Central or peripheral? Cognition elaboration cues’ effect on users’ continuance intention of mobile health applications in the developing markets

Consulting doctors online after offline treatment: investigating the effects of online information on patients' effective use of online follow-up services

Introduction

The use of online follow-up services (OFUS) is becoming an increasingly important supplement to hospital care. Through OFUS, patients can find their doctors in online health communities (OHCs) and receive remote medical follow-ups after hospital treatment. However, the rate of effective use of OFUS by current patients is still low, and there is an urgent need for research to investigate the online information factors that affect patients' effective use of OFUS.

Methods

Based on the elaboration likelihood model (ELM) of persuasion and an analysis of a panel dataset including 3,672 doctors in a leading OHC in China, this study explores how online information from doctors' knowledge contributions and patient feedback influences patients' effective use of OFUS.

Results

The results show that both doctors' knowledge contributions and patient feedback positively influence patients' effective use of OFUS. Doctors' paid knowledge contributions and patients' paid feedback have stronger persuasive effects than doctors' free knowledge contributions and patients' free feedback, respectively. Moreover, there is a substitutional relationship between doctors' paid and free knowledge contributions and between patients' paid and free feedback in influencing patients' effective use of OFUS.

Discussion

The findings of this study suggest that OHC platforms and healthcare providers should account not only for the persuasive effects of doctors' knowledge contributions and patient feedback but also for influential differences and relationships between the types of doctors' knowledge contributions and patient feedback to better persuade patients to effectively use OFUS.

Determining information system end-user satisfaction and continuance intension with a unified modeling approach

With the different characters of datatypes and large amount of data going to be managed in open-source database, localization to the specific linguistics is the major concern in Ethiopia, as the nation used different datatypes compared to the Gregorian systems. In this regard Amharic localization in open-source database can handle the difficulties in managing data for governmental and non-governmental organizations. Amharic Extension Module was introduced to governmental organizations for the data management capabilities. But, there is no research that can explore the system's quality, the users' satisfaction and intension of continuance of Amharic Extension Module from the perspective of both computer literates and illiterates. Therefore, this research work attempt or try to empirically examine and analyze the system quality, the users' satisfaction and intension of continuance of Amharic Extension Module from the perspective of all users in POESSA The major purpose/aim of this study/research is to brand or make up the research break/gap in the area of localization specific to the Amharic locals, and to show the implication of the practical and theoretical way based on the results of the research. For this purpose, questionnaires were used for the collection of the research data. A total of 395 copies of the questionnaires were distributed and 385 of them are collected without any problem from the organization indicated herewith. The statistical analysis tools such as SPSS and AMOS, and methods such as Structural equation model were used for the analysis of the research data. The results of the research recommended and suggested that system quality can significantly influence confirmation. Meanwhile, confirmation can directly and significantly influence perceived usefulness, performance expectations, and satisfaction. Additionally, performance expectation, perceived usefulness and confirmation can significantly impact/influence satisfaction. The satisfaction directly and most importantly and significantly influences the continuance intension. Finally, the research delivers/provides a concert indication for the legitimacy and validity of the integrated and combined models of UTUAT, ECTM, and D&M ISS in the field of localizations which can be a hypothetical and theoretical foundation for Amharic Extension Module-AEM users' and services of it.

The Influence of Anthropomorphic Cues on Patients' Perceived Anthropomorphism, Social Presence, Trust Building, and Acceptance of Health Care Conversational Agents: Within-Subject Web-Based Experiment

BACKGROUND

The last decade has witnessed the rapid development of health care conversational agents (CAs); however, there are still great challenges in making health care CAs trustworthy and acceptable to patients.

OBJECTIVE

Focusing on intelligent guidance CAs, a type of health care CA for web-based patient triage, this study aims to investigate how anthropomorphic cues influence patients' perceived anthropomorphism and social presence of such CAs and evaluate how these perceptions facilitate their trust-building process and acceptance behavior.

METHODS

To test the research hypotheses, the video vignette methodology was used to evaluate patients' perceptions and acceptance of various intelligent guidance CAs. The anthropomorphic cues of CAs were manipulated in a 3×2 within-subject factorial experiment with 103 participants, with the factors of agent appearance (high, medium, and low anthropomorphic levels) and verbal cues (humanlike and machine-like verbal cues) as the within-subject variables.

RESULTS

The 2-way repeated measures ANOVA analysis indicated that the higher anthropomorphic level of agent appearance significantly increased mindful anthropomorphism (high level>medium level: 4.57 vs 4.27; P=.01; high level>low level: 4.57 vs 4.04; P<.001; medium level>low level: 4.27 vs 4.04; P=.04), mindless anthropomorphism (high level>medium level: 5.39 vs 5.01; P<.001; high level>low level: 5.39 vs 4.85; P<.001), and social presence (high level>medium level: 5.19 vs 4.83; P<.001; high level>low level: 5.19 vs 4.72; P<.001), and the higher anthropomorphic level of verbal cues significantly increased mindful anthropomorphism (4.83 vs 3.76; P<.001), mindless anthropomorphism (5.60 vs 4.57; P<.001), and social presence (5.41 vs 4.41; P<.001). Meanwhile, a significant interaction between agent appearance and verbal cues (.004) was revealed. Second, the partial least squares results indicated that privacy concerns were negatively influenced by social presence (β=-.375; t312=4.494) and mindful anthropomorphism (β=-.112; t312=1.970). Privacy concerns (β=-.273; t312=9.558), social presence (β=.265; t312=4.314), and mindless anthropomorphism (β=.405; t312=7.145) predicted the trust in CAs, which further promoted the intention to disclose information (β=.675; t312=21.163), the intention to continuously use CAs (β=.190; t312=4.874), and satisfaction (β=.818; t312=46.783).

CONCLUSIONS

The findings show that a high anthropomorphic level of agent appearance and verbal cues could improve the perceptions of mindful anthropomorphism and mindless anthropomorphism as well as social presence. Furthermore, mindless anthropomorphism and social presence significantly promoted patients' trust in CAs, and mindful anthropomorphism and social presence decreased privacy concerns. It is also worth noting that trust was an important antecedent and determinant of patients' acceptance of CAs, including their satisfaction, intention to disclose information, and intention to continuously use CAs.

