Acceptance of Mobile Health Applications: Examining Key Determinants and Moderators.
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ABSTRACT:
SUBMITTER: Nunes A
PROVIDER: S-EPMC6914844 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
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Acceptance of Mobile Health Applications: Examining Key Determinants and Moderators.
Nunes Andreia A Limpo Teresa T Castro São Luís SL
Frontiers in psychology 20191210
Mobile health applications are increasingly numerous and varied. However, despite high expectations and large budgets involved in their development they are often rejected by potential users, and little is known on why this happens. This study aimed to fill this gap by investigating the determinants of technology acceptance and its moderators. Aligned with the Unified Theory of Acceptance and Use of Technology, we examined the moderating roles of age, gender, and smartphone experience in the rel ...[more]
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| S-EPMC7065029 | biostudies-literature
Project description:IntroductionSub-Saharan Africa lags in adoption of mobile health (m-health) applications and in leveraging m-health for sustainable development goals. There is a need for a comprehensive investigation of determinants of hospitals' adoption of m-health in Sub-Saharan Africa to inform policies, practices and investments.MethodsThis investigation used a logit regression model to analyze the determinants of m-health adoption in Kenyan hospitals applying the Technological, Organizational and Environmental (TOE) framework and the Diffusion of Innovation (DOI) theory. A representative sample of 211 executives of Level 4-6 hospitals in 24 counties provided primary data on Patient-Centered (PC) and Facility-Centered (FC) m-health applications.ResultsBoth PC and FC m-health adoption were predicted by competition for patients (PC p = 0.041, FC p = 0.021), IT human resource capacity (PC p = 0.048, FC p = 0.037), and hospital pursuit of market growth through technological leadership (PC p = 0.010, FC p = 0.020). Further determinants of PC m-health adoption included hospital access to slack financial resources (p = 0.006), acquisition strategy (p = 0.011), compatibility with the hospital systems (p = 0.015), trialability (p = 0.019), medical insurance company support (p = 0.025),patient pressure (p = 0.036), and perceived effect of global medical tourism (p = 0.039). FC m-health adoption was predicted by hospital size (p = 0.008), ICT infrastructure capacity (p = 0.041), and government support (p = 0.013).ConclusionA differentiated approach is required to scale up m-health adoption. PC m-health requires emphasis on establishing national and regional compatibility and interoperability, developing trialability processes and validation mechanisms, incentivizing patient competition and mobility, establishing innovative and cost-effective acquisition strategies, and ensuring integration of digital services within national insurance schemes and policies. These policies require support from patients and communities to drive demand and spur investment in adequate IT human resources to maintain reliability. Pilot PC m-health projects should prioritize hospitals with slack financial resources, while FC m-health should target large facility size. FC m-health applications are more complex and costly than PC, requiring government incentives to trigger hospital investments and national investment in ICT infrastructure. Investors and hospital managers should integrate m-health into market growth strategies for sustainable m-health scale-up in Kenya and beyond.
| S-EPMC6910672 | biostudies-literature
Project description:BackgroundMobile health applications (mHealth apps) have been widely used for various purposes for mitigating the COVID-19 pandemic, such as self-assessment, contact tracing, disseminating information, minimizing exposure, and reducing face-to-face health consultation. The objective of this study is to systematically review COVID-19 related mHealth apps and highlight gaps to inform the development of future mHealth initiatives in Indonesia.MethodsA systematic search strategy using a PRISMA flowchart was used to identify mHealth apps available in Google Play and Apple Play stores. We searched mHealth apps using certain specific terms related to COVID-19 outbreaks. The inclusion criteria were apps-based smartphone users related to COVID-19 using local language, free of cost, available in the Google Play and Apple Play Stores, and supported by the Indonesian government. We excluded games, apps on infectious diseases unrelated to COVID-19 specifically, and apps with non-Bahasa Indonesia (Indonesian language). The selected mHealth apps were assessed based on two measures: (1) the WHO guidelines on digital health intervention and (2) the four dimensions of the mHealth technology fit framework. In addition, user feedback from experienced and non-experienced users was conducted to evaluate four dimensions of the apps.ResultsA total of 339 mHealth apps were generated from the initial search, remaining seven selected apps that met inclusion criteria. The results highlighted that mHealth apps reviewed had still not been widely used by the general public. The applications were purposed to disseminate information, conduct a self-risk assessment, provide an online community forum, and telemedicine or teleconsultation regarding COVID-19. Data services, including data storage, aggregation, and data exchange, are available in most apps. The rarest function found was contact tracing and assisting health management and health workers, such as the availability of testing facilities, reporting test results, and prescribing medication. The main issues reported were the lack of data security and data privacy protection, integration and infrastructures, usability, and usefulness.ConclusionOur study highlighted the necessity to improve mHealth apps' functions related to assisting health workers and the function of digital contact tracing. An effort to increase public awareness regarding the use of mHealth is also necessary to streamline the function of this innovation. Policymakers must consider usefulness, usability, integration, and infrastructure issues to improve their mHealth function.
