Our findings suggest that it is possible to predict privacy concerns based on these three factors. We propose design approaches that can improve users’ awareness and control of their data on mobile applications

Predictors to use mobile apps for monitoring COVID-19 symptoms and contact tracing: A survey among Dutch citizens. (Preprint)

2021 ◽  
Author(s):  
Stephanie Maria Jansen-Kosterink ◽  
Marian Hurmuz ◽  
Marjolein den Ouden ◽  
Lex van Velsen
Keyword(s):  
Mobile Applications ◽  
Mobile Application ◽  
Online Survey ◽  
Reproduction Number ◽  
Mobile Apps ◽  
Contact Tracing ◽  
Snowball Sampling ◽  
Final Model ◽  
Symptom Recognition ◽  
Personal Connections

UNSTRUCTURED Background: eHealth applications have been recognized as a valuable tool to reduce COVID-19’s effective reproduction number. In this paper, we report on an online survey among Dutch citizens with the goal to identify antecedents of acceptance of a mobile application for COVID-19 symptom recognition and monitoring, and a mobile application for contact tracing. Methods: Next to the demographics, the online survey contained questions focussing on perceived health, fear of COVID-19 and intention to use. We used snowball sampling via posts on social media and personal connections. To identify antecedents of acceptance of the two mobile applications we conducted multiple linear regression analyses. Results: In total, 238 Dutch adults completed the survey. Almost 60% of the responders were female and the average age was 45.6 years (SD±17.4). For the symptom app, the final model included the predictors age, attitude towards technology and fear of COVID-19. The model had an R2 of 0.141. The final model for the tracing app included the same predictors and had an R2 of 0.156. The main reason to use both mobile applications was to control the spread of the COVID-19 virus. Concerns about privacy was mentioned as the main reason not to use the mobile applications. Conclusion: Age, attitude towards technology and fear of COVID-19 are important predictors of the acceptance of COVID-19 mobile applications for symptom recognition and monitoring and for contact tracing. These predictors should be taken into account during the development and implementation of these mobile applications to secure acceptance. Discussion: Age, attitude towards technology and fear of COVID-19 are important predictors of the acceptance of COVID-19 mobile applications for symptom recognition and monitoring and for contact tracing. These predictors should be taken into account during the development and implementation of these mobile applications to secure acceptance. Age, attitude towards technology and fear of COVID-19 are important predictors of the acceptance of COVID-19 mobile applications for symptom recognition and monitoring and for contact tracing. These predictors should be taken into account during the development and implementation of these mobile applications to secure acceptance.

A review of vocabulary learning applications: From the aspects of cognitive approaches, multimedia input, learning materials, and game elements

2021 ◽  
pp. 250-272
Keyword(s):  
Foreign Language ◽  
Mobile Applications ◽  
Mobile Apps ◽  
Vocabulary Learning ◽  
Word Knowledge ◽  
Learning Approach ◽  
Feedback Systems ◽  
Learning Materials ◽  
Systematic Understanding ◽  
Game Elements

In recent years, mobile applications (apps) have been increasingly used and investigated as a vocabulary learning approach. Despite the extensive use of commercial English as a Foreign Language (EFL) vocabulary learning apps in China, there is a lack of a review of these apps for a systematic understanding of the components and usefulness of app-assisted vocabulary learning. To fill this knowledge gap, this study presents a systematic review of 15 EFL vocabulary learning apps that were most downloaded in China, focusing on how these apps help students develop word knowledge. The results of this study showed that most apps enabled students to access word knowledge through translating words into their native language. Notably, word knowledge was usually presented through text-plus-image and text-plus-image-plus-audio. Most of these mobile apps provided sentence examples as vocabulary learning materials. Many of these apps were integrated with game elements, especially in interactivity or feedback systems and reward systems. Based on the review results, we have provided three recommendations to vocabulary learning app developers concerning the use of video for the input of word knowledge, the efficiency of vocabulary learning, and the integration of more game elements.

scholarly journals Seeing Things Differently: The use of mobile app interpretation and its effect on visitor experience at two heritage sites in Aotearoa New Zealand

2021 ◽  
Author(s):  
◽  
Jessica Aitken
Keyword(s):  
New Zealand ◽  
Case Studies ◽  
Mobile Applications ◽  
Mobile Apps ◽  
Qualitative Interviews ◽  
Mobile App ◽  
Research Approach ◽  
Visitor Experience ◽  
Heritage Sites ◽  
High Street

<p>The practice of contemporary heritage interpretation has seen increased investment in digital technologies and more recently in mobile applications. However, few empirical studies assess how effective mobile apps are to the visitor experience of heritage sites. What kind of visitor experience do mobile apps provide? How do mobile apps deliver on the aims of interpretation for heritage sites? What types of apps work best? What are the challenges for developers and heritage professionals?  A qualitative research approach is used to examine two case studies; High Street Stories: the life and times of Christchurch’s High Street Precinct and IPENZ Engineering Tours: Wellington Heritage Walking Tour. These case studies ask what kind of experience mobile apps offer as an interpretation tool at these heritage sites. To investigate the topic, email interviews were carried out with heritage professionals and digital developers; together with qualitative interviews with visitors recruited to visit the case study sites using the mobile applications.   This study explores two current examples of mobile app technology in the heritage sector in a New Zealand context. The results of this study aim to augment current literature on the topic of digital interpretation. This study seeks to offer heritage managers and interpreters some key factors to consider when making decisions regarding the methods used to present and interpret heritage sites to visitors and in developing new interpretation and digital strategies that include mobile applications. Although each scenario presents its particular set of considerations and all heritage sites are different, it is hoped these recommendations can be applied and offer working models and strategies.</p>

scholarly journals Two-dimensional taxonomy of internet addiction and assessment of smartphone addiction with diagnostic criteria and mobile apps