Do Vaping Prevention Messages Impact Adolescents and Young Adults? A Meta-Analysis of Experimental Studies

Vaping prevention messages are widely used to communicate the health harms and addiction risks of vaping and discourage vaping among adolescents and young adults. We conducted a meta-analysis of experimental studies to examine the effects of these messages and to understand their theoretical mechanisms. Systematic, comprehensive searches generated 4,451 references, among which 12 studies (cumulative N = 6,622) met inclusion criteria for the meta-analysis. Across these studies, a total of 35 different vaping-related outcomes were measured, and 14 outcomes assessed in two or more independent samples were meta-analyzed. Results showed that compared to control, exposure to vaping prevention messages led to higher vaping risk perceptions, including harm perceptions (d = 0.30, p < .001), perceived likelihood of harm (d = 0.23, p < .001), perceived relative harm (d = 0.14, p = .036), addiction perceptions (d = 0.39, p < .001), perceived likelihood of addiction (d = 0.22, p < .001), and perceived relative addiction (d = 0.33, p = .015). Also, compared to control, exposure to vaping prevention messages led to more vaping knowledge (d = 0.37, p < .001), lower intentions to vape (d = -0.09, p = .022), and higher perceived message effectiveness (message perceptions; d = 0.57, p < .001; effects perceptions; d = 0.55, p < .001). Findings suggest vaping prevention messages have an impact, yet may operate through different theoretical mechanisms than cigarette pack warnings.

Predicting students' continued intention to use E-learning platform for college English study: the mediating effect of E-satisfaction and habit

Using technology in education facilitates knowledge dissemination expediently while broadening and deepening learning modes and content diversity. As an information technological innovation, E-learning platform is widely used to learn college English. However, few studies have explored the motivations for students' e-satisfaction and continued intention towards using it for college English study. Based on the extended Unified Theory of Acceptance and Use of Technology (UTAUT2), this study identifies the influencing factors for the continued usage intention and tests the mediating role of e-satisfaction and habit. Six hundred and twenty-six usable responses from Guangxi were analyzed with partial least squares structural equation modelling. Results show that performance expectancy, learning value, hedonic motivation and habit positively affects students' continued usage intention, e-satisfaction positively mediates the relationship between the antecedents and continued usage intention, and habit positively mediates the relationship between e-satisfaction and continued usage intention. The research provides guidelines for the successful implementation of e-learning platform for college English study and key references for improvement of students' engagement and satisfaction experience with using e-learning platform for college English study.

A scale to measure the perceived quality of mHealth by elderly patients with hypertension in China

BACKGROUND

The elderly population in China is growing, with hypertension being the most prevalent chronic disease in older adults. Despite the rapid penetration and efficient management effect of mobile health on hypertension healthcare, elderly patients are often less adopted and continue to use mobile health services. Quality perception significantly affects an individual's satisfaction and continued intention to use mobile health services. The evaluation of the significant factors affecting mobile health quality perception by elderly individuals remains largely unexplored. The aim of this study was to develop and validate an evaluation scale to measure the perceived quality of mobile health applications for hypertension and determine the underlying influencing factors.

METHODS

A cross-sectional survey was conducted between November 2018 and October 2019. A quality evaluation scale with three factors and seven indicators was developed based on the Information Systems Success model. Data was analyzed using structural equations modelling (SEM) and one-way analysis of variance (ANOVA). All tests were two-sided and statistically significant at P < 0.05.

RESULTS

The proposed mobile health application quality evaluation scale from the perspective of the elderly was shown to be a hierarchical, multidimensional construct with valid reliability, convergent validity and discriminant validity, which consists of three factors and seven indicators. The SEM results suggested that information quality and service quality had a significant impact on the satisfaction of elderly individual's with mobile health applications for hypertension management. The results also suggest that the elderly individuals had a low evaluation of mobile medical service quality(4.06 ± 0.70), while the score of information quality was the highest, with an average score of 4.36(SD 0.83) out of 5. Male patients were shown to more readily accept mobile health applications, with their perception of system quality being 0.27 higher than female ones (95% CI 0.00 ~ 0.52; P < .05). Patients with 1-5 years hypertension histories assessed the system (95% CI 0.03 ~ 0.63; P < .05), information (95% CI 0.11 ~ 0.65; P < .05), and service quality (95% CI 0.00 ~ 0.47; P < .05) higher than those with hypertension histories > 10 years. Elderly patients who regularly visited primary hospitals assessed the information quality 0.13 higher (95% CI -0.08 ~ 0.34; P < .05) than those visited tertiary hospitals.

CONCLUSIONS

These findings have significant implications for theoretical and practical research on mobile health application quality evaluation, which will be helpful for policymakers and mobile health providers in improving the context and utilisation of mobile health to include elderly users. More mobile health applications attributes, such as timely information and interactive services that meet the characteristics of elderly patients with different mental and health demands need to be considered. Deeply embedding mobile health into primary health services is recommended to help increase the perceived quality of mobile health, and ensure the continuous use.

A fuzzy-set qualitative comparative analysis exploration of multiple paths to users' continuous use behavior of diabetes self-management apps

BACKGROUND

Despite the obvious potential benefits of diabetes self-management apps, users' continuous use of diabetes self-management apps is still not widespread. Influential factors coexisted in information ecologies are likely to have a synthetic effect on users' continuous use behavior. However, it is less clear how factors in information ecologies combine to influence users' continuous use behavior.

OBJECTIVE

The objectives of this study are to explore combinations of factors (perceived severity, information quality, service quality, system quality, and social influence) in information ecologies that lead to users' continuous use behavior of diabetes self-management apps and which combination is the most important.

METHODS

Purpose sampling was used to recruit diabetes self-management app users from July 1, 2021 to January 31, 2022. Fuzzy-set qualitative comparative analysis (fsQCA) was then employed by conducting necessity and sufficiency analysis.

RESULTS

In total 280 diabetes self-management app users participated. The necessity analysis indicated that no single factor was necessary to cause users' continuous use behavior, and the sufficiency analysis identified five different combinations of factors that lead to users' continuous use behavior. Of these five, the combination of high information quality, high service quality, and high social influence was found to be the most important path.

