Understanding the evaluation of mHealth app features based on a cross-country Kano analysis

Privacy Barriers in Health Monitoring: Scoping Review

BACKGROUND

Health monitoring technologies help patients and older adults live better and stay longer in their own homes. However, there are many factors influencing their adoption of these technologies. Privacy is one of them.

OBJECTIVE

The aim of this study was to provide an overview of the privacy barriers in health monitoring from current research, analyze the factors that influence patients to adopt assisted living technologies, provide a social psychological explanation, and propose suggestions for mitigating these barriers in future research.

METHODS

A scoping review was conducted, and web-based literature databases were searched for published studies to explore the available research on privacy barriers in a health monitoring environment.

RESULTS

In total, 65 articles met the inclusion criteria and were selected and analyzed. Contradictory findings and results were found in some of the included articles. We analyzed the contradictory findings and provided possible explanations for current barriers, such as demographic differences, information asymmetry, researchers' conceptual confusion, inducible experiment design and its psychological impacts on participants, researchers' confirmation bias, and a lack of distinction among different user roles. We found that few exploratory studies have been conducted so far to collect privacy-related legal norms in a health monitoring environment. Four research questions related to privacy barriers were raised, and an attempt was made to provide answers.

CONCLUSIONS

This review highlights the problems of some research, summarizes patients' privacy concerns and legal concerns from the studies conducted, and lists the factors that should be considered when gathering and analyzing people's privacy attitudes.

Keeping the Customer Satisfied: Applying a Kano Model to Improve Vaccine Promotion in the Philippines

INTRODUCTION

The success of global health interventions heavily relies on reaching populations in a way that aligns with their priorities and needs. This warrants novel approaches to determine the design of meaningful interventions and targeted delivery pathways. To date, global health scholarship and practice have largely underused approaches already established in fields that emphasize customer satisfaction, such as quality management or consumer psychology.

METHODS

In our study, we apply Kano methodology-originally designed to understand how product attributes nonlinearly influence customer satisfaction-to inform design decisions regarding a video-based vaccine intervention in the Philippines. Between September 2021 and April 2022, we administered a Kano questionnaire to 205 caregivers of small children. Data were analyzed following routine Kano approaches, supplemented by cultural consensus analysis (CCA), which is an approach used largely in anthropology to identify distinct cultural groups and competencies.

RESULTS

Applying Kano and CCA methodologies allowed us to make informed design decisions in terms of optimizing accessibility and credibility of an intervention that ultimately proved successful in bolstering vaccine intentions. Results guided us to include national and international logos, to appreciate the value of summarizing key messages, and to recognize the importance of fact- or story-based communication as attributes that influenced respondent satisfaction one-dimensionally. We found that involving trusted messengers and including text-based information were required to avoid dissatisfaction. Interacting with someone after viewing the product and creating opportunities to share the promotional material via social media were attractive attributes whose presence would increase satisfaction but would not spark severe dissatisfaction if omitted. Other attributes (short duration, video- or animation-based intervention, delivering the intervention at health centers or in group settings) played a limited role in respondent satisfaction.

CONCLUSIONS

Global health research and practice can benefit from applying approaches established in other fields when making evidence-based prioritization decisions to tailor interventions.

Exploring the factors that affect user experience in mobile-health applications: A text-mining and machine-learning approach

Recent years have witnessed an increased demand for mobile health (mHealth) platforms owing to the COVID-19 pandemic and preference for doorstep delivery. However, factors impacting user experiences and satisfaction levels across these platforms, using customer reviews, are still largely unexplored in academic research. The empirical framework we proposed in this paper addressed this research gap by analysing unmonitored user comments for some popular mHealth platforms. Using topic-modelling techniques, we identified the impacting factors (predictors) and categorised them into two major dimensions based on strategic adoption and motivational association. Findings from our study suggest that time and money, convenience, responsiveness, and availability emerge as significant predictors for delivering a positive user experience on m-health platforms. Next, we identified substantial moderating effects of review polarity on the predictors related to brand association and hedonic motivation, such as online booking and video consultation. Further, we also identified the top predictors for successful user experience across these platforms. Recommendations from our study will benefit business managers by offering an improved service design leading to higher user satisfaction across these m-health platforms.