| S-EPMC9114306 | biostudies-literature
Project description:BackgroundMobile 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.ObjectiveThis paper aims to examine the antecedents of active usage of mobile health applications.MethodsGrounded 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.ResultsOur analysis results revealed that both consumer satisfaction (β=0.351, t=6.299, P<.001) and dissatisfaction (β=-0.251, t=5.119, P<.001) significantly influenced active usage. With regard to the effect of attributes, excitement attributes (β=0.525, t=12.861, P<.001) and performance attributes (β=0.297, t=6.508, P<.001) positively influenced consumer satisfaction, while performance attributes (β=-0.231, t=3.729, P<.001) and basic attributes (β=-0.412, t=7.132, P<.001) negatively influenced consumer dissatisfaction. The results of the analysis confirmed our proposed hypotheses.ConclusionsOur 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.
| S-EPMC8734924 | biostudies-literature
Project description:BackgroundMobile health (mHealth) apps have gained significant popularity over the last few years due to their tremendous benefits, such as lowering health care costs and increasing patient awareness. However, the sensitivity of health care data makes the security of mHealth apps a serious concern. Poor security practices and lack of security knowledge on the developers' side can cause several vulnerabilities in mHealth apps.ObjectiveIn this review paper, we aimed to identify and analyze the reported challenges concerning security that developers of mHealth apps face. Additionally, our study aimed to develop a conceptual framework with the challenges for developing secure apps faced by mHealth app development organizations. The knowledge of such challenges can help to reduce the risk of developing insecure mHealth apps.MethodsWe followed the systematic literature review method for this review. We selected studies that were published between January 2008 and October 2020 since the major app stores launched in 2008. We selected 32 primary studies using predefined criteria and used a thematic analysis method for analyzing the extracted data.ResultsOf the 1867 articles obtained, 32 were included in this review based on the predefined criteria. We identified 9 challenges that can affect the development of secure mHealth apps. These challenges include lack of security guidelines and regulations for developing secure mHealth apps (20/32, 63%), developers' lack of knowledge and expertise for secure mHealth app development (18/32, 56%), lack of stakeholders' involvement during mHealth app development (6/32, 19%), no/little developer attention towards the security of mHealth apps (5/32, 16%), lack of resources for developing a secure mHealth app (4/32, 13%), project constraints during the mHealth app development process (4/32, 13%), lack of security testing during mHealth app development (4/32, 13%), developers' lack of motivation and ethical considerations (3/32, 9%), and lack of security experts' engagement during mHealth app development (2/32, 6%). Based on our analysis, we have presented a conceptual framework that highlights the correlation between the identified challenges.ConclusionsWhile mHealth app development organizations might overlook security, we conclude that our findings can help them to identify the weaknesses and improve their security practices. Similarly, mHealth app developers can identify the challenges they face to develop mHealth apps that do not pose security risks for users. Our review is a step towards providing insights into the development of secure mHealth apps. Our proposed conceptual framework can act as a practice guideline for practitioners to enhance secure mHealth app development.