CONCLUSIONS

Users' continuous use behavior of diabetes self-management apps results from the synergistic effects of factors in information ecologies. The five paths that directly contribute to users' continuous use, as well as the four user types preliminarily identified in this study may provide a reference for healthcare providers and app developers.

Understanding Post-Adoption Behavioral Intentions of Mobile Health Service Users: An Empirical Study during COVID-19

This study aims to understand the post-adoption behaviors of mobile health (m-Health) service users during the COVID-19 pandemic. Drawing on the stimulus-organism-response framework, we examined the effects of user personality traits, doctor characteristics, and perceived risks on user continuance intentions and positive word of mouth (WOM) when using m-Health, as mediated by cognitive and emotional trust. The empirical data were collected via an online survey questionnaire from 621 m-Health service users in China and were verified with partial least squares structural equation modeling. The results showed that personal traits and doctor characteristics were positively associated and the perceived risks were negatively associated with both cognitive and emotional trust. Both cognitive and emotional trust significantly influenced users' post-adoption behavioral intentions in terms of continuance intentions and positive WOM, with different magnitudes. This study provides new insights for the promotion of the sustainable development of m-Health businesses after or during the pandemic.

Counseling for Health: How Psychological Distance Influences Continuance Intention towards Mobile Medical Consultation

As mobile healthcare services entered the public sight with high frequency during the COVID-19 pandemic, patients are increasingly recognizing the effectiveness of mobile medical consultation (MMC). Earlier studies have investigated what influences continuance intention (CI) towards MMC, but few studies have scrutinized it from the perspective of patients' psychological distance. We formulated a framework to examine the psychological factors influencing CI towards MMC by integrating the information systems continuance model and psychological distance theory. The framework was validated using the partial least squares structural equation modeling (PLS-SEM) approach and data from 475 MMC users in China. The empirical results revealed that immediacy, telepresence, intimacy, and substitutability were significant predictors of CI, while satisfaction mediated these pathways. Pandemic-induced anxiety positively moderated the effect of immediacy on satisfaction and the effect of satisfaction on CI. Practical implementations for MMC healthcare practitioners, designers, and marketers are drawn.

Understanding the adoption of the mask-supply information platforms during the COVID-19

Since late 2019, coronavirus disease 2019 (COVID-19) has led to a significant increase in the demand for medical resources. To publish data on face mask supplies, the Taiwanese government collaborated with program developers to construct a mask-supply information transitional platform (MITP). To comprehend the adoption of MITP, the study proposes a research model that integrates the health behavior model (HBM) and IS/IT continuance model for examining the factors affecting intention to use an MITP. Survey data collected from 524 respondents indicated that (1) intention to use an MITP is directly influenced by perceived threat of COVID-19 and beliefs toward using the MITP; (2) cues to action directly influence the perceived threat of COVID-19; and (3) perceived ease of use of MITP is a significant determinant of perceived usefulness of MITP. These results provide practical guidelines for health authorities and government to develop health information systems and strategies to control pandemics.

Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis

The mobile health (mHealth) industry is an enormous global market; however, the dropout or continuance of mHealth is a major challenge that is affecting its positive outcomes. To date, the results of studies on the impact factors have been inconsistent. Consequently, research on the pooled effects of impact factors on the continuance intention of mHealth is limited. Therefore, this study aims to systematically analyze quantitative studies on the continuance intention of mHealth and explore the pooled effect of each direct and indirect impact factor. Until October 2021, eight literature databases were searched. Fifty-eight peer-reviewed studies on the impact factors and effects on continuance intention of mHealth were included. Out of the 19 direct impact factors of continuance intention, 15 are significant, with attitude (β = 0.450; 95% CI: 0.135, 0.683), satisfaction (β = 0.406; 95% CI: 0.292, 0.509), health empowerment (β = 0.359; 95% CI: 0.204, 0.497), perceived usefulness (β = 0.343; 95% CI: 0.280, 0.403), and perceived quality of health life (β = 0.315, 95% CI: 0.211, 0.412) having the largest pooled effect coefficients on continuance intention. There is high heterogeneity between the studies; thus, we conducted a subgroup analysis to explore the moderating effect of different characteristics on the impact effects. The geographic region, user type, mHealth type, user age, and publication year significantly moderate influential relationships, such as trust and continuance intention. Thus, mHealth developers should develop personalized continuous use promotion strategies based on user characteristics.

The Determinants of User Acceptance of Mobile Medical Platforms: An Investigation Integrating the TPB, TAM, and Patient-Centered Factors

Mobile medical platforms (MMPs) can make medical services more accessible and effective. However, the patient-centered factors that influence patients' acceptance of MMPs are not well understood. Our study examined the factors affecting patients' acceptance of MMPs by integrating the theory of planned behavior (TPB), the technology acceptance model (TAM), and three patient-centered factors (i.e., perceived convenience, perceived credibility, and perceived privacy risk). Three hundred and eighty-nine Chinese respondents were recruited in this study and completed a self-administered online questionnaire that included items adapted from validated measurement scales. The partial least squares structural equation modeling results revealed that perceived privacy risk, perceived credibility, and perceived ease of use directly determined the perceived usefulness of an MMP. Perceived convenience, perceived credibility, and perceived usefulness significantly affected the patients' attitudes toward MMPs. Perceived usefulness, attitude, perceived privacy risk, and perceived behavioral control were important determinants of the patients' behavioral intentions to use MMPs. Behavioral intention and perceived behavioral control significantly influenced perceived effective use. Perceived credibility and perceived ease of use significantly affected perceived convenience. However, social influence had no significant effect on attitude and behavioral intention. The study provides important theoretical and practical implications, which could help practitioners enhance the patients' use of MMPs for their healthcare activities.

