scholarly journals Examining consumer use of mobile health applications by the extended UTAUT model

2021 ◽  
Vol 9 (1) ◽  
pp. 267-281
Author(s):  
Buket Bora Semiz ◽  
Tarık Semiz
Keyword(s):  
Mobile Health ◽  
Structural Equation ◽  
Health Sector ◽  
Mobile Technologies ◽  
Intention To Use ◽  
Validity And Reliability ◽  
Utaut Model ◽  
Perceived Trust ◽  
Mobile Health Applications ◽  
Health Applications

Today, rapid changes and innovations in technology cause changes in the health sector as in many areas. Especially mobile technologies and applications are increasing their usage areas in the health sector day by day. Thanks to these mobile health applications, consumers provide a lot of convenience and advantages in healthy eating, reproductive health, disease monitoring, access to health records, etc.The study aims to investigate consumers’ usage of mobile health (mHealth) applications with the extended Unified Theory of Acceptance and Use of Technology (UTAUT) model. It is possible to say that it is an empirical study since the data were collected with the questionnaire method. Because this is research based on a cause-and-result relationship, the relationships were revealed with Structural Equation Modelling (SEM). The data were collected between November 2020 and January 2021 via the Google Forms platform from 354 individuals using convenience sampling through social media channels. The SPSS and SmartPLS programs were used for the analyses. First of all, it was determined that the scales' validity and reliability were ensured by performing validity and reliability analysis of the research model. According to the findings, it was revealed that performance expectancy, effort expectancy, social influence, facilitating conditions, habit, hedonic motivation, and perceived trust have a significant effect on the intention to use mHealth applications and, the intention to use mHealth applications has a significant effect on the behaviour of use mHealth applications.

Effect of Output Quality and Result Demonstrability on Generation Y’s Behavioural Intention in Adopting Mobile Health Applications

2019 ◽  
Vol 15 (3) ◽  
pp. 111-121
Author(s):  
Chen Xian Gow ◽  
Siew Chin Wong ◽  
Chui Seong Lim
Keyword(s):  
Mobile Health ◽  
Self Efficacy ◽  
Structural Equation ◽  
The Body ◽  
Behavioural Intention ◽  
Intention To Use ◽  
Body Of Knowledge ◽  
Output Quality ◽  
Mobile Health Applications ◽  
Health Applications

The aim of this study is to investigate the relationships between image, output quality, perceived self-efficacy, result demonstrability and Generation Y’s behavioural intention to use mobile health applications. Research data are gathered from a sample of 120 Generation Y participants in Malaysia. Partial least squares structural equation modelling (PLS-SEM) is employed to examine the influences of image, output quality, perceived self-efficacy and result demonstrability on behavioural intention to use mobile health applications. The results demonstrate that output quality and result demonstrability are potential predictors of behavioural intention to use mobile health applications. However, there is no significant relationship between image, perceived self-efficacy and behavioural intention. This study contributes to the body of knowledge focused on a better understanding of the behavioural intention of younger generations to adopt and use mobile health applications. Current research provides developers of mobile health applications and healthcare professionals with useful insights into how the adoption rate of mobile health applications can be enhanced.

scholarly journals Design Considerations for Mobile Health Applications Targeting Older Adults

2021 ◽  
Vol 79 (1) ◽  
pp. 1-8
Author(s):  
Clara Li ◽  
Judith Neugroschl ◽  
Carolyn W. Zhu ◽  
Amy Aloysi ◽  
Corbett A. Schimming ◽  
...  
Keyword(s):  
Older Adults ◽  
Mobile Health ◽  
Health Management ◽  
Care Delivery ◽  
Mobile Technologies ◽  
Full Potential ◽  
Design Considerations ◽  
Aging Populations ◽  
Mobile Health Applications ◽  
Health Applications

Mobile technologies are becoming ubiquitous in the world, changing the way we communicate and provide patient care and services. Some of the most compelling benefits of mobile technologies are in the areas of disease prevention, health management, and care delivery. For all the advances that are occurring in mobile health, its full potential for older adults is only starting to emerge. Yet, existing mobile health applications have design flaws that may limit usability by older adults. The aim of this paper is to review barriers and identify knowledge gaps where more research is needed to improve the accessibility of mobile health use in aging populations. The same observations might apply to those who are not elderly, including individuals suffering from severe mental or medical illnesses.