The Association between mHealth App Use and Healthcare Satisfaction among Clients at Outpatient Clinics: A Cross-Sectional Study in Inner Mongolia, China

Mobile health (mHealth) applications (apps) have been developed in hospital settings to allocate and manage medical care services, which is one of the national strategies to improve health care in China. Little is known about the comprehensive effects of hospital-based mHealth app use on client satisfaction. The aim of this study was to determine the relationship between the full range of mHealth app use and satisfaction domains among clients attending outpatient clinics. A cross-sectional survey was conducted from January to February 2021 in twelve tertiary hospitals in Inner Mongolia. After the construction of the mHealth app use, structural equation modeling was used for data analysis. Of 1889 participants, the standardized coefficients β on environment/convenience, health information, and medical service fees were 0.11 (p < 0.001), 0.06 (p = 0.039), and 0.08 (p = 0.004), respectively. However, app use was not significantly associated with satisfaction of doctor−patient communication (β = 0.05, p = 0.069), short-term outcomes (β = 0.05, p = 0.054), and general satisfaction (β = 0.02, p = 0.429). Clients of the study hospitals were satisfied with the services, but their satisfaction was not much associated with mHealth use. The limitation of the mHealth system should be improved to enhance communication and engagement among clients, doctors, and healthcare givers, as well as to pay more attention to health outcomes and satisfaction of clients.

Socio-demographic digital divide in mHealth app use among clients at outpatient departments in Inner Mongolia, China: a cross-sectional study (Preprint)

Background

Mobile health (mHealth) apps have become part of the infrastructure for access to health care in hospitals, especially during the COVID-19 pandemic. However, little is known about the effects of sociodemographic characteristics on the digital divide regarding the use of hospital-based mHealth apps and their benefits to patients and caregivers.

Objective

The aim of this study was to document the cascade of potential influences from digital access to digital use and then to mHealth use, as well as the potential influence of sociodemographic variables on elements of the cascade.

Methods

A cross-sectional survey was conducted from January to February 2021 among adult clients at outpatient departments in 12 tertiary hospitals of Inner Mongolia, China. Structural equation modeling was conducted after the construct comprising digital access, digital use, and mHealth use was validated.

Results

Of 2115 participants, the β coefficients (95% CI) of potential influence of digital access on digital use, and potential influence of digital use on mHealth use, were 0.28 (95% CI 0.22-0.34) and 0.51 (95% CI 0.38-0.64), respectively. Older adults were disadvantaged with regard to mHealth access and use (β=–0.38 and β=–0.41), as were less educated subgroups (β=–0.24 and β=–0.27), and these two factors had nonsignificant direct effects on mHealth use.

Conclusions

To overcome the mHealth use divide, it is important to improve digital access and digital use among older adults and less educated groups.

Examining Protection Motivation and Network Externality Perspective Regarding the Continued Intention to Use M-Health Apps

M-health apps have developed rapidly and are widely accepted, but users' continued intention to use m-health apps has not been fully explored. This study was designed to obtain a better understanding of users' continued intention to use m-health apps. We developed a theoretical model by incorporating the protection motivation theory and network externalities and conducted an empirical study of a 368-respondent sample. The results showed that: (1) perceived vulnerability has a direct impact on users' self-efficacy and response efficacy; (2) self-efficacy and response efficacy have a direct impact on users' attitudes and continued intention; (3) network externalities affect users' attitudes and continued intention, among which direct network externalities have an indirect impact on users' continued intention through attitude; and (4) the impacts of self-efficacy, response efficacy, and indirect network externalities on continued intention are partially meditated by attitudes.