Determinants of the Mobile Health Continuance Intention of Elders with Chronic Diseases: An Integrated Framework of ECM-ISC and UTAUT

With the deepening of population aging in China, chronic diseases are a major public health concern that threatens the life and health of nationals. Mobile health or mHealth can effectively monitor chronic diseases, which holds vital significance to the alleviation of social pressure caused by aging. To patients with chronic diseases, mHealth cannot give full play to its value, only when it is used in the long term. However, there is not yet research exploring mHealth continuance intention from the perspective of elders with chronic diseases. So, this research represents the first attempt to empirically analyze mHealth continuance intention from the perspective of elders with chronic diseases. The purpose of this research is to make up the research gap of the mHealth field and to put forward theoretical and practical implications based on research results. To obtain research data, a questionnaire was conducted. A total of 926 copies were collected online and 527 copies were collected offline. The structural equation model (SEM) was used for data analysis. Research results suggest that confirmation can significantly influence satisfaction, performance expectancy and effort expectancy. Meanwhile, confirmation and performance expectancy can significantly influence satisfaction. Additionally, effort expectancy, performance expectancy, social influence and facilitating conditions can directly and significantly influence continuance intention. Among them, performance expectancy can directly influence continuance intention in the most significant way. This research provides solid evidence for the validity of the integrated model of ECM-ISC and UTAUT in the mHealth field, which can be a theoretical basis for mHealth operators' product R&D.

Adoption of mobile health services using the unified theory of acceptance and use of technology model: Self-efficacy and privacy concerns

Mobile health (mHealth) services have been widely used in medical services and health management through mobile devices and multiple channels, such as smartphones, wearable equipment, healthcare applications (Apps), and medical platforms. However, the number of the users who are currently receiving the mHealth services is small. In China, more than 70% of internet users have never used mHealth services. Such imbalanced situation could be attributed to users’ traditional concept of medical treatment, psychological factors (such as low self-efficacy) and privacy concerns. The purpose of this study is to explore the direct and indirect effects of mHealth users’ self-efficacy and privacy concerns on their intention to adopt mHealth services, providing guidelines for mHealth service providers to enhance users’ intention of adoption. A questionnaire was designed by the research team and 386 valid responses were collected from domestic participants in China. Based on the unified theory of acceptance and use of technology (UTAUT) model, a research model integrated self-efficacy and privacy concerns was constructed to investigate their effects on users’ intention to adopt mobile mHealth services. The results show that self-efficacy could facilitate users’ intention to adopt mHealth services, and had a significantly positive effect on perceived ubiquity, effort expectancy, performance expectancy and subjective norm. This study verifies the direct and indirect effects of self-efficacy and privacy concerns on users’ intention to adopt mHealth services, providing a different perspective for studying mHealth adoption behavior. The findings could provide guidelines for mHealth service providers to improve their service quality and enhance users’ intention of adoption.

Exploring the information quality of mobile government services: a literature review

This article aims to investigate the constructs that can be used to evaluate the information quality (IQ) of mobile government services. The dimension of IQ is one of the fundamental constructs that assesses the extent of information based on its accuracy, usefulness, and timeliness. Based on the review of previous studies, there is a lack of studies related to mGovernment service quality. It is not practical to measure the service quality of mGovernment by using other measurement scales such as e-service, e-commerce, or e-government. Therefore, it is necessary to understand each dimension that guides constructing a comprehensive framework to measure service quality at mGovernment. The constructs of information quality were extracted from previous literature in mobile government, mobile application service, and e-government to understand the development stages, structure, and unique features-this guide to conduct the systematic literature review to clarify the constructs belonging to the evaluation of information quality. The present article identified six constructs-understandability, timeliness, accuracy, completeness, availability, and usefulness-to measure the information quality of mobile government service. There is limited literature on mGovernment information service quality. With the development of government services on mobile devices, it is necessary to measure information quality at mGovernment service channel to understand users' expectations. The mGovernment service provider benefits from measuring the service quality by improving the strategy and criteria of information at mGovernment portal. In addition, the end-users expect to perform the service with the best quality level of the information supplied and displayed on mGovernment platform.

Online health management continuance and the moderating effect of service type and age difference: A meta-analysis

Numerous empirical studies have been carried out to explore factors of online health management continuance. However, results were not unified. We thus conducted a meta-analysis to identify influential factors and potential moderators. A systematic literature search was performed in nine databases (PubMed, Web of Science, the Cochrane Library, Ovid of JBI, CINAHL, Embase, CNKI, VIP, and CBM) published up to December 2020 in the English or Chinese language. Meta-analysis of combined effect size, heterogeneity, moderator analysis, publication bias assessment, and inter-rater reliability was conducted. Totally 41 studies and 12 pairwise relationships were identified. Confirmation, perceived usefulness, satisfaction, information quality, service quality, perceived ease of use, and trust were all critical predictors. Service type and age difference showed their moderating effects respectively. The perceived usefulness was more noteworthy in medical service than health and fitness service. The trust was more noteworthy in young adults. The results confirmed the validity and robustness of the Expectation Confirmation Model, Information Systems Success Model, and trust theory in online health management continuance. Moderators included but are not limited to age difference and service type. The elderly research in the healthcare context and other analytical methods such as qualitative comparative analysis should be applied in the future.

Making Mobile Health Information Advice Persuasive

As M-Health apps become more popular, users can access more mobile health information (MHI) through these platforms. Yet one preeminent question among both researchers and practitioners is how to bridge the gap between simply providing MHI and persuading users to buy into the MHI for health self-management. To solve this challenge, this study extends the Elaboration Likelihood Model to explore how to make MHI advice persuasive by identifying the important central and peripheral cues of MHI under individual difference. The proposed research model was validated through a survey. The results confirm that (1) both information matching and platform credibility, as central and peripheral cues, respectively, have significant positive effects on attitudes toward MHI, but only information matching could directly affect health behavior changes; (2) health concern significantly moderates the link between information matching and cognitive attitude and only marginally moderates the link between platform credibility and attitudes. Theoretical and practical implications are also discussed.

