scholarly journals Influencing Factors of Acceptance and Use Behavior of Mobile Health Application Users: Systematic Review

Healthcare ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 357
Author(s):  
Chen Wang ◽  
Huiying Qi
Keyword(s):  
Systematic Review ◽  
Influencing Factors ◽  
Mobile Health ◽  
Source Credibility ◽  
Mobile Health Application ◽  
Mobile Health Applications ◽  
The Individual ◽  
Use Behavior ◽  
Health Application ◽  
Health Applications

Purpose/Significance: Mobile health applications provide a convenient way for users to obtain health information and services. Studying the factors that influence users’ acceptance and use of mobile health applications (apps or Apps) will help to improve users’ actual usage behavior. Method/Process: Based on the literature review method and using the Web of Science core database as the data source, this paper summarizes the relevant research results regarding the influencing factors of the acceptance and use behavior of mobile health application users and makes a systematic review of the influencing factors from the perspectives of the individual, society, and application (app or App) design. Result/Conclusion: In terms of the individual dimension, the users’ behavior is influenced by demographic characteristics and motivations. Social attributes, source credibility, and legal issues all affect user behavior in the social dimension. In the application design dimension, functionality, perceived ease of use and usefulness, security, and cost are the main factors. At the end of the paper, suggestions are given to improve the users’ acceptability of mobile health applications and improve their use behavior.

Perceptions of older men using a mobile health application to monitor lower urinary tract symptoms and tamsulosin side effects: mixed-methods study (Preprint)

2021 ◽  
Author(s):  
Elizabeth Y Wang ◽  
Benjamin N Breyer ◽  
Austin W Lee ◽  
Natalie Rios ◽  
Akinyemi Oni-Orisan ◽  
...  
Keyword(s):  
Side Effects ◽  
Mobile Health ◽  
Mobile Application ◽  
Older Men ◽  
Mobile Health Application ◽  
Urinary Tract Symptoms ◽  
Medication Side ◽  
Mobile Health Applications ◽  
Health Application ◽  
Health Applications

BACKGROUND Mobile health applications may provide an efficient way for patients with lower urinary tract symptoms (LUTS) to log and communicate symptoms and medication side effects with their clinicians. OBJECTIVE To explore the perceptions of older men with LUTS after using a mobile health application to track their symptoms and tamsulosin side effects. METHODS Structured phone interviews were conducted after a 2-week study piloting the daily use of a mobile application to track severity of patient-selected LUTS and tamsulosin side effects. Quantitative and qualitative data were considered. RESULTS Nineteen (100%) pilot study participants completed the post-study interviews. Most men (68%) reported that the daily questionnaires were the right length, with 32% reporting that the questionnaires were too short. Men with more severe symptoms were less likely to report changes in perception of health or changes in self-management; 47% of men reported improved awareness of symptoms and 5% of men adjusted fluid intake based on the questionnaire. All men were willing to share application data with their clinicians. Thematic analysis of qualitative data yielded 8 themes: 1) orientation (setting up app, format, symptom selection, side effect selection), 2) triggers (routine/habit, symptom timing), 3) daily questionnaire (reporting symptoms, reporting side effects, tailoring), 4) technology literacy, 5) perceptions (awareness, causation/relevance, data quality, convenience, usefulness, other apps), 6) self-management, 7) clinician engagement (communication, efficiency), and 8) improvement (reference materials, flexibility, language, management recommendations, optimize clinician engagement). CONCLUSIONS We assessed the perceptions of men using a mobile health application to monitor and improve management of LUTS and medication side effects. LUTS management may be further optimized by tailoring the mobile application experience to meet patients’ individual needs, such as tracking a greater number of symptoms and integrating the application with clinicians’ visits. Mobile health applications are likely a scalable modality to monitor symptoms and improve care of older men with LUTS. Further study is required to determine the best ways to tailor the mobile application and to communicate data to clinicians or incorporate data into the electronical medical record meaningfully.

scholarly journals Domain-Adaptive Service Evaluation of Mobile Health Application