An assessment of the effects of widespread use of mobile applications in the health sector: An exploratory study of its success and failures

2016 ◽  
pp. 145-149
Author(s):  
Nadire Cavus
Keyword(s):  
Health Care ◽  
Mobile Applications ◽  
Health Sector ◽  
Vital Signs ◽  
Early Warning Systems ◽  
Mobile Technologies ◽  
Warning Systems ◽  
Medical Practitioners ◽  
Mobile Health Applications ◽  
Health Applications

Abstract Prior to the introduction of mobile technologies, the manual system of checking patients’ vital signs after approximately seven hours increased the health risk of the patients. Some of the patients’ health was jeopardised, worsening their situation, others re-admitted and others even passing on. The introduction and extensive use of mobile technologies has transformed the delivery of health care. Mobile applications with early warning systems are now dominating the health sector in an attempt to alert medical practitioners to act promptly to the patients’ needs. This paper reviews effects of mobile applications in the health sector as well as the success and failures of Mobile health applications. The assimilation of mobile applications in health care is marking an incredible venture in the health care industry. Keywords: mHealth, mobile applications, success, failures, health sector, mobile technologies, adoption, patients, hospitals.

Effective Factors in Adoption of Mobile Health Applications between Medical Sciences Students Using the UTAUT Model

2019 ◽  
Vol 58 (04/05) ◽  
pp. 131-139 ◽  
Author(s):  
Ali Garavand ◽  
Mahnaz Samadbeik ◽  
Hamed Nadri ◽  
Bahlol Rahimi ◽  
Heshmatollah Asadi
Keyword(s):  
Mobile Health ◽  
Behavioral Intention ◽  
Structural Equation ◽  
Scientific Evidence ◽  
Medical Science ◽  
Equation Modeling ◽  
Intention To Use ◽  
Medical Sciences ◽  
Utaut Model ◽  
Acceptance Factors

Abstract Background Students with complex health care services process face constant challenges with regard to health education. The mobile devices are an important tool that can install various applications for using information such as clinical guidelines, drug resources, clinical calculations, and the latest scientific evidence without any time and place limitations. And this happens only when students accept and use it. Objective The purpose of this article is to identify the factors influencing students in their intention to use mobile health (mHealth) by using Unified Theory of Acceptance and Use of Technology (UTAUT) model. Methods A standard questionnaire was used to collect the data from nearly 302 Lorestan University of medical science students including nutrition and public health, paramedicine, nursing and midwifery, pharmacy, dentistry, and medical schools. The data were processed using LISREL (Scientific Software International, Inc., Lincolnwood, Illinois) and SPSS (IBM Corp., Armonk, New York) softwares and the statistical analysis technique was based on structural equation modeling (SEM). Result A total of 300 questionnaires including valid responses were used in this study. The results showed that mediator of age did not affect the predictors of intention to use mHealth, and the level of education and gender directly affected the intention to use. In addition, effort expectancy, facilitating condition, and behavioral intention directly and indirectly have effect on use, whereas the result revealed no significant relationship between two important processes of performance expectancy and social influence with students' behavioral intention to use the mHealth. Conclusions The present study provides valuable information on mobile health acceptance factors for widespread use of this device among students of universities of medical sciences as a base infrastructure for a variety of information about health services and learning. Review and comparison of results with other studies showed that mHealth acceptance factors were different from other end users (elderly, patients, and health professionals).

scholarly journals Conceptualizing Mobile Health Application Use Intention and Adoption Among Iraqian Older Adults: From the Perspective of Expanded Technology Acceptance Model

2019 ◽  
Vol 13 (10) ◽  
pp. 28
Author(s):  
Murtaja Ali Saare ◽  
Azham Hussain ◽  
Wong Seng Yue
Keyword(s):  
Older Adults ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Mobile Health ◽  
Perceived Usefulness ◽  
Intention To Use ◽  
Mobile Health Applications ◽  
Acceptance Model ◽  
The Impact ◽  
Health Applications

<p>The aim of this article is to discuss how different factors affect the decision of intention to use and adopt mobile health applications using the extended technology acceptance model (TAM) among older adults in Iraq. “Perceived usefulness (PU), perceived ease of use (PEU), subjective norm (SN), and facilitating conditions (FC)” were four key predictors. Gender and age were included as factors for moderating the impact of two key TAM components in the proposed model (PU and PEU) on intention to use and adoption behaviors. The results of the past studies indicated that PU, PEU and SN were important predictors of adoption of mobile health applications among older adults in Iraq, While PU, SN, and FC were important predictors of the intention to use mobile health applications. Previous studies highlighted a strong impact of PEU on the intention to use mobile health applications on older adults than for younger adults. Implications are discussed for future research and practices.</p>

scholarly journals Active Usage of Mobile Health Applications: Cross-sectional Study (Preprint)

2020 ◽  
Author(s):  
Yang Wang ◽  
Tailai Wu ◽  
Zhuo Chen
Keyword(s):  
Mobile Health ◽  
Consumer Satisfaction ◽  
Structural Equation ◽  
Health Management ◽  
Equation Modeling ◽  
Survey Method ◽  
Cross Sectional ◽  
Mobile Health Applications ◽  
Consumer Dissatisfaction ◽  
Health Applications

