How do Patients with Chronic Diseases Make Usage Decisions Regarding Mobile Health Monitoring Services?

The increasing population of patients with chronic diseases generates great challenge of chronic disease management. The occurrence of mobile health monitoring service is beneficial to chronic disease prevention and health promotion. The objective of this study is to investigate how the patients with chronic diseases make usage decisions on mobile health monitoring service. A survey comprising 261 subjects were conducted to validate the research model and proposed hypotheses. The results revealed that health severity positively influences mobile health monitoring service use intention, while negative health emotions do not. Health uncertainty avoidance strengthens the effect of health severity but weakens the effect of negative health emotions on mobile health monitoring service use intention. Limitations and implications for research and practice are discussed

Toward a Better Understanding of the Intention to Use mHealth Apps: Exploratory Study

Background: An increasing number of mobile health (mHealth) apps are becoming available for download and use on mobile devices. Even with the increase in availability and use of mHealth apps, there has still not been a lot of research into understanding the intention to use this kind of apps. Objective: The purpose of this study was to investigate a technology acceptance model (TAM) that has been specially designed for primary health care applications. Methods: The proposed model is an extension of the TAM, and was empirically tested using data obtained from a survey of mHealth app users (n=310). The research analyzed 2 additional external factors: promotion of health and health benefits. Data were analyzed with a PLS–SEM software and confirmed that gender moderates the adoption of mHealth apps in Spain. The explanatory capacity (R2 for behavioral intention to use) of the proposed model was 76.4%. Likewise, the relationships of the external constructs of the extended TAM were found to be significant. Results: The results show the importance of healthy habits developed by using mHealth apps. In addition, communication campaigns for these apps should be aimed at transferring the usefulness of eHealth as an agent for transforming attitudes; additionally, as more health benefits are obtained, ease of use becomes greater. Perceived usefulness (PU; β=.415, t0.001;4999=3.442, P=.001), attitude toward using (β=.301, t0.01;499=2.299, P=.02), and promotion of health (β=.210, t0.05;499=2.108, P=.03) were found to have a statistically significant impact on behavior intention to use eHealth apps (R2=76.4%). Perceived ease of use (PEOU; β=.179, t0.01;499=2.623, P=.009) and PU (β=.755, t0.001;499=12.888, P=78.2%). Furthermore, PEOU (β=.203, t0.01;499=2.810, P=.005), health benefits (β=.448, t0.001;499=4.010, P<.001), and promotion of health (β=.281, t0.01;499=2.393, P=.01) exerted a significant impact on PU (R2=72.7%). Finally, health benefits (β=.640, t0.001;499=14.948, P<.001) had a statistically significant impact on PEOU (R2=40.9%), while promotion of health (β=.865, t0.001;499=29.943, P<.001) significantly influenced health benefits (R2=74.7%). Conclusions: mHealth apps could be used to predict the behavior of patients in the face of recommendations to prevent pandemics, such as COVID-19 or SARS, and to track users’symptoms while they stay at home. Gender is a determining factor that influences the intention to use mHealth apps, so perhaps different interfaces and utilities could be designed according to gender

Social, Organizational, and Technological Factors Impacting Clinicians’ Adoption of Mobile Health Tools: A Systematic Literature Review

Background: There is a growing body of evidence highlighting the potential of mobile health (mHealth) in reducing health care costs, enhancing access, and improving the quality of patient care. However, user acceptance and adoption are key prerequisites to harness this potential; hence, a deeper understanding of the factors impacting this adoption is crucial for its success. Objective: The aim of this review was to systematically explore relevant published literature to synthesize the current understanding of the factors impacting clinicians’ adoption of mHealth tools, not only from a technological perspective but also from social and organizational perspectives. Methods: A structured search was carried out of MEDLINE, PubMed, the Cochrane Library, and the SAGE database for studies published between January 2008 and July 2018 in the English language, yielding 4993 results, of which 171 met the inclusion criteria. The Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines and the Cochrane handbook were followed to ensure a systematic process. Results: The technological factors impacting clinicians’ adoption of mHealth tools were categorized into eight key themes: usefulness, ease of use, design, compatibility, technical issues, content, personalization, and convenience, which were in turn divided into 14 subthemes altogether. Social and organizational factors were much more prevalent and were categorized into eight key themes: workflow related, patient related, policy and regulations, culture or attitude or social influence, monetary factors, evidence base, awareness, and user engagement. These were divided into 41 subthemes, highlighting the importance of considering these factors when addressing potential barriers to mHealth adoption and how to overcome them. Conclusions: The study results can help inform mHealth providers and policymakers regarding the key factors impacting mHealth adoption, guiding them into making educated decisions to foster this adoption and harness the potential benefits