| S-EPMC8277314 | biostudies-literature
Project description:BackgroundThe Carrot Rewards app was developed as part of a public-private partnership to reward Canadians with loyalty points for downloading the app, referring friends, completing educational health quizzes, and health-related behaviors with long-term objectives of increasing health knowledge and encouraging healthy behaviors. During the first 3 months after program rollout in British Columbia, a number of program design elements were adjusted, creating observed differences between groups of users with respect to the potential impact of program features on user engagement levels.ObjectiveThis study examines the impact of reducing reward size over time and explored the influence of other program features such as quiz timing, health intervention content, and type of reward program on user engagement with a mobile health (mHealth) app.MethodsParticipants in this longitudinal, nonexperimental observational study included British Columbia citizens who downloaded the app between March and July 2016. A regression methodology was used to examine the impact of changes to several program design features on quiz offer acceptance and engagement with this mHealth app.ResultsOur results, based on the longitudinal app use of 54,917 users (mean age 35, SD 13.2 years; 65.03% [35,647/54,917] female), indicated that the key drivers of the likelihood of continued user engagement, in order of greatest to least impact, were (1) type of rewards earned by users (eg, movies [+355%; P<.001], air travel [+210%; P<.001], and grocery [+140%; P<.001] relative to gas), (2) time delay between early offers (-64%; P<.001), (3) the content of the health intervention (eg, healthy eating [-10%; P<.001] vs exercise [+20%, P<.001] relative to health risk assessments), and (4) changes in the number of points offered. Our results demonstrate that reducing the number of points associated with a particular quiz by 10% only led to a 1% decrease in the likelihood of offer response (P<.001) and that each of the other design features had larger impacts on participant retention than did changes in the number of points.ConclusionsThe results of this study demonstrate that this program, built around the principles of behavioral economics in the form of the ongoing awarding of a small number of reward points instantly following the completion of health interventions, was able to drive significantly higher engagement levels than those demonstrated in previous literature exploring the intersection of mHealth apps and financial incentives. Previous studies have demonstrated the presence of incentive matters to user engagement; however, our results indicate that the number of points offered for these reward point-based health interventions is less important than other program design features such as the type of reward points being offered, the timing of intervention and reward offers, and the content of the health interventions in driving continued engagement by users.
| S-EPMC7445608 | biostudies-literature
Project description:BACKGROUND:Plant health is intimately influenced by the rhizosphere microbiome, a complex assembly of organisms that changes markedly across plant growth. However, most rhizosphere microbiome research has focused on fractions of this microbiome, particularly bacteria and fungi. It remains unknown how other microbial components, especially key microbiome predators-protists-are linked to plant health. Here, we investigated the holistic rhizosphere microbiome including bacteria, microbial eukaryotes (fungi and protists), as well as functional microbial metabolism genes. We investigated these communities and functional genes throughout the growth of tomato plants that either developed disease symptoms or remained healthy under field conditions. RESULTS:We found that pathogen dynamics across plant growth is best predicted by protists. More specifically, communities of microbial-feeding phagotrophic protists differed between later healthy and diseased plants at plant establishment. The relative abundance of these phagotrophs negatively correlated with pathogen abundance across plant growth, suggesting that predator-prey interactions influence pathogen performance. Furthermore, phagotrophic protists likely shifted bacterial functioning by enhancing pathogen-suppressing secondary metabolite genes involved in mitigating pathogen success. CONCLUSIONS:We illustrate the importance of protists as top-down controllers of microbiome functioning linked to plant health. We propose that a holistic microbiome perspective, including bacteria and protists, provides the optimal next step in predicting plant performance. Video Abstract.
| S-EPMC7055055 | biostudies-literature
Project description:BackgroundMobile health applications (mHealth apps) have created innovative service channels for patients with chronic diseases. These innovative service channels require physicians to actively use mHealth apps. However, few studies investigate physicians' participation in mHealth apps.ObjectiveThis study aims to empirically explore factors affecting physicians' usage behaviors of mHealth apps. Based on the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and mHealth apps features, we propose a research model including altruism, cognitive trust, and online ratings.MethodsWe collected data from physicians who have used mHealth apps and conducted a factor analysis to verify the convergence and discriminative effects. We used a hierarchical regression method to test the path coefficients and statistical significance of our research model. In addition, we adopted bootstrapping approach and further analyzed the mediating effects of behavioral intention between all antecedent variables and physicians' usage behavior. Finally, we conducted three robustness analyses to test the validity of results and tested the constructs to verify the common method bias.ResultsOur results support the effects of performance expectancy, effort expectancy, social influence, and altruism on the behavioral intentions of physicians using mHealth apps. Moreover, facilitating conditions and habits positively affect physicians using mHealth apps through the mediating effort of behavioral intention. Physicians' cognitive trust and online rating have significant effects on their usage behaviors through the mediating efforts of behavioral intention.ConclusionsThis study contributes to the existing literature on UTAUT2 extension of physicians' acceptance of mHealth apps by adding altruism, cognitive trust, and online ratings. The results of this study provide a novel perspective in understanding the factors affecting physicians' usage behaviors on mHealth apps in China and provide such apps' managers with an insight into the promotion of physicians' active acceptance and usage behaviors.