2019 ◽  
Author(s):  
Xiaojia Wang ◽  
Kuo Du ◽  
Wei Xia ◽  
Shanshan Zhang ◽  
Weiqun Xu ◽  
...  
Keyword(s):  
Mobile Health ◽  
Evaluation System ◽  
Interaction Information ◽  
Application Service ◽  
Mobile Health Application ◽  
Interactive Algorithm ◽  
Mobile Health Applications ◽  
Health Application ◽  
Content Information ◽  
Health Applications

Abstract Background: In the context of "Internet +" medical treatment, mobile health applications provide services for people in a new way, making it possible for people to carry out health management anytime and anywhere. According to the survey data, the most powerful consumers in the field of mobile health applications are those aged 24 to 35. Thus, it can be seen, it is particularly important to study the preferences of young people for mobile health applications.Methods: This study established a domain-adaptive mobile health application evaluation model based on users’ experience, and used an interactive algorithm combining machine learning and Delphi method to calculate the weight distribution of evaluation factors. Compared with previous studies, the establishment of evaluation index based on user experience of youth groups can more comprehensively measure users' demand for mobile health application service quality. Meanwhile, the mobile health application evaluation system established in this study adopts feedback mechanism to realize dynamic evaluation of mobile health applications.Results: The cognitive level of information (weighting 52%) was only four percentage points higher than the emotional level (weighting 48%). The importance of the four criteria is content information on cognition (weighting 31%), interaction information on emotion (weighting 29%), interaction information on cognition (weighting 21%), and content information on emotion (weighting 19%) in descending order. Among 20 sub-criteria, less disruptive (weighting 17.8%), security (weighting 10.9%), utility (weighting 9.3%), reliability (weighting 8.1%), navigational (weighting 6.7%) occupy an important position.Conclusion: We find that the weights assigned to sociability, personalization, aesthetics, and interestingness accounted for a significant proportion of the total weights assigned; however, universality and learnability were poorly weighted. These results have important reference value for the development of mobile health applications.

scholarly journals Insights into mobile health application market via a content analysis of marketplace data with machine learning

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244302
Author(s):  
Gokhan Aydin ◽  
Gokhan Silahtaroglu
Keyword(s):  
Machine Learning ◽  
Content Analysis ◽  
Mobile Health ◽  
Current Knowledge ◽  
Machine Learning Algorithms ◽  
Health Apps ◽  
Mobile Health Application ◽  
Mobile Health Applications ◽  
Health Application ◽  
Health Applications

Background Despite the benefits offered by an abundance of health applications promoted on app marketplaces (e.g., Google Play Store), the wide adoption of mobile health and e-health apps is yet to come. Objective This study aims to investigate the current landscape of smartphone apps that focus on improving and sustaining health and wellbeing. Understanding the categories that popular apps focus on and the relevant features provided to users, which lead to higher user scores and downloads will offer insights to enable higher adoption in the general populace. This study on 1,000 mobile health applications aims to shed light on the reasons why particular apps are liked and adopted while many are not. Methods User-generated data (i.e. review scores) and company-generated data (i.e. app descriptions) were collected from app marketplaces and manually coded and categorized by two researchers. For analysis, Artificial Neural Networks, Random Forest and Naïve Bayes Artificial Intelligence algorithms were used. Results The analysis led to features that attracted more download behavior and higher user scores. The findings suggest that apps that mention a privacy policy or provide videos in description lead to higher user scores, whereas free apps with in-app purchase possibilities, social networking and sharing features and feedback mechanisms lead to higher number of downloads. Moreover, differences in user scores and the total number of downloads are detected in distinct subcategories of mobile health apps. Conclusion This study contributes to the current knowledge of m-health application use by reviewing mobile health applications using content analysis and machine learning algorithms. The content analysis adds significant value by providing classification, keywords and factors that influence download behavior and user scores in a m-health context.