Trust Transfer in Sharing Accommodation: The Moderating Role of Privacy Concerns

Sharing accommodation (SA) has gained rapid growth in the last decade. To offer better service to users, the platform and hosts have to extensively collect and utilize confidential user data and information. With the extensive collection and utilization of personal user information, there are potential problems of data abuse and leakage, which makes users’ privacy concerns an important and unavoidable issue for repeated purchases and the sustainable development of SA. Privacy concerns are thus not only an important antecedent of purchase behaviors, but also an important conditional variable that will have impacts on the formation of trust and user purchase behaviors. However, the moderating effect of privacy concerns on trust formation has rarely been examined in the SA literature. To fill this knowledge gap, drawing on trust transfer theory and trust literature, this study builds a theoretical model to examine the relationships of three types of institution-based trust (i.e., trust in the SA platform, trust in the user community, and trust in the host community) and their effects on continuous use intention. Moreover, this study explores the moderating effect of privacy concerns on institution-based trust transfer in the context of SA. We then collected data through a questionnaire survey from experienced users of two reputable SA platforms in China, and empirically tested the research model with 470 valid responses. The results show that trust in the user community positively affects trust in the SA platform and trust in the host community; trust in the SA platform and trust in the host community positively affect users’ continuous use intention. Meanwhile, privacy concerns negatively moderate the relationship between trust in the user community and trust in the SA platform, as well as the relationship between trust in the user community and trust in the host community. The findings confirm the moderating role of privacy concerns in the trust transfer process, complementing existing research on trust transfer theory and trust.

Understanding the Antecedents of the Routine Use of Mobile Health Services: A Person–Technology–Health Framework

Although numerous studies have been conducted to understand the antecedents of usage of mobile health (mHealth) services, most of them solely focus on characteristics of mHealth services themselves but neglect taking users’ psychological and health-related factors into consideration. Besides, the comprehensive understanding of what influences users’ routine use intentions regarding mHealth services is lacking. Therefore, this study proposes a person–technology–health framework that underlines how personal factors (e.g., personal innovativeness in IT), technological factors (e.g., trust), and health factors (e.g., perceived health severity) jointly influence individuals’ routine use intentions regarding mHealth services. The proposed research model and related hypotheses were tested based on survey data from 270 respondents. The results indicate that personal innovativeness in IT, trust, and perceived health severity are important for enhancing routine use intention of mHealth services. Specifically, in situations of high perceived health severity, trust relates less positively to routine use intention than personal innovativeness in IT. In contrast, in situations of low perceived health severity, trust relates more positively to routine use intention than personal innovativeness in IT. The research findings extend the existing literature on routine use intention related to mHealth services and provide significant implications for practitioners.

Understanding the Drivers of Ghanaian Citizens' Adoption Intentions of Mobile Health Services

Mobile health (m-health) application development and diffusion in developing countries have always been a challenge; therefore, research that seeks to provide an elucidation of the drivers of m-Health adoption is vital. Mobile health information systems and applications can contribute to the delivery of a good healthcare system. This study examined the factors influencing citizens' adoption of mobile health services. The Technology Acceptance Model (TAM) was used as the research underpinning for this study, while the data gathered were analyzed with SmartPLS through the use of the structural equation modeling technique. The results showed that perceived usefulness and ease of use were both significant predictors of the behavioral intention to use and recommend the adoption of mobile health services. Also, perceived risk was negative but significant in predicting the intention to use and recommend adoption. Mobile self-efficacy was found to significantly determine the behavioral intention to use, intention to recommend, perceived usefulness, and perceived ease of use of mobile health services. Besides, word-of-mouth showed a positive impact on both the intention to use and recommend. Contrary to expectations, the intention to use had no significant impact on the recommendation intention. The theoretical and practical implications of these findings are thoroughly examined.

Factors Affecting Medical Students’ Continuance Intention to Use Mobile Health Applications

Background

With the dramatic growth in smartphones, mobile health applications (apps) in the field of healthcare or medicine, which are characterized by strong operability, flexibility and interactivity, provide a supplementary approach to medical learning. The aims of this study were to awaken medical students to pay more attention to the learning function of mobile health app and gain deeper insight into our understanding of the factors influencing medical students’ mobile health apps continuance intention for enhancing practical utilization.

Methods

A cross-sectional survey was conducted with a self-designed questionnaire administered to medical students at Chongqing Medical University. Data were collected from 450 participants from March to April 2019. SPSS V.25 was used for the descriptive statistical analysis of the results. Smart PLS 3.2.7 was used to construct a structural equation modelling framework to estimate the influencing factors of medical students’ continuance intention to use mobile health apps.

Results

The external characteristics of mobile health apps had a positive influence on perceived ease of use (β = 0.378, P < 0.001). Perceived ease of use had a positive impact on perceived usefulness (β = 0.573, P < 0.001). Perceived ease of use (β = 0.195, P = 0.011), perceived usefulness (β = 0.450, P < 0.001) and subjective norms (β = 0.255, P < 0.001) had a positive impact on attitude towards using mobile health apps. Additionally, perceived usefulness (β = 0.202, P < 0.001) and attitude (β = 0.730, P < 0.001) had a remarkable influence on continuance intention. Furthermore, the mediating effect of attitude between perceived usefulness and continuance intention was significant (β = 0.329, P < 0.001).

Conclusion

Both perceived usefulness and attitude have a significant effect on medical students’ mobile health apps continuance intention. So, we suggest apps providers and developers evoking and maintaining users’ interest in mobile health apps and perfecting apps’ features from various aspect. Also, more attention should be paid on social relationship to introduce medical students to familiarize mobile health apps and strengthen adhesiveness of medical students.

A study investigating user adoptive behavior and the continuance intention to use mobile health applications during the COVID-19 pandemic era: Evidence from the telemedicine applications utilized in Indonesia

During the COVID-19 pandemic era that began in 2020, there has been a growing trend in the literature to tackle the problem of health stress (HS) for promoting a sense of public health. In turn, this developing area of research has a high level of relevancy linked to business and economic recovery (Čvirik, 2020). Since HS has increased sharply during the COVID-19 pandemic era, there has been a need to further investigate the balance between coping with HS and the positive continuous intention to use mobile health applications (mHealth apps) among the public. This is the first study that takes the Asia-Pacific region as its case study and empirically investigates the validity of extensions based on the theories of expectation confirmation theory (ECT) (Bhattacherjee, 2001) on user continuous behavior relating to mHealth apps during the COVID-19 pandemic. Results reveal that HS as an emotion can positively affect perceived usefulness and satisfaction in relation to the continuous intention to use mHealth apps. The differences between new and frequent users are confirmed. Discussion and implications for practices are provided in the end.