| S-EPMC8729011 | biostudies-literature
Project description:ObjectiveWe conduct a first large-scale analysis of mobile health (mHealth) apps available on Google Play with the goal of providing a comprehensive view of mHealth apps' security features and gauging the associated risks for mHealth users and their data.Materials and methodsWe designed an app collection platform that discovered and downloaded more than 20 000 mHealth apps from the Medical and Health & Fitness categories on Google Play. We performed a suite of app code and traffic measurements to highlight a range of app security flaws: certificate security, sensitive or unnecessary permission requests, malware presence, communication security, and security-related concerns raised in user reviews.ResultsCompared to baseline non-mHealth apps, mHealth apps generally adopt more reliable signing mechanisms and request fewer dangerous permissions. However, significant fractions of mHealth apps expose users to serious security risks. Specifically, 1.8% of mHealth apps package suspicious codes (eg, trojans), 45.0% rely on unencrypted communication, and as much as 23.0% of personal data (eg, location information and passwords) is sent on unsecured traffic. An analysis of the app reviews reveals that mHealth app users are largely unaware of the surfaced security issues.ConclusionDespite being better aligned with security best practices than non-mHealth apps, mHealth apps are still far from ensuring robust security guarantees. App users, clinicians, technology developers, and policy makers alike should be cognizant of the uncovered security issues and weigh them carefully against the benefits of mHealth apps.
| S-EPMC8449631 | biostudies-literature
Project description:BACKGROUND:With the widespread use of mobile technologies, mobile information systems have become crucial tools in health care operations. Although the appropriate use of mobile health (mHealth) may result in major advances in expanding health care coverage (increasing decision-making speeds, managing chronic conditions, and providing suitable health care in emergencies), previous studies have argued that current mHealth research does not adequately evaluate mHealth interventions, and it does not provide sufficient evidence regarding the effects on health. OBJECTIVE:The aim of this study was to facilitate the widespread use of mHealth systems; an accurate evaluation of the systems from the users' perspective is essential after the implementation and use of the system in daily health care practices. This study extends the expectation-confirmation model by using characteristics of individuals, technology, and tasks to identify critical factors affecting mHealth continuance and performance from the perspective of health care professionals (HCPs). METHODS:A questionnaire survey was used to collect data from HCPs who were experienced in using mHealth systems of a Taiwanese teaching hospital. In total, 282 questionnaires were distributed, and 201 complete and valid questionnaires were returned, thus indicating a valid response rate of 71.3% (201/282). The collected data were analyzed using WarpPLS version 5.0 (ScriptWarp Systems). RESULTS:The results revealed that mHealth continuance (R2=0.522) was mainly affected by perceived usefulness, technology maturity, individual habits, task mobility, and user satisfaction, whereas individual performance (R2=0.492) was affected by mHealth continuance. In addition, user satisfaction (R2=0.548) was affected by confirmation and perceived usefulness of mHealth, whereas perceived usefulness (R2=0.521) was affected by confirmation. This implied that confirmation played a key role in affecting perceived usefulness and user satisfaction. Furthermore, the results showed that mHealth continuance positively affected individual performance. CONCLUSIONS:The identified critical factors influencing mHealth continuance and performance can be used as a useful assessment tool by hospitals that have implemented mHealth systems to facilitate the use and infusion of the systems. Furthermore, the results can help health care institutions that intend to introduce or develop mHealth applications to identify critical issues and effectively allocate limited resources to mHealth systems.
| S-EPMC6441862 | biostudies-literature