2021 ◽  
Vol 9 (4) ◽  
pp. 928-933
Author(s):  
Yi-Lun Wu ◽  
Sheng-Hsuan Lin ◽  
Yu-Hsuan Lin
Keyword(s):  
Diagnostic Criteria ◽  
Functional Impairment ◽  
Internet Addiction ◽  
Mobile Applications ◽  
Mobile Apps ◽  
Unmet Need ◽  
Smartphone Addiction ◽  
Two Dimensional ◽  
Future Assessment ◽  
Assessment And Treatment

AbstractA recent review by Montag et al. raised a taxonomical argument about internet addiction. We propose a two-dimensional taxonomy of internet addiction by both the device and the content as the solution. For the assessment of smartphone addiction, measurements should be based on functional impairment and validated by diagnostic criteria rather than solely on self-reported questionnaires. We detail the potential of mobile applications (apps) to improve the assessment of smartphone addiction. App-generated indicators could fulfill the unmet need of assessment of smartphone addiction and facilitate future assessment and treatment planning of smartphone addiction.

scholarly journals Mobile Applications for Knowledge Workers and Field Workers

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Stefan Stieglitz ◽  
Christoph Lattemann ◽  
Tobias Brockmann
Keyword(s):  
Data Storage ◽  
Mobile Applications ◽  
Mobile Apps ◽  
Knowledge Workers ◽  
Competitive Advantages ◽  
Mobile Business ◽  
Mobile Data ◽  
Individual Enterprise ◽  
Employees Satisfaction ◽  
Field Workers

In recent years, the diffusion of mobile applications (mobile apps) has risen significantly. Nowadays, mobile business apps are strongly emerging in business, enhancing productivity and employees’ satisfaction, whilst the usage of customized individual enterprise apps is still an exception. Standardized business apps enable basic functionalities, for example, mobile data storage and exchange (e.g., Dropbox), communication (e.g., Skype), and other routine processes, which support mobile workers. In addition, mobile apps can, for example, increase the flexibility of mobile workers by easing the access to firm’s information from outside the enterprise and by enabling ubiquitous collaboration. Hence, mobile apps can generate competitive advantages and can increase work efficiency on a broad scale. But mobile workers form no coherent group. Our research reveals, based on two case studies, that they can be clustered into two groups: knowledge workers and field workers. Knowledge workers and field workers fulfill different tasks and work in different environments. Hence, they have different requirements for mobile support. In this paper we conclude that standardized mobile business apps cannot meet the different requirements of various groups of mobile workers. Task- and firm-specific (individualized) requirements determine the specification, implementation, and application of mobile apps.

Protecting Privacy on Mobile Apps: A Principal–Agent Perspective

2022 ◽  
Vol 29 (1) ◽  
pp. 1-32
Author(s):  
Zilong Liu ◽  
Xuequn Wang ◽  
Xiaohan Li ◽  
Jun Liu
Keyword(s):  
Mobile Applications ◽  
Recent Literature ◽  
Mobile Apps ◽  
Theory And Practice ◽  
Principal Agent ◽  
Daily Lives ◽  
Privacy Issue ◽  
Informed Decisions ◽  
The Relationship

Although individuals increasingly use mobile applications (apps) in their daily lives, uncertainty exists regarding how the apps will use the information they request, and it is necessary to protect users from privacy-invasive apps. Recent literature has begun to pay much attention to the privacy issue in the context of mobile apps. However, little attention has been given to designing the permission request interface to reduce individuals’ perceived uncertainty and to support their informed decisions. Drawing on the principal–agent perspective, our study aims to understand the effects of permission justification, certification, and permission relevance on users’ perceived uncertainty, which in turn influences their permission authorization. Two studies were conducted with vignettes. Our results show that certification and permission relevance indeed reduce users’ perceived uncertainty. Moreover, permission relevance moderates the relationship between permission justification and perceived uncertainty. Implications for theory and practice are discussed.

Classifying Mobile Applications Using Word Embeddings

2022 ◽  
Vol 31 (2) ◽  
pp. 1-30
Author(s):  
Fahimeh Ebrahimi ◽  
Miroslav Tushev ◽  
Anas Mahmoud
Keyword(s):  
Mobile Applications ◽  
Empirical Investigation ◽  
Mobile Apps ◽  
Human Subjects ◽  
Sharing Economy ◽  
Support Vector ◽  
Word Embeddings ◽  
Mobile Software ◽  
Vector Machines ◽  
Modern Application

Modern application stores enable developers to classify their apps by choosing from a set of generic categories, or genres, such as health, games, and music. These categories are typically static—new categories do not necessarily emerge over time to reflect innovations in the mobile software landscape. With thousands of apps classified under each category, locating apps that match a specific consumer interest can be a challenging task. To overcome this challenge, in this article, we propose an automated approach for classifying mobile apps into more focused categories of functionally related application domains. Our aim is to enhance apps visibility and discoverability. Specifically, we employ word embeddings to generate numeric semantic representations of app descriptions. These representations are then classified to generate more cohesive categories of apps. Our empirical investigation is conducted using a dataset of 600 apps, sampled from the Education, Health&Fitness, and Medical categories of the Apple App Store. The results show that our classification algorithms achieve their best performance when app descriptions are vectorized using GloVe, a count-based model of word embeddings. Our findings are further validated using a dataset of Sharing Economy apps and the results are evaluated by 12 human subjects. The results show that GloVe combined with Support Vector Machines can produce app classifications that are aligned to a large extent with human-generated classifications.

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