Health Wearable Tools and Health Promotion

The application of wearable technology for health purposes is a multidisciplinary research topic. To summarize key contributions and simultaneously identify outstanding gaps in research, the input-mechanism-output (I-M-O) framework was applied to synthesize findings from 275 relevant papers in the period 2010–2021. Eighteen distinct cross-disciplinary themes were identified and organized under the I-M-O framework. Studies that covered input factors have largely been technocentric, exploring the design of various health wearables, with less emphasis on usability. While studies on user acceptance and engagement are increasing, there remains room for growth in user- centric aspects such as engagement. While measurement of physiological health indictors has grown more sophisticated due to sensitivity of sensors and the advancements in predictive algorithms, a rapidly growing area of research is that of measuring and tracking mental states and emotional health.Relatively few studies explore theoretically backed explanations of the role of health wearables, with technocentric theories predicting adoption favored. These mainly focused on mechanisms of adoption, while postadoption use and health behavior change were less explored. As a consequence, compared to adoption mechanisms, there is an opportunity to increase our understanding of the continued use of wearables and their effects on sustained health behavior change. While a range of incentives such as social, feedback, financial, and gamification are being tested, it is worth noting that negative attitudes, such as privacy concerns, are being paid much more attention as well. Output factors were studied in both individual and organizational settings, with the former receiving considerably more attention than the latter. The progress of research on health wearables was discussed from an interdisciplinary angle, and the role of social scientists was highlighted for the advancement of research on wearable health

Improving Acceptance Of Iposyandu Application In Community Health Workers: Service Science Perspective

Maternal and Child health data report by Community health workers (CHW) is still using paper manually. Consequently, it creates delays in policymaking and implementation. Therefore, the iPosyandu application as developed presenting as a digital health platform in helping CHW store the data online. Despite the benefits of iPosyandu, CHW is still reluctant to use this application. Hence, this study aims to analyze the strategies that can be used to improve the acceptance of the iPosyandu in CHW based on a service science perspective. Service science of value co-creation was chosen as a strategy to create a model of CHW acceptance. By conducting focus group discussions, this study engages the participation of CHW and other relevant stakeholders to explore and develop the strategic processes. The result found the need for government policy support for digitalization in CHW and develop the platform, both in platform regulations and application readiness. After all, digitization in CHW can make stakeholders easier to monitor and more responsive to formulate health policies.Keywords: Community health worker (CHW), iPosyandu, Service Science, Digitalizatio

Attention Deficit Hyperactivity Disorder: Is There an App for That? Suitability Assessment of Apps for Children and Young People With ADHD

Background: Attention-deficit/hyperactivity disorder (ADHD) is a complex highly comorbid disorder, which can have a huge impact on those with ADHD, their family, and the community around them. ADHD is currently managed using pharmacological and nonpharmacological interventions. However, with advances in technology and an increase in the use of mobile apps, managing ADHD can be augmented using apps specifically designed for this population. However, little is known regarding the suitability and usability of currently available apps. Objective: The aim of this study was to explore the suitability of the top 10 listed apps for children and young people with ADHD and clinicians who work with them. It is hypothesized that mobile apps designed for this population could be more suitably designed for this population. Methods: The top 10 listed apps that are specifically targeted toward children and young people with ADHD in the United Kingdom were identified via the Google Play (n=5) and iTunes store (n=5). Interviews were then undertaken with 5 clinicians who specialize in treating this population and 5 children and young people with ADHD themselves, to explore their opinions of the 10 apps identified and what they believe the key components are for apps to be suitable for this population. Results: Five themes emerged from clinician and young people interviews: the accessibility of the technology, the importance of relating to apps, addressing ADHD symptoms and related difficulties, age appropriateness, and app interaction. Three additional themes emerged from the clinician interviews alone: monitoring symptoms, side effects and app effect on relationships, and the impact of common comorbid conditions. The characteristics of the apps did not appear to match well with the views of our sample. Conclusions: These findings suggest that the apps may not be suitable in meeting the complex needs associated with this condition. Further research is required to explore the value of apps for children and young people with ADHD and their families and, in particular, any positive role for apps in the management of ADHD in this age group. A systematic review on how technology can be used to engage this population and how it can be used to help them would be a useful way forward. This could be the platform to begin exploring the use of apps further