Drivers of digital transformation adoption: A weight and meta-analysis

The advent of the global pandemic has accelerated the growing need for product and service transformation, highlighting the emerging importance of technology and creating the opportunity to update the digital transformation (DT) domain through empirical-quantitative research. This weight and meta-analysis enabled the synthesis and integration of previous literature on the scope of individual DT adoption, evaluating the state of the art and filling a void on the subject. Athwart 88 studies and 99 datasets by international sources, our results demonstrate that attitude and satisfaction are relevant predictors of behavioral intentions and promising outcomes, including compatibility and personal innovativeness. Behavioral intentions, satisfaction, and habit are the best predictors for DT use. Usefulness and ease of use are critical for DT adoption intention and use, being moderated by individualism, as a cultural factor, human capital, and knowledge-technology, as innovation indicators. We present a conceptual model of promising and best predictors for future research on DT individual adoption.

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An update of digital transformation (DT) through a weight and meta-analysis.

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Contribution to DT literature by surpassing biases and limitations of size estimates.

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Identification of promising and best predictors for further DT adoption research.

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Behavioral intentions, satisfaction, and habit are best predictors for DT use.

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Usefulness and ease of use are pivotal, being moderated by culture and innovation.

ACCU3RATE: A mobile health application rating scale based on user reviews

Background

Over the last decade, mobile health applications (mHealth App) have evolved exponentially to assess and support our health and well-being.

Objective

This paper presents an Artificial Intelligence (AI)-enabled mHealth app rating tool, called ACCU³RATE, which takes multidimensional measures such as user star rating, user review and features declared by the developer to generate the rating of an app. However, currently, there is very little conceptual understanding on how user reviews affect app rating from a multi-dimensional perspective. This study applies AI-based text mining technique to develop more comprehensive understanding of user feedback based on several important factors, determining the mHealth app ratings.

Method

Based on the literature, six variables were identified that influence the mHealth app rating scale. These factors are user star rating, user text review, user interface (UI) design, functionality, security and privacy, and clinical approval. Natural Language Toolkit package is used for interpreting text and to identify the App users’ sentiment. Additional considerations were accessibility, protection and privacy, UI design for people living with physical disability. Moreover, the details of clinical approval, if exists, were taken from the developer’s statement. Finally, we fused all the inputs using fuzzy logic to calculate the new app rating score.

Results and conclusions

ACCU³RATE concentrates on heart related Apps found in the play store and App gallery. The findings indicate the efficacy of the proposed method as opposed to the current device scale. This study has implications for both App developers and consumers who are using mHealth Apps to monitor and track their health. The performance evaluation shows that the proposed mHealth scale has shown excellent reliability as well as internal consistency of the scale, and high inter-rater reliability index. It has also been noticed that the fuzzy based rating scale, as in ACCU³RATE, matches more closely to the rating performed by experts.

Kuwaiti hospital patients' continuance intention to use telemedical systems in the wake of the COVID19 pandemic

The objective of this study is to investigate factors influencing patients' continuance intention to use telemedicine after the COVID-19 pandemic in the medical sector of Kuwait. To reach this purpose, the updated Delone and Maclean (2003) model was utilized to investigate the aforementioned factors. As such, this research applied quantitative research methods with a sample of 290 participants from patients in Dar Al Shifa Hospital, a private hospital in Kuwait which utilizes telemedical services called 'Sehaty online'. The corresponding data was analyzed using SmartPLS. The findings of this study revealed that information quality and system quality have a positive and significant influence on patient's satisfaction, whereas service quality has an insignificant influence on patient's satisfaction. Also, patients' continuance intention to use telemedicine is found to be significantly impacted by their satisfaction. Furthermore, several limitations of the study, related future research, and recommendations have been discussed.

Factors Affecting User Intention to Pay via Online Medical Service Platform

With regard to platform performance and trust, we study the influencing factors of users’ intention to pay on an online medical service platform. Results of this paper will provide a new perspective for online medical service platform research in the context of the Internet.A questionnaire survey is administered to collect 312 effective sample data, and the data are analyzed by partial least squares structural equation modeling. Results showed that the information quality, system quality, and convenience of the platform significantly affect the perceived benefit (PB) of users. Users’ perceived reliability of the platform significantly positively affects doctor reliability (DR). Users’ PB significantly positively affects their ITP and DR, and DR significantly positively affects the users’ ITP. The misdiagnosis risk positively regulates the relationship between the users’ trust tendency and DR. The timeliness of the response of the platform positively adjusts the relationship between DR and users’ ITP.

Exploring the Impact of Linguistic Signals Transmission on Patients' Health Consultation Choice: Web Mining of Online Reviews

BACKGROUND

Patients face difficulties identifying appropriate physicians owing to the sizeable quantity and uneven quality of information in physician rating websites. Therefore, an increasing dependence of consumers on online platforms as a source of information for decision-making has given rise to the need for further research into the quality of information in the form of online physician reviews (OPRs).

METHODS

Drawing on the signaling theory, this study develops a theoretical model to examine how linguistic signals (affective signals and informative signals) in physician rating websites affect consumers' decision making. The hypotheses are tested using 5521 physicians' six-month data drawn from two leading health rating platforms in the U.S (i.e., Healthgrades.com and Vitals.com) during the COVID-19 pandemic. A sentic computing-based sentiment analysis framework is used to implicitly analyze patients' opinions regarding their treatment choice.

RESULTS

The results indicate that negative sentiment, review readability, review depth, review spelling, and information helpfulness play a significant role in inducing patients' decision-making. The influence of negative sentiment, review depth on patients' treatment choice was indirectly mediated by information helpfulness.

CONCLUSIONS

This paper is a first step toward the understanding of the linguistic characteristics of information relating to the patient experience, particularly the emerging field of online health behavior and signaling theory. It is also the first effort to our knowledge that employs sentic computing-based sentiment analysis in this context and provides implications for practice.