BACKGROUND Mobile health applications are being increasingly used for people’s health management. The different uses of mobile health applications lead to different health outcomes. Although active usage of mobile health applications is shown to be linked to the effectiveness of mobile health services, the factors that influence people’s active usage of mobile health applications are not well studied. OBJECTIVE This paper aims to examine the antecedents of active usage of mobile health applications. METHODS Grounded on the 3-factor theory, we proposed 10 attributes of mobile health applications that influence the active usage of mobile health applications through consumers’ satisfaction and dissatisfaction. We classified these 10 attributes into 3 categories (ie, excitement attributes, performance attributes, and basic attributes). Using the survey method, 494 valid responses were collected and analyzed using structural equation modeling. RESULTS Our analysis results revealed that both consumer satisfaction (β=0.351, <i>t</i>=6.299, <i>P</i>&lt;.001) and dissatisfaction (β=–0.251, <i>t</i>=5.119, <i>P</i>&lt;.001) significantly influenced active usage. With regard to the effect of attributes, excitement attributes (β=0.525, <i>t</i>=12.861, <i>P</i>&lt;.001) and performance attributes (β=0.297, <i>t</i>=6.508, <i>P</i>&lt;.001) positively influenced consumer satisfaction, while performance attributes (β=–0.231, <i>t</i>=3.729, <i>P</i>&lt;.001) and basic attributes (β=–0.412, <i>t</i>=7.132, <i>P</i>&lt;.001) negatively influenced consumer dissatisfaction. The results of the analysis confirmed our proposed hypotheses. CONCLUSIONS Our study provides a novel perspective to study the active usage of mobile health applications. By categorizing the attributes of mobile health applications into 3 categories, the differential effects of different attributes can be tested. Meanwhile, consumer satisfaction and dissatisfaction are confirmed to be independent from each other.

Malaria Geo-Localization with Mobile-Health Applications

2015 ◽  
Author(s):  
Roberto Moro Visconti ◽  
Alberto Larocca ◽  
Michele Marconi
Keyword(s):  
Mobile Health ◽  
Mobile Health Applications ◽  
Health Applications

EFFECTIVNESS OF SPECIFIC MOBILE HEALTH APPLICATIONS (mHEALTH-APPS)in GESTATIONAL DIABTETES MELLITUS: A SYSTEMATIC REVIEW (Preprint)

2020 ◽  
Author(s):  
Claudia Eberle ◽  
Maxine Löhnert
Keyword(s):  
Mobile Health ◽  
Cochrane Library ◽  
Clinical Parameters ◽  
Control Groups ◽  
Manual Search ◽  
Mobile Health Applications ◽  
Short And Long Term ◽  
Mhealth Apps ◽  
Health Applications

BACKGROUND Gestational diabetes mellitus (GDM) emerges worldwide and is closely associated with short- and long-term health issues in women and their offspring, such as pregnancy and birth complications respectively comorbidities, Type 2 Diabetes (T2D), Metabolic Syndrome (MetS) as well as cardiovascular disease (CD). Against this background mobile health applications (mHealth-Apps) do open up new possibilities to improve the management of GDM clearly. OBJECTIVE Since there is – to our knowledge – no systematic literature review published, which focusses on the effectiveness of specific mHealth-Apps on clinical health-related short and long-term outcomes of mother and child, we conducted these much-needed analyses. METHODS Data sources: A systematic literature search in Medline (Pubmed), Cochrane Library, Embase, CINAHL and Web of Science was performed including full text publications since 2008 up to date. An additional manual search in references and Google Scholar was conducted subsequently. Study Eligibility Criteria: Women diagnosed with GDM using specific mHealth-Apps during pregnancy compared to control groups, which met main clinical parameters and outcomes in GDM management as well as maternity and offspring care. Study appraisal and synthesis methods: Study quality was assessed and rated “strong”, “moderate” or “weak” by using the Effective Public Health Practice Project (EPHPP) tool. Study results were strongly categorized by outcomes; an additional qualitative summary was assessed. Study selection: Overall, n= 114 studies were analyzed, n= 46 duplicates were removed, n=5 studies met the eligible criteria and n=1 study was assessed by manual search subsequently. In total, n=6 publications, analyzing n=408 GDM patients in the interventional and n=405 women diagnosed with GDM in the control groups, were included. These studies were divided into n=5 two-arm randomized controlled trials (RCT) and n=1 controlled clinical trial (CCT). RESULTS Distinct improvements in clinical parameters and outcomes, such as fasting blood glucoses (FBG), 2-hour postprandial blood glucoses (PBG), off target blood glucose measurements (OTBG), delivery modes and patient compliance were analyzed in GDM patients using specific mHealth-Apps compared to matched control groups. CONCLUSIONS mHealth-Apps clearly improve clinical outcomes in management of GDM effectively. More studies need to be done more in detail.

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