Application of Mobile Health Services to Support Patient Self-Management of Chronic Conditions

Background: Chronic conditions are the leading cause of ill-health, disability and premature death, adding huge health and socioeconomic burden to the healthcare system. Although mobile health (mHealth) services have the potential to provide patients with a timely, ubiquitous, and cost-effective means to access healthcare services, to date, much remains to be revealed for their application in chronic condition management. Aim: This doctoral project aims to comprehensively understand the application of mHealth services to support patient self-management of chronic conditions. This aim is achieved through four objectives: (1) to synthesise research evidence about health outcomes of applying mHealth services to support patient self-management of chronic conditions and the essential components to achieve these outcomes, (2) to determine the mechanism for applying mHealth services to support patient self-management of chronic conditions, (3) to explore critical factors and how these factors influence patients\u27 intention to continuously use mHealth services, and (4) to apply the above findings to guide the design of a prototype mHealth service. Methods: To increase the generalisability of the findings, three chronic conditions that could benefit from mHealth services were purposively studied to address the research objectives within the feasibility of available study sites and resources at different stages of the project. First, two literature review studies were conducted to achieve Objective 1. One was a systematic review to investigate health outcomes of mHealth services to support patient self-management of one chronic condition, unhealthy alcohol use, and the essential components to achieve these outcomes. The other was a rapid review on using behavioural theory to guide the design of mHealth services that support patient self-management of another chronic condition, hypertension. Second, two field studies were conducted to achieve Objectives 2 and 3, respectively. One was an interview study that explored patients\u27 perceptions of a mHealth service to support their self-management of hypertension in China. The other was a questionnaire survey study conducted on the same site that explored critical factors influencing patients\u27 intention to continuously use the mHealth service. Third, a clinician-led, experience-based co-design approach was implemented to apply the above-mentioned learning experience to the development practice of a mHealth service that supports patient self-management of obesity before elective surgery in Australia, achieving Objective 4. Results: Literature reviews identify five structural components - context, theory, content, delivery mode, and implementation procedure - which are essential for mHealth services to achieve three health outcomes - behavioural, physiological, and cognitive outcomes. Inductive synthesis of the interview findings lead to a 6A framework that summarises the mechanisms for mHealth services: access, assessment, assistance, awareness, ability, and activation. Mobile health services provide patients with easy access to health assessment and healthcare assistance to increase their self-management awareness and ability, thereby activating their self-management behaviours. Questionnaire survey study finds that patients\u27 intention to continuously use mHealth services can be influenced by the information quality, system quality and service quality by influencing their perceived usefulness and satisfaction with the mHealth services. Guided by Social Cognitive Theory, the developed prototype mHealth service provide patients with functions of automatic push notifications, online resources, goal setting and monitoring, and interactive health-related exchanges that encourage their physical activity, healthy eating, psychological preparation, and a positive outlook for elective surgery. The patients\u27 requirements in two focus group discussions enabled the research team to improve the mHealth service design. Conclusion: Mobile health services guided by behavioural theories can provide patients with easy access to health assessment and healthcare assistance to increase their self-management awareness and ability, thereby activating their self-management behaviours. The effort for designing mHealth services needs to be placed on crafting content (to improve information quality), developing useful functions and selecting a proper delivery mode (to improve system quality), and establishing effective implementation procedures (to improve service quality). These will ensure patients\u27 perceived usefulness and satisfaction with mHealth services, increase their intention to continuously use such services, thus supporting long-term patient self-management of chronic conditions. As demonstrated by the design case, the findings of this PhD project can be generalised to guide the design of other mHealth services that aim to support patient self-management of chronic conditions