Proposing a mobile apps acceptance model for users in the health area: A systematic literature review and meta-analysis

Due to rapid advancements in the field of information and communication technologies, mobile health (mHealth) has become a significant topic in the delivery of healthcare. Despite the perceived advantages and the large number of mHealth initiatives, the success of mHealth ultimately relies on whether these initiatives are used; their benefits will be diminished should people not use them. Previous literature has found that the adoption of mHealth by users is not yet widespread, and little research has been conducted on this problem. Therefore, this study identifies the antecedents of the intention to use mHealth and proposes a general model that might prove beneficial in explaining the acceptance of mHealth. The authors performed a quantitative meta-analysis of 49 journal papers published over the past 10 years and systematically reviewed the evidence regarding the most commonly identified factors that may affect the acceptance of mHealth. The findings indicate that the proposed model includes the seven most commonly used relationships in the selected articles. More specifically, the model assumes that perceived usefulness positively affects perceived ease of use and user behavioral intention to use mHealth is commonly influenced by five factors: perceived usefulness, perceived ease of use, attitude toward behavior, subjective norms, and facilitating conditions. The results of this work provide important insights into the predictors of mHealth acceptance for future researchers and practitioners.

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

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.

Re-Examining the Impact of Multidimensional Trust on Patients' Online Medical Consultation Service Continuance Decision

Recent years have witnessed the rapid growth of an emerging digital healthcare service - online medical consultation (OMC). Despite its popularity, many OMC platforms have encountered issues in initial adoption and continuance use among patients. We posit that many of the hesitation and resistance may arise from a lack of trust toward OMC, which is a complex phenomenon that involves both interpersonal and technological-oriented considerations. This study seeks to clarify the conceptualization of online trust in the context of OMC. It compares two plausible explanations (i.e., trust as a direct cause vs. trust as a moderator) regarding how interpersonal and technological trust contributes to the service continuance decision in OMC. By contextualizing the valence framework, we identify the critical factors in making the risk-benefit assessment of patients' OMC decision. We conduct an online survey of 365 experienced OMC users and analyze our structural model using a partial least square approach. Our results show that the multidimensional conceptualization approach, which incorporates both interpersonal and technological aspects of trust, is superior to the unitary approach. Besides, our findings suggest that the role trust plays in determining service continuance decisions in OMC is more of a direct cause than a qualifier that buffers the impacts of risk-benefit evaluation. We believe the findings can help both researchers and practitioners recognize the multidimensional perspective of trust and better understand the role trust plays in OMC and other online healthcare delivery problems.

Trust and elderly users' continuance intention regarding mobile health services: the contingent role of health and technology anxieties

Purpose

Mobile health (mHealth) services are considered an important means of relieving the problems of the aging population. The efficiency of mHealth services can be enhanced by engaging more elderly users and guaranteeing their continued use. However, limited attention has been directed toward investigating elderly users' continuance intention regarding mHealth services. The purpose of this paper is to explain elderly users' continuance intention by investigating the contingent role of technology anxiety and health anxiety on affective trust and cognitive trust.

Design/methodology/approach

Survey data were collected from 232 elderly users to verify the research model and hypotheses based on structural equation modeling (SEM).

Findings

This study revealed that both affective and cognitive trust enhance elderly users' continuance intention regarding their use of mHealth services. Health anxiety strengthens the effect of cognitive trust but weakens the effect of affective trust with regard to continuance intention. Furthermore, technology anxiety strengthens the effect of affective trust but not the effect of cognitive trust with regard to continuance intention.

Originality/value

This study is one of the first to examine elderly users' continuance intention regarding mHealth services use from the perspective of affective and cognitive trust, thus enriching the extant literature on the use of mHealth services. Additionally, this study sheds light on the contingent effects of technology anxiety and health anxiety on affective and cognitive trust, which have been neglected by previous research.

The role of self-efficacy and information processing in weight loss during an mHealth behavioral intervention

Self-efficacy (SE) and information processing (IP) may be important constructs to target when designing mHealth interventions for weight loss. The goal of this study was to examine the relationship between SE and IP with weight loss at six-months as part of the Dietary Interventions Examining Tracking with mobile study, a six-month randomized trial with content delivered remotely via twice-weekly podcasts. Participants were randomized to self-monitor their diet with either a mobile app (n = 42) or wearable Bite Counter device (n = 39). SE was assessed using the Weight Efficacy Life-Style Questionnaire and the IP variables assessed included user control, cognitive load, novelty, elaboration. Regression analysis examined the relationship between weight loss, SE change & IP at six months. Results indicate that elaboration was the strongest predictor of weight loss (ß =−0.423, P = 0.011) among all SE & IP variables and that for every point increase in elaboration, participants lost 0.34 kg body weight.

Investigating Patients' Intention to Continue Using Teleconsultation to Anticipate Postcrisis Momentum: Survey Study

Background

The COVID-19 crisis has drastically changed care delivery with teleconsultation platforms experiencing substantial spikes in demand, helping patients and care providers avoid infections and maintain health care services. Beyond the current pandemic, teleconsultation is considered a significant opportunity to address persistent health system challenges, including accessibility, continuity, and cost of care, while ensuring quality.

Objective

This study aims at identifying the determinants of patients’ intention to continue using a teleconsultation platform. It extends prior research on information technology use continuance intention and teleconsultation services.

Methods

Data was collected in November 2018 and May 2019 with Canadian patients who had access to a teleconsultation platform. Measures included patients’ intention to continue their use; teleconsultation usefulness; teleconsultation quality; patients’ trust toward the digital platform, its provider. and health care professionals; and confirmation of patients’ expectations toward teleconsultation. We used structural equation modeling employing the partial least squares component-based technique to test our research model and hypotheses.

Results

We analyzed a sample of 178 participants who had used teleconsultation services. Our findings revealed that confirmation of expectations had the greatest influence on continuance intention (total effects=0.722; P<.001), followed by usefulness (total effects=0.587; P<.001) and quality (total effects=0.511; P<.001). Usefulness (β=.60; P<.001) and quality (β=.34; P=.01) had direct effects on the dependent variable. The confirmation of expectations had direct effects both on usefulness (β=.56; P<.001) and quality (β=.75; P<.001) in addition to having an indirect effect on usefulness (indirect effects=0.282; P<.001). Last, quality directly influenced usefulness (β=.34; P=.002) and trust (β=.88; P<.001). Trust does not play a role in the context under study.

Conclusions

Teleconsultation is central to care going forward, and it represents a significant lever for an improved, digital delivery of health care in the future. We believe that our findings will help drive long-term teleconsultation adoption and use, including in the aftermath of the current COVID-19 crisis, so that general care improvement and greater preparedness for exceptional situations can be achieved.