Barriers and drivers regarding the use of mobile health applications among type 2 diabetes patients in the Netherlands: an explanatory sequential design (Preprint)

2021 ◽  
Author(s):  
Marloes Bults ◽  
Catharina Margaretha Van Leersum ◽  
Theo Olthuis ◽  
Robin Bekhuis ◽  
Marjolein Elisabeth Maria Den Ouden
Keyword(s):  
Mobile Health ◽  
Healthcare Professionals ◽  
Insurance Companies ◽  
Actual Use ◽  
Mobile Health Applications ◽  
Explanatory Sequential Design ◽  
The Individual ◽  
Depth Interviews ◽  
Health Applications

BACKGROUND In the Netherlands, type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases and the number of patients is expected to increase in the coming years. Self-monitoring of blood glucose levels, food intake and physical activity supports the self-management of patients with T2DM. In the past few years, there has been a rise in the development and availability of mobile health applications (apps) for T2DM. OBJECTIVE The aim of this study was to explore the actual use of diabetes mobile health applications among T2DM-patients and main barriers and drivers among app-users and non-users. METHODS An explanatory sequential design was applied, starting with a web-based questionnaire followed by semi-structured in-depth interviews. Data were collected between July and December 2020. Questionnaire data from 103 respondents were analyzed using IBM SPSS Statistics 25.0. Descriptive statistics were performed for actual use of apps among T2DM-patients and the individual items of the Unified Theory of Acceptance and Use of Technology (UTAUT). Differences between users and non-users were tested through chi-square tests for the individual items. Independent t-tests were performed to test for differences in mean scores per UTAUT-construct. A total of 16 respondents contributed to the in-depth interviews, of which ten were users and six non-users of apps for T2DM. Content analysis with a deductive approach was performed on all transcripts guided by the UTAUT. RESULTS Regarding actual use, 55% (n=57) were non-users and 45% (n=46) were users of apps for T2DM. Mean scores were significantly higher among users of apps for T2DM for the constructs performance expectancy, effort expectancy, facilitating conditions and knowledge compared to the non-users (P<.001). One of the main drivers for use was the belief that using diabetes-apps would result in better personal health and well-being. Time and energy needed to keep track of data and understand the app were mentioned as barriers. Users scored significantly higher regarding social influence compared to the non-users (P.007). Healthcare professionals play an important role in the support of T2DM-patients in using apps. Respondents wanted to use the apps and acquired data together with their healthcare professionals. However, respondents noticed that their professionals often were not supportive regarding the use of diabetes-apps, didn’t had interest or did not talk about apps or acquired data. Reimbursement by insurance companies was mentioned as missing facilitator. CONCLUSIONS Empowering healthcare professionals’ engagement is of utmost important to support T2DM-patients in using apps. Insurance companies can have a role in facilitating the use of diabetes-apps, for example to assure reimbursement. Further research should focus on evaluation of patients experiences with different diabetes-apps and how to integrate mobile health applications with diabetes self-management care.

The Functionality, Quality and Consistency with International Guidelines of Asthma Mobile Health Applications: Protocol for a Systematic Review. (Preprint)

2021 ◽  
Author(s):  
Billy Robinson ◽  
Enying Gong ◽  
Brian Oldenburg ◽  
Katharine See
Keyword(s):  
Systematic Review ◽  
Mobile Health ◽  
Airflow Limitation ◽  
Significant Variable ◽  
Assessment Framework ◽  
Mobile Health Applications ◽  
Gina Guidelines ◽  
Mhealth Apps ◽  
Health Applications