Understanding the Drivers of Wearable Health Monitoring Technology: An Extension of the Unified Theory of Acceptance and Use of Technology

The market for wearable health monitoring technology is promising globally and in Saudi Arabia particularly. The country has a very high prevalence of chronic diseases that can be managed using wearable health monitoring technology. However, wearable devices are not fully advantageous if people do not accept them. Due to the parsimony of studies on the acceptance of wearable health monitoring technology, understanding the key drivers of using wearable health monitoring technology remains uncertain. This cross-sectional study extends the extended unified theory of acceptance and use of technology (UTAUT2) to explain the variance in the adoption intention of wearable health monitoring technology. A total of 256 responses were analyzed using the partial least squares structural equation modeling technique, in addition to the importance-performance map analysis. The results indicate that performance expectancy (PE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM) and habit (HA) significantly impact users’ behavioral intention (BI) to adopt wearable health monitoring technology. The results also demonstrate that effort expectancy (EE), price value (PV), government health policy (GHP) and trust (TR) are not important. Based on the findings, this research presents a set of recommendations for decisions makers, managers and system developers in the healthcare sector to enhance the use and quality of wearable technology.

Tianxia120: A Multimodal Medical Data Collection Bioinformatic System for Proactive Health Management in Internet of Medical Things

A digital medical health system named Tianxia120 that can provide patients and hospitals with “one-step service” is proposed in this paper. Evolving from the techniques of Internet of Medical Things (IoMT), medical dig data, and medical Artificial Intelligence, the system can systematically promote the change of service status between doctors and patients from “passive mode” to “proactive mode” and realize online service that is similar to offline medical treatment scenarios. The system consists of a patient terminal and a doctor terminal. They can perform online inquiry (through graphic, voice, telephone, video, etc.), electronic prescription, multiparameter self-diagnosis, cold chain logistics, medicine distribution, etc. The system can provide rich medical health information, medical tools browsing, and health care big data aggregation processing functions. Compared with the traditional medical system, this system has the characteristics of full function, rich data, and high security. It is expected to be applied to hospital applications and medical research to promote the construction and innovation of clinical medical disciplines.

Consumers' continuance intention to use fitness and health apps: an integration of the expectation–confirmation model and investment model

Purpose

This study aimed to explore consumers' continuance intention to use a fitness and health app by applying two theoretical models: the expectation–confirmation model (ECM) and the investment model (IM).

Design/methodology/approach

An online survey was administered to consumers who are currently using fitness and health apps (N = 342). Structural equation modeling (SEM) was conducted using Amos 22.0 software to examine the hypothesized relationships in the research model.

Findings

Results revealed that users' continuance intention was significantly predicted by the two models. Within the ECM, the positive and significant relationships among variables were found. Moreover, users' satisfaction and investment size had positive impacts on their commitment, which, in turn, positively affected the intention. Also, confirmation of expectations had a positive impact on investment size.

Originality/value

The integrated model helps better understand fitness and health app users' decision-making process from the perspective of relationship commitment and suggests practical implications for health and fitness app providers.

Examining User's Initial Trust Building in Mobile Online Health Community Adopting

Due to the high perceived risk, it is critical to foster users’ initial trust in the promotion of mobile online health community (MOHC) adoption. The present study focused on the role of two different trust elements and examined the initial trust building process based on elaboration likelihood model and trust transfer theory. The results indicated that initial trust in MOHC context was composed of two interrelated components: health service provider (doctor) and underlying technology (MOHC platform). Especially, the initial trust in MOHC platform exerted greater effects on adopting intention. Both performance-based cue (doctors’ information quality and interaction quality) and transfer-based cue (trust in the offline doctors’ health service) positively shaped the initial trust in doctor. Meanwhile, only the performance-based cue (MOHC platform’s information quality and service quality) has significant positive association with initial trust in MOHC platform. However, interpersonal recommend is insignificantly related to the initial trust in doctor. Trust in the mobile internet service is insignificantly related to the initial trust in MOHC platform.

Determinant Factors of Public Acceptance of Stress Management Apps: Survey Study

BACKGROUND

Chronic stress is a major public health concern. Mobile health (mHealth) apps can help promote coping skills in daily life and prevent stress-related issues. However, little is known about the determinant factors of public acceptance of stress management in relation to preferences for psychological services.

OBJECTIVE

The aim of this survey study was to (1) assess determinant factors of public acceptance (behavioral use intention) of stress management apps based on an adapted and extended version of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and (2) explore preferences for mHealth apps compared with other mental health services.

METHODS

Using convenience sampling, participants completed a multiscale 54-item Web-based survey. Based on significant correlations with acceptance, hierarchical stepwise regression analysis was performed within three blocks: (1) background and stress-related control variables, (2) beliefs and attitudes toward using mHealth, and (3) the core UTAUT determinants. The preference for mHealth apps in comparison with nine other mental health services (operationalized as readiness to use) was analyzed using paired t tests.

RESULTS

Of 141 participants, nearly half (69/141, 48.9%) indicated prior mHealth use. Acceptance of stress coping apps was moderate (mean 3.10, SD 1.03, range 1-5). Hierarchical stepwise regression including four of 11 variables (R²=.62; P=.01, f²=1.63) identified positive attitudes toward using mHealth for stress coping (beta=0.69, P<.001, 46% R² increase above block 1, f²=0.85), skepticism/perceived risks (beta=-0.14, P=.01, f²=0.16), and stress symptoms (beta=0.12, P=.03, f²=0.14) as significant predictors of acceptance. UTAUT determinants added no predictive contribution beyond attitudes (all P>.05, R² increase of 1%), whereas post hoc analysis showed significant R² increases of attitudes and skepticism/perceived risks beyond UTAUT determinants (all P<.001, R² increase of 13%). The readiness to use apps was equivalent to or significantly higher than most service types, but lower than information websites.

CONCLUSIONS

Attitudes may be at least as predictive for the acceptance of stress management apps as for more elaborated outcome beliefs. Efforts aimed at improving the public adoption of mHealth could put more emphasis on the pleasant aspects of app use, address misconceptions, offer stress screening tools on health websites, and increase options to try high-quality apps.