BACKGROUND Asthma is a chronic respiratory disorder defined clinically as a combination of typical respiratory symptoms, and significant variable reversible airflow limitation. In addition to pharmacotherapy, a key aspect of asthma management is empowering patients to manage their condition and recognise and respond to asthma exacerbations. Mobile health applications (mHealth apps) represent a potential medium through which patients could improve the ability to self-manage their asthma. Few studies have conducted a systematic evaluation of both free and paid asthma mobile applications for the quality and functionality of the apps using a validated tool and to our knowledge none have systematically assessed these applications for the quality of information that they provide compared to available international best practice guidelines. This represents the first study that will undertake both of these evaluations for all available mHealth Apps in Australia targeted towards adult asthmatics. The Global Initiative for Asthma (GINA) guidelines represent a regularly updated guideline based on reviews of the available scientific literature by an international panel of experts. This review will examine the functionality and quality of available asthma mobile health applications and the consistency of these available applications with recommendations from the GINA guidelines. OBJECTIVE The objective of this study is to conduct a systematic review of adult-targeted asthma mobile health applications on the Australian market. As part of this review the potential for an mHealth app to improve asthma self-management and the overall quality of the application will be evaluated, using the Mobile App Rating Scale (MARS) framework, and the quality of the information within an app, using the current GINA guidelines as a reference, will be assessed. METHODS A methodological stepwise approach was taken in creating this review. First the most recent GINA guidelines were independently reviewed by two authors to identify key recommendations that could feasibly be incorporated into a mHealth app. These identified recommendations were then compared to a previously developed asthma application assessment framework. A modified assessment framework was created, ensuring all of these identified recommendations were included. Two popular App stores were then reviewed to identify potential mHealth Apps and then a screening process based on pre-defined inclusion and exclusion criteria occurred to establish what mHealth Apps would be evaluated. Application evaluation then occurred. Technical information was obtained from publicly available information on the application store or within the app itself. The next step was to perform an application quality assessment using the validated MARS framework to objectively determine the quality of the application. Application functionality was then assessed using the IMS Institute for Health Informatics Functionality Scoring system. Finally, the mHealth applications will be assessed using a checklist that we have developed based on what was identified from the international GINA guidelines. RESULTS To date, funding has been received for the project from the Respiratory Department at Northern Health, Victoria. Three reviewers have been recruited to systematically evaluate the applications. Results for this study are expected by the end of this year. CONCLUSIONS Nil as protocol CLINICALTRIAL PROSPERO 269894

scholarly journals Patient Self-Management of Asthma Using Mobile Health Applications: A Systematic Review of the Functionalities and Effects

2017 ◽  
Vol 08 (04) ◽  
pp. 1068-1081 ◽  
Author(s):  
Mehrdad Farzandipour ◽  
Ehsan Nabovati ◽  
Reihane Sharif ◽  
Marzieh Arani ◽  
Shima Anvari
Keyword(s):  
Quality Of Life ◽  
Systematic Review ◽  
Mobile Health ◽  
Self Management ◽  
Cochrane Central Register ◽  
Patient Reported ◽  
Mobile Health Applications ◽  
Mhealth Apps ◽  
Health Applications

Objective The aim of this systematic review was to summarize the evidence regarding the effects of mobile health applications (mHealth apps) for self-management outcomes in patients with asthma and to assess the functionalities of effective interventions. Methods We systematically searched Medline, Scopus, and the Cochrane Central Register of Controlled Trials. We included English-language studies that evaluated the effects of smartphone or tablet computer apps on self-management outcomes in asthmatic patients. The characteristics of these studies, effects of interventions, and features of mHealth apps were extracted. Results A total of 10 studies met all the inclusion criteria. Outcomes that were assessed in the included studies were categorized into three groups (clinical, patient-reported, and economic). mHealth apps improved asthma control (five studies) and lung function (two studies) from the clinical outcomes. From the patient-reported outcomes, quality of life (three studies) was statistically significantly improved, while there was no significant impact on self-efficacy scores (two studies). Effects on economic outcomes were equivocal, so that the number of visits (in two studies) and admission and hospitalization-relevant outcomes (in one study) statistically significantly improved; and in four other studies, these outcomes did not improve significantly. mHealth apps features were categorized into seven categories (inform, instruct, record, display, guide, remind/alert, and communicate). Eight of the 10 mHealth apps included more than one functionality. Nearly all interventions had the functionality of recording user-entered data and half of them had the functionality of providing educational information and reminders to patients. Conclusion Multifunctional mHealth apps have good potential in the control of asthma and in improving the quality of life in such patients compared with traditional interventions. Further studies are needed to identify the effectiveness of these interventions on outcomes related to medication adherence and costs.

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